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Fu J, Chen H, Xu C, Jia Z, Lu Q, Zhang H, Hu Y, Lv K, Zhang J, Geng D. Harnessing routine MRI for the early screening of Parkinson's disease: a multicenter machine learning study using T2-weighted FLAIR imaging. Insights Imaging 2025; 16:92. [PMID: 40285905 PMCID: PMC12033128 DOI: 10.1186/s13244-025-01961-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2024] [Accepted: 03/25/2025] [Indexed: 04/29/2025] Open
Abstract
OBJECTIVE To explore the potential of radiomics features derived from T2-weighted fluid-attenuated inversion recovery (T2W FLAIR) images to distinguish idiopathic Parkinson's disease (PD) patients from healthy controls (HCs). METHODS T2W FLAIR images from 1727 subjects were retrospectively obtained from five cohorts and divided into a training set (395 PD/574 HC), an internal test set (99 PD/144 HC) and an external test set (295 PD/220 HC). Regions of interest (ROIs), including bilateral globus pallidus (GP), putamen (PU), substantia nigra (SN), and red nucleus (RN), were manually delineated. The radiomics features were extracted from ROIs. Six independent machine learning (ML) classifiers were trained on the training set, and validated on the internal and external test sets. RESULTS A selection of five, two, three, and ten highly correlated diagnostic features were identified from SN, RN, GP, and PU regions, respectively. Six ML classifiers were implemented based on the combined 20 radiomics features. In the internal test cohort, the six models achieved AUC of 0.96-0.98 with the accuracy ranging from 0.80 to 0.90. In the external test cohort, the multilayer perceptron model demonstrated the highest AUC of 0.85 (95% CI: 0.80-0.89) with an accuracy of 0.78. CONCLUSION ML models based on the conventional T2W FLAIR images demonstrated promising diagnostic performance for PD and those models may serve as a basis for future investigations on PD diagnosis with the aid of ML methods. CRITICAL RELEVANCE STATEMENT Our study confirmed that early screening of Parkinson's Disease based on the conventional T2W FLAIR images was feasible with the aid of machine learning algorithms in a large multicenter cohort and those models had certain generalization. KEY POINTS Conventional head MRI is routinely performed in Parkinson's disease (PD) but exhibits inadequate specificity for diagnosis. Machine learning (ML) models based on conventional T2W FLAIR images showed favorable accuracy for PD diagnosis. ML algorithm enables early screening of PD on routine T2W FLAIR sequence.
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Affiliation(s)
- Junyan Fu
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Hongyi Chen
- Academy for Engineering and Technology, Fudan University, Shanghai, China
| | - Chengling Xu
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Zhongzheng Jia
- Department of Radiology, Affiliated Hospital of Nantong University, Nantong, China
| | - Qingqing Lu
- Department of Radiology, The First Affiliated Hospital of Ningbo University, Ningbo, China
| | - Haiyan Zhang
- Department of Radiology, The Second Affiliated Hospital of Xuzhou Medical University, Xuzhou, China
| | - Yue Hu
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Kun Lv
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Jun Zhang
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China.
| | - Daoying Geng
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China.
- Center for Shanghai Intelligent Imaging for Critical Brain Diseases Engineering and Technology Research, Shanghai, China.
- Institute of Functional and Molecular Medical Imaging, Fudan University, Shanghai, China.
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Liu J, Ruzi R, Jian C, Wang Q, Zhao S, Ng ML, Zhao S, Wang L, Yan N. Mapping subcortical brain lesions, behavioral and acoustic analysis for early assessment of subacute stroke patients with dysarthria. Front Neurosci 2025; 18:1455085. [PMID: 39844850 PMCID: PMC11753205 DOI: 10.3389/fnins.2024.1455085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2024] [Accepted: 12/16/2024] [Indexed: 01/24/2025] Open
Abstract
Introduction Dysarthria is a motor speech disorder frequently associated with subcortical damage. However, the precise roles of the subcortical nuclei, particularly the basal ganglia and thalamus, in the speech production process remain poorly understood. Methods The present study aimed to better understand their roles by mapping neuroimaging, behavioral, and speech data obtained from subacute stroke patients with subcortical lesions. Multivariate lesion-symptom mapping and voxel-based morphometry methods were employed to correlate lesions in the basal ganglia and thalamus with speech production, with emphases on linguistic processing and articulation. Results The present findings revealed that the left thalamus and putamen are significantly correlated with concept preparation (r = 0.64, p < 0.01) and word retrieval (r = 0.56, p < 0.01). As the difficulty of the behavioral tasks increased, the influence of cognitive factors on early linguistic processing gradually intensified. The globus pallidus and caudate nucleus were found to significantly impact the movements of the larynx (r = 0.63, p < 0.01) and tongue (r = 0.59, p = 0.01). These insights underscore the complex and interconnected roles of the basal ganglia and thalamus in the intricate processes of speech production. The lateralization and hierarchical organization of each nucleus are crucial to their contributions to these speech functions. Discussion The present study provides a nuanced understanding of how lesions in the basal ganglia and thalamus impact various stages of speech production, thereby enhancing our understanding of the subcortical neuromechanisms underlying dysarthria. The findings could also contribute to the identification of multimodal assessment indicators, which could aid in the precise evaluation and personalized treatment of speech impairments.
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Affiliation(s)
- Juan Liu
- Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Rukiye Ruzi
- Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Chuyao Jian
- Department of Rehabilitation Medicine, The Eighth Affiliated Hospital of Sun Yat-sen University, Shenzhen, China
| | - Qiuyu Wang
- Department of Radiology, The Eighth Affiliated Hospital of Sun Yat-sen University, Shenzhen, China
| | - Shuzhi Zhao
- Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Manwa L. Ng
- Speech Science Laboratory, Faculty of Education, University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Shaofeng Zhao
- Department of Rehabilitation Medicine, The Eighth Affiliated Hospital of Sun Yat-sen University, Shenzhen, China
| | - Lan Wang
- Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Nan Yan
- Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
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Saqib M, Horovitz SG. Harmonization for Parkinson's Disease Multi-Dataset T1 MRI Morphometry Classification. NEUROSCI 2024; 5:600-613. [PMID: 39728674 DOI: 10.3390/neurosci5040042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2024] [Revised: 10/28/2024] [Accepted: 10/31/2024] [Indexed: 12/28/2024] Open
Abstract
Classification of disease and healthy volunteer cohorts provides a useful clinical alternative to traditional group statistics due to individualized, personalized predictions. Classifiers for neurodegenerative disease can be trained on structural MRI morphometry, but require large multi-scanner datasets, introducing confounding batch effects. We test ComBat, a common harmonization model, in an example application to classify subjects with Parkinson's disease from healthy volunteers and identify common pitfalls, including data leakage. We used a multi-dataset cohort of 372 subjects (216 with Parkinson's disease, 156 healthy volunteers) from 11 identified scanners. We extracted both FreeSurfer and the determinant of Jacobian morphometry to compare single-scanner and multi-scanner classification pipelines. We confirm the presence of batch effects by running single scanner classifiers which could achieve wildly divergent AUCs on scanner-specific datasets (mean:0.651 ± 0.144). Multi-scanner classifiers that considered neurobiological batch effects between sites could easily achieve a test AUC of 0.902, though pipelines that prevented data leakage could only achieve a test AUC of 0.550. We conclude that batch effects remain a major issue for classification problems, such that even impressive single-scanner classifiers are unlikely to generalize to multiple scanners, and that solving for batch effects in a classifier problem must avoid circularity and reporting overly optimistic results.
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Affiliation(s)
- Mohammed Saqib
- University of Pennsylvania, Philadelphia, PA 19104, USA
- National Institute of Neurological Disorders and Strokes, National Institutes of Health, Bethesda, MD 20892, USA
| | - Silvina G Horovitz
- National Institute of Neurological Disorders and Strokes, National Institutes of Health, Bethesda, MD 20892, USA
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Laansma MA, Zhao Y, van Heese EM, Bright JK, Owens-Walton C, Al-Bachari S, Anderson TJ, Assogna F, van Balkom TD, Berendse HW, Cendes F, Dalrymple-Alford JC, Debove I, Dirkx MF, Druzgal J, Emsley HCA, Fouche JP, Garraux G, Guimarães RP, Helmich RC, Hu M, van den Heuvel OA, Isaev D, Kim HB, Klein JC, Lochner C, McMillan CT, Melzer TR, Newman B, Parkes LM, Pellicano C, Piras F, Pitcher TL, Poston KL, Rango M, Ribeiro LF, Rocha CS, Rummel C, Santos LSR, Schmidt R, Schwingenschuh P, Squarcina L, Stein DJ, Vecchio D, Vriend C, Wang J, Weintraub D, Wiest R, Yasuda CL, Jahanshad N, Thompson PM, van der Werf YD, Gutman BA. A worldwide study of subcortical shape as a marker for clinical staging in Parkinson's disease. NPJ Parkinsons Dis 2024; 10:223. [PMID: 39557903 PMCID: PMC11574005 DOI: 10.1038/s41531-024-00825-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2024] [Accepted: 10/21/2024] [Indexed: 11/20/2024] Open
Abstract
Alterations in subcortical brain regions are linked to motor and non-motor symptoms in Parkinson's disease (PD). However, associations between clinical expression and regional morphological abnormalities of the basal ganglia, thalamus, amygdala and hippocampus are not well established. We analyzed 3D T1-weighted brain MRI and clinical data from 2525 individuals with PD and 1326 controls from 22 global sources in the ENIGMA-PD consortium. We investigated disease effects using mass univariate and multivariate models on the medial thickness of 27,120 vertices of seven bilateral subcortical structures. Shape differences were observed across all Hoehn and Yahr (HY) stages, as well as correlations with motor and cognitive symptoms. Notably, we observed incrementally thinner putamen from HY1, caudate nucleus and amygdala from HY2, hippocampus, nucleus accumbens, and thalamus from HY3, and globus pallidus from HY4-5. Subregions of the thalami were thicker in HY1 and HY2. Largely congruent patterns were associated with a longer time since diagnosis and worse motor symptoms and cognitive performance. Multivariate regression revealed patterns predictive of disease stage. These cross-sectional findings provide new insights into PD subcortical degeneration by demonstrating patterns of disease stage-specific morphology, largely consistent with ongoing degeneration.
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Affiliation(s)
- Max A Laansma
- Amsterdam UMC, Department of Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands.
| | - Yuji Zhao
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, USA
| | - Eva M van Heese
- Amsterdam UMC, Department of Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Joanna K Bright
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Conor Owens-Walton
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Sarah Al-Bachari
- Faculty of Health and Medicine, The University of Lancaster, Lancaster, UK
- Department of Neurology, Royal Preston Hospital, Preston, UK
| | - Tim J Anderson
- Department of Medicine, University of Otago, Christchurch, Christchurch, New Zealand
- New Zealand Brain Research Institute, Christchurch, New Zealand
- Neurology Department, Te Wahtu Ora-Health New Zealand Waitaha Canterbury, Christchurch, New Zealand
| | - Francesca Assogna
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Tim D van Balkom
- Amsterdam UMC, Department of Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Amsterdam UMC, Department Psychiatry, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Henk W Berendse
- Amsterdam UMC, Department Neurology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Fernando Cendes
- Department of Neurology, University of Campinas-UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - John C Dalrymple-Alford
- New Zealand Brain Research Institute, Christchurch, New Zealand
- School of Psychology, Speech and Hearing, University of Canterbury, Christchurch, New Zealand
| | - Ines Debove
- Department of Neurology, Inselspital, University of Bern, Bern, Switzerland
| | - Michiel F Dirkx
- Department of Neurology and Center of Expertise for Parkinson & Movement Disorders, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands
| | - Jason Druzgal
- Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, VA, USA
| | - Hedley C A Emsley
- Lancaster Medical School, Lancaster University, Lancaster, UK
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Jean-Paul Fouche
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Gaëtan Garraux
- GIGA-CRC in vivo imaging, University of Liège, Liège, Belgium
- Department of Neurology, CHU Liège, Liège, Belgium
| | - Rachel P Guimarães
- Department of Neurology, University of Campinas-UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Rick C Helmich
- Department of Neurology and Center of Expertise for Parkinson & Movement Disorders, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands
- Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Michele Hu
- Division of Clinical Neurology, Department of Clinical Neurosciences, Oxford Parkinson's Disease Centre, Nuffield, University of Oxford, Oxford, UK
| | - Odile A van den Heuvel
- Amsterdam UMC, Department of Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Amsterdam UMC, Department Psychiatry, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Dmitry Isaev
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Ho-Bin Kim
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, CA, USA
| | - Johannes C Klein
- Division of Clinical Neurology, Department of Clinical Neurosciences, Oxford Parkinson's Disease Centre, Nuffield, University of Oxford, Oxford, UK
| | - Christine Lochner
- SA MRC Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry, Stellenbosch University, Cape Town, South Africa
| | - Corey T McMillan
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Tracy R Melzer
- Department of Medicine, University of Otago, Christchurch, Christchurch, New Zealand
- New Zealand Brain Research Institute, Christchurch, New Zealand
- School of Psychology, Speech and Hearing, University of Canterbury, Christchurch, New Zealand
| | - Benjamin Newman
- Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, VA, USA
| | - Laura M Parkes
- Division of Psychology, Communication and Human Neuroscience, School of Health Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Northern Care Alliance & University of Manchester, Manchester, UK
| | - Clelia Pellicano
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Fabrizio Piras
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Toni L Pitcher
- Department of Medicine, University of Otago, Christchurch, Christchurch, New Zealand
- New Zealand Brain Research Institute, Christchurch, New Zealand
| | - Kathleen L Poston
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, CA, USA
| | - Mario Rango
- Excellence Center for Advanced MR Techniques and Parkinson's Disease Center, Neurology unit, Fondazione IRCCS Cà Granda Maggiore Policlinico Hospital, University of Milan, Milan, Italy
- Department of Neurosciences, Neurology Unit, Fondazione Ca' Granda, IRCCS, Ospedale Policlinico, Univeristy of Milan, Milano, Italy
| | - Leticia F Ribeiro
- Department of Neurology, University of Campinas-UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Cristiane S Rocha
- Department of Neurology, University of Campinas-UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Christian Rummel
- Support Center for Advanced Neuroimaging, (SCAN) University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Lucas S R Santos
- Department of Neurology, University of Campinas-UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Reinhold Schmidt
- Department of Neurology, Medical University of Graz, Graz, Austria
| | | | - Letizia Squarcina
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Dan J Stein
- SA MRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Daniela Vecchio
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Chris Vriend
- Amsterdam UMC, Department of Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam UMC, Department Psychiatry, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
| | - Jiunjie Wang
- Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan City, Taiwan
- Department of Diagnostic Radiology, Chang Gung Memorial Hospital, Keelung Branch, Keelung City, Taiwan
- Healthy Ageing Research Center, Chang Gung University, Taoyuan City, Taiwan
| | - Daniel Weintraub
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Roland Wiest
- Support Center for Advanced Neuroimaging (SCAN), University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Bern, Switzerland
| | - Clarissa L Yasuda
- Department of Neurology, University of Campinas-UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Ysbrand D van der Werf
- Amsterdam UMC, Department of Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Boris A Gutman
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, USA
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Yang Q, Chen G, Yang Z, Raviv TR, Gao Y. Fine hippocampal morphology analysis with a multi-dataset cross-sectional study on 2911 subjects. Neuroimage Clin 2024; 43:103620. [PMID: 38823250 PMCID: PMC11168486 DOI: 10.1016/j.nicl.2024.103620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 05/07/2024] [Accepted: 05/18/2024] [Indexed: 06/03/2024]
Abstract
CA1 subfield and subiculum of the hippocampus contain a series of dentate bulges, which are also called hippocampus dentation (HD). There have been several studies demonstrating an association between HD and brain disorders. Such as the number of hippocampal dentation correlates with temporal lobe epilepsy. And epileptic hippocampus have a lower number of dentation compared to contralateral hippocampus. However, most studies rely on subjective assessment by manual searching and counting in HD areas, which is time-consuming and labor-intensive to process large amounts of samples. And to date, only one objective method for quantifying HD has been proposed. Therefore, to fill this gap, we developed an automated and objective method to quantify HD and explore its relationship with neurodegenerative diseases. In this work, we performed a fine-scale morphological characterization of HD in 2911 subjects from four different cohorts of ADNI, PPMI, HCP, and IXI to quantify and explore differences between them in MR T1w images. The results showed that the degree of right hippocampal dentation are lower in patients with Alzheimer's disease than samples in mild cognitive impairment or cognitively normal, whereas this change is not significant in Parkinson's disease progression. The innovation of this paper that we propose a quantitative, robust, and fully automated method. These methodological innovation and corresponding results delineated above constitute the significance and novelty of our study. What's more, the proposed method breaks through the limitations of manual labeling and is the first to quantitatively measure and compare HD in four different brain populations including thousands of subjects. These findings revealed new morphological patterns in the hippocampal dentation, which can help with subsequent fine-scale hippocampal morphology research.
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Affiliation(s)
- Qinzhu Yang
- School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, China
| | - Guojing Chen
- School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, China
| | - Zhi Yang
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Tammy Riklin Raviv
- The School of Electrical and Computer Engineering, Ben-Gurion University of the Negev, Be'er Sheva, Israel
| | - Yi Gao
- School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, China; Shenzhen Key Laboratory of Precision Medicine for Hematological Malignancies, Shenzhen, China; Marshall Laboratory of Biomedical Engineering, Shenzhen University, Shenzhen, China.
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Yang W, Bai X, Guan X, Zhou C, Guo T, Wu J, Xu X, Zhang M, Zhang B, Pu J, Tian J. The longitudinal volumetric and shape changes of subcortical nuclei in Parkinson's disease. Sci Rep 2024; 14:7494. [PMID: 38553518 PMCID: PMC10980751 DOI: 10.1038/s41598-024-58187-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 03/26/2024] [Indexed: 04/02/2024] Open
Abstract
Brain structural changes in Parkinson's disease (PD) are progressive throughout the disease course. Changes in surface morphology with disease progression remain unclear. This study aimed to assess the volumetric and shape changes of the subcortical nuclei during disease progression and explore their association with clinical symptoms. Thirty-four patients and 32 healthy controls were enrolled. The global volume and shape of the subcortical nuclei were compared between patients and controls at baseline. The volume and shape changes of the subcortical nuclei were also explored between baseline and 2 years of follow-up. Association analysis was performed between the volume of subcortical structures and clinical symptoms. In patients with PD, there were significantly atrophied areas in the left pallidum and left putamen, while in healthy controls, the right putamen was dilated compared to baseline. The local morphology of the left pallidum was correlated with Mini Mental State Examination scores. The left putamen shape variation was negatively correlated with changes in Unified Parkinson's Disease Rating Scale PART III scores. Local morphological atrophy of the putamen and pallidum is an important pathophysiological change in the development of PD, and is associated with motor symptoms and cognitive status in patients with PD.
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Affiliation(s)
- Wenyi Yang
- Department of Neurology, Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310009, Zhejiang, People's Republic of China
| | - Xueqin Bai
- Department of Radiology, Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310009, Zhejiang, People's Republic of China
| | - Xiaojun Guan
- Department of Radiology, Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310009, Zhejiang, People's Republic of China
| | - Cheng Zhou
- Department of Radiology, Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310009, Zhejiang, People's Republic of China
| | - Tao Guo
- Department of Radiology, Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310009, Zhejiang, People's Republic of China
| | - Jingjing Wu
- Department of Radiology, Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310009, Zhejiang, People's Republic of China
| | - Xiaojun Xu
- Department of Radiology, Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310009, Zhejiang, People's Republic of China
| | - Minming Zhang
- Department of Radiology, Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310009, Zhejiang, People's Republic of China
| | - Baorong Zhang
- Department of Neurology, Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310009, Zhejiang, People's Republic of China
| | - Jiali Pu
- Department of Neurology, Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310009, Zhejiang, People's Republic of China
| | - Jun Tian
- Department of Neurology, Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310009, Zhejiang, People's Republic of China.
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Kadaba Sridhar S, Dysterheft Robb J, Gupta R, Cheong S, Kuang R, Samadani U. Structural neuroimaging markers of normal pressure hydrocephalus versus Alzheimer's dementia and Parkinson's disease, and hydrocephalus versus atrophy in chronic TBI-a narrative review. Front Neurol 2024; 15:1347200. [PMID: 38576534 PMCID: PMC10991762 DOI: 10.3389/fneur.2024.1347200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Accepted: 02/07/2024] [Indexed: 04/06/2024] Open
Abstract
Introduction Normal Pressure Hydrocephalus (NPH) is a prominent type of reversible dementia that may be treated with shunt surgery, and it is crucial to differentiate it from irreversible degeneration caused by its symptomatic mimics like Alzheimer's Dementia (AD) and Parkinson's Disease (PD). Similarly, it is important to distinguish between (normal pressure) hydrocephalus and irreversible atrophy/degeneration which are among the chronic effects of Traumatic Brain Injury (cTBI), as the former may be reversed through shunt placement. The purpose of this review is to elucidate the structural imaging markers which may be foundational to the development of accurate, noninvasive, and accessible solutions to this problem. Methods By searching the PubMed database for keywords related to NPH, AD, PD, and cTBI, we reviewed studies that examined the (1) distinct neuroanatomical markers of degeneration in NPH versus AD and PD, and atrophy versus hydrocephalus in cTBI and (2) computational methods for their (semi-) automatic assessment on Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) scans. Results Structural markers of NPH and those that can distinguish it from AD have been well studied, but only a few studies have explored its structural distinction between PD. The structural implications of cTBI over time have been studied. But neuroanatomical markers that can predict shunt response in patients with either symptomatic idiopathic NPH or post-traumatic hydrocephalus have not been reliably established. MRI-based markers dominate this field of investigation as compared to CT, which is also reflected in the disproportionate number of MRI-based computational methods for their automatic assessment. Conclusion Along with an up-to-date literature review on the structural neurodegeneration due to NPH versus AD/PD, and hydrocephalus versus atrophy in cTBI, this article sheds light on the potential of structural imaging markers as (differential) diagnostic aids for the timely recognition of patients with reversible (normal pressure) hydrocephalus, and opportunities to develop computational tools for their objective assessment.
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Affiliation(s)
- Sharada Kadaba Sridhar
- Department of Bioinformatics and Computational Biology, University of Minnesota, Minneapolis, MN, United States
- Neurotrauma Research Lab, Center for Veterans Research and Education, Minneapolis, MN, United States
| | - Jen Dysterheft Robb
- Neurotrauma Research Lab, Center for Veterans Research and Education, Minneapolis, MN, United States
| | - Rishabh Gupta
- Neurotrauma Research Lab, Center for Veterans Research and Education, Minneapolis, MN, United States
- University of Minnesota Twin Cities Medical School, Minneapolis, MN, United States
| | - Scarlett Cheong
- Department of Bioinformatics and Computational Biology, University of Minnesota, Minneapolis, MN, United States
- Neurotrauma Research Lab, Center for Veterans Research and Education, Minneapolis, MN, United States
| | - Rui Kuang
- Department of Bioinformatics and Computational Biology, University of Minnesota, Minneapolis, MN, United States
- Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN, United States
| | - Uzma Samadani
- Department of Bioinformatics and Computational Biology, University of Minnesota, Minneapolis, MN, United States
- Neurotrauma Research Lab, Center for Veterans Research and Education, Minneapolis, MN, United States
- University of Minnesota Twin Cities Medical School, Minneapolis, MN, United States
- Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN, United States
- Division of Neurosurgery, Department of Surgery, Minneapolis Veterans Affairs Health Care System, Minneapolis, MN, United States
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8
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Say B, Bayar Muluk N, İnal M, Göncüoğlu A, Yörübulut S, Ergün U. Evaluation of putamen area and cerebral peduncle with surrounding cistern in patients with Parkinson's disease: is there a difference from controls in cranial MRI? Neurol Res 2024; 46:220-226. [PMID: 37953510 DOI: 10.1080/01616412.2023.2281088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2023] [Accepted: 11/04/2023] [Indexed: 11/14/2023]
Abstract
OBJECTIVES Nigrostriatal dopaminergic neuron loss is essential in pathogenesis of Parkinson's disease (PD). The purpose of this study was to evaluate nigrostriatal structures including the putamen, cerebral peduncle, widths of interpeduncular cistern, and ambient cistern around the midbrain with conventional cranial magnetic resonance images (MRI) in patients with PD. METHODS The MRI of 56 subjects was included, which was selected from the radiological data system for this retrospective study. The 29 patients with idiopathic PD were included and their disease duration, Hoehn&Yahr stage, and Levodopa equivalent dose (LED) were recorded. The 27 controls had a normal neurologic examination and cranial MRI. All subjects in the patient and control groups had right-hand dominance. Putamen and cerebral peduncle areas and widths of interpeduncular and ambient cisterns were measured in T2 sequences of MRI. Further statistical analysis was applied to exclude gender and age effect on areas. RESULTS The areas of putamen and cerebral peduncles were significantly reduced in patients with PD compared to the control bilaterally (p < 0.001). Enlargement of interpeduncular and ambient cisterns in patients was higher than in controls, and it was significant (p < 0.001). A correlation was not observed between measurement results and clinical characteristics of patients with PD. Only the cerebral peduncle area/ambient cistern width ratio was significantly correlated with disease duration positively (right r = 0.46 p = 0.012, left r = 0.389 p = 0.037). CONCLUSION Clinicians should be careful with conventional MRIs of patients with idiopathic PD in practice. It may be different from controls without any neurological disorder, particularly putamen, cerebral peduncles, interpeduncular, and ambient cisterns.
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Affiliation(s)
- Bahar Say
- Faculty of Medicine, Neurology Department, Kırıkkale University, Kırıkkale, Turkey
| | - Nuray Bayar Muluk
- Faculty of Medicine, ENT Department, Kırıkkale University, Kırıkkale, Turkey
| | - Mikail İnal
- Faculty of Medicine, Radiology Department, Kırıkkale University, Kırıkkale, Turkey
| | - Alper Göncüoğlu
- Faculty of Medicine, Radiology Department, Kırıkkale University, Kırıkkale, Turkey
| | - Serap Yörübulut
- Faculty of Science and Literature, Statistics Department, Kırıkkale University, Kırıkkale, Turkey
| | - Ufuk Ergün
- Faculty of Medicine, Neurology Department, Kırıkkale University, Kırıkkale, Turkey
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9
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Bu S, Pang H, Li X, Zhao M, Wang J, Liu Y, Yu H. Multi-parametric radiomics of conventional T1 weighted and susceptibility-weighted imaging for differential diagnosis of idiopathic Parkinson's disease and multiple system atrophy. BMC Med Imaging 2023; 23:204. [PMID: 38066432 PMCID: PMC10709839 DOI: 10.1186/s12880-023-01169-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Accepted: 12/01/2023] [Indexed: 12/18/2023] Open
Abstract
OBJECTIVES This study aims to investigate the potential of radiomics with multiple parameters from conventional T1 weighted imaging (T1WI) and susceptibility weighted imaging (SWI) in distinguishing between idiopathic Parkinson's disease (PD) and multiple system atrophy (MSA). METHODS A total of 201 participants, including 57 patients with PD, 74 with MSA, and 70 healthy control (HCs) individuals, underwent T1WI and SWI scans. From the 12 subcortical nuclei (e.g. red nucleus, substantia nigra, subthalamic nucleus, putamen, globus pallidus, and caudate nucleus), 2640 radiomic features were extracted from both T1WI and SWI scans. Three classification models - logistic regression (LR), support vector machine (SVM), and light gradient boosting machine (LGBM) - were used to distinguish between MSA and PD, as well as among MSA, PD, and HC. These classifications were based on features extracted from T1WI, SWI, and a combination of T1WI and SWI. Five-fold cross-validation was used to evaluate the performance of the models with metrics such as sensitivity, specificity, accuracy, and area under the receiver operating curve (AUC). During each fold, the ANOVA and least absolute shrinkage and selection operator (LASSO) methods were used to identify the most relevant subset of features for the model training process. RESULTS The LGBM model trained by the features combination of T1WI and SWI exhibited the most outstanding differential performance in both the three-class classification task of MSA vs. PD vs. HC and the binary classification task of MSA vs. PD, with an accuracy of 0.814 and 0.854, and an AUC of 0.904 and 0.881, respectively. The texture-based differences (GLCM) of the SN and the shape-based differences of the GP were highly effective in discriminating between the three classes and two classes, respectively. CONCLUSIONS Radiomic features combining T1WI and SWI can achieve a satisfactory differential diagnosis for PD, MSA, and HC groups, as well as for PD and MSA groups, thus providing a useful tool for clinical decision-making based on routine MRI sequences.
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Affiliation(s)
- Shuting Bu
- Department of Radiology, the First Hospital of China Medical University, Shenyang, 110001, China
| | - Huize Pang
- Department of Radiology, the First Hospital of China Medical University, Shenyang, 110001, China
| | - Xiaolu Li
- Department of Radiology, the First Hospital of China Medical University, Shenyang, 110001, China
| | - Mengwan Zhao
- Department of Radiology, the First Hospital of China Medical University, Shenyang, 110001, China
| | - Juzhou Wang
- Department of Radiology, the First Hospital of China Medical University, Shenyang, 110001, China
| | - Yu Liu
- Department of Radiology, the First Hospital of China Medical University, Shenyang, 110001, China
| | - Hongmei Yu
- Department of Neurology, the First Hospital of China Medical University, 155 Nanjing North Street, Shenyang, Liaoning, 110001, PR China.
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10
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Erlinger M, Molina-Ruiz R, Brumby A, Cordas D, Hunter M, Ferreiro Arguelles C, Yus M, Owens-Walton C, Jakabek D, Shaw M, Lopez Valdes E, Looi JCL. Striatal and thalamic automatic segmentation, morphology, and clinical correlates in Parkinsonism: Parkinson's disease, multiple system atrophy and progressive supranuclear palsy. Psychiatry Res Neuroimaging 2023; 335:111719. [PMID: 37806261 DOI: 10.1016/j.pscychresns.2023.111719] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Revised: 09/20/2023] [Accepted: 09/23/2023] [Indexed: 10/10/2023]
Abstract
Parkinson's disease (PD), multisystem atrophy (MSA), and progressive supranuclear palsy (PSP) present similarly with bradykinesia, tremor, rigidity, and cognitive impairments. Neuroimaging studies have found differential changes in the nigrostriatal pathway in these disorders, however whether the volume and shape of specific regions within this pathway can distinguish between atypical Parkinsonian disorders remains to be determined. This paper investigates striatal and thalamic volume and morphology as distinguishing biomarkers, and their relationship to neuropsychiatric symptoms. Automatic segmentation to calculate volume and shape analysis of the caudate nucleus, putamen, and thalamus were performed in 18 PD patients, 12 MSA, 15 PSP, and 20 healthy controls, then correlated with clinical measures. PSP bilateral thalami and right putamen were significantly smaller than controls, but not MSA or PD. The left caudate and putamen significantly correlated with the Neuropsychiatric Inventory total score. Bilateral thalamus, caudate, and left putamen had significantly different morphology between groups, driven by differences between PSP and healthy controls. This study demonstrated that PSP patient striatal and thalamic volume and shape are significantly different when compared with controls. Parkinsonian disorders could not be differentiated on volumetry or morphology, however there are trends for volumetric and morphological changes associated with PD, MSA, and PSP.
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Affiliation(s)
- M Erlinger
- Research Centre for the Neurosciences of Ageing, Academic Unit of Psychiatry and Addiction Medicine, School of Clinical Medicine, Australian National University, Canberra, Australia.
| | | | - A Brumby
- Research Centre for the Neurosciences of Ageing, Academic Unit of Psychiatry and Addiction Medicine, School of Clinical Medicine, Australian National University, Canberra, Australia
| | - D Cordas
- Research Centre for the Neurosciences of Ageing, Academic Unit of Psychiatry and Addiction Medicine, School of Clinical Medicine, Australian National University, Canberra, Australia
| | - M Hunter
- Research Centre for the Neurosciences of Ageing, Academic Unit of Psychiatry and Addiction Medicine, School of Clinical Medicine, Australian National University, Canberra, Australia
| | | | - M Yus
- Hospital Clinico San Carlos, Madrid, Spain
| | - C Owens-Walton
- Research Centre for the Neurosciences of Ageing, Academic Unit of Psychiatry and Addiction Medicine, School of Clinical Medicine, Australian National University, Canberra, Australia
| | - D Jakabek
- Neuroscience Research Australia, Sydney, Australia
| | - M Shaw
- Hospital Clinico San Carlos, Madrid, Spain
| | | | - J C L Looi
- Research Centre for the Neurosciences of Ageing, Academic Unit of Psychiatry and Addiction Medicine, School of Clinical Medicine, Australian National University, Canberra, Australia
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11
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Deng JH, Zhang HW, Liu XL, Deng HZ, Lin F. Morphological changes in Parkinson's disease based on magnetic resonance imaging: A mini-review of subcortical structures segmentation and shape analysis. World J Psychiatry 2022; 12:1356-1366. [PMID: 36579355 PMCID: PMC9791612 DOI: 10.5498/wjp.v12.i12.1356] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Revised: 11/02/2022] [Accepted: 11/22/2022] [Indexed: 12/16/2022] Open
Abstract
Parkinson's disease (PD) is a neurodegenerative disorder caused by the loss of dopaminergic neurons in the substantia nigra, resulting in clinical symptoms, including bradykinesia, resting tremor, rigidity, and postural instability. The pathophysiological changes in PD are inextricably linked to the subcortical structures. Shape analysis is a method for quantifying the volume or surface morphology of structures using magnetic resonance imaging. In this review, we discuss the recent advances in morphological analysis techniques for studying the subcortical structures in PD in vivo. This approach includes available pipelines for volume and shape analysis, focusing on the morphological features of volume and surface area.
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Affiliation(s)
- Jin-Huan Deng
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People’s Hospital, Shenzhen 518035, Guangdong Province, China
| | - Han-Wen Zhang
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People’s Hospital, Shenzhen 518035, Guangdong Province, China
| | - Xiao-Lei Liu
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People’s Hospital, Shenzhen 518035, Guangdong Province, China
| | - Hua-Zhen Deng
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People’s Hospital, Shenzhen 518035, Guangdong Province, China
| | - Fan Lin
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People’s Hospital, Shenzhen 518035, Guangdong Province, China
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12
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Jeong SH, Lee EC, Chung SJ, Lee HS, Jung JH, Sohn YH, Seong JK, Lee PH. Local striatal volume and motor reserve in drug-naïve Parkinson's disease. NPJ Parkinsons Dis 2022; 8:168. [PMID: 36470876 PMCID: PMC9722895 DOI: 10.1038/s41531-022-00429-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Accepted: 11/11/2022] [Indexed: 12/12/2022] Open
Abstract
Motor reserve (MR) may explain why individuals with similar pathological changes show marked differences in motor deficits in Parkinson's disease (PD). In this study, we investigated whether estimated individual MR was linked to local striatal volume (LSV) in PD. We analyzed data obtained from 333 patients with drug naïve PD who underwent dopamine transporter scans and high-resolution 3-tesla T1-weighted structural magnetic resonance images. Using a residual model, we estimated individual MRs on the basis of initial UPDRS-III score and striatal dopamine depletion. We performed a correlation analysis between MR estimates and LSV. Furthermore, we assessed the effect of LSV, which is correlated with MR estimates, on the longitudinal increase in the levodopa-equivalent dose (LED) during the 4-year follow-up period using a linear mixed model. After controlling for intracranial volume, there was a significant positive correlation between LSV and MR estimates in the bilateral caudate, anterior putamen, and ventro-posterior putamen. The linear mixed model showed that the large local volume of anterior and ventro-posterior putamen was associated with the low requirement of LED initially and accelerated LED increment thereafter. The present study demonstrated that LSV is crucial to MR in early-stage PD, suggesting LSV as a neural correlate of MR in PD.
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Affiliation(s)
- Seong Ho Jeong
- grid.15444.300000 0004 0470 5454Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea ,grid.411627.70000 0004 0647 4151Department of Neurology, Inje University Sanggye Paik Hospital, Seoul, South Korea
| | - Eun-Chong Lee
- grid.222754.40000 0001 0840 2678School of Biomedical Engineering, Korea University, Seoul, South Korea
| | - Seok Jong Chung
- grid.15444.300000 0004 0470 5454Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea ,grid.413046.40000 0004 0439 4086Department of Neurology, Yongin Severance Hospital, Yonsei University Health System, Yongin, South Korea
| | - Hye Sun Lee
- grid.15444.300000 0004 0470 5454Biostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, South Korea
| | - Jin Ho Jung
- grid.411625.50000 0004 0647 1102Department of Neurology, Inje University Busan Paik Hospital, Seoul, South Korea
| | - Young H. Sohn
- grid.15444.300000 0004 0470 5454Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea
| | - Joon-Kyung Seong
- grid.222754.40000 0001 0840 2678School of Biomedical Engineering, Korea University, Seoul, South Korea ,grid.222754.40000 0001 0840 2678Department of Artificial Intelligence, Korea University, Seoul, South Korea
| | - Phil Hyu Lee
- grid.15444.300000 0004 0470 5454Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea ,grid.15444.300000 0004 0470 5454Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul, South Korea
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13
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Wu N, Yu H, Xu M. Alteration of brain nuclei in obese children with and without Prader-Willi syndrome. Front Neuroinform 2022; 16:1032636. [PMID: 36465689 PMCID: PMC9716021 DOI: 10.3389/fninf.2022.1032636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Accepted: 10/31/2022] [Indexed: 09/10/2024] Open
Abstract
Introduction: Prader-Willi syndrome (PWS) is a multisystem genetic imprinting disorder mainly characterized by hyperphagia and childhood obesity. Extensive structural alterations are expected in PWS patients, and their influence on brain nuclei should be early and profound. To date, few studies have investigated brain nuclei in children with PWS, although functional and structural alterations of the cortex have been reported widely. Methods: In the current study, we used T1-weighted magnetic resonance imaging to investigate alterations in brain nuclei by three automated analysis methods: shape analysis to evaluate the shape of 14 cerebral nuclei (bilateral thalamus, caudate, putamen, globus pallidus, hippocampus, amygdala, and nucleus accumbens), automated segmentation methods integrated in Freesurfer 7.2.0 to investigate the volume of hypothalamic subregions, and region of interest-based analysis to investigate the volume of deep cerebellar nuclei (DCN). Twelve age- and sex-matched children with PWS, 18 obese children without PWS (OB) and 18 healthy controls participated in this study. Results: Compared with control and OB individuals, the PWS group exhibited significant atrophy in the bilateral thalamus, pallidum, hippocampus, amygdala, nucleus accumbens, right caudate, bilateral hypothalamus (left anterior-inferior, bilateral posterior, and bilateral tubular inferior subunits) and bilateral DCN (dentate, interposed, and fastigial nuclei), whereas no significant difference was found between the OB and control groups. Discussion: Based on our evidence, we suggested that alterations in brain nuclei influenced by imprinted genes were associated with clinical manifestations of PWS, such as eating disorders, cognitive disability and endocrine abnormalities, which were distinct from the neural mechanisms of obese children.
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Affiliation(s)
- Ning Wu
- Department of Medical Imaging, Yanjing Medical College, Capital Medical University, Beijing, China
| | - Huan Yu
- Department of Radiology, Liangxiang Hospital, Beijing, China
| | - Mingze Xu
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
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14
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Banwinkler M, Dzialas V, Hoenig MC, van Eimeren T. Gray Matter Volume Loss in Proposed Brain-First and Body-First Parkinson's Disease Subtypes. Mov Disord 2022; 37:2066-2074. [PMID: 35943058 DOI: 10.1002/mds.29172] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Revised: 06/24/2022] [Accepted: 07/10/2022] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND α-Synuclein pathology is associated with neuronal degeneration in Parkinson's disease (PD) and considered to sequentially spread across the brain (Braak stages). According to a new hypothesis of distinct α-synuclein spreading directions based on the initial site of pathology, the "brain-first" spreading subtype would be associated with a more asymmetric cerebral and nigrostriatal pathology than the "body-first" subtype. OBJECTIVE Here, we tested if proposed markers of brain-first PD (ie, higher dopamine transporter [DaT] asymmetry; absence of rapid eye movement sleep behavior disorder [RBD]) are associated with a greater or more asymmetric reduction in gray matter volume (GMV) in comparison to body-first PD. METHODS Data of 255 de novo PD patients and 110 healthy controls (HCs) were retrieved from the Parkinson's Progression Markers Initiative. Structural magnetic resonance images were preprocessed, and GMVs and their hemispherical asymmetry were obtained for each of the neuropathologically defined Braak stages. Group and correlation comparisons were performed to assess differences in GMV and GMV asymmetry between PD subtypes. RESULTS PD patients demonstrated significantly smaller bilateral GMVs compared to HCs, in a pattern denoting stage-dependent disease-related brain atrophy. However, the degree of putaminal DaT asymmetry was not associated with reduced GMV or higher GMV asymmetry. Furthermore, RBD-negative and RBD-positive patients did not demonstrate a significant difference in GMV or GMV asymmetry. CONCLUSIONS Our findings suggest that putative brain-first and body-first patients do not present diverging brain atrophy patterns. Although certainly not disproving the brain-first/body-first spreading hypothesis, this study fails to provide evidence in support of it. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Magdalena Banwinkler
- Faculty of Medicine and University Hospital Cologne, Department of Nuclear Medicine, University of Cologne, Cologne, Germany
| | - Verena Dzialas
- Faculty of Medicine and University Hospital Cologne, Department of Nuclear Medicine, University of Cologne, Cologne, Germany.,Faculty of Mathematics and Natural Sciences, University of Cologne, Cologne, Germany
| | | | - Merle C Hoenig
- Faculty of Medicine and University Hospital Cologne, Department of Nuclear Medicine, University of Cologne, Cologne, Germany.,Institute for Neuroscience and Medicine II, Molecular Organization of the Brain, Research Center Juelich, Juelich, Germany
| | - Thilo van Eimeren
- Faculty of Medicine and University Hospital Cologne, Department of Nuclear Medicine, University of Cologne, Cologne, Germany.,Faculty of Medicine and University Hospital Cologne, Department of Neurology, University of Cologne, Cologne, Germany
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15
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Yoo HS, Lee EC, Chung SJ, Ye BS, Sohn YH, Seong JK, Lee PH. Contracted thalamic shape is associated with early development of levodopa-induced dyskinesia in Parkinson's disease. Sci Rep 2022; 12:12631. [PMID: 35879381 PMCID: PMC9314442 DOI: 10.1038/s41598-022-16747-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Accepted: 07/14/2022] [Indexed: 01/18/2023] Open
Abstract
Levodopa-induced dyskinesia (LID), a long-term motor complication in Parkinson’s disease (PD), is attributable to both presynaptic and postsynaptic mechanisms. However, no studies have evaluated the baseline structural changes associated with LID at a subcortical level in PD. A total of 116 right-handed PD patients were recruited and based on the LID latency of 5 years, we classified patients into those vulnerable to LID (PD-vLID, n = 49) and those resistant to LID (PD-rLID, n = 67). After adjusting for covariates including dopamine transporter (DAT) availability of the posterior putamen, we compared the subcortical shape between the groups and investigated its association with the onset of LID. The PD-vLID group had lower DAT availability in the posterior putamen, higher parkinsonian motor deficits, and faster increment in levodopa equivalent dose than the PD-rLID group. The PD-vLID group had significant inward deformation in the right thalamus compared to the PD-rLID group. Inward deformation in the thalamus was associated with an earlier onset of LID at baseline. This study suggests that independent of presynaptic dopamine depletion, the thalamus is a major neural substrate for LID and that a contracted thalamic shape at baseline is closely associated with an early development of LID.
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Affiliation(s)
- Han Soo Yoo
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Eun-Chong Lee
- School of Biomedical Engineering, Korea University, 145, Anam-ro, Seongbuk-gu, Seoul, 02841, South Korea
| | - Seok Jong Chung
- Department of Neurology, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin, South Korea
| | - Byoung Seok Ye
- Department of Neurology, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea
| | - Young H Sohn
- Department of Neurology, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea
| | - Joon-Kyung Seong
- School of Biomedical Engineering, Korea University, 145, Anam-ro, Seongbuk-gu, Seoul, 02841, South Korea. .,Department of Artificial Intelligence, Korea University, Seoul, South Korea. .,Interdisciplinary Program in Precision Public Health, Korea University, Seoul, South Korea.
| | - Phil Hyu Lee
- Department of Neurology, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea. .,Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul, South Korea.
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16
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Sanmartino F, Cruz-Gómez ÁJ, Rashid-López R, Lozano-Soto E, López-Sosa F, Zuazo A, Riqué-Dormido J, Espinosa-Rosso R, González-Rosa JJ. Subthalamic Beta Activity in Parkinson's Disease May Be Linked to Dorsal Striatum Gray Matter Volume and Prefrontal Cortical Thickness: A Pilot Study. Front Neurol 2022; 13:799696. [PMID: 35401426 PMCID: PMC8985754 DOI: 10.3389/fneur.2022.799696] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Accepted: 02/24/2022] [Indexed: 11/30/2022] Open
Abstract
Background Excessive oscillations at beta frequencies (13–35 Hz) in the subthalamic nucleus (STN) represent a pathophysiological hallmark of Parkinson's disease (PD), which correlates well with parkinsonian symptoms and is reduced in response to standard disease treatments. However, the association of disease-specific regional gray matter (GM) atrophy or cortical thickness (CT) with the presence of STN beta oscillatory activity has been poorly investigated but is of relevance given the potential of these variables for extracting information about PD pathophysiology. This exploratory study investigated the involvement of regional GM volume and CT in the basal ganglia-cortical network and its potential association with the presence of STN beta oscillatory activity in PD. Methods We acquired preoperative GM densities on T1-weighted magnetic resonance imaging scans and we carried out regional estimation of GM volume and CT. LFP activities from the STN were recorded post-operatively in 7 cognitively preserved PD patients off dopaminergic medication undergoing deep-brain stimulation surgery. Oscillatory beta power was determined by power spectral density of 4-min resting state STN LFP activity. Spearman partial correlations and regression analysis were used to screen the presence of STN beta power for their relationship with GM volume and CT measurements. Results After controlling for the effects of age, educational level, and disease duration, and after correcting for multiple testing, enhanced STN beta power showed significant and negative correlations between, first, volume of the right putamen and left caudate nucleus, and second, smaller CT in frontal regions involving the left rostral middle frontal gyrus (MFG) and left medial orbitofrontal gyrus. A lower volume in the right putamen and a lower CT in the left MFG demonstrated the strongest associations with increased STN beta power. Conclusions These tentative results seem to suggest that STN LFP beta frequencies may be mainly linked to different but ongoing parallel neurodegenerative processes, on the one hand, to GM volume reduction in dorsal striatum, and on the other hand, to CT reduction of prefrontal-“associative” regions. These findings could further delineate the brain structural interactions underpinning the exaggerated STN beta activity commonly observed in PD patients.
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Affiliation(s)
- Florencia Sanmartino
- Department of Psychology, University of Cadiz, Cádiz, Spain.,Psychophysiology and Neuroimaging Group, Institute of Biomedical Research Cadiz (INiBICA), Cádiz, Spain
| | - Álvaro J Cruz-Gómez
- Department of Psychology, University of Cadiz, Cádiz, Spain.,Psychophysiology and Neuroimaging Group, Institute of Biomedical Research Cadiz (INiBICA), Cádiz, Spain
| | - Raúl Rashid-López
- Psychophysiology and Neuroimaging Group, Institute of Biomedical Research Cadiz (INiBICA), Cádiz, Spain.,Department of Neurology, Puerta del Mar University Hospital, Cádiz, Spain
| | - Elena Lozano-Soto
- Department of Psychology, University of Cadiz, Cádiz, Spain.,Psychophysiology and Neuroimaging Group, Institute of Biomedical Research Cadiz (INiBICA), Cádiz, Spain
| | - Fernando López-Sosa
- Psychophysiology and Neuroimaging Group, Institute of Biomedical Research Cadiz (INiBICA), Cádiz, Spain
| | - Amaya Zuazo
- Department of Radiodiagnostic and Medical Imaging, Puerta del Mar University Hospital, Cádiz, Spain
| | - Jesús Riqué-Dormido
- Department of Neurosurgery, Puerta del Mar University Hospital, Cádiz, Spain
| | - Raúl Espinosa-Rosso
- Psychophysiology and Neuroimaging Group, Institute of Biomedical Research Cadiz (INiBICA), Cádiz, Spain.,Department of Neurology, Puerta del Mar University Hospital, Cádiz, Spain.,Department of Neurology, Jerez de la Frontera University Hospital, Jerez de la Frontera, Spain
| | - Javier J González-Rosa
- Department of Psychology, University of Cadiz, Cádiz, Spain.,Psychophysiology and Neuroimaging Group, Institute of Biomedical Research Cadiz (INiBICA), Cádiz, Spain
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Mining imaging and clinical data with machine learning approaches for the diagnosis and early detection of Parkinson's disease. NPJ Parkinsons Dis 2022; 8:13. [PMID: 35064123 PMCID: PMC8783003 DOI: 10.1038/s41531-021-00266-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Accepted: 12/10/2021] [Indexed: 12/14/2022] Open
Abstract
Parkinson’s disease (PD) is a common, progressive, and currently incurable neurodegenerative movement disorder. The diagnosis of PD is challenging, especially in the differential diagnosis of parkinsonism and in early PD detection. Due to the advantages of machine learning such as learning complex data patterns and making inferences for individuals, machine-learning techniques have been increasingly applied to the diagnosis of PD, and have shown some promising results. Machine-learning-based imaging applications have made it possible to help differentiate parkinsonism and detect PD at early stages automatically in a number of neuroimaging studies. Comparative studies have shown that machine-learning-based SPECT image analysis applications in PD have outperformed conventional semi-quantitative analysis in detecting PD-associated dopaminergic degeneration, performed comparably well as experts’ visual inspection, and helped improve PD diagnostic accuracy of radiologists. Using combined multi-modal (imaging and clinical) data in these applications may further enhance PD diagnosis and early detection. To integrate machine-learning-based diagnostic applications into clinical systems, further validation and optimization of these applications are needed to make them accurate and reliable. It is anticipated that machine-learning techniques will further help improve differential diagnosis of parkinsonism and early detection of PD, which may reduce the error rate of PD diagnosis and help detect PD at pre-motor stage to make it possible for early treatments (e.g., neuroprotective treatment) to slow down PD progression, prevent severe motor symptoms from emerging, and relieve patients from suffering.
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Gu W, He R, Su H, Ren Z, Zhang L, Yuan H, Zhang M, Ma S. Changes in the Shape and Volume of Subcortical Structures in Patients With End-Stage Renal Disease. Front Hum Neurosci 2022; 15:778807. [PMID: 34975435 PMCID: PMC8716492 DOI: 10.3389/fnhum.2021.778807] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Accepted: 11/15/2021] [Indexed: 01/22/2023] Open
Abstract
Introduction: End-stage renal disease (ESRD) typically causes changes in brain structure, and patients with ESRD often experience cognitive and sleep disorders. We aimed to assess the changes in the subcortical structure of patients with ESRD and how they are associated with cognitive and sleep disorders. Methods: We involved 36 adult patients for maintenance hemodialysis and 35 age- and gender-matched control individuals. All participants underwent neuropsychological examination and 3T magnetic resonance imaging (MRI) to acquire T1 anatomical images. The laboratory blood tests were performed in all patients with ESRD close to the time of the MR examination. We used volumetric and vertex-wise shape analysis approaches to investigate the volumes of 14 subcortical structural (e.g., bilateral accumbens, amygdala, hippocampus, caudate, globus pallidus, putamen, and thalamus) abnormalities in the two groups. Analyses of partial correlations and shape correlations were performed in order to identify the associations between subcortical structure, cognition, and sleep quality in patients with ESRD. Results: The volumetric analysis showed that compared with the healthy control group, patients with ESRD had less bilateral thalamus (left: p < 0.001; right: p < 0.001), bilateral accumbens (left: p < 0.001; right: p = 0.001), and right amygdala (p = 0.002) volumes. In the vertex-wise shape analysis, patients with ESRD had abnormal regional surface atrophy in the bilateral thalamus, right accumbens, left putamen, and bilateral caudate. Moreover, the Montreal Cognitive Assessment (MoCA) score was associated with volume reduction in the bilateral thalamus (left: Spearman ρ = 0.427, p = 0.009; right: ρ = 0.319, p = 0.018), and the Pittsburgh Sleep Quality Index (PSQI) score was associated with volume reduction in the bilateral accumbens (left: ρ = −0.546, p = 0.001; right: ρ = −0.544, p = 0.001). In vertex-wise shape correlation analysis, there was a positive significant correlation between regional shape deformations on the bilateral thalamus and MoCA score in patients with ESRD. Conclusion: Our study suggested that patients with ESRD have subcortical structural atrophy, which is related to impaired cognitive performance and sleep disturbances. These findings may help to further understand the underlying neural mechanisms of brain changes in patients with ESRD.
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Affiliation(s)
- Wen Gu
- Department of Medical Imaging, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Ronghua He
- Department of Radiology, Baoji Center Hospital, Baoji, China
| | - Hang Su
- Department of Radiology, Baoji Center Hospital, Baoji, China
| | - Zhuanqin Ren
- Department of Radiology, Baoji Center Hospital, Baoji, China
| | - Lei Zhang
- Department of Medical Imaging, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Department of Radiology, Baoji High-Tech Hospital, Baoji, China
| | - Huijie Yuan
- Department of Medical Imaging, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Ming Zhang
- Department of Medical Imaging, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Shaohui Ma
- Department of Medical Imaging, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
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Betrouni N, Moreau C, Rolland AS, Carrière N, Viard R, Lopes R, Kuchcinski G, Eusebio A, Thobois S, Hainque E, Hubsch C, Rascol O, Brefel C, Drapier S, Giordana C, Durif F, Maltête D, Guehl D, Hopes L, Rouaud T, Jarraya B, Benatru I, Tranchant C, Tir M, Chupin M, Bardinet E, Defebvre L, Corvol JC, Devos D. Can Dopamine Responsiveness Be Predicted in Parkinson's Disease Without an Acute Administration Test? JOURNAL OF PARKINSON'S DISEASE 2022; 12:2179-2190. [PMID: 35871363 DOI: 10.3233/jpd-223334] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
BACKGROUND Dopamine responsiveness (dopa-sensitivity) is an important parameter in the management of patients with Parkinson's disease (PD). For quantification of this parameter, patients undergo a challenge test with acute Levodopa administration after drug withdrawal, which may lead to patient discomfort and use of significant resources. OBJECTIVE Our objective was to develop a predictive model combining clinical scores and imaging. METHODS 350 patients, recruited by 13 specialist French centers and considered for deep brain stimulation, underwent an acute L-dopa challenge (dopa-sensitivity > 30%), full assessment, and MRI investigations, including T1w and R2* images. Data were randomly divided into a learning base from 10 centers and data from the remaining centers for testing. A machine selection approach was applied to choose the optimal variables and these were then used in regression modeling. Complexity of the modelling was incremental, while the first model considered only clinical variables, the subsequent included imaging features. The performances were evaluated by comparing the estimated values and actual valuesResults:Whatever the model, the variables age, sex, disease duration, and motor scores were selected as contributors. The first model used them and the coefficients of determination (R2) was 0.60 for the testing set and 0.69 in the learning set (p < 0.001). The models that added imaging features enhanced the performances: with T1w (R2 = 0.65 and 0.76, p < 0.001) and with R2* (R2 = 0.60 and 0.72, p < 0.001). CONCLUSION These results suggest that modeling is potentially a simple way to estimate dopa-sensitivity, but requires confirmation in a larger population, including patients with dopa-sensitivity < 30.
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Affiliation(s)
- Nacim Betrouni
- University Lille, INSERM, CHU Lille, U1172 - LilNCog - Lille Neuroscience & Cognition, LICEND, Lille, France
| | - Caroline Moreau
- University Lille, INSERM, CHU Lille, U1172 - LilNCog - Lille Neuroscience & Cognition, LICEND, Lille, France
- CHU Lille, Neurology and Movement Disorders Department, Reference Center for Parkinson's Disease, Lille, France; NS-Park French Network
| | - Anne-Sophie Rolland
- University Lille, INSERM, CHU Lille, U1172 - LilNCog - Lille Neuroscience & Cognition, LICEND, Lille, France
| | - Nicolas Carrière
- University Lille, INSERM, CHU Lille, U1172 - LilNCog - Lille Neuroscience & Cognition, LICEND, Lille, France
- CHU Lille, Neurology and Movement Disorders Department, Reference Center for Parkinson's Disease, Lille, France; NS-Park French Network
- University Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, US 41 - UMS 2014 - PLBS, Lille, France; NS-Park French Network
| | - Romain Viard
- University Lille, INSERM, CHU Lille, U1172 - LilNCog - Lille Neuroscience & Cognition, LICEND, Lille, France
- University Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, US 41 - UMS 2014 - PLBS, Lille, France; NS-Park French Network
| | - Renaud Lopes
- University Lille, INSERM, CHU Lille, U1172 - LilNCog - Lille Neuroscience & Cognition, LICEND, Lille, France
- University Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, US 41 - UMS 2014 - PLBS, Lille, France; NS-Park French Network
| | - Gregory Kuchcinski
- University Lille, INSERM, CHU Lille, U1172 - LilNCog - Lille Neuroscience & Cognition, LICEND, Lille, France
- CHU Lille, Neuroradioloy Department, Lille, France
| | - Alexandre Eusebio
- Aix Marseille Universitë, AP-HM, Hôpital de La Timone, Service de Neurologie et Pathologie du Mouvement, UMR CNRS 7289, Institut de Neuroscience de La Timone, Marseille, France; NS-Park French Network
| | - Stephane Thobois
- Hospices Civils de Lyon, Hôpital Neurologique Pierre Wertheimer, Neurologie C, Bron, France
| | - Elodie Hainque
- Dëpartement de Neurologie, Hôpital Pitië-Salpêtrière, AP-HP, Paris, France; NS-Park French Network
| | - Cecile Hubsch
- Fondation Ophtalmologique A de Rothschild, Unitë James Parkinson, Paris, France; NS-Park French Network
| | - Olivier Rascol
- University of Toulouse 3, University Hospital of Toulouse, INSERM, Departments of Neuroscience and Clinical Pharmacology, Clinical Investigation Center CIC 1436, Toulouse Parkinson Expert Center, NS-NeuroToul Center of Excellence for Neurodegenerative Disorders (COEN), Toulouse, France; NS-Park French Network
| | - Christine Brefel
- University of Toulouse 3, University Hospital of Toulouse, INSERM, Departments of Neuroscience and Clinical Pharmacology, Clinical Investigation Center CIC 1436, Toulouse Parkinson Expert Center, NS-NeuroToul Center of Excellence for Neurodegenerative Disorders (COEN), Toulouse, France; NS-Park French Network
| | - Sophie Drapier
- Service de Neurologie, CHU Pont Chaillou, 2 rue Henri le Guilloux, Rennes cedex, France; NS-Park French Network
| | - Caroline Giordana
- Universitë Clermont Auvergne, EA7280, Clermont-Ferrand University Hospital, Neurology Department, Clermont-Ferrand, France; NS-Park French Network
| | - Franck Durif
- Universitë Clermont Auvergne, EA7280, Clermont-Ferrand University Hospital, Neurology Department, Clermont-Ferrand, France; NS-Park French Network
| | - David Maltête
- Department of Neurology, Rouen University Hospital and University of Rouen, France; INSERM U1239, Laboratory of Neuronal and Neuroendocrine Differentiation and Communication, Mont-Saint-Aignan, France; NS-Park French Network
| | - Dominique Guehl
- Service d'Explorations Fonctionnelles du Système Nerveux, Institut des Maladies Neurodëgënëratives Cliniques, CHU de Bordeaux, Bordeaux, France; NS-Park French Network
| | - Lucie Hopes
- Neurology Department, Nancy University Hospital, Nancy, France; NS-Park French Network
| | - Tiphaine Rouaud
- Clinique Neurologique, Hôpital Guillaume et Renë Laennec, Boulevard Jacques Monod, Nantes Cedex, France; NS-Park French Network
| | - Bechir Jarraya
- Movement Disorders Unit, Foch Hospital, Universitë Paris-Saclay (UVSQ), INSERM U992, NeuroSpin, CEA Paris-Saclay, Suresnes, France; NS-Park French Network
| | - Isabelle Benatru
- Service de Neurologie, Centre Expert Parkinson, CIC-INSERM 1402, CHU Poitiers, Poitiers, France; NS-Park French Network
| | - Christine Tranchant
- Service de Neurologie, Hôpitaux Universitaires de Strasbourg, Strasbourg, France; Institut de Gënëtique et de Biologie Molëculaire et Cellulaire (IGBMC), INSERM-U964/CNRS-UMR7104/Universitë de Strasbourg, Illkirch, France; Fëdëration de Mëdecine Translationnelle de Strasbourg (FMTS), Universitë de Strasbourg, Strasbourg, France; NS-Park French Network
| | - Melissa Tir
- Department of Neurosurgery, Amiens University Hospital, Amiens, France; Medical Imaging Unit, Amiens University Hospital, Amiens, France; BioFlowImage Research Group, Jules Verne University of Picardie, Amiens, France; NS-Park French Network
| | - Marie Chupin
- CATI, Institut du Cerveau et de le Moelle Epinière, ICM, INSERM U1127, CNRS UMR7225, Sorbonne Universitë, Paris, France
| | - Eric Bardinet
- Institut du Cerveau et de le Moelle Epinière, ICM, INSERM U1127, CNRS UMR7225, Sorbonne Universitë, Paris, France
| | - Luc Defebvre
- University Lille, INSERM, CHU Lille, U1172 - LilNCog - Lille Neuroscience & Cognition, LICEND, Lille, France
- CHU Lille, Neurology and Movement Disorders Department, Reference Center for Parkinson's Disease, Lille, France; NS-Park French Network
| | - Jean-Christophe Corvol
- Dëpartement de Neurologie, Hôpital Pitië-Salpêtrière, AP-HP, Paris, France; NS-Park French Network
- Facultë de Mëdecine de Sorbonne Universitë, UMR S 1127, INSERM U 1127, and CNRS UMR 7225, and Institut du Cerveau et de la Moëlle Epinière, Paris, France; NS-Park French Network
| | - David Devos
- University Lille, INSERM, CHU Lille, U1172 - LilNCog - Lille Neuroscience & Cognition, LICEND, Lille, France
- CHU Lille, Neurology and Movement Disorders Department, Reference Center for Parkinson's Disease, Lille, France; NS-Park French Network
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20
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Sivaranjini S, Sujatha CM. Morphological analysis of subcortical structures for assessment of cognitive dysfunction in Parkinson's disease using multi-atlas based segmentation. Cogn Neurodyn 2021; 15:835-845. [PMID: 34603545 PMCID: PMC8448821 DOI: 10.1007/s11571-021-09671-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Revised: 01/27/2021] [Accepted: 02/25/2021] [Indexed: 12/16/2022] Open
Abstract
Cognitive impairment in Parkinson's Disease (PD) is the most prevalent non-motor symptom that requires analysis of anatomical associations to cognitive decline in PD. The objective of this study is to analyse the morphological variations of the subcortical structures to assess cognitive dysfunction in PD. In this study, T1 MR images of 58 Healthy Control (HC) and 135 PD subjects categorised as 91 Cognitively normal PD (NC-PD), 25 PD with Mild Cognitive Impairment (PD-MCI) and 19 PD with Dementia (PD-D) subjects, based on cognitive scores are utilised. The 132 anatomical regions are segmented using spatially localized multi-atlas model and volumetric analysis is carried out. The morphological alterations through textural features are captured to differentiate among the HC and PD subjects under different cognitive domains. The volumetric differences in the segmented subcortical structures of accumbens, amygdala, caudate, putamen and thalamus are able to predict cognitive impairment in PD. The volumetric distribution of the subcortical structures in PD-MCI subjects exhibit an overlap with the HC group due to lack of spatial specificity in their atrophy levels. The 3D GLCM features extracted from the significant subcortical structures could discriminate HC, NC-PD, PD-MCI and PD-D subjects with better classification accuracies. The disease related atrophy levels of the subcortical structures captured through morphological analysis provide sensitive evaluation of cognitive impairment in PD.
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Affiliation(s)
- S. Sivaranjini
- Department of Electronics and Communication Engineering, College of Engineering (CEG), Anna University, Chennai, India
| | - C. M. Sujatha
- Department of Electronics and Communication Engineering, College of Engineering (CEG), Anna University, Chennai, India
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21
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Owens-Walton C, Jakabek D, Power BD, Walterfang M, Hall S, van Westen D, Looi JCL, Shaw M, Hansson O. Structural and functional neuroimaging changes associated with cognitive impairment and dementia in Parkinson's disease. Psychiatry Res Neuroimaging 2021; 312:111273. [PMID: 33892387 DOI: 10.1016/j.pscychresns.2021.111273] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/04/2020] [Revised: 12/09/2020] [Accepted: 01/12/2021] [Indexed: 12/29/2022]
Abstract
This study seeks a better understanding of possible pathophysiological mechanisms associated with cognitive impairment and dementia in Parkinson's disease using structural and functional MRI. We investigated resting-state functional connectivity of important subdivisions of the caudate nucleus, putamen and thalamus, and also how the morphology of these structures are impacted in the disorder. We found cognitively unimpaired Parkinson's disease subjects (n = 33), compared to controls (n = 26), display increased functional connectivity of the dorsal caudate, anterior putamen and mediodorsal thalamic subdivisions with areas across the frontal lobe, as well as reduced functional connectivity of the dorsal caudate with posterior cortical and cerebellar regions. Compared to cognitively unimpaired subjects, those with mild cognitive impairment (n = 22) demonstrated reduced functional connectivity of the mediodorsal thalamus with the paracingulate cortex, while also demonstrating increased functional connectivity of the mediodorsal thalamus with the posterior cingulate cortex, compared to subjects with dementia (n = 17). Extensive volumetric and surface-based deflation was found in subjects with dementia compared to cognitively unimpaired Parkinson's disease participants and controls. Our research suggests that structures within basal ganglia-thalamocortical circuits are implicated in cognitive impairment and dementia in Parkinson's disease, with cognitive impairment and dementia associated with a breakdown in functional connectivity of the mediodorsal thalamus with para- and posterior cingulate regions of the brain respectively.
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Affiliation(s)
- Conor Owens-Walton
- Research Centre for the Neurosciences of Ageing, Academic Unit of Psychiatry and Addiction Medicine, School of Clinical Medicine, Medical School, Australian National University, Canberra, Australia.
| | - David Jakabek
- Graduate School of Medicine, University of Wollongong, Wollongong, Australia
| | - Brian D Power
- School of Medicine, The University of Notre Dame, Fremantle, Australia; Clinical Research Centre, North Metropolitan Health Service - Mental Health, Perth, Australia
| | - Mark Walterfang
- Neuropsychiatry Unit, Royal Melbourne Hospital, Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Australia; Florey Institute of Neurosciences and Mental Health, University of Melbourne, Melbourne, Australia
| | - Sara Hall
- Memory Clinic, Skåne University Hospital, Malmö, Sweden; Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Danielle van Westen
- Centre for Medical Imaging and Physiology, Skåne University Hospital, Lund, Sweden; Diagnostic Radiology, Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Jeffrey C L Looi
- Research Centre for the Neurosciences of Ageing, Academic Unit of Psychiatry and Addiction Medicine, School of Clinical Medicine, Medical School, Australian National University, Canberra, Australia; Neuropsychiatry Unit, Royal Melbourne Hospital, Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Australia
| | - Marnie Shaw
- College of Engineering and Computer Science, The Australian National University, Canberra, Australia
| | - Oskar Hansson
- Memory Clinic, Skåne University Hospital, Malmö, Sweden; Department of Clinical Sciences, Lund University, Malmö, Sweden
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22
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A longitudinal study of the association between basal ganglia volumes and psychomotor symptoms in subjects with late life depression undergoing ECT. Transl Psychiatry 2021; 11:199. [PMID: 33795659 PMCID: PMC8017007 DOI: 10.1038/s41398-021-01314-w] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Revised: 02/22/2021] [Accepted: 03/11/2021] [Indexed: 12/14/2022] Open
Abstract
Psychomotor dysfunction (PMD) is a core element and key contributor to disability in late life depression (LLD), which responds well to electroconvulsive therapy (ECT). The neurobiology of PMD and its response to ECT are not well understood. We hypothesized that PMD in LLD is associated with lower striatal volume, and that striatal volume increase following ECT explains PMD improvement. We analyzed data from a two-center prospective cohort study of 110 LLD subjects (>55 years) receiving ECT. Brain MRI and assessment of mood, cognition, and PMD was performed 1 week before, 1 week after, and 6 months after ECT. Volumetry of the caudate nucleus, putamen, globus pallidus, and nucleus accumbens was derived from automatically segmented brain MRIs using Freesurfer®. Linear multiple regression analyses were used to study associations between basal ganglia volume and PMD. Brain MRI was available for 66 patients 1 week post ECT and in 22 patients also six months post ECT. Baseline PMD was associated with a smaller left caudate nucleus. One week after ECT, PMD improved and volume increases were detected bilaterally in the caudate nucleus and putamen, and in the right nucleus accumbens. Improved PMD after ECT did not relate to the significant volume increases in these structures, but was predicted by a nonsignificant volume change in the right globus pallidus. No volume differences were detected 6 months after ECT, compared to baseline. Although PMD is related to lower striatal volume in LLD, ECT-induced increase of striatal volume does not explain PMD improvement.
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23
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Texture-based markers from structural imaging correlate with motor handicap in Parkinson's disease. Sci Rep 2021; 11:2724. [PMID: 33526820 PMCID: PMC7851138 DOI: 10.1038/s41598-021-81209-4] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Accepted: 12/28/2020] [Indexed: 01/17/2023] Open
Abstract
There is a growing need for surrogate biomarkers for Parkinson’s disease (PD). Structural analysis using magnetic resonance imaging with T1-weighted sequences has the potential to quantify histopathological changes. Degeneration is typically measured by the volume and shape of morphological changes. However, these changes appear late in the disease, preventing their use as surrogate markers. We investigated texture changes in 108 individuals, divided into three groups, matched in terms of sex and age: (1) healthy controls (n = 32); (2) patients with early-stage PD (n = 39); and (3) patients with late-stage PD and severe L-dopa-related complications (n = 37). All patients were assessed in off-treatment conditions. Statistical analysis of first- and second-order texture features was conducted in the substantia nigra, striatum, thalamus and sub-thalamic nucleus. Regions of interest volumetry and voxel-based morphometry were performed for comparison. Significantly different texture features were observed between the three populations, with some showing a gradual linear progression between the groups. The volumetric changes in the two PD patient groups were not significantly different. Texture features were significantly associated with clinical scores for motor handicap. These results suggest that texture features, measured in the nigrostriatal pathway at PD diagnosis, may be useful in predicting clinical progression of motor handicap.
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24
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MR Image Synthesis Using Generative Adversarial Networks for Parkinson’s Disease Classification. ACTA ACUST UNITED AC 2020. [DOI: 10.1007/978-981-15-4992-2_30] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/21/2023]
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25
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Peralta M, Baxter JSH, Khan AR, Haegelen C, Jannin P. Striatal shape alteration as a staging biomarker for Parkinson's Disease. Neuroimage Clin 2020; 27:102272. [PMID: 32473544 PMCID: PMC7260673 DOI: 10.1016/j.nicl.2020.102272] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Revised: 04/20/2020] [Accepted: 04/21/2020] [Indexed: 12/13/2022]
Abstract
Parkinson's Disease provokes alterations of subcortical deep gray matter, leading to subtle changes in the shape of several subcortical structures even before the manifestation of motor and non-motor clinical symptoms. We used an automated registration and segmentation pipeline to measure this structural alteration in one early and one advanced Parkinson's Disease (PD) cohorts, one prodromal stage cohort and one healthy control cohort. These structural alterations are then passed to a machine learning pipeline to classify these populations. Our workflow is able to distinguish different stages of PD based solely on shape analysis of the bilateral caudate nucleus and putamen, with balanced accuracies in the range of 59% to 85%. Furthermore, we compared the significance of each of these subcortical structure, compared the performances of different classifiers on this task, thus quantifying the informativeness of striatal shape alteration as a staging bio-marker for PD.
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Affiliation(s)
- Maxime Peralta
- INSERM, LTSI - UMR 1099, University of Rennes, Rennes, France
| | - John S H Baxter
- INSERM, LTSI - UMR 1099, University of Rennes, Rennes, France
| | - Ali R Khan
- Imaging Research Laboratories, Robarts Research institute, Western University, London, Canada
| | - Claire Haegelen
- INSERM, LTSI - UMR 1099, University of Rennes, Rennes, France; CHU Rennes, Rennes, France
| | - Pierre Jannin
- INSERM, LTSI - UMR 1099, University of Rennes, Rennes, France.
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26
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Rahayel S, Gaubert M, Postuma RB, Montplaisir J, Carrier J, Monchi O, Rémillard-Pelchat D, Bourgouin PA, Panisset M, Chouinard S, Joubert S, Gagnon JF. Brain atrophy in Parkinson's disease with polysomnography-confirmed REM sleep behavior disorder. Sleep 2020; 42:5373066. [PMID: 30854555 DOI: 10.1093/sleep/zsz062] [Citation(s) in RCA: 47] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2018] [Accepted: 01/20/2019] [Indexed: 12/16/2022] Open
Abstract
We aimed to investigate cortical and subcortical brain alterations in people with Parkinson's disease with polysomnography-confirmed rapid eye movement (REM) sleep behavior disorder (RBD). Thirty people with Parkinson's disease, including 15 people with RBD, were recruited and compared with 41 healthy controls. Surface-based cortical and subcortical analyses were performed on T1-weighted images to investigate thickness and shape abnormalities between groups, and voxel-based and deformation-based morphometry were performed to investigate local volume. Correlations were performed in patients to investigate the structural correlates of motor activity during REM sleep. People with RBD showed cortical thinning in the right perisylvian and inferior temporal cortices and shape contraction in the putamen compared with people without RBD. Compared with controls, people with RBD had extensive cortical thinning and volume loss, brainstem volume was reduced, and shape contraction was found in the basal ganglia and hippocampus. In comparison to controls, people without RBD showed more restricted thinning in the sensorimotor, parietal, and occipital cortices, reduced volume in the brainstem, temporal and more posterior areas, and shape contraction in the pallidum and hippocampus. In Parkinson's disease, higher tonic and phasic REM sleep motor activity was associated with contraction of the thalamic surface, extensive cortical thinning, and subtle volume reduction in the middle temporal gyrus. In Parkinson's disease, the presence of RBD is associated with extensive cortical and subcortical abnormalities, suggesting more severe neurodegeneration in people with RBD. This provides potential neuroanatomical correlates for the more severe clinical phenotype reported in people with Parkinson's disease with RBD.
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Affiliation(s)
- Shady Rahayel
- Centre for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal, Montreal, Canada.,Department of Psychology, Université du Québec à Montréal, Montreal, Canada.,Research Centre, Institut universitaire de gériatrie de Montréal, Montreal, Canada
| | - Malo Gaubert
- Centre for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal, Montreal, Canada.,Department of Psychology, Université du Québec à Montréal, Montreal, Canada
| | - Ronald B Postuma
- Centre for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal, Montreal, Canada.,Department of Neurology, Montreal General Hospital, Montreal, Canada
| | - Jacques Montplaisir
- Centre for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal, Montreal, Canada.,Department of Psychiatry, Université de Montréal, Montreal, Canada
| | - Julie Carrier
- Centre for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal, Montreal, Canada.,Research Centre, Institut universitaire de gériatrie de Montréal, Montreal, Canada.,Department of Psychology, Université de Montréal, Montreal, Canada
| | - Oury Monchi
- Research Centre, Institut universitaire de gériatrie de Montréal, Montreal, Canada.,Department of Radiology, Radio-Oncology, and Nuclear Medicine, Université de Montréal, Montreal, Canada.,Departments of Clinical Neurosciences, Radiology, and Hotchkiss Brain Institute, University of Calgary, Calgary, Canada
| | - David Rémillard-Pelchat
- Centre for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal, Montreal, Canada.,Department of Psychology, Université du Québec à Montréal, Montreal, Canada
| | - Pierre-Alexandre Bourgouin
- Centre for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal, Montreal, Canada.,Department of Psychology, Université du Québec à Montréal, Montreal, Canada
| | - Michel Panisset
- Unité des troubles du mouvement André-Barbeau, Centre Hospitalier de l'Université de Montréal, Montreal, Canada
| | - Sylvain Chouinard
- Unité des troubles du mouvement André-Barbeau, Centre Hospitalier de l'Université de Montréal, Montreal, Canada
| | - Sven Joubert
- Research Centre, Institut universitaire de gériatrie de Montréal, Montreal, Canada.,Department of Psychology, Université de Montréal, Montreal, Canada
| | - Jean-François Gagnon
- Centre for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal, Montreal, Canada.,Research Centre, Institut universitaire de gériatrie de Montréal, Montreal, Canada
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Arribarat G, Péran P. Quantitative MRI markers in Parkinson's disease and parkinsonian syndromes. Curr Opin Neurol 2020; 33:222-229. [DOI: 10.1097/wco.0000000000000796] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
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Ryman SG, Poston KL. MRI biomarkers of motor and non-motor symptoms in Parkinson's disease. Parkinsonism Relat Disord 2020; 73:85-93. [PMID: 31629653 PMCID: PMC7145760 DOI: 10.1016/j.parkreldis.2019.10.002] [Citation(s) in RCA: 54] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Revised: 10/03/2019] [Accepted: 10/05/2019] [Indexed: 12/19/2022]
Abstract
Parkinson's disease is a heterogeneous disorder with both motor and non-motor symptoms that contribute to functional impairment. To develop effective, disease modifying treatments for these symptoms, biomarkers are necessary to detect neuropathological changes early in the disease course and monitor changes over time. Advances in MRI scan sequences and analytical techniques present numerous promising metrics to detect changes within the nigrostriatal system, implicated in the cardinal motor symptoms of the disease, and detect broader dysfunction involved in the non-motor symptoms, such as cognitive impairment. There is emerging evidence that iron sensitive, neuromelanin sensitive, diffusion sensitive, and resting state functional magnetic imaging measures can capture changes within the nigrostriatal system. Iron, neuromelanin, and diffusion sensitive measures demonstrate high specificity and sensitivity in distinguishing Parkinson's disease relative to controls, with inconsistent results differentiating Parkinson's disease relative to atypical parkinsonian disorders. They may also serve as useful monitoring biomarkers, with each possibly detecting different aspects of the disease course (early nigrosome changes versus broader substantia nigra changes). Investigations of non-motor symptoms, such as cognitive impairment, require careful consideration of the nature of cognitive deficits to characterize regional and network specific impairment. While the early, executive dysfunction observed is consistent with nigrostriatal degeneration, the memory and visuospatial impairments, the harbingers of a dementia process reflect dopaminergic independent dysfunction involving broader regions of the brain.
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Affiliation(s)
- Sephira G Ryman
- Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford University, 300 Pasteur Dr. Room A343. MC-5235, Stanford, CA, 94305, USA.
| | - Kathleen L Poston
- Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford University, 300 Pasteur Dr. Room A343. MC-5235, Stanford, CA, 94305, USA.
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29
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Gong L, Li H, Yang D, Peng Y, Liu D, Zhong M, Zhang B, Xu R, Kang J. Striatum Shape Hypertrophy in Early Stage Parkinson's Disease With Excessive Daytime Sleepiness. Front Neurosci 2020; 13:1353. [PMID: 31992965 PMCID: PMC6964599 DOI: 10.3389/fnins.2019.01353] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2019] [Accepted: 12/02/2019] [Indexed: 12/16/2022] Open
Abstract
INTRODUCTION Excessive daytime sleepiness (EDS) is one of the common and burdensome non-motor symptoms of Parkinson's disease (PD). However, the underlying neuropathology mechanism in PD patients with EDS (PD-EDS) remains unclear. The present study aims to delineate potential locations of structural alteration of subcortical regions in early stage and drug-naïve PD-EDS. METHODS The study had 252 patients with PD and 92 matched healthy controls (HC). EDS was estimated with the Epworth Sleepiness Scale, with a cutoff of 10. Ultimately, 59 patients were considered as PD-EDS. The remaining 193 were PD patients without EDS (PD-nEDS). FMRIB's Integrated Registration and Segmentation Tool (FIRST) was employed to assess the volumetric and surface alterations of subcortical nuclei in PD and PD-EDS. RESULTS Volumetric analyses found no difference in the subcortical nucleus volume between PD and HC, or PD-EDS and PD-nEDS groups. The shape analyses revealed the local atrophic changes in bilateral caudate and right putamen in patients with PD. In addition, the hypertrophic changes were located in the right putamen and left pallidum in PD-EDS than in PD-nEDS. CONCLUSION Our findings revealed the regional hypertrophy of the striatum in PD-EDS. Our results indicate that local hypertrophic striatum would be a valuable early biomarker for detecting the alteration in PD-EDS. The shape analysis contributes valuable information when investigating PD-EDS.
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Affiliation(s)
- Liang Gong
- Department of Neurology, Chengdu Second People’s Hospital, Chengdu, China
| | - Huaisu Li
- Department of Neurology, Chengdu Second People’s Hospital, Chengdu, China
| | - Dan Yang
- Department of Neurology, Chengdu Second People’s Hospital, Chengdu, China
| | - Yinwei Peng
- Department of Neurology, Chengdu Second People’s Hospital, Chengdu, China
| | - Duan Liu
- Department of Neurology, Chengdu Second People’s Hospital, Chengdu, China
| | - Ming Zhong
- Department of Neurology, Chengdu Second People’s Hospital, Chengdu, China
| | - Bei Zhang
- Department of Neurology, Chengdu Second People’s Hospital, Chengdu, China
| | - Ronghua Xu
- Department of Neurology, Chengdu Second People’s Hospital, Chengdu, China
| | - Jian Kang
- Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China
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Differentiation of multiple system atrophy from Parkinson's disease by structural connectivity derived from probabilistic tractography. Sci Rep 2019; 9:16488. [PMID: 31712681 PMCID: PMC6848175 DOI: 10.1038/s41598-019-52829-8] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2019] [Accepted: 10/02/2019] [Indexed: 02/06/2023] Open
Abstract
Recent studies combining diffusion tensor-derived metrics and machine learning have shown promising results in the discrimination of multiple system atrophy (MSA) and Parkinson’s disease (PD) patients. This approach has not been tested using more complex methodologies such as probabilistic tractography. The aim of this work is assessing whether the strength of structural connectivity between subcortical structures, measured as the number of streamlines (NOS) derived from tractography, can be used to classify MSA and PD patients at the single-patient level. The classification performance of subcortical FA and MD was also evaluated to compare the discriminant ability between diffusion tensor-derived metrics and NOS. Using diffusion-weighted images acquired in a 3 T MRI scanner and probabilistic tractography, we reconstructed the white matter tracts between 18 subcortical structures from a sample of 54 healthy controls, 31 MSA patients and 65 PD patients. NOS between subcortical structures were compared between groups and entered as features into a machine learning algorithm. Reduced NOS in MSA compared with controls and PD were found in connections between the putamen, pallidum, ventral diencephalon, thalamus, and cerebellum, in both right and left hemispheres. The classification procedure achieved an overall accuracy of 78%, with 71% of the MSA subjects and 86% of the PD patients correctly classified. NOS features outperformed the discrimination performance obtained with FA and MD. Our findings suggest that structural connectivity derived from tractography has the potential to correctly distinguish between MSA and PD patients. Furthermore, NOS measures obtained from tractography might be more useful than diffusion tensor-derived metrics for the detection of MSA.
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31
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Yoo HS, Lee EC, Chung SJ, Lee YH, Lee SG, Yun M, Lee PH, Sohn YH, Seong JK, Ye BS. Effects of Alzheimer's disease and Lewy body disease on subcortical atrophy. Eur J Neurol 2019; 27:318-326. [PMID: 31487756 DOI: 10.1111/ene.14080] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2019] [Accepted: 08/21/2019] [Indexed: 11/30/2022]
Abstract
BACKGROUND AND PURPOSE Subcortical structures are affected by neurodegeneration in Alzheimer's disease (AD) and Lewy body disease (LBD). Although the co-occurrence of AD and LBD pathologies and their possible interaction have been reported, the effect of AD and LBD on subcortical structures remains unknown. The effects of AD and LBD on subcortical atrophy and their relationship with cognitive dysfunction were investigated. METHODS The cross-sectional study recruited 42 patients with pure AD related cognitive impairment (ADCI), 30 patients with pure LBD related cognitive impairment (LBCI), 58 patients with mixed ADCI and LBCI, and 29 normal subjects. A general linear model was used to compare subcortical volume and shape amongst the groups, to investigate the independent and interaction effects of ADCI and LBCI on subcortical shape and volume, and to analyze the relationship between subcortical volume and cognitive dysfunction in each group. RESULTS Alzheimer's disease related cognitive impairment and LBCI were independently associated with subcortical atrophies in the hippocampus and amygdala and in the hippocampus and putamen respectively, but their interaction effect was not significant. Compared to the control group, the pure LBCI group exhibited additional local atrophies in the amygdala, caudate and thalamus. Subcortical atrophies correlated differently with cognitive dysfunction according to the underlying causes of cognitive dysfunction. CONCLUSIONS The patterns of subcortical atrophies and their correlation with cognitive dysfunction differ according to the underlying AD, LBD or concomitant AD and LBD.
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Affiliation(s)
- H S Yoo
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea
| | - E C Lee
- Department of Bio-convergence Engineering, Korea University, Seoul, South Korea
| | - S J Chung
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea
| | - Y H Lee
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea
| | - S G Lee
- Department of Radiology, Yonsei University College of Medicine, Seoul, South Korea
| | - M Yun
- Department of Nuclear Medicine, Yonsei University College of Medicine, Seoul, South Korea
| | - P H Lee
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea
| | - Y H Sohn
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea
| | - J-K Seong
- Department of Bio-convergence Engineering, Korea University, Seoul, South Korea.,School of Biomedical Engineering, Korea University, Seoul, South Korea
| | - B S Ye
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea
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32
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Increased functional connectivity of thalamic subdivisions in patients with Parkinson's disease. PLoS One 2019; 14:e0222002. [PMID: 31483847 PMCID: PMC6726201 DOI: 10.1371/journal.pone.0222002] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2019] [Accepted: 08/20/2019] [Indexed: 01/09/2023] Open
Abstract
Parkinson’s disease (PD) affects 2–3% of the population over the age of 65 with loss of dopaminergic neurons in the substantia nigra impacting the functioning of basal ganglia-thalamocortical circuits. The precise role played by the thalamus is unknown, despite its critical role in the functioning of the cerebral cortex, and the abnormal neuronal activity of the structure in PD. Our objective was to more clearly elucidate how functional connectivity and morphology of the thalamus are impacted in PD (n = 32) compared to Controls (n = 20). To investigate functional connectivity of the thalamus we subdivided the structure into two important regions-of-interest, the first with putative connections to the motor cortices and the second with putative connections to prefrontal cortices. We then investigated potential differences in the size and shape of the thalamus in PD, and how morphology and functional connectivity relate to clinical variables. Our data demonstrate that PD is associated with increases in functional connectivity between motor subdivisions of the thalamus and the supplementary motor area, and between prefrontal thalamic subdivisions and nuclei of the basal ganglia, anterior and dorsolateral prefrontal cortices, as well as the anterior and paracingulate gyri. These results suggest that PD is associated with increased functional connectivity of subdivisions of the thalamus which may be indicative alterations to basal ganglia-thalamocortical circuitry.
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Pelizzari L, Laganà MM, Di Tella S, Rossetto F, Bergsland N, Nemni R, Clerici M, Baglio F. Combined Assessment of Diffusion Parameters and Cerebral Blood Flow Within Basal Ganglia in Early Parkinson's Disease. Front Aging Neurosci 2019; 11:134. [PMID: 31214017 PMCID: PMC6558180 DOI: 10.3389/fnagi.2019.00134] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2019] [Accepted: 05/21/2019] [Indexed: 12/12/2022] Open
Abstract
Diffusion tensor imaging (DTI) is a sensitive tool for detecting brain tissue microstructural alterations in Parkinson’s disease (PD). Abnormal cerebral perfusion patterns have also been reported in PD patients using arterial spin labeling (ASL) MRI. In this study we aimed to perform a combined DTI and ASL assessment in PD patients within the basal ganglia, in order to test the relationship between microstructural and perfusion alterations. Fifty-two subjects participated in this study. Specifically, 26 PD patients [mean age (SD) = 66.7 (8.9) years, 21 males, median (IQR) Modified Hoehn and Yahr = 1.5 (1–1.6)] and twenty-six healthy controls [HC, mean age (SD) = 65.2 (7.5), 15 males] were scanned with 1.5T MRI. Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD) maps were derived from diffusion-weighted images, while cerebral blood flow (CBF) maps were computed from ASL data. After registration to Montreal Neurological Institute standard space, FA, MD, AD, RD and CBF median values were extracted within specific regions of interest: substantia nigra, caudate, putamen, globus pallidus, thalamus, red nucleus and subthalamic nucleus. DTI measures and CBF were compared between the two groups. The relationship between diffusion parameters and CBF was tested with Spearman’s correlations. False discovery rate (FDR)-corrected p-values lower than 0.05 were considered significant, while uncorrected p-values <0.05 were considered a trend. No significant FA, MD and RD differences were observed. AD was significantly increased in PD patients compared with HC in the putamen (p = 0.005, pFDR = 0.035). No significant CBF differences were found between PD patients and HC. Diffusion parameters were not significantly correlated with CBF in the HC group, while a significant correlation emerged for PD patients in the caudate nucleus, for all DTI measures (with FA: r = 0.543, pFDR = 0.028; with MD: r = −0.661, pFDR = 0.002; with AD: r = −0.628, pFDR = 0.007; with RD: r = −0.635, pFDR = 0.003). This study showed that DTI is a more sensitive technique than ASL to detect alterations in the basal ganglia in the early phase of PD. Our results suggest that, although DTI and ASL convey different information, a relationship between microstructural integrity and perfusion changes in the caudate may be present.
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Affiliation(s)
| | | | | | | | - Niels Bergsland
- IRCCS, Fondazione Don Carlo Gnocchi, Milan, Italy.,Department of Neurology, Buffalo Neuroimaging Analysis Center, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, United States
| | - Raffaello Nemni
- IRCCS, Fondazione Don Carlo Gnocchi, Milan, Italy.,Department of Pathophysiology and Transplantation, Università degli Studi di Milano, Milan, Italy
| | - Mario Clerici
- IRCCS, Fondazione Don Carlo Gnocchi, Milan, Italy.,Department of Pathophysiology and Transplantation, Università degli Studi di Milano, Milan, Italy
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Nemmi F, Pavy-Le Traon A, Phillips OR, Galitzky M, Meissner WG, Rascol O, Péran P. A totally data-driven whole-brain multimodal pipeline for the discrimination of Parkinson's disease, multiple system atrophy and healthy control. NEUROIMAGE-CLINICAL 2019; 23:101858. [PMID: 31128523 PMCID: PMC6531871 DOI: 10.1016/j.nicl.2019.101858] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/21/2019] [Revised: 04/17/2019] [Accepted: 05/11/2019] [Indexed: 01/10/2023]
Abstract
Parkinson's Disease (PD) and Multiple System Atrophy (MSA) are two parkinsonian syndromes that share many symptoms, albeit having very different prognosis. Although previous studies have proposed multimodal MRI protocols combined with multivariate analysis to discriminate between these two populations and healthy controls, studies combining all MRI indexes relevant for these disorders (i.e. grey matter volume, fractional anisotropy, mean diffusivity, iron deposition, brain activity at rest and brain connectivity) with a completely data-driven voxelwise analysis for discrimination are still lacking. In this study, we used such a complete MRI protocol and adapted a fully-data driven analysis pipeline to discriminate between these populations and a healthy controls (HC) group. The pipeline combined several feature selection and reduction steps to obtain interpretable models with a low number of discriminant features that can shed light onto the brain pathology of PD and MSA. Using this pipeline, we could discriminate between PD and HC (best accuracy = 0.78), MSA and HC (best accuracy = 0.94) and PD and MSA (best accuracy = 0.88). Moreover, we showed that indexes derived from resting-state fMRI alone could discriminate between PD and HC, while mean diffusivity in the cerebellum and the putamen alone could discriminate between MSA and HC. On the other hand, a more diverse set of indexes derived by multiple modalities was needed to discriminate between the two disorders. We showed that our pipeline was able to discriminate between distinct pathological populations while delivering sparse model that could be used to better understand the neural underpinning of the pathologies.
Structuro-functional MRI can discriminate between parkinsonian syndromes Discriminant MRI modalities vary as a function of the discrimination task fMRI is crucial in discriminating between Parkinson's disease patients and controls Structural MRI discriminate between Multiple System Atrophy patients and controls
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Affiliation(s)
- F Nemmi
- ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, France.
| | - A Pavy-Le Traon
- UMR Institut National de la Santé et de la Recherche Médicale 1048, Institut des Maladies Métaboliques et Cardiovasculaires, Toulouse, France; Department of Neurology and Institute for Neurosciences, University Hospital of Toulouse, Toulouse, France
| | - O R Phillips
- Brain Key, Palo Alto, California, USA; NeuroToul COEN Center, INSERM, CHU de Toulouse, Université de Toulouse 3, Toulouse, France
| | - M Galitzky
- Centre d'Investigation Clinique (CIC), CHU de Toulouse, Toulouse, France
| | - W G Meissner
- French Reference Center for MSA, Department of Neurology, University Hospital Bordeaux, Bordeaux and Institute of Neurodegenerative Disorders, University Bordeaux, CNRS UMR 5293, 33000 Bordeaux, France; Dept. Medicine, University of Otago, Christchurch, and New Zealand Brain Research Institute, Christchurch, New Zealand
| | - O Rascol
- Departments of Clinical Pharmacology and Neurosciences, Clinical Investigation Center CIC 1436, NS-Park/FCRIN network and NeuroToul COEN Center, INSERM, CHU de Toulouse, Université de Toulouse 3, Toulouse, France
| | - P Péran
- ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, France
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35
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Berner LA, Wang Z, Stefan M, Lee S, Huo Z, Cyr M, Marsh R. Subcortical Shape Abnormalities in Bulimia Nervosa. BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2019; 4:1070-1079. [PMID: 30846367 DOI: 10.1016/j.bpsc.2018.12.011] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2018] [Accepted: 12/24/2018] [Indexed: 12/18/2022]
Abstract
BACKGROUND Bulimia nervosa (BN) is associated with functional abnormalities in frontostriatal and frontolimbic circuits. Although structural alterations in the frontal portions of these circuits have been observed, this is the first study of subcortical surface morphometry and the largest study of subcortical volume in BN. METHODS Anatomical magnetic resonance scans were acquired from 62 female participants with full and subthreshold BN (mean age ± SD, 18.7 ± 4.0 years) and 65 group-matched healthy control participants (mean age ± SD, 19.3 ± 5.7 years). General linear models were used to compare groups and assess the significance of group-by-age interactions on the shape and total volume of 15 subcortical structures (p < .05, familywise error corrected). Associations with illness severity and duration were assessed in the BN group. RESULTS Subcortical volumes did not differ across groups, but vertexwise analyses revealed inward shape deformations on the anterior surface of the pallidum in BN relative to control participants that were associated with binge-eating frequency and illness duration. Inward deformations on the ventrolateral thalamus and dorsal amygdala were more pronounced with advancing age in the BN group, and inward deformations on the caudate, putamen, and amygdala were associated with self-induced vomiting frequency. CONCLUSIONS Our findings point to localized deformations on the surface of subcortical structures in areas that comprise both reward and cognitive control circuits. These deformations were more pronounced among older BN participants and among those with the most severe symptoms. Such precise localization of alterations in subcortical morphometry may ultimately aid in efforts to identify markers of risk and BN persistence.
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Affiliation(s)
- Laura A Berner
- Department of Psychiatry, University of California, San Diego, San Diego, California.
| | - Zhishun Wang
- Division of Child and Adolescent Psychiatry, Columbia University Medical Center and the New York State Psychiatric Institute, New York, New York
| | - Mihaela Stefan
- Division of Child and Adolescent Psychiatry, Columbia University Medical Center and the New York State Psychiatric Institute, New York, New York
| | - Seonjoo Lee
- Division of Child and Adolescent Psychiatry, Columbia University Medical Center and the New York State Psychiatric Institute, New York, New York
| | - Zhiyong Huo
- Division of Child and Adolescent Psychiatry, Columbia University Medical Center and the New York State Psychiatric Institute, New York, New York; Key Laboratory of Image Communication and Image Processing, Nanjing University of Posts and Telecommunications, Nanjing, China
| | - Marilyn Cyr
- Division of Child and Adolescent Psychiatry, Columbia University Medical Center and the New York State Psychiatric Institute, New York, New York
| | - Rachel Marsh
- Division of Child and Adolescent Psychiatry, Columbia University Medical Center and the New York State Psychiatric Institute, New York, New York
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Zou L, Song Y, Zhou X, Chu J, Tang X. Regional morphometric abnormalities and clinical relevance in Wilson's disease. Mov Disord 2019; 34:545-554. [PMID: 30817852 DOI: 10.1002/mds.27641] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2018] [Revised: 12/17/2018] [Accepted: 01/04/2019] [Indexed: 11/08/2022] Open
Affiliation(s)
- Lin Zou
- Department of Electrical and Electronic Engineering; Southern University of Science and Technology; Shenzhen Guangdong China
| | - Yukun Song
- Department of Radiology; The First Affiliated Hospital of Xiamen University; Xiamen Fujian China
| | - Xiangxue Zhou
- Department of Neurology, Eastern Hospital; The First Affiliated Hospital of Sun Yat-sen University; Guangzhou Guangdong China
| | - Jianping Chu
- Department of Radiology; The First Affiliated Hospital of Sun Yat-sen University; Guangzhou Guangdong China
| | - Xiaoying Tang
- Department of Electrical and Electronic Engineering; Southern University of Science and Technology; Shenzhen Guangdong China
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37
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Asami T, Yoshida H, Takaishi M, Nakamura R, Yoshimi A, Whitford TJ, Hirayasu Y. Thalamic shape and volume abnormalities in female patients with panic disorder. PLoS One 2018; 13:e0208152. [PMID: 30566534 PMCID: PMC6300210 DOI: 10.1371/journal.pone.0208152] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2018] [Accepted: 11/12/2018] [Indexed: 12/27/2022] Open
Abstract
The thalamus is believed to play crucial role in processing viscero-sensory information, and regulating the activity of amygdala in patients with panic disorder (PD). Previous functional neuroimaging studies have detected abnormal activation in the thalamus in patients with PD compared with healthy control subjects (HC). Very few studies, however, have investigated for volumetric abnormalities in the thalamus in patients with PD. Furthermore, to the best of our knowledge, no previous study has investigated for shape abnormalities in the thalamus in patients with PD. Twenty-five patients with PD and 25 HC participants (all female) were recruited for the study. A voxel-wise volume comparison analysis and a vertex-wise shape analysis were conducted to evaluate structural abnormalities in the PD patients compared to HC. The patients with PD demonstrated significant gray matter volume reductions in the thalamus bilaterally, relative to the HC. The shape analysis detected significant inward deformation in some thalamic regions in the PD patients, including the anterior nucleus, mediodorsal nucleus, and pulvinar nucleus. PD patients showed shape deformations in key thalamic regions that are believed to play a role in regulating emotional and cognitive functions.
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Affiliation(s)
- Takeshi Asami
- Department of Psychiatry, Graduate School of Medicine, Yokohama City University, Yokohama, Japan
| | - Haruhisa Yoshida
- Department of Psychiatry, Graduate School of Medicine, Yokohama City University, Yokohama, Japan
| | - Masao Takaishi
- Department of Psychiatry, Graduate School of Medicine, Yokohama City University, Yokohama, Japan
| | - Ryota Nakamura
- Department of Psychiatry, Graduate School of Medicine, Yokohama City University, Yokohama, Japan
| | - Asuka Yoshimi
- Department of Psychiatry, Graduate School of Medicine, Yokohama City University, Yokohama, Japan
| | - Thomas J. Whitford
- School of Psychology, University of New South Wales, Sydney, New South Wales, Australia
| | - Yoshio Hirayasu
- Department of Psychiatry, Graduate School of Medicine, Yokohama City University, Yokohama, Japan
- Heian Hospital, Urazoe, Japan
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Abstract
Qualitative and quantitative structural magnetic resonance imaging offer objective measures of the underlying neurodegeneration in atypical parkinsonism. Regional changes in tissue volume, signal changes and increased deposition of iron as assessed with different structural MRI techniques are surrogate markers of underlying neurodegeneration and may reflect cell loss, microglial proliferation and astroglial activation. Structural MRI has been explored as a tool to enhance diagnostic accuracy in differentiating atypical parkinsonian disorders (APDs). Moreover, the longitudinal assessment of serial structural MRI-derived parameters offers the opportunity for robust inferences regarding the progression of APDs. This review summarizes recent research findings as (1) a diagnostic tool for APDs as well as (2) as a tool to assess longitudinal changes of serial MRI-derived parameters in the different APDs.
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Di Tella S, Baglio F, Cabinio M, Nemni R, Traficante D, Silveri MC. Selection Processing in Noun and Verb Production in Left- and Right-Sided Parkinson's Disease Patients. Front Psychol 2018; 9:1241. [PMID: 30079043 PMCID: PMC6062671 DOI: 10.3389/fpsyg.2018.01241] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2018] [Accepted: 06/28/2018] [Indexed: 12/17/2022] Open
Abstract
Verbs are more difficult to produce than nouns. Thus, if executive resources are reduced as in Parkinson's disease (PD), verbs are penalized compared to nouns. However, in an experimental condition in which it is the noun that must be selected from a larger number of alternatives compared to the verb, it is the noun production that becomes slower and more prone to errors. Indeed, patients are slower and less accurate than normal subjects when required to produce nouns from verbs (VN) in a morphology derivation tasks (e.g., "osservazione" from "osservare") ["observation" from "observe"] than verbs from nouns in a morphology generation task, in which only a verb can be generated from the noun (NV) (e.g., "fallire" from "fallimento") ["to fail" from "failure"]. In the Italian language morphology, in fact, generation and derivation tasks differ in the number of lexical entries among which the response must be selected. The left Inferior Frontal Gyrus (IFG) has been demonstrated to be involved in selection processes. In the present study, we explored if the ability to select words is related to the cortical thickness of the left IFG. Twelve right-sided PD with nigrostriatal hypofunctionality in the left hemisphere (RPD-LH), 9 left-sided PD with nigrostriatal hypofunctionality in the right hemisphere (LPD-RH) and 19 healthy controls (HC) took part in the study. NV and VN production tasks were administered; accuracy and reaction times (RTs) were collected. All 40 subjects received a structural MRI examination. Cortical thickness of the IFG and volumetric measurements for subcortical regions, thought to support selection processes, were computed using FreeSurfer. In VN derivation tasks RPD-LH patients were less accurate than LPD-RH patients (accuracy: 66% vs. 77%). No difference emerged among the three groups in RTs. Task accuracy/RTs and IFG thickness showed a significant correlation only in RPD-LH. Not only nouns (as expected) but also verbs were correlated with cortical thickness. This suggests that the linguistic nature of the stimuli along with executive resources are both relevant during word selection processes. Our data confirm that executive resources and language interact in the left IFG in word production tasks.
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Affiliation(s)
| | | | - Monia Cabinio
- IRCCS, Fondazione don Carlo Gnocchi ONLUS, Milan, Italy
| | - Raffaello Nemni
- IRCCS, Fondazione don Carlo Gnocchi ONLUS, Milan, Italy
- Department of Pathophysiology and Transplantation, Università degli Studi di Milano, Milan, Italy
| | - Daniela Traficante
- Department of Psychology, Università Cattolica del Sacro Cuore, Milan, Italy
| | - Maria C. Silveri
- Department of Psychology, Università Cattolica del Sacro Cuore, Milan, Italy
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Owens-Walton C, Jakabek D, Li X, Wilkes FA, Walterfang M, Velakoulis D, van Westen D, Looi JCL, Hansson O. Striatal changes in Parkinson disease: An investigation of morphology, functional connectivity and their relationship to clinical symptoms. Psychiatry Res Neuroimaging 2018; 275:5-13. [PMID: 29555381 DOI: 10.1016/j.pscychresns.2018.03.004] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2017] [Revised: 02/28/2018] [Accepted: 03/02/2018] [Indexed: 12/16/2022]
Abstract
We sought to investigate morphological and resting state functional connectivity changes to the striatal nuclei in Parkinson disease (PD) and examine whether changes were associated with measures of clinical function. Striatal nuclei were manually segmented on 3T-T1 weighted MRI scans of 74 PD participants and 27 control subjects, quantitatively analysed for volume, shape and also functional connectivity using functional MRI data. Bilateral caudate nuclei and putamen volumes were significantly reduced in the PD cohort compared to controls. When looking at left and right hemispheres, the PD cohort had significantly smaller left caudate nucleus and right putamen volumes compared to controls. A significant correlation was found between greater atrophy of the caudate nucleus and poorer cognitive function, and between greater atrophy of the putamen and more severe motor symptoms. Resting-state functional MRI analysis revealed altered functional connectivity of the striatal structures in the PD group. This research demonstrates that PD involves atrophic changes to the caudate nucleus and putamen that are linked to clinical dysfunction. Our work reveals important information about a key structure-function relationship in the brain and provides support for caudate nucleus and putamen atrophy as neuroimaging biomeasures in PD.
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Affiliation(s)
- Conor Owens-Walton
- Research Centre for the Neurosciences of Ageing, Academic Unit of Psychiatry and Addiction Medicine, School of Clinical Medicine, Australian National University Medical School, Canberra, Australia.
| | - David Jakabek
- Graduate School of Medicine, University of Wollongong, Wollongong, Australia
| | - Xiaozhen Li
- Division of Clinical Geriatrics, Centre for Alzheimer Disease Research, Department of Neurobiology, Care Sciences and Society (NVS), Karolinska Institute, Huddinge, Sweden; Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Fiona A Wilkes
- Research Centre for the Neurosciences of Ageing, Academic Unit of Psychiatry and Addiction Medicine, School of Clinical Medicine, Australian National University Medical School, Canberra, Australia
| | - Mark Walterfang
- Neuropsychiatry Unit, Royal Melbourne Hospital, Melbourne Neuropsychiatry Centre, University of Melbourne & Northwestern Mental Health, Melbourne, Australia; Florey Institute of Neurosciences and Mental Health, University of Melbourne, Melbourne, Australia
| | - Dennis Velakoulis
- Neuropsychiatry Unit, Royal Melbourne Hospital, Melbourne Neuropsychiatry Centre, University of Melbourne & Northwestern Mental Health, Melbourne, Australia
| | - Danielle van Westen
- Center for Medical Imaging and Physiology, Skåne University Hospital, Lund, Sweden; Diagnostic Radiology, Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Jeffrey C L Looi
- Research Centre for the Neurosciences of Ageing, Academic Unit of Psychiatry and Addiction Medicine, School of Clinical Medicine, Australian National University Medical School, Canberra, Australia; Neuropsychiatry Unit, Royal Melbourne Hospital, Melbourne Neuropsychiatry Centre, University of Melbourne & Northwestern Mental Health, Melbourne, Australia
| | - Oskar Hansson
- Department of Clinical Sciences, Lund University, Malmö, Sweden; Memory Clinic, Skåne University Hospital, Malmö, Sweden
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Tang X, Luo Y, Chen Z, Huang N, Johnson HJ, Paulsen JS, Miller MI. A Fully-Automated Subcortical and Ventricular Shape Generation Pipeline Preserving Smoothness and Anatomical Topology. Front Neurosci 2018; 12:321. [PMID: 29867332 PMCID: PMC5966575 DOI: 10.3389/fnins.2018.00321] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2016] [Accepted: 04/25/2018] [Indexed: 11/13/2022] Open
Abstract
In this paper, we present a fully-automated subcortical and ventricular shape generation pipeline that acts on structural magnetic resonance images (MRIs) of the human brain. Principally, the proposed pipeline consists of three steps: (1) automated structure segmentation using the diffeomorphic multi-atlas likelihood-fusion algorithm; (2) study-specific shape template creation based on the Delaunay triangulation; (3) deformation-based shape filtering using the large deformation diffeomorphic metric mapping for surfaces. The proposed pipeline is shown to provide high accuracy, sufficient smoothness, and accurate anatomical topology. Two datasets focused upon Huntington's disease (HD) were used for evaluating the performance of the proposed pipeline. The first of these contains a total of 16 MRI scans, each with a gold standard available, on which the proposed pipeline's outputs were observed to be highly accurate and smooth when compared with the gold standard. Visual examinations and outlier analyses on the second dataset, which contains a total of 1,445 MRI scans, revealed 100% success rates for the putamen, the thalamus, the globus pallidus, the amygdala, and the lateral ventricle in both hemispheres and rates no smaller than 97% for the bilateral hippocampus and caudate. Another independent dataset, consisting of 15 atlas images and 20 testing images, was also used to quantitatively evaluate the proposed pipeline, with high accuracy having been obtained. In short, the proposed pipeline is herein demonstrated to be effective, both quantitatively and qualitatively, using a large collection of MRI scans.
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Affiliation(s)
- Xiaoying Tang
- Sun Yat-sen University-Carnegie Mellon University Joint Institute of Engineering, Sun Yat-sen University, Guangzhou, China.,Sun Yat-sen University-Carnegie Mellon University Shunde International Joint Research Institute, Shunde, China.,School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou, China.,Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, United States
| | - Yuan Luo
- Sun Yat-sen University-Carnegie Mellon University Joint Institute of Engineering, Sun Yat-sen University, Guangzhou, China.,Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, United States
| | - Zhibin Chen
- Sun Yat-sen University-Carnegie Mellon University Joint Institute of Engineering, Sun Yat-sen University, Guangzhou, China.,Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, United States
| | - Nianwei Huang
- Sun Yat-sen University-Carnegie Mellon University Shunde International Joint Research Institute, Shunde, China
| | - Hans J Johnson
- Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, IA, United States
| | - Jane S Paulsen
- Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, IA, United States
| | - Michael I Miller
- Center for Imaging Science, Johns Hopkins University, Baltimore, MD, United States.,Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, United States.,Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States
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Rahayel S, Postuma RB, Montplaisir J, Génier Marchand D, Escudier F, Gaubert M, Bourgouin PA, Carrier J, Monchi O, Joubert S, Blanc F, Gagnon JF. Cortical and subcortical gray matter bases of cognitive deficits in REM sleep behavior disorder. Neurology 2018; 90:e1759-e1770. [PMID: 29669906 DOI: 10.1212/wnl.0000000000005523] [Citation(s) in RCA: 76] [Impact Index Per Article: 10.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2017] [Accepted: 02/20/2018] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To investigate cortical and subcortical gray matter abnormalities underlying cognitive impairment in patients with REM sleep behavior disorder (RBD) with or without mild cognitive impairment (MCI). METHODS Fifty-two patients with RBD, including 17 patients with MCI, were recruited and compared to 41 controls. All participants underwent extensive clinical assessments, neuropsychological examination, and 3-tesla MRI acquisition of T1 anatomical images. Vertex-based cortical analyses of volume, thickness, and surface area were performed to investigate cortical abnormalities between groups, whereas vertex-based shape analysis was performed to investigate subcortical structure surfaces. Correlations were performed to investigate associations between cortical and subcortical metrics, cognitive domains, and other markers of neurodegeneration (color discrimination, olfaction, and autonomic measures). RESULTS Patients with MCI had cortical thinning in the frontal, cingulate, temporal, and occipital cortices, and abnormal surface contraction in the lenticular nucleus and thalamus. Patients without MCI had cortical thinning restricted to the frontal cortex. Lower patient performance in cognitive domains was associated with cortical and subcortical abnormalities. Moreover, impaired performance on olfaction, color discrimination, and autonomic measures was associated with thinning in the occipital lobe. CONCLUSIONS Cortical and subcortical gray matter abnormalities are associated with cognitive status in patients with RBD, with more extensive patterns in patients with MCI. Our results highlight the importance of distinguishing between subgroups of patients with RBD according to cognitive status in order to better understand the neurodegenerative process in this population.
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Affiliation(s)
- Shady Rahayel
- From the Centre for Advanced Research in Sleep Medicine (S.R., R.B.P., J.M., D.G.M., M.G., P.-A.B., J.C., J.-F.G.), Hôpital du Sacré-Cœur de Montréal; Department of Psychology (S.R., D.G.M., M.G., P.-A.B., J.-F.G.), Université du Québec à Montréal; Department of Neurology (R.B.P.), Montreal General Hospital; Departments of Psychiatry (J.M.), Psychology (F.E., J.C., S.J.), and Radiology, Radio-Oncology, and Nuclear Medicine (O.M.), Université de Montréal; Research Centre (F.E., J.C., O.M., S.J., J.-F.G.), Institut universitaire de gériatrie de Montréal; Departments of Clinical Neurosciences and Radiology (O.M.), and Hotchkiss Brain Institute, University of Calgary, Canada; Université de Strasbourg and CNRS (F.B.), ICube UMR 7357 and FMTS (Fédération de Médecine Translationnelle de Strasbourg), Team IMIS, Strasbourg; and Saint François Day Hospital, Department of Geriatrics (F.B.), and Memory Resources and Research Centre (CM2R), Departments of Geriatrics and Neurology (F.B.), Hôpitaux Universitaires de Strasbourg, France
| | - Ronald B Postuma
- From the Centre for Advanced Research in Sleep Medicine (S.R., R.B.P., J.M., D.G.M., M.G., P.-A.B., J.C., J.-F.G.), Hôpital du Sacré-Cœur de Montréal; Department of Psychology (S.R., D.G.M., M.G., P.-A.B., J.-F.G.), Université du Québec à Montréal; Department of Neurology (R.B.P.), Montreal General Hospital; Departments of Psychiatry (J.M.), Psychology (F.E., J.C., S.J.), and Radiology, Radio-Oncology, and Nuclear Medicine (O.M.), Université de Montréal; Research Centre (F.E., J.C., O.M., S.J., J.-F.G.), Institut universitaire de gériatrie de Montréal; Departments of Clinical Neurosciences and Radiology (O.M.), and Hotchkiss Brain Institute, University of Calgary, Canada; Université de Strasbourg and CNRS (F.B.), ICube UMR 7357 and FMTS (Fédération de Médecine Translationnelle de Strasbourg), Team IMIS, Strasbourg; and Saint François Day Hospital, Department of Geriatrics (F.B.), and Memory Resources and Research Centre (CM2R), Departments of Geriatrics and Neurology (F.B.), Hôpitaux Universitaires de Strasbourg, France
| | - Jacques Montplaisir
- From the Centre for Advanced Research in Sleep Medicine (S.R., R.B.P., J.M., D.G.M., M.G., P.-A.B., J.C., J.-F.G.), Hôpital du Sacré-Cœur de Montréal; Department of Psychology (S.R., D.G.M., M.G., P.-A.B., J.-F.G.), Université du Québec à Montréal; Department of Neurology (R.B.P.), Montreal General Hospital; Departments of Psychiatry (J.M.), Psychology (F.E., J.C., S.J.), and Radiology, Radio-Oncology, and Nuclear Medicine (O.M.), Université de Montréal; Research Centre (F.E., J.C., O.M., S.J., J.-F.G.), Institut universitaire de gériatrie de Montréal; Departments of Clinical Neurosciences and Radiology (O.M.), and Hotchkiss Brain Institute, University of Calgary, Canada; Université de Strasbourg and CNRS (F.B.), ICube UMR 7357 and FMTS (Fédération de Médecine Translationnelle de Strasbourg), Team IMIS, Strasbourg; and Saint François Day Hospital, Department of Geriatrics (F.B.), and Memory Resources and Research Centre (CM2R), Departments of Geriatrics and Neurology (F.B.), Hôpitaux Universitaires de Strasbourg, France
| | - Daphné Génier Marchand
- From the Centre for Advanced Research in Sleep Medicine (S.R., R.B.P., J.M., D.G.M., M.G., P.-A.B., J.C., J.-F.G.), Hôpital du Sacré-Cœur de Montréal; Department of Psychology (S.R., D.G.M., M.G., P.-A.B., J.-F.G.), Université du Québec à Montréal; Department of Neurology (R.B.P.), Montreal General Hospital; Departments of Psychiatry (J.M.), Psychology (F.E., J.C., S.J.), and Radiology, Radio-Oncology, and Nuclear Medicine (O.M.), Université de Montréal; Research Centre (F.E., J.C., O.M., S.J., J.-F.G.), Institut universitaire de gériatrie de Montréal; Departments of Clinical Neurosciences and Radiology (O.M.), and Hotchkiss Brain Institute, University of Calgary, Canada; Université de Strasbourg and CNRS (F.B.), ICube UMR 7357 and FMTS (Fédération de Médecine Translationnelle de Strasbourg), Team IMIS, Strasbourg; and Saint François Day Hospital, Department of Geriatrics (F.B.), and Memory Resources and Research Centre (CM2R), Departments of Geriatrics and Neurology (F.B.), Hôpitaux Universitaires de Strasbourg, France
| | - Frédérique Escudier
- From the Centre for Advanced Research in Sleep Medicine (S.R., R.B.P., J.M., D.G.M., M.G., P.-A.B., J.C., J.-F.G.), Hôpital du Sacré-Cœur de Montréal; Department of Psychology (S.R., D.G.M., M.G., P.-A.B., J.-F.G.), Université du Québec à Montréal; Department of Neurology (R.B.P.), Montreal General Hospital; Departments of Psychiatry (J.M.), Psychology (F.E., J.C., S.J.), and Radiology, Radio-Oncology, and Nuclear Medicine (O.M.), Université de Montréal; Research Centre (F.E., J.C., O.M., S.J., J.-F.G.), Institut universitaire de gériatrie de Montréal; Departments of Clinical Neurosciences and Radiology (O.M.), and Hotchkiss Brain Institute, University of Calgary, Canada; Université de Strasbourg and CNRS (F.B.), ICube UMR 7357 and FMTS (Fédération de Médecine Translationnelle de Strasbourg), Team IMIS, Strasbourg; and Saint François Day Hospital, Department of Geriatrics (F.B.), and Memory Resources and Research Centre (CM2R), Departments of Geriatrics and Neurology (F.B.), Hôpitaux Universitaires de Strasbourg, France
| | - Malo Gaubert
- From the Centre for Advanced Research in Sleep Medicine (S.R., R.B.P., J.M., D.G.M., M.G., P.-A.B., J.C., J.-F.G.), Hôpital du Sacré-Cœur de Montréal; Department of Psychology (S.R., D.G.M., M.G., P.-A.B., J.-F.G.), Université du Québec à Montréal; Department of Neurology (R.B.P.), Montreal General Hospital; Departments of Psychiatry (J.M.), Psychology (F.E., J.C., S.J.), and Radiology, Radio-Oncology, and Nuclear Medicine (O.M.), Université de Montréal; Research Centre (F.E., J.C., O.M., S.J., J.-F.G.), Institut universitaire de gériatrie de Montréal; Departments of Clinical Neurosciences and Radiology (O.M.), and Hotchkiss Brain Institute, University of Calgary, Canada; Université de Strasbourg and CNRS (F.B.), ICube UMR 7357 and FMTS (Fédération de Médecine Translationnelle de Strasbourg), Team IMIS, Strasbourg; and Saint François Day Hospital, Department of Geriatrics (F.B.), and Memory Resources and Research Centre (CM2R), Departments of Geriatrics and Neurology (F.B.), Hôpitaux Universitaires de Strasbourg, France
| | - Pierre-Alexandre Bourgouin
- From the Centre for Advanced Research in Sleep Medicine (S.R., R.B.P., J.M., D.G.M., M.G., P.-A.B., J.C., J.-F.G.), Hôpital du Sacré-Cœur de Montréal; Department of Psychology (S.R., D.G.M., M.G., P.-A.B., J.-F.G.), Université du Québec à Montréal; Department of Neurology (R.B.P.), Montreal General Hospital; Departments of Psychiatry (J.M.), Psychology (F.E., J.C., S.J.), and Radiology, Radio-Oncology, and Nuclear Medicine (O.M.), Université de Montréal; Research Centre (F.E., J.C., O.M., S.J., J.-F.G.), Institut universitaire de gériatrie de Montréal; Departments of Clinical Neurosciences and Radiology (O.M.), and Hotchkiss Brain Institute, University of Calgary, Canada; Université de Strasbourg and CNRS (F.B.), ICube UMR 7357 and FMTS (Fédération de Médecine Translationnelle de Strasbourg), Team IMIS, Strasbourg; and Saint François Day Hospital, Department of Geriatrics (F.B.), and Memory Resources and Research Centre (CM2R), Departments of Geriatrics and Neurology (F.B.), Hôpitaux Universitaires de Strasbourg, France
| | - Julie Carrier
- From the Centre for Advanced Research in Sleep Medicine (S.R., R.B.P., J.M., D.G.M., M.G., P.-A.B., J.C., J.-F.G.), Hôpital du Sacré-Cœur de Montréal; Department of Psychology (S.R., D.G.M., M.G., P.-A.B., J.-F.G.), Université du Québec à Montréal; Department of Neurology (R.B.P.), Montreal General Hospital; Departments of Psychiatry (J.M.), Psychology (F.E., J.C., S.J.), and Radiology, Radio-Oncology, and Nuclear Medicine (O.M.), Université de Montréal; Research Centre (F.E., J.C., O.M., S.J., J.-F.G.), Institut universitaire de gériatrie de Montréal; Departments of Clinical Neurosciences and Radiology (O.M.), and Hotchkiss Brain Institute, University of Calgary, Canada; Université de Strasbourg and CNRS (F.B.), ICube UMR 7357 and FMTS (Fédération de Médecine Translationnelle de Strasbourg), Team IMIS, Strasbourg; and Saint François Day Hospital, Department of Geriatrics (F.B.), and Memory Resources and Research Centre (CM2R), Departments of Geriatrics and Neurology (F.B.), Hôpitaux Universitaires de Strasbourg, France
| | - Oury Monchi
- From the Centre for Advanced Research in Sleep Medicine (S.R., R.B.P., J.M., D.G.M., M.G., P.-A.B., J.C., J.-F.G.), Hôpital du Sacré-Cœur de Montréal; Department of Psychology (S.R., D.G.M., M.G., P.-A.B., J.-F.G.), Université du Québec à Montréal; Department of Neurology (R.B.P.), Montreal General Hospital; Departments of Psychiatry (J.M.), Psychology (F.E., J.C., S.J.), and Radiology, Radio-Oncology, and Nuclear Medicine (O.M.), Université de Montréal; Research Centre (F.E., J.C., O.M., S.J., J.-F.G.), Institut universitaire de gériatrie de Montréal; Departments of Clinical Neurosciences and Radiology (O.M.), and Hotchkiss Brain Institute, University of Calgary, Canada; Université de Strasbourg and CNRS (F.B.), ICube UMR 7357 and FMTS (Fédération de Médecine Translationnelle de Strasbourg), Team IMIS, Strasbourg; and Saint François Day Hospital, Department of Geriatrics (F.B.), and Memory Resources and Research Centre (CM2R), Departments of Geriatrics and Neurology (F.B.), Hôpitaux Universitaires de Strasbourg, France
| | - Sven Joubert
- From the Centre for Advanced Research in Sleep Medicine (S.R., R.B.P., J.M., D.G.M., M.G., P.-A.B., J.C., J.-F.G.), Hôpital du Sacré-Cœur de Montréal; Department of Psychology (S.R., D.G.M., M.G., P.-A.B., J.-F.G.), Université du Québec à Montréal; Department of Neurology (R.B.P.), Montreal General Hospital; Departments of Psychiatry (J.M.), Psychology (F.E., J.C., S.J.), and Radiology, Radio-Oncology, and Nuclear Medicine (O.M.), Université de Montréal; Research Centre (F.E., J.C., O.M., S.J., J.-F.G.), Institut universitaire de gériatrie de Montréal; Departments of Clinical Neurosciences and Radiology (O.M.), and Hotchkiss Brain Institute, University of Calgary, Canada; Université de Strasbourg and CNRS (F.B.), ICube UMR 7357 and FMTS (Fédération de Médecine Translationnelle de Strasbourg), Team IMIS, Strasbourg; and Saint François Day Hospital, Department of Geriatrics (F.B.), and Memory Resources and Research Centre (CM2R), Departments of Geriatrics and Neurology (F.B.), Hôpitaux Universitaires de Strasbourg, France
| | - Frédéric Blanc
- From the Centre for Advanced Research in Sleep Medicine (S.R., R.B.P., J.M., D.G.M., M.G., P.-A.B., J.C., J.-F.G.), Hôpital du Sacré-Cœur de Montréal; Department of Psychology (S.R., D.G.M., M.G., P.-A.B., J.-F.G.), Université du Québec à Montréal; Department of Neurology (R.B.P.), Montreal General Hospital; Departments of Psychiatry (J.M.), Psychology (F.E., J.C., S.J.), and Radiology, Radio-Oncology, and Nuclear Medicine (O.M.), Université de Montréal; Research Centre (F.E., J.C., O.M., S.J., J.-F.G.), Institut universitaire de gériatrie de Montréal; Departments of Clinical Neurosciences and Radiology (O.M.), and Hotchkiss Brain Institute, University of Calgary, Canada; Université de Strasbourg and CNRS (F.B.), ICube UMR 7357 and FMTS (Fédération de Médecine Translationnelle de Strasbourg), Team IMIS, Strasbourg; and Saint François Day Hospital, Department of Geriatrics (F.B.), and Memory Resources and Research Centre (CM2R), Departments of Geriatrics and Neurology (F.B.), Hôpitaux Universitaires de Strasbourg, France
| | - Jean-François Gagnon
- From the Centre for Advanced Research in Sleep Medicine (S.R., R.B.P., J.M., D.G.M., M.G., P.-A.B., J.C., J.-F.G.), Hôpital du Sacré-Cœur de Montréal; Department of Psychology (S.R., D.G.M., M.G., P.-A.B., J.-F.G.), Université du Québec à Montréal; Department of Neurology (R.B.P.), Montreal General Hospital; Departments of Psychiatry (J.M.), Psychology (F.E., J.C., S.J.), and Radiology, Radio-Oncology, and Nuclear Medicine (O.M.), Université de Montréal; Research Centre (F.E., J.C., O.M., S.J., J.-F.G.), Institut universitaire de gériatrie de Montréal; Departments of Clinical Neurosciences and Radiology (O.M.), and Hotchkiss Brain Institute, University of Calgary, Canada; Université de Strasbourg and CNRS (F.B.), ICube UMR 7357 and FMTS (Fédération de Médecine Translationnelle de Strasbourg), Team IMIS, Strasbourg; and Saint François Day Hospital, Department of Geriatrics (F.B.), and Memory Resources and Research Centre (CM2R), Departments of Geriatrics and Neurology (F.B.), Hôpitaux Universitaires de Strasbourg, France.
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Colon-Perez LM, Tanner JJ, Couret M, Goicochea S, Mareci TH, Price CC. Cognition and connectomes in nondementia idiopathic Parkinson's disease. Netw Neurosci 2018; 2:106-124. [PMID: 29911667 PMCID: PMC5989988 DOI: 10.1162/netn_a_00027] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2017] [Accepted: 09/18/2017] [Indexed: 01/01/2023] Open
Abstract
In this study, we investigate the organization of the structural connectome in cognitively well participants with Parkinson’s disease (PD-Well; n = 31) and a subgroup of participants with Parkinson’s disease who have amnestic disturbances (PD-MI; n = 9). We explore correlations between connectome topology and vulnerable cognitive domains in Parkinson’s disease relative to non-Parkinson’s disease peers (control, n = 40). Diffusion-weighted MRI data and deterministic tractography were used to generate connectomes. Connectome topological indices under study included weighted indices of node strength, path length, clustering coefficient, and small-worldness. Relative to controls, node strength was reduced 4.99% for PD-Well (p = 0.041) and 13.2% for PD-MI (p = 0.004). We found bilateral differences in the node strength between PD-MI and controls for inferior parietal, caudal middle frontal, posterior cingulate, precentral, and rostral middle frontal. Correlations between connectome and cognitive domains of interest showed that topological indices of global connectivity negatively associated with working memory and displayed more and larger negative correlations with neuropsychological indices of memory in PD-MI than in PD-Well and controls. These findings suggest that indices of network connectivity are reduced in PD-MI relative to PD-Well and control participants. Parkinson’s disease (PD) patients with amnestic mild cognitive impairment (e.g., primary processing-speed impairments or primary memory impairments) are at greater risk of developing dementia. Recent evidence suggests that patients with PD and mild cognitive impairment present an altered connectome connectivity. In this work, we further explore the structural connectome of PD patients to provide clues to identify possible sensitive markers of disease progression, and cognitive impairment, in susceptible PD patients. We employed a weighted network framework that yields more stable topological results than the binary network framework and is robust despite graph density differences, hence it does not require thresholding to analyze the connectomes. As Supplementary Information (Colon-Perez et al., 2017), we include databases sharing the results of the network data.
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Affiliation(s)
| | - Jared J Tanner
- Department of Clinical and Health Psychology, University of Florida, Gainesville, FL, USA
| | - Michelle Couret
- Department of Medicine, Columbia University, New York, NY, USA
| | - Shelby Goicochea
- Department of Medicine, University of Florida, Gainesville, FL, USA
| | - Thomas H Mareci
- Department of Biochemistry and Molecular Biology, University of Florida, Gainesville, FL, USA
| | - Catherine C Price
- Department of Clinical and Health Psychology, University of Florida, Gainesville, FL, USA
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44
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Péran P, Nemmi F, Barbagallo G. Brain Morphometry: Parkinson’s Disease. NEUROMETHODS 2018:267-277. [DOI: 10.1007/978-1-4939-7647-8_16] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/02/2023]
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45
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Meijerman A, Amiri H, Steenwijk MD, Jonker MA, van Schijndel RA, Cover KS, Vrenken H. Reproducibility of Deep Gray Matter Atrophy Rate Measurement in a Large Multicenter Dataset. AJNR Am J Neuroradiol 2017; 39:46-53. [PMID: 29191870 DOI: 10.3174/ajnr.a5459] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2017] [Accepted: 08/28/2017] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Precise in vivo measurement of deep GM volume change is a highly demanded prerequisite for an adequate evaluation of disease progression and new treatments. However, quantitative data on the reproducibility of deep GM structure volumetry are not yet available. In this paper we aim to investigate this reproducibility using a large multicenter dataset. MATERIALS AND METHODS We have assessed the reproducibility of 2 automated segmentation software packages (FreeSurfer and the FMRIB Integrated Registration and Segmentation Tool) by quantifying the volume changes of deep GM structures by using back-to-back MR imaging scans from the Alzheimer Disease Neuroimaging Initiative's multicenter dataset. Five hundred sixty-two subjects with scans at baseline and 1 year were included. Reproducibility was investigated in the bilateral caudate nucleus, putamen, amygdala, globus pallidus, and thalamus by carrying out descriptives as well as multilevel and variance component analysis. RESULTS Median absolute back-to-back differences varied between GM structures, ranging from 59.6-156.4 μL for volume change, and 1.26%-8.63% for percentage volume change. FreeSurfer had a better performance for the outcome of longitudinal volume change for the bilateral amygdala, putamen, left caudate nucleus (P < .005), and right thalamus (P < .001). For longitudinal percentage volume change, Freesurfer performed better for the left amygdala, bilateral caudate nucleus, and left putamen (P < .001). Smaller limits of agreement were found for FreeSurfer for both outcomes for all GM structures except the globus pallidus. Our results showed that back-to-back differences in 1-year percentage volume change were approximately 1.5-3.5 times larger than the mean measured 1-year volume change of those structures. CONCLUSIONS Longitudinal deep GM atrophy measures should be interpreted with caution. Furthermore, deep GM atrophy measurement techniques require substantially improved reproducibility, specifically when aiming for personalized medicine.
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Affiliation(s)
- A Meijerman
- From the Departments of Radiology and Nuclear Medicine (A.M., H.A., M.D.S., R.A.v.S., K.S.C., H.V.).,Epidemiology and Biostatistics (A.M., M.A.J.), Vrije University Medical Center, Amsterdam, The Netherlands
| | - H Amiri
- From the Departments of Radiology and Nuclear Medicine (A.M., H.A., M.D.S., R.A.v.S., K.S.C., H.V.) .,the Neuroscience Research Center, Institute of Neuropharmacology (H.A.), Kerman University of Medical Sciences, Kerman, Iran
| | - M D Steenwijk
- From the Departments of Radiology and Nuclear Medicine (A.M., H.A., M.D.S., R.A.v.S., K.S.C., H.V.)
| | - M A Jonker
- Epidemiology and Biostatistics (A.M., M.A.J.), Vrije University Medical Center, Amsterdam, The Netherlands
| | - R A van Schijndel
- From the Departments of Radiology and Nuclear Medicine (A.M., H.A., M.D.S., R.A.v.S., K.S.C., H.V.)
| | - K S Cover
- From the Departments of Radiology and Nuclear Medicine (A.M., H.A., M.D.S., R.A.v.S., K.S.C., H.V.)
| | - H Vrenken
- From the Departments of Radiology and Nuclear Medicine (A.M., H.A., M.D.S., R.A.v.S., K.S.C., H.V.)
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46
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Tang X, Chen N, Zhang S, Jones JA, Zhang B, Li J, Liu P, Liu H. Predicting auditory feedback control of speech production from subregional shape of subcortical structures. Hum Brain Mapp 2017; 39:459-471. [PMID: 29058356 DOI: 10.1002/hbm.23855] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2017] [Revised: 09/27/2017] [Accepted: 10/11/2017] [Indexed: 11/06/2022] Open
Abstract
Although a growing body of research has focused on the cortical sensorimotor mechanisms that support auditory feedback control of speech production, much less is known about the subcortical contributions to this control process. This study examined whether subregional anatomy of subcortical structures assessed by statistical shape analysis is associated with vocal compensations and cortical event-related potentials in response to pitch feedback errors. The results revealed significant negative correlations between the magnitudes of vocal compensations and subregional shape of the right thalamus, between the latencies of vocal compensations and subregional shape of the left caudate and pallidum, and between the latencies of cortical N1 responses and subregional shape of the left putamen. These associations indicate that smaller local volumes of the basal ganglia and thalamus are predictive of slower and larger neurobehavioral responses to vocal pitch errors. Furthermore, increased local volumes of the left hippocampus and right amygdala were predictive of larger vocal compensations, suggesting that there is an interplay between the memory-related subcortical structures and auditory-vocal integration. These results, for the first time, provide evidence for differential associations of subregional morphology of the basal ganglia, thalamus, hippocampus, and amygdala with neurobehavioral processing of vocal pitch errors, suggesting that subregional shape measures of subcortical structures can predict behavioral outcome of auditory-vocal integration and associated neural features. Hum Brain Mapp 39:459-471, 2018. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Xiaoying Tang
- Sun Yat-sen University-Carnegie Melon University (SYSU-CMU) Joint Institute of Engineering, Sun Yat-sen University, Guangzhou, 510006, China.,Sun Yat-sen University-Carnegie Melon University (SYSU-CMU) Shunde International Joint Research Institute, Shunde, 528300, China.,School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou, 510006, China.,Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, 15213, Pennsylvania
| | - Na Chen
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, China
| | - Siyun Zhang
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, China
| | - Jeffery A Jones
- Psychology Department and Laurier Centre for Cognitive Neuroscience, Wilfrid Laurier University, Waterloo, Ontario, N2L 3C5, Canada
| | - Baofeng Zhang
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, China
| | - Jingyuan Li
- Sun Yat-sen University-Carnegie Melon University (SYSU-CMU) Joint Institute of Engineering, Sun Yat-sen University, Guangzhou, 510006, China.,Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, 15213, Pennsylvania
| | - Peng Liu
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, China
| | - Hanjun Liu
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, China.,Guangdong Provincial Key Laboratory of Brain Function and Disease, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
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47
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Heim B, Krismer F, De Marzi R, Seppi K. Magnetic resonance imaging for the diagnosis of Parkinson's disease. J Neural Transm (Vienna) 2017; 124:915-964. [PMID: 28378231 PMCID: PMC5514207 DOI: 10.1007/s00702-017-1717-8] [Citation(s) in RCA: 156] [Impact Index Per Article: 19.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2017] [Accepted: 03/22/2017] [Indexed: 12/11/2022]
Abstract
The differential diagnosis of parkinsonian syndromes is considered one of the most challenging in neurology and error rates in the clinical diagnosis can be high even at specialized centres. Despite several limitations, magnetic resonance imaging (MRI) has undoubtedly enhanced the diagnostic accuracy in the differential diagnosis of neurodegenerative parkinsonism over the last three decades. This review aims to summarize research findings regarding the value of the different MRI techniques, including advanced sequences at high- and ultra-high-field MRI and modern image analysis algorithms, in the diagnostic work-up of Parkinson's disease. This includes not only the exclusion of alternative diagnoses for Parkinson's disease such as symptomatic parkinsonism and atypical parkinsonism, but also the diagnosis of early, new onset, and even prodromal Parkinson's disease.
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Affiliation(s)
- Beatrice Heim
- Department of Neurology, Medical University of Innsbruck, Anichstraße 35, 6020, Innsbruck, Austria
| | - Florian Krismer
- Department of Neurology, Medical University of Innsbruck, Anichstraße 35, 6020, Innsbruck, Austria.
| | - Roberto De Marzi
- Department of Neurology, Medical University of Innsbruck, Anichstraße 35, 6020, Innsbruck, Austria
| | - Klaus Seppi
- Department of Neurology, Medical University of Innsbruck, Anichstraße 35, 6020, Innsbruck, Austria.
- Neuroimaging Research Core Facility, Medical University Innsbruck, Innsbruck, Austria.
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48
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Uono S, Sato W, Kochiyama T, Kubota Y, Sawada R, Yoshimura S, Toichi M. Putamen Volume is Negatively Correlated with the Ability to Recognize Fearful Facial Expressions. Brain Topogr 2017; 30:774-784. [PMID: 28748407 DOI: 10.1007/s10548-017-0578-7] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2016] [Accepted: 07/19/2017] [Indexed: 12/16/2022]
Abstract
Findings of previous functional magnetic resonance imaging (MRI) and neuropsychological studies have suggested that specific aspects of the basal ganglia, particularly the putamen, are involved in the recognition of emotional facial expressions. However, it remains unknown whether variations in putamen structure reflect individual differences in the ability to recognize facial expressions. Thus, the present study assessed the putamen volumes and shapes of 50 healthy Japanese adults using structural MRI scans and evaluated the ability of participants to recognize facial expressions associated with six basic emotions: anger, disgust, fear, happiness, sadness, and surprise. The volume of the bilateral putamen was negatively associated with the recognition of fearful faces, and the local shapes of both the anterior and posterior subregions of the bilateral putamen, which are thought to support cognitive/affective and motor processing, respectively, exhibited similar negative relationships with the recognition of fearful expressions. These results suggest that individual differences in putamen structure can predict the ability to recognize fearful facial expressions in others. Additionally, these findings indicate that cognitive/affective and motor processing underlie this process.
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Affiliation(s)
- Shota Uono
- Department of Neurodevelopmental Psychiatry, Habiliration, and Rehabilitation, Graduate School of Medicine, Kyoto University, 53 Shogoin-Kawahara-cho, Sakyo-ku, Kyoto, 606-8507, Japan.
| | - Wataru Sato
- Department of Neurodevelopmental Psychiatry, Habiliration, and Rehabilitation, Graduate School of Medicine, Kyoto University, 53 Shogoin-Kawahara-cho, Sakyo-ku, Kyoto, 606-8507, Japan
| | - Takanori Kochiyama
- ATR Brain Activity Imaging Center, 2-2-2, Hikaridai, Seika-cho, Souraku-gun, Kyoto, 619-0288, Japan
| | - Yasutaka Kubota
- Health and Medical Services Center, Shiga University, 1-1-1, Baba, Hikone, Shiga, 522-8522, Japan
| | - Reiko Sawada
- Department of Neurodevelopmental Psychiatry, Habiliration, and Rehabilitation, Graduate School of Medicine, Kyoto University, 53 Shogoin-Kawahara-cho, Sakyo-ku, Kyoto, 606-8507, Japan.,The Organization for Promoting Neurodevelopmental Disorder Research, 40 Shogoin-Sannocho, Sakyo-ku, Kyoto, 606-8392, Japan
| | - Sayaka Yoshimura
- Department of Neurodevelopmental Psychiatry, Habiliration, and Rehabilitation, Graduate School of Medicine, Kyoto University, 53 Shogoin-Kawahara-cho, Sakyo-ku, Kyoto, 606-8507, Japan
| | - Motomi Toichi
- The Organization for Promoting Neurodevelopmental Disorder Research, 40 Shogoin-Sannocho, Sakyo-ku, Kyoto, 606-8392, Japan.,Faculty of Human Health Sciences, Graduate School of Medicine, Kyoto University, 53 Shogoin-Kawahara-cho, Sakyo-ku, Kyoto, 606-8507, Japan
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49
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Zhang M, Wells WM, Golland P. Probabilistic modeling of anatomical variability using a low dimensional parameterization of diffeomorphisms. Med Image Anal 2017; 41:55-62. [PMID: 28732595 DOI: 10.1016/j.media.2017.06.013] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2017] [Revised: 06/19/2017] [Accepted: 06/28/2017] [Indexed: 11/29/2022]
Abstract
We present an efficient probabilistic model of anatomical variability in a linear space of initial velocities of diffeomorphic transformations and demonstrate its benefits in clinical studies of brain anatomy. To overcome the computational challenges of the high dimensional deformation-based descriptors, we develop a latent variable model for principal geodesic analysis (PGA) based on a low dimensional shape descriptor that effectively captures the intrinsic variability in a population. We define a novel shape prior that explicitly represents principal modes as a multivariate complex Gaussian distribution on the initial velocities in a bandlimited space. We demonstrate the performance of our model on a set of 3D brain MRI scans from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Our model yields a more compact representation of group variation at substantially lower computational cost than the state-of-the-art method such as tangent space PCA (TPCA) and probabilistic principal geodesic analysis (PPGA) that operate in the high dimensional image space.
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Affiliation(s)
- Miaomiao Zhang
- Computer Science and Artificial Intelligence Laboratory, MIT, Massachusetts.
| | - William M Wells
- Computer Science and Artificial Intelligence Laboratory, MIT, Massachusetts; Brigham and Women's Hospital, Harvard Medical School, Massachusetts
| | - Polina Golland
- Computer Science and Artificial Intelligence Laboratory, MIT, Massachusetts
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50
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Rahayel S, Postuma RB, Montplaisir J, Bedetti C, Brambati S, Carrier J, Monchi O, Bourgouin PA, Gaubert M, Gagnon JF. Abnormal Gray Matter Shape, Thickness, and Volume in the Motor Cortico-Subcortical Loop in Idiopathic Rapid Eye Movement Sleep Behavior Disorder: Association with Clinical and Motor Features. Cereb Cortex 2017; 28:658-671. [DOI: 10.1093/cercor/bhx137] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2017] [Indexed: 11/13/2022] Open
Affiliation(s)
- Shady Rahayel
- Centre for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal, Montreal, Quebec H4J 1C5, Canada
- Department of Psychology, Université du Québec à Montréal, Montreal, Quebec H2X 3P2, Canada
| | - Ronald B Postuma
- Centre for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal, Montreal, Quebec H4J 1C5, Canada
- Department of Neurology, Montreal General Hospital, Montreal, Quebec H3G 1A4, Canada
| | - Jacques Montplaisir
- Centre for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal, Montreal, Quebec H4J 1C5, Canada
- Department of Psychiatry, Université de Montréal, Montreal, Quebec H3C 3J7, Canada
| | - Christophe Bedetti
- Centre for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal, Montreal, Quebec H4J 1C5, Canada
- Research Centre, Institut universitaire de gériatrie de Montréal, Montreal, Quebec H3W 1W5, Canada
| | - Simona Brambati
- Research Centre, Institut universitaire de gériatrie de Montréal, Montreal, Quebec H3W 1W5, Canada
- Department of Psychology, Université de Montréal, Montreal, Quebec H2V 2S9, Canada
| | - Julie Carrier
- Centre for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal, Montreal, Quebec H4J 1C5, Canada
- Research Centre, Institut universitaire de gériatrie de Montréal, Montreal, Quebec H3W 1W5, Canada
- Department of Psychology, Université de Montréal, Montreal, Quebec H2V 2S9, Canada
| | - Oury Monchi
- Department of Neurology, Montreal General Hospital, Montreal, Quebec H3G 1A4, Canada
- Research Centre, Institut universitaire de gériatrie de Montréal, Montreal, Quebec H3W 1W5, Canada
- Department of Radiology, Radio-Oncology, and Nuclear Medicine, Université de Montréal, Montreal, Quebec H3T 1A4, Canada
- Departments of Clinical Neurosciences and Radiology, and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta T2N 4N1, Canada
| | - Pierre-Alexandre Bourgouin
- Centre for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal, Montreal, Quebec H4J 1C5, Canada
- Department of Psychology, Université du Québec à Montréal, Montreal, Quebec H2X 3P2, Canada
| | - Malo Gaubert
- Centre for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal, Montreal, Quebec H4J 1C5, Canada
- Department of Psychology, Université du Québec à Montréal, Montreal, Quebec H2X 3P2, Canada
| | - Jean-François Gagnon
- Centre for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal, Montreal, Quebec H4J 1C5, Canada
- Department of Psychology, Université du Québec à Montréal, Montreal, Quebec H2X 3P2, Canada
- Research Centre, Institut universitaire de gériatrie de Montréal, Montreal, Quebec H3W 1W5, Canada
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