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Chen Y, Guo W, Li Y, Lin H, Dong D, Qi Y, Pu R, Liu A, Li W, Sun B. Differentiation of Glioblastoma and Solitary Brain Metastasis Using Brain-Tumor Interface Radiomics Features Based on MR Images: A Multicenter Study. Acad Radiol 2025:S1076-6332(25)00308-3. [PMID: 40280830 DOI: 10.1016/j.acra.2025.04.008] [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: 02/10/2025] [Revised: 03/27/2025] [Accepted: 04/03/2025] [Indexed: 04/29/2025]
Abstract
RATIONALE AND OBJECTIVES Glioblastoma (GBM) and solitary brain metastasis (SBM) exhibit similar radiomics features on magnetic resonance imaging (MRI), yet their treatment strategies and prognoses significantly differ. Therefore, accurate differentiation between these two types of tumors is crucial for clinical decision-making. This study aims to establish and validate an efficient diagnostic model based on the radiomic features of the T1-weighted contrast-enhanced (T1CE) sequence in the 10 mm brain-tumor interface region to achieve precise differentiation between GBM and SBM. METHODS This study retrospectively collected contrast-enhanced T1-weighted imaging data from 226 GBM patients and 206 SBM patients at three centers between January 2010 and October 2024. Samples from centers 1 and 2 were used as the training set, while samples from center 3 were used as the test set. Two observers manually delineated the tumor edges on the T1CE images layer by layer to obtain the Region of Interest (ROI) covering the entire tumor volume. A 10 mm brain-to-tumor interface (BTI) was extracted using Python code. Radiomic features were extracted from the 10 mm BTI region, followed by feature selection and model construction. Finally, SHAP (SHapley Additive exPlanations) was used to visualize the model. Three radiologists with 2, 6, and 18 years of diagnostic experience independently evaluated the test set samples without knowing the patient information or pathology results, establishing three diagnostic models. The DeLong test was used to compare these models with the radiomic model. RESULTS Ultimately, ten radiomic features were used for modeling. The model established using the logistic regression (LR) algorithm had an AUC of 0.893 on the training set and 0.808 on the test set. The AUCs of the three radiologists with different diagnostic experiences on the test set were 0.699, 0.740, and 0.789, respectively, all lower than that of the radiomic model. The DeLong test showed that ModelBTI performed significantly better than Doctor 1 (p<0.05) in the test set, but there was no statistically significant difference in performance between ModelBTI and Doctors 2 and 3. CONCLUSION The radiomic model constructed based on the 10 mm brain-tumor interface can effectively differentiate between GBM and SBM, capturing tumor heterogeneity from a new perspective, thereby significantly improving diagnostic performance and providing assistance for clinical diagnosis. DATA AVAILABILITY STATEMENT The original contributions presented in the study are included in the article/Supplemental material, further inquiries can be directed to the corresponding authors.
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Affiliation(s)
- Yini Chen
- Department of Radiology, The First Affiliated Hospital of DalianMedical University, Dalian, China (Y.C., H.L., D.D., Y.Q., R.P., A.L., B.S.)
| | - Weiya Guo
- Department of Radiology, Dalian Municipal Women and Children's Medical Center (Group), Dalian, China (W.G.)
| | - Yushi Li
- Department of Radiology, The Second Affiliated Hospital of DalianMedical University, Dalian, China (Y.L.)
| | - Hongsen Lin
- Department of Radiology, The First Affiliated Hospital of DalianMedical University, Dalian, China (Y.C., H.L., D.D., Y.Q., R.P., A.L., B.S.)
| | - Deshuo Dong
- Department of Radiology, The First Affiliated Hospital of DalianMedical University, Dalian, China (Y.C., H.L., D.D., Y.Q., R.P., A.L., B.S.)
| | - Yiwei Qi
- Department of Radiology, The First Affiliated Hospital of DalianMedical University, Dalian, China (Y.C., H.L., D.D., Y.Q., R.P., A.L., B.S.)
| | - Renwang Pu
- Department of Radiology, The First Affiliated Hospital of DalianMedical University, Dalian, China (Y.C., H.L., D.D., Y.Q., R.P., A.L., B.S.)
| | - Ailian Liu
- Department of Radiology, The First Affiliated Hospital of DalianMedical University, Dalian, China (Y.C., H.L., D.D., Y.Q., R.P., A.L., B.S.)
| | - Wei Li
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China (W.L.)
| | - Bo Sun
- Department of Radiology, The First Affiliated Hospital of DalianMedical University, Dalian, China (Y.C., H.L., D.D., Y.Q., R.P., A.L., B.S.).
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Ghaderi S, Mohammadi S, Fatehi F. Diffusion Tensor Imaging (DTI) Biomarker Alterations in Brain Metastases and Comparable Tumors: A Systematic Review of DTI and Tractography Findings. World Neurosurg 2024; 190:113-129. [PMID: 38986953 DOI: 10.1016/j.wneu.2024.07.037] [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: 03/05/2024] [Revised: 07/03/2024] [Accepted: 07/04/2024] [Indexed: 07/12/2024]
Abstract
BACKGROUND Brain metastases (BMs) are the most frequent tumors of the central nervous system. Diffusion tensor imaging (DTI) is a magnetic resonance imaging technique that provides insights into brain microstructural alterations and tensor metrics and generates tractography to visualize white matter fiber tracts based on diffusion directionality. This systematic review assessed evidence from DTI biomarker alterations in BMs and comparable tumors such as glioblastoma. METHODS PubMed, Scopus, and Web of Science were searched, and published between January 2000 and August 2023. The key inclusion criteria were studies reporting DTI metrics in BMs and comparisons with other tumors. Data on study characteristics, tumor types, sample details, and main DTI findings were extracted. RESULTS Fifty-seven studies with 1592 BM patients and 1578 comparable brain tumors were included. Peritumoral fractional anisotropy (FA) consistently differentiates BMs from primary brain tumors, whereas intratumoral FA shows limited discriminatory power. Mean diffusivity increased in BMs versus comparators. Intratumoral metrics were less consistent but revealed differences in BM origin. Axial and radial diffusivity have provided insights into the effects of radiation, tumor origin, and infiltration. Axial diffusivity/radial diffusivity differentiated tumor infiltration from vasogenic edema. Tractography revealed anatomical relationships between white matter tracts and BMs. In addition, tractography-guided BM surgery and radiotherapy planning are required. Machine learning models incorporating DTI biomarkers/metrics accurately classified BMs versus comparators and improved diagnostic classification. CONCLUSIONS DTI metrics provide noninvasive biomarkers for distinguishing BMs from other tumors and predicting outcomes. Key metrics included peritumoral FA and mean diffusivity.
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Affiliation(s)
- Sadegh Ghaderi
- Department of Neurology, Neuromuscular Research Center, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran; Department of Neuroscience and Addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Sana Mohammadi
- Department of Neuroscience and Addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Farzad Fatehi
- Department of Neuroscience and Addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran; Neurology Department, University Hospitals of Leicester NHS Trust, Leicester, United Kingdom.
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Würtemberger U, Rau A, Diebold M, Becker L, Hohenhaus M, Beck J, Reinacher PC, Erny D, Reisert M, Urbach H, Demerath T. Advanced diffusion MRI provides evidence for altered axonal microstructure and gradual peritumoral infiltration in GBM in comparison to brain metastases. Clin Neuroradiol 2024; 34:703-711. [PMID: 38683350 PMCID: PMC11339137 DOI: 10.1007/s00062-024-01416-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2023] [Accepted: 04/15/2024] [Indexed: 05/01/2024]
Abstract
PURPOSE In contrast to peritumoral edema in metastases, GBM is histopathologically characterized by infiltrating tumor cells within the T2 signal alterations. We hypothesized that depending on the distance from the outline of the contrast-enhancing tumor we might reveal imaging evidence of gradual peritumoral infiltration in GBM and predominantly vasogenic edema around metastases. We thus investigated the gradual change of advanced diffusion metrics with the peritumoral zone in metastases and GBM. METHODS In 30 patients with GBM and 28 with brain metastases, peritumoral T2 hyperintensity was segmented in 33% partitions based on the total volume beginning at the enhancing tumor margin and divided into inner, middle and outer zones. Diffusion Tensor Imaging (DTI)-derived fractional anisotropy and mean diffusivity as well as Diffusion Microstructure Imaging (DMI)-based parameters Dax-intra, Dax-extra, V‑CSF and V-intra were employed to assess group-wise differences between inner and outer zones as well as within-group gradients between the inner and outer zones. RESULTS In metastases, fractional anisotropy and Dax-extra were significantly reduced in the inner zone compared to the outer zone (FA p = 0.01; Dax-extra p = 0.03). In GBM, we noted a reduced Dax-extra and significantly lower intraaxonal volume fraction (Dax-extra p = 0.008, V‑intra p = 0.006) accompanied by elevated axial intraaxonal diffusivity in the inner zone (p = 0.035). Between-group comparison of the outer to the inner zones revealed significantly higher gradients in metastases over GBM for FA (p = 0.04) as well as the axial diffusivity in the intra- (p = 0.02) and extraaxonal compartment (p < 0.001). CONCLUSION Our findings provide evidence of gradual alterations within the peritumoral zone of brain tumors. These are compatible with predominant (vasogenic) edema formation in metastases, whereas our findings in GBM are in line with an axonal destructive component in the immediate peritumoral area and evidence of tumor cell infiltration with accentuation in the tumor's vicinity.
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Affiliation(s)
- U Würtemberger
- Department of Neuroradiology, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, 79106, Freiburg, Germany.
- Dept. of Neuroradiology, University Medical Center Freiburg, Breisacher Str. 64, 79106, Freiburg, Germany.
| | - A Rau
- Department of Neuroradiology, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, 79106, Freiburg, Germany
- Department of Diagnostic and Interventional Radiology, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, 79106, Freiburg, Germany
| | - M Diebold
- Institute of Neuropathology, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, 79106, Freiburg, Germany
| | - L Becker
- Department of Neuroradiology, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, 79106, Freiburg, Germany
| | - M Hohenhaus
- Department of Neurosurgery, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, 79106, Freiburg, Germany
| | - J Beck
- Department of Neurosurgery, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, 79106, Freiburg, Germany
| | - P C Reinacher
- Department of Neurosurgery, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, 79106, Freiburg, Germany
- Fraunhofer Institute for Laser Technology, 52074, Aachen, Germany
| | - D Erny
- Institute of Neuropathology, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, 79106, Freiburg, Germany
| | - M Reisert
- Department of Medical Physics, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, 79106, Freiburg, Germany
- Department of Stereotactic and Functional Neurosurgery, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, 79106, Freiburg, Germany
| | - H Urbach
- Department of Neuroradiology, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, 79106, Freiburg, Germany
| | - T Demerath
- Department of Neuroradiology, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, 79106, Freiburg, Germany
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Cheng C, Lu CF, Hsieh BY, Huang SH, Kao YCJ. Anisotropy component of DTI reveals long-term neuroinflammation following repetitive mild traumatic brain injury in rats. Eur Radiol Exp 2024; 8:82. [PMID: 39046630 PMCID: PMC11269550 DOI: 10.1186/s41747-024-00490-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Accepted: 06/18/2024] [Indexed: 07/25/2024] Open
Abstract
BACKGROUND This study aimed to investigate the long-term effects of repetitive mild traumatic brain injury (rmTBI) with varying inter-injury intervals by measuring diffusion tensor metrics, including mean diffusivity (MD), fractional anisotropy (FA), and diffusion magnitude (L) and pure anisotropy (q). METHODS Eighteen rats were randomly divided into three groups: short-interval rmTBI (n = 6), long-interval rmTBI (n = 6), and sham controls (n = 6). MD, FA, L, and q values were analyzed from longitudinal diffusion tensor imaging at days 50 and 90 after rmTBI. Immunohistochemical staining against neurons, astrocytes, microglia, and myelin was performed. Analysis of variance, Pearson correlation coefficient, and simple linear regression model were used. RESULTS At day 50 post-rmTBI, lower cortical FA and q values were shown in the short-interval group (p ≤ 0.038). In contrast, higher FA and q values were shown for the long-interval group (p ≤ 0.039) in the corpus callosum. In the ipsilesional external capsule and internal capsule, no significant changes were found in FA, while lower L and q values were shown in the short-interval group (p ≤ 0.028) at day 90. The q values in the external capsule and internal capsule were negatively correlated with the number of microglial cells and the total number of astroglial cells (p ≤ 0.035). CONCLUSION Tensor scalar measurements, such as L and q values, are sensitive to exacerbated chronic injury induced by rmTBI with shorter inter-injury intervals and reflect long-term astrogliosis induced by the cumulative injury. RELEVANCE STATEMENT Tensor scalar measurements, including L and q values, are potential DTI metrics for detecting long-term and subtle injury following rmTBI; in particular, q values may be used for quantifying remote white matter (WM) changes following rmTBI. KEY POINTS The alteration of L and q values was demonstrated after chronic repetitive mild traumatic brain injury. Changing q values were observed in the impact site and remote WM. The lower q values in the remote WM were associated with astrogliosis.
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Affiliation(s)
- Ching Cheng
- Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Chia-Feng Lu
- Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Bao-Yu Hsieh
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang-Gung University, Taoyuan, Taiwan
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
| | - Shu-Hui Huang
- Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Yu-Chieh Jill Kao
- Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, Taipei, Taiwan.
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Elliott A, Villemoes E, Farhat M, Klingberg E, Langshaw H, Svensson S, Chung C. Development and benchmarking diffusion magnetic resonance imaging analysis for integration into radiation treatment planning. Med Phys 2024; 51:2108-2118. [PMID: 37633837 DOI: 10.1002/mp.16670] [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: 03/12/2022] [Revised: 02/20/2023] [Accepted: 04/28/2023] [Indexed: 08/28/2023] Open
Abstract
PURPOSE The rising promise in the utility of advanced multi-parametric magnetic resonance (MR) imaging in radiotherapy (RT) treatment planning creates a necessity for testing and enhancing the accuracy of quantitative imaging analysis. Standardizing the analysis of diffusion weighted imaging (DWI) and diffusion tensor imaging (DTI) to generate meaningful and reproducible apparent diffusion coefficient (ADC) and fractional anisotropy (FA) lays the requisite needed for clinical integration. The aim of the demonstrated work is to benchmark the generation of the ADC and FA parametric map analyses using integrated tools in a commercial treatment planning system against the currently used ones. METHODS Three software packages were used for generating ADC and FA maps in this study; one tool was developed within a commercial treatment planning system, another by the Functional Magnetic Resonance Imaging of the Brain (FMRIB) Software Library FSL (Analysis Group, FMRIB, Oxford, United Kingdom), and an in-house tool developed at the M.D. Anderson Cancer Center. The ADC and FA maps generated by all three packages for 35 subjects were subtracted from one another, and the standard deviation of the images' differences was used to compare the reproducibility. The reproducibility of the ADC maps was compared with the Quantitative Imaging Biomarkers Alliance (QIBA) protocol, while that of the FA maps was compared to data in published literature. RESULTS Results show that the discrepancies between the ADC maps calculated for each patient using the three different software algorithms are less than 2% which meets the 3.6% recommended QIBA requirement. Except for a small number of isolated points, the majority of differences in FA maps for each patient produced by the three methods did not exceed 0.02 which is 10 times lower than the differences seen in healthy gray and white matter. The results were also compared to the maps generated by existing MR Imaging consoles and showed that the robustness of console generated ADC and FA maps is largely dependent on the correct application of scaling factors, that only if correctly placed; the differences between the three tested methods and the console generated values were within the recommended QIBA guidelines. CONCLUSIONS Cross-comparison difference maps demonstrated that quantitative reproducibility of ADC and FA metrics generated using our tested commercial treatment planning system were comparable to in-house and established tools as benchmarks. This integrated approach facilitates the clinical utility of diffusion imaging in radiation treatment planning workflow.
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Affiliation(s)
- Andrew Elliott
- Department Radiation Oncology, The University of Texas M. D. Anderson Cancer Center, Houston, Texas, USA
| | | | - Maguy Farhat
- Department Radiation Oncology, The University of Texas M. D. Anderson Cancer Center, Houston, Texas, USA
| | | | - Holly Langshaw
- Department Radiation Oncology, The University of Texas M. D. Anderson Cancer Center, Houston, Texas, USA
| | | | - Caroline Chung
- Department Radiation Oncology, The University of Texas M. D. Anderson Cancer Center, Houston, Texas, USA
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Würtemberger U, Erny D, Rau A, Hosp JA, Akgün V, Reisert M, Kiselev VG, Beck J, Jankovic S, Reinacher PC, Hohenhaus M, Urbach H, Diebold M, Demerath T. Mesoscopic Assessment of Microstructure in Glioblastomas and Metastases by Merging Advanced Diffusion Imaging with Immunohistopathology. AJNR Am J Neuroradiol 2023; 44:1262-1269. [PMID: 37884304 PMCID: PMC10631536 DOI: 10.3174/ajnr.a8022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 08/30/2023] [Indexed: 10/28/2023]
Abstract
BACKGROUND AND PURPOSE Glioblastomas and metastases are the most common malignant intra-axial brain tumors in adults and can be difficult to distinguish on conventional MR imaging due to similar imaging features. We used advanced diffusion techniques and structural histopathology to distinguish these tumor entities on the basis of microstructural axonal and fibrillar signatures in the contrast-enhancing tumor component. MATERIALS AND METHODS Contrast-enhancing tumor components were analyzed in 22 glioblastomas and 21 brain metastases on 3T MR imaging using DTI-fractional anisotropy, neurite orientation dispersion and density imaging-orientation dispersion, and diffusion microstructural imaging-micro-fractional anisotropy. Available histopathologic specimens (10 glioblastomas and 9 metastases) were assessed for the presence of axonal structures and scored using 4-level scales for Bielschowsky staining (0: no axonal structures, 1: minimal axonal fragments preserved, 2: decreased axonal density, 3: no axonal loss) and glial fibrillary acid protein expression (0: no glial fibrillary acid protein positivity, 1: limited expression, 2: equivalent to surrounding parenchyma, 3: increased expression). RESULTS When we compared glioblastomas and metastases, fractional anisotropy was significantly increased and orientation dispersion was decreased in glioblastomas (each P < .001), with a significant shift toward increased glial fibrillary acid protein and Bielschowsky scores. Positive associations of fractional anisotropy and negative associations of orientation dispersion with glial fibrillary acid protein and Bielschowsky scores were revealed, whereas no association between micro-fractional anisotropy with glial fibrillary acid protein and Bielschowsky scores was detected. Receiver operating characteristic curves revealed high predictive values of both fractional anisotropy (area under the curve = 0.8463) and orientation dispersion (area under the curve = 0.8398) regarding the presence of a glioblastoma. CONCLUSIONS Diffusion imaging fractional anisotropy and orientation dispersion metrics correlated with histopathologic markers of directionality and may serve as imaging biomarkers in contrast-enhancing tumor components.
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Affiliation(s)
- Urs Würtemberger
- From the Department of Neuroradiology (U.W., A.R., V.A., H.U., T.D.), Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Daniel Erny
- Institute of Neuropathology (D.E., M.D.), Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
- Berta-Ottenstein-Program for Advanced Clinician Scientists (D.E.), Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Alexander Rau
- From the Department of Neuroradiology (U.W., A.R., V.A., H.U., T.D.), Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
- Department of Diagnostic and Interventional Radiology (A.R.), Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Jonas A Hosp
- Department of Neurology and Neurophysiology (J.A.H.), Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Veysel Akgün
- From the Department of Neuroradiology (U.W., A.R., V.A., H.U., T.D.), Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Marco Reisert
- Department of Medical Physics (M.R., V.G.K.), Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
- Department of Stereotactic and Functional Neurosurgery (M.R., P.C.R.), Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Valerij G Kiselev
- Department of Medical Physics (M.R., V.G.K.), Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Jürgen Beck
- Department of Neurosurgery (J.B., M.H.), Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Sonja Jankovic
- Department of Radiology (S.J.), Faculty of Medicine, University Clinical Center Nis, University of Nis, Nis, Serbia
| | - Peter C Reinacher
- Department of Stereotactic and Functional Neurosurgery (M.R., P.C.R.), Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
- Fraunhofer Institute for Laser Technology (P.C.R.), Aachen, Germany
| | - Marc Hohenhaus
- Department of Neurosurgery (J.B., M.H.), Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Horst Urbach
- From the Department of Neuroradiology (U.W., A.R., V.A., H.U., T.D.), Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Martin Diebold
- Institute of Neuropathology (D.E., M.D.), Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
- IMM-PACT Clinician Scientist Program (M.D.), Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Theo Demerath
- From the Department of Neuroradiology (U.W., A.R., V.A., H.U., T.D.), Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
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Yang ZC, Yin CD, Yeh FC, Xue BW, Song XY, Li G, Deng ZH, Sun SJ, Hou ZG, Xie J. A preliminary study on corticospinal tract morphology in incidental and symptomatic insular low-grade glioma: implications for post-surgical motor outcomes. Neuroimage Clin 2023; 40:103521. [PMID: 37857233 PMCID: PMC10598056 DOI: 10.1016/j.nicl.2023.103521] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 09/11/2023] [Accepted: 09/30/2023] [Indexed: 10/21/2023]
Abstract
OBJECTIVE Our study aimed to investigate the shape and diffusion properties of the corticospinal tract (CST) in patients with insular incidental and symptomatic low-grade gliomas (LGGs), especially those in the incidental group, and evaluate their association with post-surgical motor function. METHODS We performed automatic fiber tracking on 41 LGG patients, comparing macroscopic shape and microscopic diffusion properties of CST between ipsilateral and contralateral tracts in both incidental and symptomatic groups. A correlation analysis was conducted between properties of CST and post-operative motor strength grades. RESULTS In the incidental group, no significant differences in mean diffusion properties were found between bilateral CST. While decreased anisotropy of the CST around the superior limiting sulcus and increased axial diffusivity of the CST near the midbrain level were noted, there was no significant correlation between pre-operative diffusion metrics and post-operative motor strength. In comparison, we found significant correlations between the elongation of the affected CST in the preoperative scans and post-operative motor strength in short-term and long-term follow ups (p = 1.810 × 10-4 and p = 9.560 × 10-4, respectively). CONCLUSIONS We found a significant correlation between CST shape measures and post-operative motor function outcomes in patients with incidental insular LGGs. CST morphology shows promise as a potential prognostic factor for identifying functional deficits in this patient population.
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Affiliation(s)
- Zuo-Cheng Yang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Chuan-Dong Yin
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Fang-Cheng Yeh
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Bo-Wen Xue
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xin-Yu Song
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Gen Li
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Zheng-Hai Deng
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Sheng-Jun Sun
- Department of Neuroradiology, Beijing Neurosurgical Institute, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Zong-Gang Hou
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
| | - Jian Xie
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
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Hooper GW, Ansari S, Johnson JM, Ginat DT. Advances in the Radiological Evaluation of and Theranostics for Glioblastoma. Cancers (Basel) 2023; 15:4162. [PMID: 37627190 PMCID: PMC10453051 DOI: 10.3390/cancers15164162] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 08/14/2023] [Accepted: 08/16/2023] [Indexed: 08/27/2023] Open
Abstract
Imaging is essential for evaluating patients with glioblastoma. Traditionally a multimodality undertaking, CT, including CT cerebral blood profusion, PET/CT with traditional fluorine-18 fluorodeoxyglucose (18F-FDG), and MRI have been the mainstays for diagnosis and post-therapeutic assessment. However, recent advances in these modalities, in league with the emerging fields of radiomics and theranostics, may prove helpful in improving diagnostic accuracy and treating the disease.
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Affiliation(s)
| | - Shehbaz Ansari
- Rush University Medical Center, Department of Radiology and Nuclear Medicine, Chicago, IL 60612, USA;
| | - Jason M. Johnson
- Department of Neuroradiology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA;
| | - Daniel T. Ginat
- Department of Radiology, University of Chicago, Chicago, IL 60637, USA
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Battalapalli D, Vidyadharan S, Prabhakar Rao BVVSN, Yogeeswari P, Kesavadas C, Rajagopalan V. Fractal dimension: analyzing its potential as a neuroimaging biomarker for brain tumor diagnosis using machine learning. Front Physiol 2023; 14:1201617. [PMID: 37528895 PMCID: PMC10390093 DOI: 10.3389/fphys.2023.1201617] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 06/28/2023] [Indexed: 08/03/2023] Open
Abstract
Purpose: The main purpose of this study was to comprehensively investigate the potential of fractal dimension (FD) measures in discriminating brain gliomas into low-grade glioma (LGG) and high-grade glioma (HGG) by examining tumor constituents and non-tumorous gray matter (GM) and white matter (WM) regions. Methods: Retrospective magnetic resonance imaging (MRI) data of 42 glioma patients (LGG, n = 27 and HGG, n = 15) were used in this study. Using MRI, we calculated different FD measures based on the general structure, boundary, and skeleton aspects of the tumorous and non-tumorous brain GM and WM regions. Texture features, namely, angular second moment, contrast, inverse difference moment, correlation, and entropy, were also measured in the tumorous and non-tumorous regions. The efficacy of FD features was assessed by comparing them with texture features. Statistical inference and machine learning approaches were used on the aforementioned measures to distinguish LGG and HGG patients. Results: FD measures from tumorous and non-tumorous regions were able to distinguish LGG and HGG patients. Among the 15 different FD measures, the general structure FD values of enhanced tumor regions yielded high accuracy (93%), sensitivity (97%), specificity (98%), and area under the receiver operating characteristic curve (AUC) score (98%). Non-tumorous GM skeleton FD values also yielded good accuracy (83.3%), sensitivity (100%), specificity (60%), and AUC score (80%) in classifying the tumor grades. These measures were also found to be significantly (p < 0.05) different between LGG and HGG patients. On the other hand, among the 25 texture features, enhanced tumor region features, namely, contrast, correlation, and entropy, revealed significant differences between LGG and HGG. In machine learning, the enhanced tumor region texture features yielded high accuracy, sensitivity, specificity, and AUC score. Conclusion: A comparison between texture and FD features revealed that FD analysis on different aspects of the tumorous and non-tumorous components not only distinguished LGG and HGG patients with high statistical significance and classification accuracy but also provided better insights into glioma grade classification. Therefore, FD features can serve as potential neuroimaging biomarkers for glioma.
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Affiliation(s)
- Dheerendranath Battalapalli
- Department of Electrical and Electronics Engineering, Birla Institute of Technology and Science Pilani, Hyderabad Campus, Hyderabad, India
| | - Sreejith Vidyadharan
- Department of Electrical and Electronics Engineering, Birla Institute of Technology and Science Pilani, Hyderabad Campus, Hyderabad, India
| | - B. V. V. S. N. Prabhakar Rao
- Department of Electrical and Electronics Engineering, Birla Institute of Technology and Science Pilani, Hyderabad Campus, Hyderabad, India
| | - P. Yogeeswari
- Department of Pharmacy, Birla Institute of Technology and Science Pilani, Hyderabad Campus, Hyderabad, India
| | - C. Kesavadas
- Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, India
| | - Venkateswaran Rajagopalan
- Department of Electrical and Electronics Engineering, Birla Institute of Technology and Science Pilani, Hyderabad Campus, Hyderabad, India
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10
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Qi D, Li J, Quarles CC, Fonkem E, Wu E. Assessment and prediction of glioblastoma therapy response: challenges and opportunities. Brain 2023; 146:1281-1298. [PMID: 36445396 PMCID: PMC10319779 DOI: 10.1093/brain/awac450] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Revised: 11/03/2022] [Accepted: 11/10/2022] [Indexed: 11/30/2022] Open
Abstract
Glioblastoma is the most aggressive type of primary adult brain tumour. The median survival of patients with glioblastoma remains approximately 15 months, and the 5-year survival rate is <10%. Current treatment options are limited, and the standard of care has remained relatively constant since 2011. Over the last decade, a range of different treatment regimens have been investigated with very limited success. Tumour recurrence is almost inevitable with the current treatment strategies, as glioblastoma tumours are highly heterogeneous and invasive. Additionally, another challenging issue facing patients with glioblastoma is how to distinguish between tumour progression and treatment effects, especially when relying on routine diagnostic imaging techniques in the clinic. The specificity of routine imaging for identifying tumour progression early or in a timely manner is poor due to the appearance similarity of post-treatment effects. Here, we concisely describe the current status and challenges in the assessment and early prediction of therapy response and the early detection of tumour progression or recurrence. We also summarize and discuss studies of advanced approaches such as quantitative imaging, liquid biomarker discovery and machine intelligence that hold exceptional potential to aid in the therapy monitoring of this malignancy and early prediction of therapy response, which may decisively transform the conventional detection methods in the era of precision medicine.
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Affiliation(s)
- Dan Qi
- Department of Neurosurgery and Neuroscience Institute, Baylor Scott & White Health, Temple, TX 76502, USA
| | - Jing Li
- School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - C Chad Quarles
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77054, USA
| | - Ekokobe Fonkem
- Department of Neurosurgery and Neuroscience Institute, Baylor Scott & White Health, Temple, TX 76502, USA
- Department of Medical Education, School of Medicine, Texas A&M University, Bryan, TX 77807, USA
| | - Erxi Wu
- Department of Neurosurgery and Neuroscience Institute, Baylor Scott & White Health, Temple, TX 76502, USA
- Department of Medical Education, School of Medicine, Texas A&M University, Bryan, TX 77807, USA
- Department of Pharmaceutical Sciences, Irma Lerma Rangel School of Pharmacy, Texas A&M University, College Station, TX 77843, USA
- Department of Oncology and LIVESTRONG Cancer Institutes, Dell Medical School, The University of Texas at Austin, Austin, TX 78712, USA
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11
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Kumar R, Shijith K, Dhanalakshmi B, Kovilapu UB, Sharma V, Debnath J, Sridhar M, Gahlot G, Das AK. Role of regional diffusion tensor imaging (DTI)-derived tensor metrics in the evaluation of intracranial gliomas and its histopathological correlation. Med J Armed Forces India 2023; 79:173-180. [PMID: 36969123 PMCID: PMC10037060 DOI: 10.1016/j.mjafi.2021.05.020] [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: 10/12/2020] [Accepted: 05/21/2021] [Indexed: 11/25/2022] Open
Abstract
Background The imaging of brain tumours has significantly improved with the use of advanced magnetic resonance (MR) techniques like diffusion tensor imaging (DTI). This study was conducted to analyse the utility of DTI-derived tensor metrics in the evaluation of intracranial gliomas with histopathological correlation and further adoption of these image-data analyses in clinical setting. Methods A total of 50 patients with suspected diagnosis of intracranial gliomas underwent DTI along with conventional MR examination. The study correlated various DTI parameters in the enhancing part of the tumour and the peritumoral region with the histopathological grades of the intracranial gliomas. Results The study revealed higher values of Cl (linear anisotropy), Cp (planar anisotropy), AD (axial diffusivity), FA (fractional anisotropy) and RA (relative anisotropy) and lower values of Cs (spherical anisotropy), MD (mean diffusivity) and RD (radial diffusivity) in the enhancing part of the tumour in case of high-grade gliomas. However, in the peritumoral region, the values of Cl, Cp, AD, FA and RA were less whereas values of Cs, MD and RD were more in high-grade gliomas than in the low-grade gliomas. The various cutoff values of these DTI-derived tensor metrics were found to be statistically significant. Conclusion DTI-derived tensor metrics can be a valuable tool in differentiation between high-grade and low-grade gliomas which might be accepted in clinical practice in near future.
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Affiliation(s)
- Rakesh Kumar
- Graded Specialist (Radiodiagnosis), 165 Military Hospital, C/o 99 APO, India
| | - K.P. Shijith
- Senior Advisor (Radiodiagnosis), Army Hospital (R&R), Delhi Cantt, India
| | - B. Dhanalakshmi
- Classified Specialist (Radiodiagnosis), Army Institute of Cardio Thoracic Sciences (AICTS), Pune, India
| | - Uday Bhanu Kovilapu
- Associate Professor, Department of Radiology, Armed Forces Medical College, Pune, India
| | - Vivek Sharma
- Professor (Radiodiagnosis), Bharati Vidyapeeth Medical College, Pune, India
| | - Jyotindu Debnath
- Consultant, Professor & Head (Radiodiagnosis), Army Hospital (R&R), Delhi Cantt, India
| | - M.S. Sridhar
- Deputy Commandant, Command Hospital (Air Force), Bengaluru, India
| | - G.P.S. Gahlot
- Classified Specialist (Pathology & Oncopathology), Command Hospital (Western Command), Chandimandir, India
| | - Amit Kumar Das
- Commanding Officer & Senior Advisor (Pathology), 165 Military Hospital, C/o 99 APO, India
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12
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Wang LM, Englander ZK, Miller ML, Bruce JN. Malignant Glioma. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2023; 1405:1-30. [PMID: 37452933 DOI: 10.1007/978-3-031-23705-8_1] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/18/2023]
Abstract
This chapter provides a comprehensive overview of malignant gliomas, the most common primary brain tumor in adults. These tumors are varied in their cellular origin, genetic profile, and morphology under the microscope, but together they share some of the most dismal prognoses of all neoplasms in the body. Although there is currently no cure for malignant glioma, persistent efforts to improve outcomes in patients with these tumors have led to modest increases in survival, and researchers worldwide continue to strive toward a deeper understanding of the factors that influence glioma development and response to treatment. In addition to well-established epidemiology, clinical manifestations, and common histopathologic and radiologic features of malignant gliomas, this section considers recent advances in molecular biology that have led to a more nuanced understanding of the genetic changes that characterize the different types of malignant glioma, as well as their implications for treatment. Beyond the traditional classification of malignant gliomas based on histopathological features, this chapter incorporates the World Health Organization's 2016 criteria for the classification of brain tumors, with special focus on disease-defining genetic alterations and newly established subcategories of malignant glioma that were previously unidentifiable based on microscopic examination alone. Traditional therapeutic modalities that form the cornerstone of treatment for malignant glioma, such as aggressive surgical resection followed by adjuvant chemotherapy and radiation therapy, and the studies that support their efficacy are reviewed in detail. This provides a foundation for additional discussion of novel therapeutic methods such as immunotherapy and convection-enhanced delivery, as well as new techniques for enhancing extent of resection such as fluorescence-guided surgery.
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Affiliation(s)
- Linda M Wang
- Columbia University Irving Medical Center, New York, NY, 10032, USA
| | | | - Michael L Miller
- Columbia University Irving Medical Center, New York, NY, 10032, USA
| | - Jeffrey N Bruce
- Department of Neurosurgery, Columbia University Irving Medical Center, New York, NY, 10032, USA.
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Afzali M, Mueller L, Sakaie K, Hu S, Chen Y, Szczepankiewicz F, Griswold MA, Jones DK, Ma D. MR Fingerprinting with b-Tensor Encoding for Simultaneous Quantification of Relaxation and Diffusion in a Single Scan. Magn Reson Med 2022; 88:2043-2057. [PMID: 35713357 PMCID: PMC9420788 DOI: 10.1002/mrm.29352] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 05/19/2022] [Accepted: 05/20/2022] [Indexed: 11/08/2022]
Abstract
PURPOSE Although both relaxation and diffusion imaging are sensitive to tissue microstructure, studies have reported limited sensitivity and robustness of using relaxation or conventional diffusion alone to characterize tissue microstructure. Recently, it has been shown that tensor-valued diffusion encoding and joint relaxation-diffusion quantification enable more reliable quantification of compartment-specific microstructural properties. However, scan times to acquire such data can be prohibitive. Here, we aim to simultaneously quantify relaxation and diffusion using MR fingerprinting (MRF) and b-tensor encoding in a clinically feasible time. METHODS We developed multidimensional MRF scans (mdMRF) with linear and spherical b-tensor encoding (LTE and STE) to simultaneously quantify T1, T2, and ADC maps from a single scan. The image quality, accuracy, and scan efficiency were compared between the mdMRF using LTE and STE. Moreover, we investigated the robustness of different sequence designs to signal errors and their impact on the maps. RESULTS T1 and T2 maps derived from the mdMRF scans have consistently high image quality, while ADC maps are sensitive to different sequence designs. Notably, the fast imaging steady state precession (FISP)-based mdMRF scan with peripheral pulse gating provides the best ADC maps that are free of image distortion and shading artifacts. CONCLUSION We demonstrated the feasibility of quantifying T1, T2, and ADC maps simultaneously from a single mdMRF scan in around 24 s/slice. The map quality and quantitative values are consistent with the reference scans.
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Affiliation(s)
- Maryam Afzali
- Leeds Institute of Cardiovascular and Metabolic MedicineUniversity of Leeds
LeedsUK
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff UniversityCardiffUK
| | - Lars Mueller
- Leeds Institute of Cardiovascular and Metabolic MedicineUniversity of Leeds
LeedsUK
| | - Ken Sakaie
- Imaging Institute, Cleveland ClinicClevelandOhioUSA
| | - Siyuan Hu
- Biomedical EngineeringCase Western Reserve UniversityClevelandOhioUSA
| | - Yong Chen
- RadiologyCase Western Reserve UniversityClevelandOhioUSA
| | | | | | - Derek K. Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff UniversityCardiffUK
| | - Dan Ma
- Biomedical EngineeringCase Western Reserve UniversityClevelandOhioUSA
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14
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Radiomics can differentiate high-grade glioma from brain metastasis: a systematic review and meta-analysis. Eur Radiol 2022; 32:8039-8051. [PMID: 35587827 DOI: 10.1007/s00330-022-08828-x] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Revised: 04/05/2022] [Accepted: 04/18/2022] [Indexed: 01/03/2023]
Abstract
OBJECTIVE (1) To evaluate the diagnostic performance of radiomics in differentiating high-grade glioma from brain metastasis and how to improve the model. (2) To assess the methodological quality of radiomics studies and explore ways of embracing the clinical application of radiomics. METHODS Studies using radiomics to differentiate high-grade glioma from brain metastasis published by 26 July 2021 were systematically reviewed. Methodological quality and risk of bias were assessed using the Radiomics Quality Score (RQS) system and Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool, respectively. Pooled sensitivity and specificity of the radiomics model were also calculated. RESULTS Seventeen studies combining 1,717 patients were included in the systematic review, of which 10 studies without data leakage suspicion were employed for the quantitative statistical analysis. The average RQS was 5.13 (14.25% of total), with substantial or almost perfect inter-rater agreements. The inclusion of clinical features in the radiomics model was only reported in one study, as was the case for publicly available algorithm code. The pooled sensitivity and specificity were 84% (95% CI, 80-88%) and 84% (95% CI, 81-87%), respectively. The performances of feature extraction from the volume of interest (VOI) or (semi) automatic segmentation in the radiomics models were superior to those of protocols employing region of interest (ROI) or manual segmentation. CONCLUSION Radiomics can accurately differentiate high-grade glioma from brain metastasis. The adoption of standardized workflow to avoid potential data leakage as well as the integration of clinical features and radiomics are advised to consider in future studies. KEY POINTS • The pooled sensitivity and specificity of radiomics for differentiating high-grade gliomas from brain metastasis were 84% and 84%, respectively. • Avoiding potential data leakage by adopting an intensive and standardized workflow is essential to improve the quality and generalizability of the radiomics model. • The application of radiomics in combination with clinical features in differentiating high-grade gliomas from brain metastasis needs further validation.
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15
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Würtemberger U, Diebold M, Erny D, Hosp JA, Schnell O, Reinacher PC, Rau A, Kellner E, Reisert M, Urbach H, Demerath T. Diffusion Microstructure Imaging to Analyze Perilesional T2 Signal Changes in Brain Metastases and Glioblastomas. Cancers (Basel) 2022; 14:cancers14051155. [PMID: 35267463 PMCID: PMC8908999 DOI: 10.3390/cancers14051155] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 02/21/2022] [Accepted: 02/22/2022] [Indexed: 12/12/2022] Open
Abstract
Purpose: Glioblastomas (GBM) and brain metastases are often difficult to differentiate in conventional MRI. Diffusion microstructure imaging (DMI) is a novel MR technique that allows the approximation of the distribution of the intra-axonal compartment, the extra-axonal cellular, and the compartment of interstitial/free water within the white matter. We hypothesize that alterations in the T2 hyperintense areas surrounding contrast-enhancing tumor components may be used to differentiate GBM from metastases. Methods: DMI was performed in 19 patients with glioblastomas and 17 with metastatic lesions. DMI metrics were obtained from the T2 hyperintense areas surrounding contrast-enhancing tumor components. Resected brain tissue was assessed in six patients in each group for features of an edema pattern and tumor infiltration in the perilesional interstitium. Results: Within the perimetastatic T2 hyperintensities, we observed a significant increase in free water (p < 0.001) and a decrease in both the intra-axonal (p = 0.006) and extra-axonal compartments (p = 0.024) compared to GBM. Perilesional free water fraction was discriminative regarding the presence of GBM vs. metastasis with a ROC AUC of 0.824. Histologically, features of perilesional edema were present in all assessed metastases and absent or marginal in GBM. Conclusion: Perilesional T2 hyperintensities in brain metastases and GBM differ significantly in DMI-values. The increased free water fraction in brain metastases suits the histopathologically based hypothesis of perimetastatic vasogenic edema, whereas in glioblastomas there is additional tumor infiltration.
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Affiliation(s)
- Urs Würtemberger
- Department of Neuroradiology, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany; (A.R.); (H.U.); (T.D.)
- Correspondence: urs.wü; Tel.: +49-761-270-51810; Fax: +49-761-270-51950
| | - Martin Diebold
- Institute of Neuropathology, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany; (M.D.); (D.E.)
- IMM-PACT Clinician Scientist Program, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany
| | - Daniel Erny
- Institute of Neuropathology, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany; (M.D.); (D.E.)
- Berta-Ottenstein-Program for Advanced Clinician Scientists, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany
| | - Jonas A. Hosp
- Department of Neurology and Neurophysiology, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany;
| | - Oliver Schnell
- Department of Neurosurgery, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany;
| | - Peter C. Reinacher
- Department of Stereotactic and Functional Neurosurgery, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany; (P.C.R.); (M.R.)
- Fraunhofer Institute for Laser Technology, 52074 Aachen, Germany
| | - Alexander Rau
- Department of Neuroradiology, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany; (A.R.); (H.U.); (T.D.)
- Department of Diagnostic and Interventional Radiology, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany
| | - Elias Kellner
- Department of Medical Physics, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany;
| | - Marco Reisert
- Department of Stereotactic and Functional Neurosurgery, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany; (P.C.R.); (M.R.)
- Department of Medical Physics, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany;
| | - Horst Urbach
- Department of Neuroradiology, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany; (A.R.); (H.U.); (T.D.)
| | - Theo Demerath
- Department of Neuroradiology, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany; (A.R.); (H.U.); (T.D.)
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16
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Mărginean L, Ștefan PA, Lebovici A, Opincariu I, Csutak C, Lupean RA, Coroian PA, Suciu BA. CT in the Differentiation of Gliomas from Brain Metastases: The Radiomics Analysis of the Peritumoral Zone. Brain Sci 2022; 12:brainsci12010109. [PMID: 35053852 PMCID: PMC8774238 DOI: 10.3390/brainsci12010109] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 12/20/2021] [Accepted: 12/21/2021] [Indexed: 02/06/2023] Open
Abstract
Due to their similar imaging features, high-grade gliomas (HGGs) and solitary brain metastases (BMs) can be easily misclassified. The peritumoral zone (PZ) of HGGs develops neoplastic cell infiltration, while in BMs the PZ contains pure vasogenic edema. As the two PZs cannot be differentiated macroscopically, this study investigated whether computed tomography (CT)-based texture analysis (TA) of the PZ can reflect the histological difference between the two entities. Thirty-six patients with solitary brain tumors (HGGs, n = 17; BMs, n = 19) that underwent CT examinations were retrospectively included in this pilot study. TA of the PZ was analyzed using dedicated software (MaZda version 5). Univariate, multivariate, and receiver operating characteristics analyses were used to identify the best-suited parameters for distinguishing between the two groups. Seven texture parameters were able to differentiate between HGGs and BMs with variable sensitivity (56.67–96.67%) and specificity (69.23–100%) rates. Their combined ability successfully identified HGGs with 77.9–99.2% sensitivity and 75.3–100% specificity. In conclusion, the CT-based TA can be a useful tool for differentiating between primary and secondary malignancies. The TA features indicate a more heterogenous content of the HGGs’ PZ, possibly due to the local infiltration of neoplastic cells.
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Affiliation(s)
- Lucian Mărginean
- Radiology and Medical Imaging, Clinical Sciences Department, “George Emil Palade” University of Medicine, Pharmacy, Science, and Technology, 540139 Targu Mures, Romania;
- Interventional Radiology Department, Târgu Mureș County Emergency Clinical Hospital, 540136 Targu Mures, Romania
| | - Paul Andrei Ștefan
- Interventional Radiology Department, Târgu Mureș County Emergency Clinical Hospital, 540136 Targu Mures, Romania
- Department of Biomedical Imaging and Image-Guided Therapy, General Hospital of Vienna (AKH), Medical University of Vienna, 1090 Vienna, Austria
- Anatomy and Embriology, Morphological Sciences Department, “Iuliu Hațieganu” University of Medicine and Pharmacy, 400012 Cluj-Napoca, Romania;
- Radiology and Imaging Department, Cluj County Emergency Clinical Hospital, 400006 Cluj-Napoca, Romania; (A.L.); (C.C.); (P.A.C.)
- Correspondence:
| | - Andrei Lebovici
- Radiology and Imaging Department, Cluj County Emergency Clinical Hospital, 400006 Cluj-Napoca, Romania; (A.L.); (C.C.); (P.A.C.)
- Radiology, Surgical Specialties Department, “Iuliu Hațieganu” University of Medicine and Pharmacy, 400006 Cluj-Napoca, Romania
| | - Iulian Opincariu
- Anatomy and Embriology, Morphological Sciences Department, “Iuliu Hațieganu” University of Medicine and Pharmacy, 400012 Cluj-Napoca, Romania;
| | - Csaba Csutak
- Radiology and Imaging Department, Cluj County Emergency Clinical Hospital, 400006 Cluj-Napoca, Romania; (A.L.); (C.C.); (P.A.C.)
- Radiology, Surgical Specialties Department, “Iuliu Hațieganu” University of Medicine and Pharmacy, 400006 Cluj-Napoca, Romania
| | - Roxana Adelina Lupean
- Histology, Morphological Sciences Department, “Iuliu Hațieganu” University of Medicine and Pharmacy, 400012 Cluj-Napoca, Romania;
- Obstetrics and Gynecology Clinic “Dominic Stanca”, Cluj County Emergency Clinical Hospital, 400006 Cluj-Napoca, Romania
| | - Paul Alexandru Coroian
- Radiology and Imaging Department, Cluj County Emergency Clinical Hospital, 400006 Cluj-Napoca, Romania; (A.L.); (C.C.); (P.A.C.)
| | - Bogdan Andrei Suciu
- The First Surgical Clinic, Târgu Mureș County Emergency Clinical Hospital, 540136 Targu Mures, Romania;
- Anatomy, Morphological Sciences Department, “George Emil Palade” University of Medicine, Pharmacy, Science, and Technology, 540139 Targu Mures, Romania
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17
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Diffusion tensor imaging derived metrics in high grade glioma and brain metastasis differentiation. ARCHIVE OF ONCOLOGY 2022. [DOI: 10.2298/aoo210828007b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
Abstract
Background: Pretreatment differentiation between glioblastoma and metastasis
is a frequently encountered dilemma in neurosurgical practice. Distinction
is required for precise planning of resection or radiotherapy, and also for
defining further diagnostic procedures. Morphology and spectroscopy imaging
features are not specific and frequently overlap. This limitation of
magnetic resonance imaging and magnetic resonance spectroscopy was the
reason to initiate this study. The aim of the present study was to determine
whether the dataset of diffusion tensor imaging metrics contains information
which may be used for the distinction between primary and secondary
intra-axial neoplasms. Methods: Two diffusion tensor imaging parameters were
measured in 81 patients with an expansive, ring-enhancing, intra-axial
lesion on standard magnetic resonance imaging (1.5 T system). All tumors
were histologically verified glioblastoma or secondary deposit. For
qualitative analysis, two regions of interest were defined: intratumoral and
immediate peritumoral region (locations 1 and 2, respectively). Fractional
anisotropy and mean difusivity values of both groups were compared.
Additional test was performed to determine if there was a significant
difference in mean values between two locations. Results: A statistically
significant difference was found in fractional anisotropy values among two
locations, with decreasing values in the direction of neoplastic
infiltration, although such difference was not observed in fractional
anisotropy values in the group with secondary tumors. Mean difusivity values
did not appear helpful in differentiation between these two entities. In
both groups there was no significant difference in mean difusivity values,
neither in intratumoral nor in peritumoral location. Conclusion: The results
of our study justify associating the diffusion tensor imaging technique to
conventional morphologic magnetic resonance imaging as an additional
diagnostic tool for the distinction between primary and secondary
intra-axial lesions. Quantitative analysis of diffusion tensor imaging
metric, in particular measurement of fractional anisotropy in peritumoral
edema facilitates accurate diagnosis.
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18
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Khan B, Dixit R, Prakash A, Aggarwal S. Tuberculoma - a great mimicker: can diffusion tensor imaging and tractography help? Acta Radiol 2021; 64:274-281. [PMID: 34905973 DOI: 10.1177/02841851211063603] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Central nervous system (CNS) tuberculomas often mimic tumors on conventional imaging, differentiation of which may not be possible without invasive tissue sampling. Diffusion tensor imaging (DTI), owing to its unrivalled property of characterizing molecular diffusion, may help in better lesion characterization and tractography may help understand the pattern of white matter involvement by tuberculomas. PURPOSE To estimate qualitative and quantitative diffusion tensor changes in brain tuberculomas and to evaluate patterns of white matter involvement using 3D tractography. MATERIAL AND METHODS Thirty patients with brain tuberculomas were evaluated on a 3-T magnetic resonance scanner. Diffusion tensor images were acquired along 20 non-colinear encoding directions with two b-values (b = 0, b = 1000). Regions of interest (ROIs) were drawn on quantitative fractional anisotropy (FA) and apparent diffusion coefficient (ADC) maps in the center of the tuberculoma and perilesional area. Similar ROIs were placed in contralateral hemispheres for comparison. Tractography maps were also generated. RESULTS Mean FA in the center and perilesional area of tuberculomas were 0.098 ± 0.041 and 0.311 ± 0.135, respectively. ADC values in corresponding regions were 0.920 ± 0.272 ×10-3 mm2/s and 1.157 ± 0.277 ×10-3 mm2/s. These values were significantly different compared to contralateral similar brain parenchyma. Tractography revealed interruption of white fibers in the center with deviation of fibers at the periphery in the majority of tuberculomas with none showing infiltration of white matter described in tumors. CONCLUSION Significant qualitative as well as quantitative DTI changes were seen in tuberculoma and perilesional areas compared to contralateral hemisphere with tractography showing a pattern different from that described in tumors. These findings may help to differentiate tuberculomas from infiltrating tumors.
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Affiliation(s)
- Beenish Khan
- Department of Radiodiagnosis, Maulana Azad Medical College and associated Lok Nayak Hospital, Delhi, India
| | - Rashmi Dixit
- Department of Radiodiagnosis, Maulana Azad Medical College and associated Lok Nayak Hospital, Delhi, India
| | - Anjali Prakash
- Department of Radiodiagnosis, Maulana Azad Medical College and associated Lok Nayak Hospital, Delhi, India
| | - Sunita Aggarwal
- Department of Medicine, Maulana Azad Medical College and associated Lok Nayak Hospital, Delhi, India
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Seow P, Hernowo AT, Narayanan V, Wong JHD, Bahuri NFA, Cham CY, Abdullah NA, Kadir KAA, Rahmat K, Ramli N. Neural Fiber Integrity in High- Versus Low-Grade Glioma using Probabilistic Fiber Tracking. Acad Radiol 2021; 28:1721-1732. [PMID: 33023809 DOI: 10.1016/j.acra.2020.09.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Revised: 09/05/2020] [Accepted: 09/07/2020] [Indexed: 02/02/2023]
Abstract
RATIONALE AND OBJECTIVES Gliomatous tumors are known to affect neural fiber integrity, either by displacement or destruction. The aim of this study is to investigate the integrity and distribution of the white matter tracts within and around the glioma regions using probabilistic fiber tracking. MATERIAL AND METHODS Forty-two glioma patients were subjected to MRI using a standard tumor protocol with diffusion tensor imaging (DTI). The tumor and peritumor regions were delineated using snake model with reference to structural and diffusion MRI. A preprocessing pipeline of the structural MRI image, DTI data, and tumor regions was implemented. Tractography was performed to delineate the white matter (WM) tracts in the selected tumor regions via probabilistic fiber tracking. DTI indices were investigated through comparative mapping of WM tracts and tumor regions in low-grade gliomas (LGG) and high-grade gliomas (HGG). RESULTS Significant differences were seen in the planar tensor (Cp) in peritumor regions; mean diffusivity, axial diffusivity and pure isotropic diffusion in solid-enhancing tumor regions; and fractional anisotropy, axial diffusivity, pure anisotropic diffusion (q), total magnitude of diffusion tensor (L), relative anisotropy, Cp and spherical tensor (Cs) in solid nonenhancing tumor regions for affected WM tracts. In most cases of HGG, the WM tracts were not completely destroyed, but found intact inside the tumor. DISCUSSION Probabilistic fiber tracking revealed the existence and distribution of WM tracts inside tumor core for both LGG and HGG groups. There were more DTI indices in the solid nonenhancing tumor region, which showed significant differences between LGG and HGG.
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20
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Samani ZR, Parker D, Wolf R, Hodges W, Brem S, Verma R. Distinct tumor signatures using deep learning-based characterization of the peritumoral microenvironment in glioblastomas and brain metastases. Sci Rep 2021; 11:14469. [PMID: 34262079 PMCID: PMC8280204 DOI: 10.1038/s41598-021-93804-6] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Accepted: 06/30/2021] [Indexed: 11/25/2022] Open
Abstract
Tumor types are classically distinguished based on biopsies of the tumor itself, as well as a radiological interpretation using diverse MRI modalities. In the current study, the overarching goal is to demonstrate that primary (glioblastomas) and secondary (brain metastases) malignancies can be differentiated based on the microstructure of the peritumoral region. This is achieved by exploiting the extracellular water differences between vasogenic edema and infiltrative tissue and training a convolutional neural network (CNN) on the Diffusion Tensor Imaging (DTI)-derived free water volume fraction. We obtained 85% accuracy in discriminating extracellular water differences between local patches in the peritumoral area of 66 glioblastomas and 40 metastatic patients in a cross-validation setting. On an independent test cohort consisting of 20 glioblastomas and 10 metastases, we got 93% accuracy in discriminating metastases from glioblastomas using majority voting on patches. This level of accuracy surpasses CNNs trained on other conventional DTI-based measures such as fractional anisotropy (FA) and mean diffusivity (MD), that have been used in other studies. Additionally, the CNN captures the peritumoral heterogeneity better than conventional texture features, including Gabor and radiomic features. Our results demonstrate that the extracellular water content of the peritumoral tissue, as captured by the free water volume fraction, is best able to characterize the differences between infiltrative and vasogenic peritumoral regions, paving the way for its use in classifying and benchmarking peritumoral tissue with varying degrees of infiltration.
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Affiliation(s)
- Zahra Riahi Samani
- Diffusion and Connectomics in Precision Healthcare Research Lab (DiCIPHR), Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Drew Parker
- Diffusion and Connectomics in Precision Healthcare Research Lab (DiCIPHR), Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Ronald Wolf
- Department of Radiology, Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, USA
| | - Wes Hodges
- Founder at Synaptive Medical, Toronto, ON, Canada
| | - Steven Brem
- Department of Radiology, Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, USA
| | - Ragini Verma
- Diffusion and Connectomics in Precision Healthcare Research Lab (DiCIPHR), Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
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Differentiating Glioblastomas from Solitary Brain Metastases: An Update on the Current Literature of Advanced Imaging Modalities. Cancers (Basel) 2021; 13:cancers13122960. [PMID: 34199151 PMCID: PMC8231515 DOI: 10.3390/cancers13122960] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Revised: 06/09/2021] [Accepted: 06/09/2021] [Indexed: 12/12/2022] Open
Abstract
Differentiating between glioblastomas and solitary brain metastases proves to be a challenging diagnosis for neuroradiologists, as both present with imaging patterns consisting of peritumoral hyperintensities with similar intratumoral texture on traditional magnetic resonance imaging sequences. Early diagnosis is paramount, as each pathology has completely different methods of clinical assessment. In the past decade, recent developments in advanced imaging modalities enabled providers to acquire a more accurate diagnosis earlier in the patient's clinical assessment, thus optimizing clinical outcome. Dynamic susceptibility contrast has been optimized for detecting relative cerebral blood flow and relative cerebral blood volume. Diffusion tensor imaging can be used to detect changes in mean diffusivity. Neurite orientation dispersion and density imaging is an innovative modality detecting changes in intracellular volume fraction, isotropic volume fraction, and extracellular volume fraction. Magnetic resonance spectroscopy is able to assist by providing a metabolic descriptor while detecting variable ratios of choline/N-acetylaspartate, choline/creatine, and N-acetylaspartate/creatine. Finally, radiomics and machine learning algorithms have been devised to assist in improving diagnostic accuracy while often utilizing more than one advanced imaging protocol per patient. In this review, we provide an update on all the current evidence regarding the identification and differentiation of glioblastomas from solitary brain metastases.
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The Diagnostic Value of Apparent Diffusion Coefficient and Proton Magnetic Resonance Spectroscopy in the Grading of Pediatric Gliomas. J Comput Assist Tomogr 2021; 45:269-276. [PMID: 33346568 PMCID: PMC7972297 DOI: 10.1097/rct.0000000000001130] [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] [Indexed: 12/21/2022]
Abstract
The aims of this retrospective study were to assess the value of the quantitative analysis of apparent diffusion coefficient (ADC) and proton magnetic resonance spectroscopy (1H-MRS) metabolites in differentiating grades of pediatric gliomas.
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Tepe M, Saylisoy S, Toprak U, Inan I. The Potential Role of Peritumoral Apparent Diffusion Coefficient Evaluation in Differentiating Glioblastoma and Solitary Metastatic Lesions of the Brain. Curr Med Imaging 2021; 17:1200-1208. [PMID: 33726654 DOI: 10.2174/1573405617666210316120314] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Revised: 02/14/2021] [Accepted: 02/16/2021] [Indexed: 11/22/2022]
Abstract
OBJECTIVE Differentiating glioblastoma (GBM) and solitary metastasis is not always possible using conventional magnetic resonance imaging (MRI) techniques. In conventional brain MRI, GBM and brain metastases are lesions with mostly similar imaging findings. In this study, we investigated whether apparent diffusion coefficient (ADC) ratios, ADC gradients, and minimum ADC values in the peritumoral edema tissue can be used to discriminate between these two tumors. METHODS This retrospective study was approved by the local institutional review board with a waiver of written informed consent. Prior to surgical and medical treatment, conventional brain MRI and diffusion-weighted MRI (b = 0 and b = 1000) images were taken from 43 patients (12 GBM and 31 solitary metastasis cases). Quantitative ADC measurements were performed on the peritumoral tissue from the nearest segment to the tumor (ADC1), the middle segment (ADC2), and the most distant segment (ADC3). The ratios of these three values were determined proportionally to calculate the peritumoral ADC ratios. In addition, these three values were subtracted from each other to obtain the peritumoral ADC gradients. Lastly, the minimum peritumoral and tumoral ADC values, and the quantitative ADC values from the normal appearing ipsilateral white matter, contralateral white matter and ADC values from cerebrospinal fluid (CSF) were recorded. RESULTS For the differentiation of GBM and solitary metastasis, ADC3 / ADC1 was the most powerful parameter with a sensitivity of 91.7% and specificity of 87.1% at the cut-off value of 1.105 (p < 0.001), followed by ADC3 / ADC2 with a cut-off value of 1.025 (p = 0.001), sensitivity of 91.7%, and specificity of 74.2%. The cut-off, sensitivity and specificity of ADC2 / ADC1 were 1.055 (p = 0.002), 83.3%, and 67.7%, respectively. For ADC3 - ADC1, the cut-off value, sensitivity and specificity were calculated as 150 (p < 0.001), 91.7% and 83.9%, respectively. ADC3 - ADC2 had a cut-off value of 55 (p = 0.001), sensitivity of 91.7%, and specificity of 77.4 whereas ADC2 - ADC1 had a cut-off value of 75 (p = 0.003), sensitivity of 91.7%, and specificity of 61.3%. Among the remaining parameters, only the ADC3 value successfully differentiated between GBM and metastasis (GBM 1802.50 ± 189.74 vs. metastasis 1634.52 ± 212.65, p = 0.022). CONCLUSION The integration of the evaluation of peritumoral ADC ratio and ADC gradient into conventional MR imaging may provide valuable information for differentiating GBM from solitary metastatic lesions.
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Affiliation(s)
- Murat Tepe
- Yunus Emre State Hospital, Department of Radiology, Tepebasi Eskisehir. Turkey
| | - Suzan Saylisoy
- Eskisehir Osmangazi University, Faculty of Medicine, Department of Radiology, Eskisehir. Turkey
| | - Ugur Toprak
- Eskisehir Osmangazi University, Faculty of Medicine, Department of Radiology, Eskisehir. Turkey
| | - Ibrahim Inan
- Adiyaman University, Training and Research Hospital, Department of Radiology, Adiyaman. Turkey
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Gultekin MA, Turk HM, Yurtsever I, Atasoy B, Aliyev A, Yilmaz TF, Alkan A. The Utility and Efficiency of Diffusion Tensor Imaging Values to Determine Epidermal Growth Factor Receptor Gene Mutation Status in Brain Metastasis from Lung Adenocarcinoma; A Preliminary Study. Curr Med Imaging 2021; 16:1271-1277. [PMID: 33461445 DOI: 10.2174/1573405615666191122122207] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2019] [Revised: 11/04/2019] [Accepted: 11/12/2019] [Indexed: 11/22/2022]
Abstract
BACKGROUND This study aims to investigate the existence of any Diffusion Tensor Imaging (DTI) value differences in Brain Metastases (BM) due to lung adenocarcinoma based on the Epidermal Growth Factor Receptor (EGFR) gene mutation status. MATERIAL AND METHODS 17 patients with 32 solid intracranial metastatic lesions from lung adenocarcinoma were included prospectively. Patients were divided according to the EGFR mutation status as EGFR (+) (group 1, n:8) and EGFR wild type (group 2, n:9). The Fractional Anisotropy (FA), apparent diffusion coefficient (ADC), normalized ADC (nADC), Axial Diffusivity (AD), and Radial Diffusivity (RD) values were measured from the solid component of the metastatic lesions and nADC values were calculated. DTI values were compared between group 1 and group 2. The receiver-operating characteristic analysis was used to obtain cut-off values for the parameters presenting a statistical difference between the EGFR gene mutation-positive and wild type group. RESULTS There were statistically significant differences in measured ADC, nADC, AD, and RD values between group 1 and group 2. The ADC, nADC, AD, and RD values were significantly lower in group 1. There was no significant difference in FA values between the two groups. Analysis by the ROC curve method revealed a cut-off value of ≤721 x 10-6 mm2/s for ADC (Sensitivity= 72.7, Specificity=85.7); ≤0.820 for nADC (Sensitivity=72.7, Specificity=90.5), ≤ 886 for AD (Sensitivity=81.8, Specificity=81.0), and ≤588 for RD (Sensitivity=63.6, Specificity=90.5) in differentiating EGFR mutation (+) group from wild type group. CONCLUSION A combination of the decreased ADC, nADC, AD, and RD values in BM due to lung adenocarcinoma can be important for predicting the EGFR gene mutation status. DTI features of the brain metastases from lung adenocarcinoma may be utilized to provide insight into the EGFR mutation status and guide the clinicians for the initiation of targeted therapy.
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Affiliation(s)
- Mehmet Ali Gultekin
- Department of Radiology, Faculty of Medicine, Bezmialem Vakif University, Istanbul, Turkey
| | - Hacı Mehmet Turk
- Department of Medical Oncology, Faculty of Medicine, Bezmialem Vakif University, Istanbul, Turkey
| | - Ismail Yurtsever
- Department of Radiology, Faculty of Medicine, Bezmialem Vakif University, Istanbul, Turkey
| | - Bahar Atasoy
- Department of Radiology, Haseki Training and Research Hospital, Istanbul, Turkey
| | - Altay Aliyev
- Department of Medical Oncology, Faculty of Medicine, Bezmialem Vakif University, Istanbul, Turkey
| | - Temel Fatih Yilmaz
- Department of Radiology, Faculty of Medicine, Bezmialem Vakif University, Istanbul, Turkey
| | - Alpay Alkan
- Department of Radiology, Faculty of Medicine, Bezmialem Vakif University, Istanbul, Turkey
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Yan G, Yi M, Li S, Yang L, Dai Z, Xuan Y, Wu R. Quantitative metabolic characteristics in the peritumoral region of gliomas at 7T. Technol Health Care 2021; 29:509-517. [PMID: 33682787 PMCID: PMC8150443 DOI: 10.3233/thc-218048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
BACKGROUND The determination of tumor peripheral is of great significance in clinical diagnosis and treatment. OBJECTIVE In this study, we aim to obtain the metabolic condition in tumor peripheral of gliomas in vivo at 7T. METHODS C6 glioma cells were implanted into the right basal ganglia of Sprague-Dawley (SD) rats under stereotactic guided to create the glioma models. The models were sequentially undergone MRI and MRS examination on an 7T MR scanner designed for animals 7 days after the operation. Neuro metabolites were investigated from the center of the tumor, solid part of the tumor, peritumoral region, and contralateral white matter, and be quantified using the LCmodel software. Glial fibrillary acidic protein (GFAP) immunohistochemistry and conventional hematoxylin and eosin (HE) staining were performed after the imaging protocol. RESULTS Our results found that the inositol (Ins) and taurine (Tau) significantly defected in tumor peripheral compared to both tumor solid and normal tissues (P< 0.05). In contrast, the glutamate and glutamine (Glx) escalated and peaked at the tumor peripheral (P< 0.05). CONCLUSIONS This study revealed that Ins, Tau, and Glx have the potential to provide specific biomarkers for the location of tumor peripheral of glioma.
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Affiliation(s)
- Gen Yan
- Department of Radiology, The Second Affiliated Hospital of Xiamen Medical College, Xiamen, Fujian, China
| | - Meizhi Yi
- Department of Radiology, The Second Affiliated Hospital of Xiamen Medical College, Xiamen, Fujian, China
- The First Affiliated Hospital of University of South China, Hengyang, Hunan, China
| | - Shengkai Li
- Department of Radiology, Huizhou Municipal Central Hospital, Huizhou, Guangdong, China
| | - Lin Yang
- Department of Medical Imaging, The Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China
| | - Zhuozhi Dai
- Department of Medical Imaging, The Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China
| | - Yinghua Xuan
- Department of Basic Medicine, Xiamen Medical College, Xiamen, Fujian, China
- Corresponding authors: Yinghua Xuan, Department of Basic Medicine, Xiamen Medical College, Xiamen, Fujian 361008, China. E-mail: . Renhua Wu, Provincial Key Laboratory of Medical Molecular Imaging, %****␣thc-29-thc218048_temp.tex␣Line␣125␣**** Shantou, Guangdong 515041, China. E-mail:
| | - Renhua Wu
- Provincial Key Laboratory of Medical Molecular Imaging, Shantou, Guangdong, China
- Department of Medical Imaging, The Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China
- Corresponding authors: Yinghua Xuan, Department of Basic Medicine, Xiamen Medical College, Xiamen, Fujian 361008, China. E-mail: . Renhua Wu, Provincial Key Laboratory of Medical Molecular Imaging, %****␣thc-29-thc218048_temp.tex␣Line␣125␣**** Shantou, Guangdong 515041, China. E-mail:
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Flores-Alvarez E, Anselmo Rios Piedra E, Cruz-Priego GA, Durand-Muñoz C, Moreno-Jimenez S, Roldan-Valadez E. Correlations between DTI-derived metrics and MRS metabolites in tumour regions of glioblastoma: a pilot study. Radiol Oncol 2020; 54:394-408. [PMID: 32990651 PMCID: PMC7585345 DOI: 10.2478/raon-2020-0055] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Accepted: 07/31/2020] [Indexed: 02/08/2023] Open
Abstract
Introduction Specific correlations among diffusion tensor imaging (DTI)-derived metrics and magnetic resonance spectroscopy (MRS) metabolite ratios in brains with glioblastoma are still not completely understood. Patients and methods We made retrospective cohort study. MRS ratios (choline-to-N-acetyl aspartate [Cho/NAA], lipids and lactate to creatine [LL/Cr], and myo-inositol/creatine [mI/Cr]) were correlated with eleven DTI biomarkers: mean diffusivity (MD), fractional anisotropy (FA), pure isotropic diffusion (p), pure anisotropic diffusion (q), the total magnitude of the diffusion tensor (L), linear tensor (Cl), planar tensor (Cp), spherical tensor (Cs), relative anisotropy (RA), axial diffusivity (AD) and radial diffusivity (RD) at the same regions: enhanced rim, peritumoral oedema and normal-appearing white matter. Correlational analyses of 546 MRS and DTI measurements used Spearman coefficient. Results At the enhancing rim we found four significant correlations: FA ⇔ LL/Cr, Rs = -.364, p = .034; Cp ⇔ LL/Cr, Rs = .362, p = .035; q ⇔ LL/Cr, Rs = -.349, p = .035; RA ⇔ LL/Cr, Rs = -.357, p = .038. Another ten pairs of significant correlations were found in the peritumoral edema: AD ⇔ LL/Cr, AD ⇔ mI/Cr, MD ⇔ LL/Cr, MD ⇔ mI/Cr, p ⇔ LL/Cr, p ⇔ mI/ Cr, RD ⇔ mI/Cr, RD ⇔ mI/Cr, L ⇔ LL/Cr, L ⇔ mI/Cr. Conclusions DTI and MRS biomarkers answer different questions; peritumoral oedema represents the biggest challenge with at least ten significant correlations between DTI and MRS that need additional studies. The fact that DTI and MRS measures are not specific of one histologic type of tumour broadens their application to a wider variety of intracranial pathologies.
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Affiliation(s)
- Eduardo Flores-Alvarez
- Department of Neurosurgery, General Hospital of Mexico, Secretariat of Health. Mexico City, Mexico
| | - Edgar Anselmo Rios Piedra
- Department of Radiology, Stanford University, CA, USA
- Department of Electrical Engineering, Stanford University, CA, USA
| | | | - Coral Durand-Muñoz
- Department of Internal Medicine, Medica Sur Clinic and Foundation, Mexico City, Mexico
| | - Sergio Moreno-Jimenez
- Radioneurosurgery Unit, The National Institute of Neurology and Neurosurgery, Mexico City, Mexico
| | - Ernesto Roldan-Valadez
- Department of Radiology, I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russia
- Directorate of Research, General Hospital of Mexico, Secretariat of Health, Mexico City, Mexico
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Csutak C, Ștefan PA, Lenghel LM, Moroșanu CO, Lupean RA, Șimonca L, Mihu CM, Lebovici A. Differentiating High-Grade Gliomas from Brain Metastases at Magnetic Resonance: The Role of Texture Analysis of the Peritumoral Zone. Brain Sci 2020; 10:brainsci10090638. [PMID: 32947822 PMCID: PMC7565295 DOI: 10.3390/brainsci10090638] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Revised: 09/03/2020] [Accepted: 09/14/2020] [Indexed: 11/16/2022] Open
Abstract
High-grade gliomas (HGGs) and solitary brain metastases (BMs) have similar imaging appearances, which often leads to misclassification. In HGGs, the surrounding tissues show malignant invasion, while BMs tend to displace the adjacent area. The surrounding edema produced by the two cannot be differentiated by conventional magnetic resonance (MRI) examinations. Forty-two patients with pathology-proven brain tumors who underwent conventional pretreatment MRIs were retrospectively included (HGGs, n = 16; BMs, n = 26). Texture analysis of the peritumoral zone was performed on the T2-weighted sequence using dedicated software. The most discriminative texture features were selected using the Fisher and the probability of classification error and average correlation coefficients. The ability of texture parameters to distinguish between HGGs and BMs was evaluated through univariate, receiver operating, and multivariate analyses. The first percentile and wavelet energy texture parameters were independent predictors of HGGs (75–87.5% sensitivity, 53.85–88.46% specificity). The prediction model consisting of all parameters that showed statistically significant results at the univariate analysis was able to identify HGGs with 100% sensitivity and 66.7% specificity. Texture analysis can provide a quantitative description of the peritumoral zone encountered in solitary brain tumors, that can provide adequate differentiation between HGGs and BMs.
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Affiliation(s)
- Csaba Csutak
- Radiology and Imaging Department, County Emergency Hospital, Cluj-Napoca, Clinicilor Street, Number 5, Cluj-Napoca, 400006 Cluj, Romania; (C.C.); (L.M.L.); (C.M.M.); (A.L.)
- Radiology, Surgical Specialties Department, “Iuliu Haţieganu” University of Medicine and Pharmacy, Clinicilor Street, number 3–5, Cluj-Napoca, 400006 Cluj, Romania
| | - Paul-Andrei Ștefan
- Radiology and Imaging Department, County Emergency Hospital, Cluj-Napoca, Clinicilor Street, Number 5, Cluj-Napoca, 400006 Cluj, Romania; (C.C.); (L.M.L.); (C.M.M.); (A.L.)
- Anatomy and Embryology, Morphological Sciences Department, “Iuliu Haţieganu” University of Medicine and Pharmacy, Victor Babeș Street, number 8, Cluj-Napoca, 400012 Cluj, Romania
- Correspondence: ; Tel.: +40-743-957-206
| | - Lavinia Manuela Lenghel
- Radiology and Imaging Department, County Emergency Hospital, Cluj-Napoca, Clinicilor Street, Number 5, Cluj-Napoca, 400006 Cluj, Romania; (C.C.); (L.M.L.); (C.M.M.); (A.L.)
- Radiology, Surgical Specialties Department, “Iuliu Haţieganu” University of Medicine and Pharmacy, Clinicilor Street, number 3–5, Cluj-Napoca, 400006 Cluj, Romania
| | - Cezar Octavian Moroșanu
- Department of Neurosurgery, North Bristol Trust, Southmead Hospital, Southmead Road, Westbury on Trym, Bristol BS2 8BJ, UK;
| | - Roxana-Adelina Lupean
- Histology, Morphological Sciences Department, “Iuliu Hațieganu” University of Medicine and Pharmacy, Louis Pasteur Street, number 4, Cluj-Napoca, 400349 Cluj, Romania;
| | - Larisa Șimonca
- Department of Paediatric Surgery, Bristol Royal Hospital for Children, Upper Maudlin Street, Bristol BS2 8BJ, UK;
| | - Carmen Mihaela Mihu
- Radiology and Imaging Department, County Emergency Hospital, Cluj-Napoca, Clinicilor Street, Number 5, Cluj-Napoca, 400006 Cluj, Romania; (C.C.); (L.M.L.); (C.M.M.); (A.L.)
- Histology, Morphological Sciences Department, “Iuliu Hațieganu” University of Medicine and Pharmacy, Louis Pasteur Street, number 4, Cluj-Napoca, 400349 Cluj, Romania;
| | - Andrei Lebovici
- Radiology and Imaging Department, County Emergency Hospital, Cluj-Napoca, Clinicilor Street, Number 5, Cluj-Napoca, 400006 Cluj, Romania; (C.C.); (L.M.L.); (C.M.M.); (A.L.)
- Radiology, Surgical Specialties Department, “Iuliu Haţieganu” University of Medicine and Pharmacy, Clinicilor Street, number 3–5, Cluj-Napoca, 400006 Cluj, Romania
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Gonçalves FG, Chawla S, Mohan S. Emerging MRI Techniques to Redefine Treatment Response in Patients With Glioblastoma. J Magn Reson Imaging 2020; 52:978-997. [PMID: 32190946 DOI: 10.1002/jmri.27105] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2019] [Revised: 01/28/2020] [Accepted: 01/30/2020] [Indexed: 12/14/2022] Open
Abstract
Glioblastoma is the most common and most malignant primary brain tumor. Despite aggressive multimodal treatment, its prognosis remains poor. Even with continuous developments in MRI, which has provided us with newer insights into the diagnosis and understanding of tumor biology, response assessment in the posttherapy setting remains challenging. We believe that the integration of additional information from advanced neuroimaging techniques can further improve the diagnostic accuracy of conventional MRI. In this article, we review the utility of advanced neuroimaging techniques such as diffusion-weighted imaging, diffusion tensor imaging, perfusion-weighted imaging, proton magnetic resonance spectroscopy, and chemical exchange saturation transfer in characterizing and evaluating treatment response in patients with glioblastoma. We will also discuss the existing challenges and limitations of using these techniques in clinical settings and possible solutions to avoiding pitfalls in study design, data acquisition, and analysis for future studies. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 3 J. Magn. Reson. Imaging 2020;52:978-997.
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Affiliation(s)
| | - Sanjeev Chawla
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Suyash Mohan
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
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Differentiation of Glioblastoma and Solitary Brain Metastasis by Gradient of Relative Cerebral Blood Volume in the Peritumoral Brain Zone Derived from Dynamic Susceptibility Contrast Perfusion Magnetic Resonance Imaging. J Comput Assist Tomogr 2019; 43:13-17. [PMID: 30015801 DOI: 10.1097/rct.0000000000000771] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
OBJECTIVE The purpose of our study was to evaluate the efficacy of the relative cerebral blood volume (rCBV) gradient in the peritumoral brain zone (PBZ)-the difference in the rCBV values from the area closest to the enhancing lesion to the area closest to the healthy white matter-in differentiating glioblastoma (GB) from solitary brain metastasis (MET). METHODS A 3.0-T magnetic resonance imaging (MRI) machine was used to perform dynamic susceptibility contrast perfusion MRI (DSC-MRI) on 43 patients with a solitary brain tumor (24 GB, 19 MET). The rCBV ratios were acquired by DSC-MRI data in 3 regions of the PBZ (near the enhancing tumor, G1; intermediate distance from the enhancing tumor, G2; far from the enhancing tumor, G3). The maximum rCBV ratios in the PBZ (rCBVp) and the enhancing tumor were also calculated, respectively. The perfusion parameters were evaluated using the nonparametric Mann-Whitney test. The sensitivity, specificity, accuracy, and the area under the receiver operating characteristic curve were identified. RESULTS The rCBVp ratios and rCBV gradient in the PBZ were significantly higher in GB compared with MET (P < 0.05 for both rCBVp ratios and rCBV gradient). The threshold values of 0.50 or greater for rCBVp ratios provide sensitivity and specificity of 57.69% and 79.17%, respectively, for differentiation of GB from MET. Compared with rCBVp ratios, rCBV gradient had higher sensitivity (94.44%) and specificity (91.67%) using the threshold value of greater than 0.06. CONCLUSIONS The parameter of rCBV gradient derived from DSC-MRI in the PBZ seems to be the most efficient parameter to differentiate GB from METs.
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30
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Li Y, Zhang W. Quantitative evaluation of diffusion tensor imaging for clinical management of glioma. Neurosurg Rev 2018; 43:881-891. [PMID: 30417213 DOI: 10.1007/s10143-018-1050-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2018] [Revised: 09/26/2018] [Accepted: 11/01/2018] [Indexed: 11/26/2022]
Abstract
Diffusion tensor imaging (DTI), assessing physiological motion of water in vivo, provides macroscopic view of microstructures of white matter in the central nervous system, and such imaging technique had been extensively used for the clinical treatment and research of glioma. This review mainly focuses on illuminating the merits of quantitative evaluation of DTI for glioma management. The content of the article includes DTI's application on tissue characterization, white matter tracts mapping, radiotherapy delineation, post-therapy outcome assessment, and multimodal imaging. At last, we elucidate a synoptic presentation of DTI limitation, which is critical for physicians making DTI-based clinical decisions in glioma management.
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Affiliation(s)
- Ye Li
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, 45 Changchun Street, Xicheng District, Beijing, 100853, China.
| | - Wenyao Zhang
- Beijing Key Laboratory of Intelligent Information Technology, School of Computer Science, Beijing Institute of Technology, Beijing, 100081, China
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Askaner K, Rydelius A, Engelholm S, Knutsson L, Lätt J, Abul-Kasim K, Sundgren PC. Differentiation between glioblastomas and brain metastases and regarding their primary site of malignancy using dynamic susceptibility contrast MRI at 3T. J Neuroradiol 2018; 46:367-372. [PMID: 30389510 DOI: 10.1016/j.neurad.2018.09.006] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2018] [Revised: 07/23/2018] [Accepted: 09/26/2018] [Indexed: 11/19/2022]
Abstract
BACKGROUND Differentiation between glioblastoma and brain metastasis may be challenging in conventional contrast-enhanced MRI. PURPOSE To investigate if perfusion-weighted MRI is able to differentiate glioblastoma from metastasis and, as a second aim was to see if it was possible in the latter group, to predict the primary site of neoplasm. MATERIAL AND METHODS Hundred and fourteen patients with newly discovered tumor lesion (76 metastases and 38 glioblastomas) underwent conventional contrast-enhanced MRI including dynamic susceptibility contrast perfusion sequence. The calculated relative cerebral blood volumes were analyzed in the solid tumor area, peritumoral area, area adjacent to peritumoral area, and normal appearing white matter in contralateral semioval center. The Student t-test was used to detect statistically significant differences in relative cerebral blood volume between glioblastomas and metastases in the aforementioned areas. Furthermore, the metastasis group was divided in four sub groups (lung-, breast-, melanoma-, and gastrointestinal origin) and using one-way ANOVA test. P-values < 0.05 were considered significant. RESULTS Relative cerebral blood volume (rCBV) in the peritumoral edema was significantly higher in glioblastomas than in metastases (mean 3.2 ± 1.4 and mean 0.9 ± 0.7), respectively, (P < 0.0001). No significant differences in the solid tumor area or the area adjacent to edema were found, (P = 0.28 and 0.21 respectively). There were no significant differences among metastases in the four groups. CONCLUSION It is possible to differentiate glioblastomas from metastases by measuring the CBV in the peritumoral edema. It is not possible to differentiate between brain metastases from different primaries (lung-, breast-, melanoma or gastrointestinal) using CBV-measurements in the solid tumor area, peritumoral edema or area adjacent to edema.
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Affiliation(s)
- K Askaner
- Centre for Medical Imaging and Physiology, SUS, Malmoe, Sweden.
| | | | | | - L Knutsson
- Department of Medical Radiation Physics, Lund University, Lund, Sweden; Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, US
| | - J Lätt
- Centre for Medical Imaging and Physiology, SUS, Lund, Sweden
| | - K Abul-Kasim
- Centre for Medical Imaging and Physiology, SUS, Malmoe, Sweden
| | - P C Sundgren
- Institution of Clinical Sciences, Lund University, Lund, Sweden; Department of Radiology, University of Michigan, Ann Arbor, US
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Kazerooni AF, Nabil M, Zadeh MZ, Firouznia K, Azmoudeh-Ardalan F, Frangi AF, Davatzikos C, Rad HS. Characterization of active and infiltrative tumorous subregions from normal tissue in brain gliomas using multiparametric MRI. J Magn Reson Imaging 2018; 48:938-950. [PMID: 29412496 PMCID: PMC6081259 DOI: 10.1002/jmri.25963] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2017] [Accepted: 01/20/2018] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Targeted localized biopsies and treatments for diffuse gliomas rely on accurate identification of tissue subregions, for which current MRI techniques lack specificity. PURPOSE To explore the complementary and competitive roles of a variety of conventional and quantitative MRI methods for distinguishing subregions of brain gliomas. STUDY TYPE Prospective. POPULATION Fifty-one tissue specimens were collected using image-guided localized biopsy surgery from 10 patients with newly diagnosed gliomas. FIELD STRENGTH/SEQUENCE Conventional and quantitative MR images consisting of pre- and postcontrast T1 w, T2 w, T2 -FLAIR, T2 -relaxometry, DWI, DTI, IVIM, and DSC-MRI were acquired preoperatively at 3T. ASSESSMENT Biopsy specimens were histopathologically attributed to glioma tissue subregion categories of active tumor (AT), infiltrative edema (IE), and normal tissue (NT) subregions. For each tissue sample, a feature vector comprising 15 MRI-based parameters was derived from preoperative images and assessed by a machine learning algorithm to determine the best multiparametric feature combination for characterizing the tissue subregions. STATISTICAL TESTS For discrimination of AT, IE, and NT subregions, a one-way analysis of variance (ANOVA) test and for pairwise tissue subregion differentiation, Tukey honest significant difference, and Games-Howell tests were applied (P < 0.05). Cross-validated feature selection and classification methods were implemented for identification of accurate multiparametric MRI parameter combination. RESULTS After exclusion of 17 tissue specimens, 34 samples (AT = 6, IE = 20, and NT = 8) were considered for analysis. Highest accuracies and statistically significant differences for discrimination of IE from NT and AT from NT were observed for diffusion-based parameters (AUCs >90%), and the perfusion-derived parameter as the most accurate feature in distinguishing IE from AT. A combination of "CBV, MD, T2 _ISO, FLAIR" parameters showed high diagnostic performance for identification of the three subregions (AUC ∼90%). DATA CONCLUSION Integration of a few quantitative along with conventional MRI parameters may provide a potential multiparametric imaging biomarker for predicting the histopathologically proven glioma tissue subregions. LEVEL OF EVIDENCE 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;48:938-950.
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Affiliation(s)
- Anahita Fathi Kazerooni
- Quantitative MR Imaging and Spectroscopy Group, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran
- Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran
| | - Mahnaz Nabil
- Department of Statistics, Faculty of Mathematical Science, University of Guilan, Rasht, Iran
| | - Mehdi Zeinali Zadeh
- Department of Neurological Surgery, Imam Khomeini Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Kavous Firouznia
- Advanced Diagnostic and Interventional Radiology Research Center, Imam Khomeini Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Farid Azmoudeh-Ardalan
- Department of Pathology, Imam Khomeini Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Alejandro F. Frangi
- Department of Electronic and Electrical Engineering, University of Sheffield, Sheffield, UK
| | - Christos Davatzikos
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Hamidreza Saligheh Rad
- Quantitative MR Imaging and Spectroscopy Group, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran
- Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran
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Doishita S, Sakamoto S, Yoneda T, Uda T, Tsukamoto T, Yamada E, Yoneyama M, Kimura D, Katayama Y, Tatekawa H, Shimono T, Ohata K, Miki Y. Differentiation of Brain Metastases and Gliomas Based on Color Map of Phase Difference Enhanced Imaging. Front Neurol 2018; 9:788. [PMID: 30298047 PMCID: PMC6160550 DOI: 10.3389/fneur.2018.00788] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2018] [Accepted: 08/31/2018] [Indexed: 12/14/2022] Open
Abstract
Background and objective: Phase difference enhanced imaging (PADRE), a new phase-related MRI technique, can enhance both paramagnetic and diamagnetic substances, and select which phases to be enhanced. Utilizing these characteristics, we developed color map of PADRE (Color PADRE), which enables simultaneous visualization of myelin-rich structures and veins. Our aim was to determine whether Color PADRE is sufficient to delineate the characteristics of non-gadolinium-enhancing T2-hyperintense regions related with metastatic tumors (MTs), diffuse astrocytomas (DAs) and glioblastomas (GBs), and whether it can contribute to the differentiation of MTs from GBs. Methods: Color PADRE images of 11 patients with MTs, nine with DAs and 17 with GBs were created by combining tissue-enhanced, vessel-enhanced and magnitude images of PADRE, and then retrospectively reviewed. First, predominant visibility of superficial white matter and deep medullary veins within non-gadolinium-enhancing T2-hyperintense regions were compared among the three groups. Then, the discriminatory power to differentiate MTs from GBs was assessed using receiver operating characteristic analysis. Results: The degree of visibility of superficial white matter was significantly better in MTs than in GBs (p = 0.017), better in GBs than in DAs (p = 0.014), and better in MTs than in DAs (p = 0.0021). On the contrary, the difference in the visibility of deep medullary veins was not significant (p = 0.065). The area under the receiver operating characteristic curve to discriminate MTs from GBs was 0.76 with a sensitivity of 80% and specificity of 64%. Conclusion: Visibility of superficial white matter on Color PADRE reflects inferred differences in the proportion of vasogenic edema and tumoral infiltration within non-gadolinium-enhancing T2-hyperintense regions of MTs, DAs and GBs. Evaluation of peritumoral areas on Color PADRE can help to distinguish MTs from GBs.
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Affiliation(s)
- Satoshi Doishita
- Department of Diagnostic and Interventional Radiology, Osaka City University Graduate School of Medicine, Osaka, Japan
| | - Shinichi Sakamoto
- Department of Diagnostic and Interventional Radiology, Osaka City University Graduate School of Medicine, Osaka, Japan
| | - Tetsuya Yoneda
- Department of Medical Physics in Advanced Biomedical Sciences, Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan
| | - Takehiro Uda
- Department of Neurosurgery, Osaka City University Graduate School of Medicine, Osaka, Japan
| | - Taro Tsukamoto
- Department of Diagnostic and Interventional Radiology, Osaka City University Graduate School of Medicine, Osaka, Japan
| | - Eiji Yamada
- Department of Radiological Technology, Osaka City University Hospital, Osaka, Japan
| | | | - Daisuke Kimura
- Department of Radiological Technology, Osaka City University Hospital, Osaka, Japan
| | - Yutaka Katayama
- Department of Radiological Technology, Osaka City University Hospital, Osaka, Japan
| | - Hiroyuki Tatekawa
- Department of Diagnostic and Interventional Radiology, Osaka City University Graduate School of Medicine, Osaka, Japan
| | - Taro Shimono
- Department of Diagnostic and Interventional Radiology, Osaka City University Graduate School of Medicine, Osaka, Japan
| | - Kenji Ohata
- Department of Neurosurgery, Osaka City University Graduate School of Medicine, Osaka, Japan
| | - Yukio Miki
- Department of Diagnostic and Interventional Radiology, Osaka City University Graduate School of Medicine, Osaka, Japan
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Holly KS, Fitz-Gerald JS, Barker BJ, Murcia D, Daggett R, Ledbetter C, Gonzalez-Toledo E, Sun H. Differentiation of High-Grade Glioma and Intracranial Metastasis Using Volumetric Diffusion Tensor Imaging Tractography. World Neurosurg 2018; 120:e131-e141. [PMID: 30165214 DOI: 10.1016/j.wneu.2018.07.230] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2018] [Revised: 07/24/2018] [Accepted: 07/25/2018] [Indexed: 11/15/2022]
Abstract
OBJECTIVE A reliable, noninvasive method to differentiate high-grade glioma (HGG) and intracranial metastasis (IM) has remained elusive. The aim of this study was to differentiate between HGG and IM using tumoral and peritumoral diffusion tensor imaging characteristics. METHODS A semiautomated script generated volumetric regions of interest (ROIs) for the tumor and a peritumoral shell at a predetermined voxel thickness. ROI differences in diffusion tensor imaging-related metrics between HGG and IM groups were estimated, including fractional anisotropy, mean diffusivity, total fiber tract counts, and tract density. RESULTS The HGG group (n = 46) had a significantly higher tumor-to-brain volume ratio than the IM group (n = 35) (P < 0.001). The HGG group exhibited significantly higher mean fractional anisotropy and significantly lower mean diffusivity within peritumoral ROI than the IM group (P < 0.05). The HGG group exhibited significantly higher total tract count and higher tract density in tumoral and peritumoral ROIs than the IM group (P < 0.05). Tumoral tract count and peritumoral tract density were the most optimal metrics to differentiate the groups based on receiver operating characteristic curve analysis. Predictive analysis using receiver operating characteristic curve thresholds was performed on 13 additional participants. Compared with correct clinical diagnoses, the 2 thresholds exhibited equal specificities (66.7%), but the tumoral tract count (85.7%) seemed more sensitive in differentiating the 2 groups. CONCLUSIONS Tract count and tract density were significantly different in tumoral and peritumoral regions between HGG and IM. Differences in microenvironmental interactions between the tumor types may cause these tract differences.
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Affiliation(s)
- Kevin S Holly
- Department of Neurosurgery, Louisiana State University Health Sciences Center Shreveport, Shreveport, Louisiana, USA
| | - Joseph S Fitz-Gerald
- Department of Neurosurgery, Louisiana State University Health Sciences Center Shreveport, Shreveport, Louisiana, USA
| | - Benjamin J Barker
- Department of Neurosurgery, Louisiana State University Health Sciences Center Shreveport, Shreveport, Louisiana, USA
| | - Derrick Murcia
- Department of Neurosurgery, Louisiana State University Health Sciences Center Shreveport, Shreveport, Louisiana, USA
| | - Rebekah Daggett
- Department of Neurosurgery, Louisiana State University Health Sciences Center Shreveport, Shreveport, Louisiana, USA
| | - Christina Ledbetter
- Department of Neurosurgery, Louisiana State University Health Sciences Center Shreveport, Shreveport, Louisiana, USA
| | - Eduardo Gonzalez-Toledo
- Department of Radiology, Louisiana State University Health Sciences Center Shreveport, Shreveport, Louisiana, USA
| | - Hai Sun
- Department of Neurosurgery, Louisiana State University Health Sciences Center Shreveport, Shreveport, Louisiana, USA.
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Suh CH, Kim HS, Jung SC, Kim SJ. Diffusion-Weighted Imaging and Diffusion Tensor Imaging for Differentiating High-Grade Glioma from Solitary Brain Metastasis: A Systematic Review and Meta-Analysis. AJNR Am J Neuroradiol 2018; 39:1208-1214. [PMID: 29724766 DOI: 10.3174/ajnr.a5650] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2017] [Accepted: 03/07/2018] [Indexed: 12/13/2022]
Abstract
BACKGROUND Accurate diagnosis of high-grade glioma and solitary brain metastasis is clinically important because it affects the patient's outcome and alters patient management. PURPOSE To evaluate the diagnostic performance of DWI and DTI for differentiating high-grade glioma from solitary brain metastasis. DATA SOURCES A literature search of Ovid MEDLINE and EMBASE was conducted up to November 10, 2017. STUDY SELECTION Studies evaluating the diagnostic performance of DWI and DTI for differentiating high-grade glioma from solitary brain metastasis were selected. DATA ANALYSIS Summary sensitivity and specificity were established by hierarchic logistic regression modeling. Multiple subgroup analyses were also performed. DATA SYNTHESIS Fourteen studies with 1143 patients were included. The individual sensitivities and specificities of the 14 included studies showed a wide variation, ranging from 46.2% to 96.0% for sensitivity and 40.0% to 100.0% for specificity. The pooled sensitivity of both DWI and DTI was 79.8% (95% CI, 70.9%-86.4%), and the pooled specificity was 80.9% (95% CI, 75.1%-85.5%). The area under the hierarchical summary receiver operating characteristic curve was 0.87 (95% CI, 0.84-0.89). The multiple subgroup analyses also demonstrated similar diagnostic performances (sensitivities of 76.8%-84.7% and specificities of 79.7%-84.0%). There was some level of heterogeneity across the included studies (I2 = 36%); however, it did not reach a level of concern. LIMITATIONS The included studies used various DWI and DTI parameters. CONCLUSIONS DWI and DTI demonstrated a moderate diagnostic performance for differentiation of high-grade glioma from solitary brain metastasis.
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Affiliation(s)
- C H Suh
- From the Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - H S Kim
- From the Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea.
| | - S C Jung
- From the Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - S J Kim
- From the Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
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Vamvakas A, Tsougos I, Arikidis N, Kapsalaki E, Fountas K, Fezoulidis I, Costaridou L. Exploiting morphology and texture of 3D tumor models in DTI for differentiating glioblastoma multiforme from solitary metastasis. Biomed Signal Process Control 2018. [DOI: 10.1016/j.bspc.2018.02.014] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
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Lin L, Xue Y, Duan Q, Sun B, Lin H, Huang X, Chen X. The role of cerebral blood flow gradient in peritumoral edema for differentiation of glioblastomas from solitary metastatic lesions. Oncotarget 2018; 7:69051-69059. [PMID: 27655705 PMCID: PMC5356611 DOI: 10.18632/oncotarget.12053] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2016] [Accepted: 09/02/2016] [Indexed: 11/25/2022] Open
Abstract
OBJECTIVE Differentiation of glioblastomas from solitary brain metastases using conventional MRI remains an important unsolved problem. In this study, we introduced the conception of the cerebral blood flow (CBF) gradient in peritumoral edema-the difference in CBF values from the proximity of the enhancing tumor to the normal-appearing white matter, and investigated the contribution of perfusion metrics on the discrimination of glioblastoma from a metastatic lesion. MATERIALS AND METHODS Fifty-two consecutive patients with glioblastoma or a solitary metastatic lesion underwent three-dimensional arterial spin labeling (3D-ASL) before surgical resection. The CBF values were measured in the peritumoral edema (near: G1; Intermediate: G2; Far: G3). The CBF gradient was calculated as the subtractions CBFG1 -CBFG3, CBFG1 - CBFG2 and CBFG2 - CBFG3. A receiver operating characteristic (ROC) curve analysis was used to seek for the best cutoff value permitting discrimination between these two tumors. RESULTS The absolute/related CBF values and the CBF gradient in the peritumoral regions of glioblastomas were significantly higher than those in metastases(P < 0.038). ROC curve analysis reveals, a cutoff value of 1.92 ml/100g for the CBF gradient of CBFG1 -CBFG3 generated the best combination of sensitivity (92.86%) and specificity (100.00%) for distinguishing between a glioblastoma and metastasis. CONCLUSION The CBF gradient in peritumoral edema appears to be a more promising ASL perfusion metrics in differentiating high grade glioma from a solitary metastasis.
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Affiliation(s)
- Lin Lin
- Department of Radiology, Union Hospital of Fujian Medical University, Fuzhou, Fujian, China
| | - Yunjing Xue
- Department of Radiology, Union Hospital of Fujian Medical University, Fuzhou, Fujian, China
| | - Qing Duan
- Department of Radiology, Union Hospital of Fujian Medical University, Fuzhou, Fujian, China
| | - Bin Sun
- Department of Radiology, Union Hospital of Fujian Medical University, Fuzhou, Fujian, China
| | - Hailong Lin
- Department of Radiology, Union Hospital of Fujian Medical University, Fuzhou, Fujian, China
| | - Xinming Huang
- Department of Radiology, Union Hospital of Fujian Medical University, Fuzhou, Fujian, China
| | - Xiaodan Chen
- Department of Radiology, Fujian Provincial Cancer Hospital, Fuzhou, Fujian, China
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Nandu H, Wen PY, Huang RY. Imaging in neuro-oncology. Ther Adv Neurol Disord 2018; 11:1756286418759865. [PMID: 29511385 PMCID: PMC5833173 DOI: 10.1177/1756286418759865] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2017] [Accepted: 01/18/2018] [Indexed: 12/11/2022] Open
Abstract
Imaging plays several key roles in managing brain tumors, including diagnosis, prognosis, and treatment response assessment. Ongoing challenges remain as new therapies emerge and there are urgent needs to find accurate and clinically feasible methods to noninvasively evaluate brain tumors before and after treatment. This review aims to provide an overview of several advanced imaging modalities including magnetic resonance imaging and positron emission tomography (PET), including advances in new PET agents, and summarize several key areas of their applications, including improving the accuracy of diagnosis and addressing the challenging clinical problems such as evaluation of pseudoprogression and anti-angiogenic therapy, and rising challenges of imaging with immunotherapy.
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Affiliation(s)
- Hari Nandu
- Department of Radiology, Brigham and Women's Hospital, Boston, MA, USA
| | | | - Raymond Y Huang
- Department of Radiology, Brigham and Women's Hospital, 75 Francis Street, Boston, MA 02445, USA
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Oros-Peusquens A, Loução R, Zimmermann M, Langen KJ, Shah N. Methods for molecular imaging of brain tumours in a hybrid MR-PET context: Water content, T 2 ∗ , diffusion indices and FET-PET. Methods 2017; 130:135-151. [DOI: 10.1016/j.ymeth.2017.07.025] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2017] [Revised: 05/22/2017] [Accepted: 07/27/2017] [Indexed: 11/27/2022] Open
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Jiang L, Xiao CY, Xu Q, Sun J, Chen H, Chen YC, Yin X. Analysis of DTI-Derived Tensor Metrics in Differential Diagnosis between Low-grade and High-grade Gliomas. Front Aging Neurosci 2017; 9:271. [PMID: 28848428 PMCID: PMC5551510 DOI: 10.3389/fnagi.2017.00271] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2017] [Accepted: 07/27/2017] [Indexed: 01/24/2023] Open
Abstract
Purpose: It is critical and difficult to accurately discriminate between high- and low-grade gliomas preoperatively. This study aimed to ascertain the role of several scalar measures in distinguishing high-grade from low-grade gliomas, especially the axial diffusivity (AD), radial diffusivity (RD), planar tensor (Cp), spherical tensor (Cs), and linear tensor (Cl) derived from diffusion tensor imaging (DTI). Materials and Methods: Fifty-three patients with pathologically confirmed brain gliomas (21 low-grade and 32 high-grade) were included. Contrast-enhanced T1-weighted images and DTI were performed in all patients. The AD, RD, Cp, Cs, and Cl values in the tumor zone, peritumoral edema zone, white matter (WM) adjacent to edema and contralateral normal-appearing white matter (NAWM) were calculated. The DTI parameters and tumor grades were statistically analyzed, and receiver operating characteristic (ROC) curve analysis was also performed. Results: The DTI metrics in the affected hemisphere showed significant differences from those in the NAWM, except for the AD values in the tumor zone and the RD values in WM adjacent to edema in the low-grade groups, as well as the Cp values in WM adjacent to edema in the high-grade groups. AD in the tumor zone as well as Cs and Cl in WM adjacent to edema revealed significant differences between the low- and high-grade gliomas. The areas under the curve (Az) of all three metrics were greater than 0.5 in distinguishing low-grade from high-grade gliomas by ROC curve analysis, and the best DTI metric was Cs in WM adjacent to edema (Az: 0.692). Conclusion: AD in the tumor zone as well as Cs and Cl in WM adjacent to edema will provide additional information to better classify gliomas and can be used as non-invasive reliable biomarkers in glioma grading.
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Affiliation(s)
- Liang Jiang
- Department of Radiology, Nanjing First Hospital, Nanjing Medical UniversityNanjing, China
| | - Chao-Yong Xiao
- Department of Radiology, Brain Hospital Affiliated to Nanjing Medical UniversityNanjing, China
| | - Quan Xu
- Department of Radiology, Nanjing First Hospital, Nanjing Medical UniversityNanjing, China
| | - Jun Sun
- Department of Radiology, Nanjing First Hospital, Nanjing Medical UniversityNanjing, China
| | - Huiyou Chen
- Department of Radiology, Nanjing First Hospital, Nanjing Medical UniversityNanjing, China
| | - Yu-Chen Chen
- Department of Radiology, Nanjing First Hospital, Nanjing Medical UniversityNanjing, China
| | - Xindao Yin
- Department of Radiology, Nanjing First Hospital, Nanjing Medical UniversityNanjing, China
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Taylor EN, Ding Y, Zhu S, Cheah E, Alexander P, Lin L, Aninwene GE, Hoffman MP, Mahajan A, Mohamed AS, McDannold N, Fuller CD, Chen CC, Gilbert RJ. Association between tumor architecture derived from generalized Q-space MRI and survival in glioblastoma. Oncotarget 2017; 8:41815-41826. [PMID: 28404971 PMCID: PMC5522030 DOI: 10.18632/oncotarget.16296] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2016] [Accepted: 01/24/2017] [Indexed: 01/22/2023] Open
Abstract
While it is recognized that the overall resistance of glioblastoma to treatment may be related to intra-tumor patterns of structural heterogeneity, imaging methods to assess such patterns remain rudimentary. METHODS We utilized a generalized Q-space imaging (GQI) algorithm to analyze magnetic resonance imaging (MRI) derived from a rodent model of glioblastoma and 2 clinical datasets to correlate GQI, histology, and survival. RESULTS In a rodent glioblastoma model, GQI demonstrated a poorly coherent core region, consisting of diffusion tracts <5 mm, surrounded by a shell of highly coherent diffusion tracts, 6-25 mm. Histologically, the core region possessed a high degree of necrosis, whereas the shell consisted of organized sheets of anaplastic cells with elevated mitotic index. These attributes define tumor architecture as the macroscopic organization of variably aligned tumor cells. Applied to MRI data from The Cancer Imaging Atlas (TCGA), the core-shell diffusion tract-length ratio (c/s ratio) correlated linearly with necrosis, which, in turn, was inversely associated with survival (p = 0.00002). We confirmed in an independent cohort of patients (n = 62) that the c/s ratio correlated inversely with survival (p = 0.0004). CONCLUSIONS The analysis of MR images by GQI affords insight into tumor architectural patterns in glioblastoma that correlate with biological heterogeneity and clinical outcome.
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Affiliation(s)
- Erik N. Taylor
- Chemistry and Chemical Biology, Northeastern University, Boston, MA, USA
| | - Yao Ding
- Radiation Oncology, University of Texas, MD Anderson Cancer Center, Houston, TX, USA
| | - Shan Zhu
- Chemistry and Chemical Biology, Northeastern University, Boston, MA, USA
| | - Eric Cheah
- Chemistry and Chemical Biology, Northeastern University, Boston, MA, USA
| | - Phillip Alexander
- Department of Radiology, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Engineering Science, University of Oxford, Oxford, UK
| | - Leon Lin
- Chemistry and Chemical Biology, Northeastern University, Boston, MA, USA
| | - George E. Aninwene
- Chemistry and Chemical Biology, Northeastern University, Boston, MA, USA
| | - Matthew P. Hoffman
- Chemistry and Chemical Biology, Northeastern University, Boston, MA, USA
| | - Anita Mahajan
- Radiation Oncology, University of Texas, MD Anderson Cancer Center, Houston, TX, USA
| | - Abdallah S.R. Mohamed
- Radiation Oncology, University of Texas, MD Anderson Cancer Center, Houston, TX, USA
| | - Nathan McDannold
- Department of Radiology, Brigham and Women’s Hospital, Boston, MA, USA
| | - Clifton D. Fuller
- Radiation Oncology, University of Texas, MD Anderson Cancer Center, Houston, TX, USA
| | - Clark C. Chen
- Center for Theoretical and Applied Neuro-Oncology and Department of Neurosurgery, University of California, San Diego, CA, USA
| | - Richard J. Gilbert
- Chemistry and Chemical Biology, Northeastern University, Boston, MA, USA
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Bette S, Huber T, Gempt J, Boeckh-Behrens T, Wiestler B, Kehl V, Ringel F, Meyer B, Zimmer C, Kirschke JS. Local Fractional Anisotropy Is Reduced in Areas with Tumor Recurrence in Glioblastoma. Radiology 2017; 283:499-507. [DOI: 10.1148/radiol.2016152832] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Stefanie Bette
- From the Departments of Neuroradiology (S.B., T.H., T.B.B., B.W., C.Z., J.S.K.), Neurosurgery (J.G., F.R., B.M.), and Statistics and Epidemiology (V.K.), Klinikum Rechts der Isar, Technische Universität München, Ismaningerstr 22, 81675 Munich, Germany
| | - Thomas Huber
- From the Departments of Neuroradiology (S.B., T.H., T.B.B., B.W., C.Z., J.S.K.), Neurosurgery (J.G., F.R., B.M.), and Statistics and Epidemiology (V.K.), Klinikum Rechts der Isar, Technische Universität München, Ismaningerstr 22, 81675 Munich, Germany
| | - Jens Gempt
- From the Departments of Neuroradiology (S.B., T.H., T.B.B., B.W., C.Z., J.S.K.), Neurosurgery (J.G., F.R., B.M.), and Statistics and Epidemiology (V.K.), Klinikum Rechts der Isar, Technische Universität München, Ismaningerstr 22, 81675 Munich, Germany
| | - Tobias Boeckh-Behrens
- From the Departments of Neuroradiology (S.B., T.H., T.B.B., B.W., C.Z., J.S.K.), Neurosurgery (J.G., F.R., B.M.), and Statistics and Epidemiology (V.K.), Klinikum Rechts der Isar, Technische Universität München, Ismaningerstr 22, 81675 Munich, Germany
| | - Benedikt Wiestler
- From the Departments of Neuroradiology (S.B., T.H., T.B.B., B.W., C.Z., J.S.K.), Neurosurgery (J.G., F.R., B.M.), and Statistics and Epidemiology (V.K.), Klinikum Rechts der Isar, Technische Universität München, Ismaningerstr 22, 81675 Munich, Germany
| | - Victoria Kehl
- From the Departments of Neuroradiology (S.B., T.H., T.B.B., B.W., C.Z., J.S.K.), Neurosurgery (J.G., F.R., B.M.), and Statistics and Epidemiology (V.K.), Klinikum Rechts der Isar, Technische Universität München, Ismaningerstr 22, 81675 Munich, Germany
| | - Florian Ringel
- From the Departments of Neuroradiology (S.B., T.H., T.B.B., B.W., C.Z., J.S.K.), Neurosurgery (J.G., F.R., B.M.), and Statistics and Epidemiology (V.K.), Klinikum Rechts der Isar, Technische Universität München, Ismaningerstr 22, 81675 Munich, Germany
| | - Bernhard Meyer
- From the Departments of Neuroradiology (S.B., T.H., T.B.B., B.W., C.Z., J.S.K.), Neurosurgery (J.G., F.R., B.M.), and Statistics and Epidemiology (V.K.), Klinikum Rechts der Isar, Technische Universität München, Ismaningerstr 22, 81675 Munich, Germany
| | - Claus Zimmer
- From the Departments of Neuroradiology (S.B., T.H., T.B.B., B.W., C.Z., J.S.K.), Neurosurgery (J.G., F.R., B.M.), and Statistics and Epidemiology (V.K.), Klinikum Rechts der Isar, Technische Universität München, Ismaningerstr 22, 81675 Munich, Germany
| | - Jan S. Kirschke
- From the Departments of Neuroradiology (S.B., T.H., T.B.B., B.W., C.Z., J.S.K.), Neurosurgery (J.G., F.R., B.M.), and Statistics and Epidemiology (V.K.), Klinikum Rechts der Isar, Technische Universität München, Ismaningerstr 22, 81675 Munich, Germany
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43
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Holly KS, Barker BJ, Murcia D, Bennett R, Kalakoti P, Ledbetter C, Gonzalez-Toledo E, Nanda A, Sun H. High-grade Gliomas Exhibit Higher Peritumoral Fractional Anisotropy and Lower Mean Diffusivity than Intracranial Metastases. Front Surg 2017; 4:18. [PMID: 28443285 PMCID: PMC5385351 DOI: 10.3389/fsurg.2017.00018] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2017] [Accepted: 03/16/2017] [Indexed: 11/18/2022] Open
Abstract
Differentiating high-grade gliomas and intracranial metastases through non-invasive imaging has been challenging. Here, we retrospectively compared both intratumoral and peritumoral fractional anisotropy (FA), mean diffusivity (MD), and fluid-attenuated inversion recovery (FLAIR) measurements between high-grade gliomas and metastases. Two methods were utilized to select peritumoral region of interest (ROI). The first method utilized the manual placement of four ROIs adjacent to the lesion. The second method utilized a semiautomated and proprietary MATLAB script to generate an ROI encompassing the entire tumor. The average peritumoral FA, MD, and FLAIR values were determined within the ROIs for both methods. Forty patients with high-grade gliomas and 44 with metastases were enrolled in this study. Thirty-five patients with high-grade glioma and 30 patients with metastases had FLAIR images. There was no significant difference in age, gender, or race between the two patient groups. The high-grade gliomas had a significantly higher tumor-to-brain area ratio compared to the metastases. There were no differences in average intratumoral FA, MD, and FLAIR values between the two groups. Both the manual sample method and the semiautomated peritumoral ring method resulted in significantly higher peritumoral FA and significantly lower peritumoral MD in high-grade gliomas compared to metastases (p < 0.05). No significant difference was found in FLAIR values between the two groups peritumorally. Receiver operating curve analysis revealed FA to be a more sensitive and specific metric to differentiate high-grade gliomas and metastases than MD. The differences in the peritumoral FA and MD values between high-grade gliomas and metastases seemed due to the infiltration of glioma to the surrounding brain parenchyma.
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Affiliation(s)
- Kevin S Holly
- Department of Neurosurgery, Louisiana State University Health Sciences Center Shreveport, Shreveport, LA, USA
| | - Benjamin J Barker
- Department of Neurology, Louisiana State University Health Sciences Center Shreveport, Shreveport, LA, USA
| | - Derrick Murcia
- Department of Neurosurgery, Louisiana State University Health Sciences Center Shreveport, Shreveport, LA, USA
| | - Rebekah Bennett
- Department of Biological Sciences, Louisiana State University Shreveport, Shreveport, LA, USA
| | - Piyush Kalakoti
- Department of Neurosurgery, Louisiana State University Health Sciences Center Shreveport, Shreveport, LA, USA
| | - Christina Ledbetter
- Department of Neurosurgery, Louisiana State University Health Sciences Center Shreveport, Shreveport, LA, USA
| | - Eduardo Gonzalez-Toledo
- Department of Radiology, Louisiana State University Health Sciences Center Shreveport, Shreveport, LA, USA
| | - Anil Nanda
- Department of Neurosurgery, Louisiana State University Health Sciences Center Shreveport, Shreveport, LA, USA
| | - Hai Sun
- Department of Neurosurgery, Louisiana State University Health Sciences Center Shreveport, Shreveport, LA, USA
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Hiremath SB, Muraleedharan A, Kumar S, Nagesh C, Kesavadas C, Abraham M, Kapilamoorthy TR, Thomas B. Combining Diffusion Tensor Metrics and DSC Perfusion Imaging: Can It Improve the Diagnostic Accuracy in Differentiating Tumefactive Demyelination from High-Grade Glioma? AJNR Am J Neuroradiol 2017; 38:685-690. [PMID: 28209583 DOI: 10.3174/ajnr.a5089] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2016] [Accepted: 12/04/2016] [Indexed: 12/12/2022]
Abstract
BACKGROUND AND PURPOSE Tumefactive demyelinating lesions with atypical features can mimic high-grade gliomas on conventional imaging sequences. The aim of this study was to assess the role of conventional imaging, DTI metrics (p:q tensor decomposition), and DSC perfusion in differentiating tumefactive demyelinating lesions and high-grade gliomas. MATERIALS AND METHODS Fourteen patients with tumefactive demyelinating lesions and 21 patients with high-grade gliomas underwent brain MR imaging with conventional, DTI, and DSC perfusion imaging. Imaging sequences were assessed for differentiation of the lesions. DTI metrics in the enhancing areas and perilesional hyperintensity were obtained by ROI analysis, and the relative CBV values in enhancing areas were calculated on DSC perfusion imaging. RESULTS Conventional imaging sequences had a sensitivity of 80.9% and specificity of 57.1% in differentiating high-grade gliomas (P = .049) from tumefactive demyelinating lesions. DTI metrics (p:q tensor decomposition) and DSC perfusion demonstrated a statistically significant difference in the mean values of ADC, the isotropic component of the diffusion tensor, the anisotropic component of the diffusion tensor, the total magnitude of the diffusion tensor, and rCBV among enhancing portions in tumefactive demyelinating lesions and high-grade gliomas (P ≤ .02), with the highest specificity for ADC, the anisotropic component of the diffusion tensor, and relative CBV (92.9%). Mean fractional anisotropy values showed no significant statistical difference between tumefactive demyelinating lesions and high-grade gliomas. The combination of DTI and DSC parameters improved the diagnostic accuracy (area under the curve = 0.901). Addition of a heterogeneous enhancement pattern to DTI and DSC parameters improved it further (area under the curve = 0.966). The sensitivity increased from 71.4% to 85.7% after the addition of the enhancement pattern. CONCLUSIONS DTI and DSC perfusion add profoundly to conventional imaging in differentiating tumefactive demyelinating lesions and high-grade gliomas. The combination of DTI metrics and DSC perfusion markedly improved diagnostic accuracy.
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Affiliation(s)
- S B Hiremath
- From the Departments of Imaging Sciences and Interventional Radiology (S.B.H., A.M., S.K., C.N., C.K., T.R.K., B.T.)
| | - A Muraleedharan
- From the Departments of Imaging Sciences and Interventional Radiology (S.B.H., A.M., S.K., C.N., C.K., T.R.K., B.T.)
| | - S Kumar
- From the Departments of Imaging Sciences and Interventional Radiology (S.B.H., A.M., S.K., C.N., C.K., T.R.K., B.T.)
| | - C Nagesh
- From the Departments of Imaging Sciences and Interventional Radiology (S.B.H., A.M., S.K., C.N., C.K., T.R.K., B.T.)
| | - C Kesavadas
- From the Departments of Imaging Sciences and Interventional Radiology (S.B.H., A.M., S.K., C.N., C.K., T.R.K., B.T.)
| | - M Abraham
- Neurosurgery (M.A.), Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, India
| | - T R Kapilamoorthy
- From the Departments of Imaging Sciences and Interventional Radiology (S.B.H., A.M., S.K., C.N., C.K., T.R.K., B.T.)
| | - B Thomas
- From the Departments of Imaging Sciences and Interventional Radiology (S.B.H., A.M., S.K., C.N., C.K., T.R.K., B.T.)
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45
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Kuo DP, Lu CF, Liou M, Chen YC, Chung HW, Chen CY. Differentiation of the Infarct Core from Ischemic Penumbra within the First 4.5 Hours, Using Diffusion Tensor Imaging-Derived Metrics: A Rat Model. Korean J Radiol 2017; 18:269-278. [PMID: 28246507 PMCID: PMC5313515 DOI: 10.3348/kjr.2017.18.2.269] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2016] [Accepted: 09/02/2016] [Indexed: 12/21/2022] Open
Abstract
Objective To investigate whether the diffusion tensor imaging-derived metrics are capable of differentiating the ischemic penumbra (IP) from the infarct core (IC), and determining stroke onset within the first 4.5 hours. Materials and Methods All procedures were approved by the local animal care committee. Eight of the eleven rats having permanent middle cerebral artery occlusion were included for analyses. Using a 7 tesla magnetic resonance system, the relative cerebral blood flow and apparent diffusion coefficient maps were generated to define IP and IC, half hour after surgery and then every hour, up to 6.5 hours. Relative fractional anisotropy, pure anisotropy (rq) and diffusion magnitude (rL) maps were obtained. One-way analysis of variance, receiver operating characteristic curve and nonlinear regression analyses were performed. Results The evolutions of tensor metrics were different in ischemic regions (IC and IP) and topographic subtypes (cortical, subcortical gray matter, and white matter). The rL had a significant drop of 40% at 0.5 hour, and remained stagnant up to 6.5 hours. Significant differences (p < 0.05) in rL values were found between IP, IC, and normal tissue for all topographic subtypes. Optimal rL threshold in discriminating IP from IC was about -29%. The evolution of rq showed an exponential decrease in cortical IC, from -26.9% to -47.6%; an rq reduction smaller than 44.6% can be used to predict an acute stroke onset in less than 4.5 hours. Conclusion Diffusion tensor metrics may potentially help discriminate IP from IC and determine the acute stroke age within the therapeutic time window.
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Affiliation(s)
- Duen-Pang Kuo
- Department of Electrical Engineering, National Taiwan University, Taipei 10617, Taiwan.; Department of Radiology, Taoyuan Armed Forces General Hospital, Taoyuan 32551, Taiwan
| | - Chia-Feng Lu
- Research Center of Translational Imaging, College of Medicine, Taipei Medical University, Taipei 11031, Taiwan.; Department of Radiology, School of Medicine, College of Medicine, Taipei Medical University, Taipei 11031, Taiwan.; Department of Biomedical Imaging and Radiological Sciences, National Yang-Ming University, Taipei 112, Taiwan.; Department of Physical Therapy and Assistive Technology, National Yang-Ming University, Taipei 112, Taiwan
| | - Michelle Liou
- Institute of Statistical Science, Academia Sinica, Taipei 11529, Taiwan
| | - Yung-Chieh Chen
- Department of Biomedical Imaging and Radiological Sciences, National Yang-Ming University, Taipei 112, Taiwan
| | - Hsiao-Wen Chung
- Graduate Institute of Biomedical Electrics and Bioinformatics, National Taiwan University, Taipei 10617, Taiwan
| | - Cheng-Yu Chen
- Research Center of Translational Imaging, College of Medicine, Taipei Medical University, Taipei 11031, Taiwan.; Department of Radiology, School of Medicine, College of Medicine, Taipei Medical University, Taipei 11031, Taiwan.; Department of Medical Imaging and Imaging Research Center, Taipei Medical University Hospital, Taipei Medical University, Taipei 11031, Taiwan.; Department of Radiology, Tri-Service General Hospital, Taipei 114, Taiwan.; Department of Radiology, National Defense Medical Center, Taipei 114, Taiwan
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46
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Badve C, Yu A, Dastmalchian S, Rogers M, Ma D, Jiang Y, Margevicius S, Pahwa S, Lu Z, Schluchter M, Sunshine J, Griswold M, Sloan A, Gulani V. MR Fingerprinting of Adult Brain Tumors: Initial Experience. AJNR Am J Neuroradiol 2016; 38:492-499. [PMID: 28034994 DOI: 10.3174/ajnr.a5035] [Citation(s) in RCA: 128] [Impact Index Per Article: 14.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2016] [Accepted: 10/11/2016] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE MR fingerprinting allows rapid simultaneous quantification of T1 and T2 relaxation times. This study assessed the utility of MR fingerprinting in differentiating common types of adult intra-axial brain tumors. MATERIALS AND METHODS MR fingerprinting acquisition was performed in 31 patients with untreated intra-axial brain tumors: 17 glioblastomas, 6 World Health Organization grade II lower grade gliomas, and 8 metastases. T1, T2 of the solid tumor, immediate peritumoral white matter, and contralateral white matter were summarized within each ROI. Statistical comparisons on mean, SD, skewness, and kurtosis were performed by using the univariate Wilcoxon rank sum test across various tumor types. Bonferroni correction was used to correct for multiple-comparison testing. Multivariable logistic regression analysis was performed for discrimination between glioblastomas and metastases, and area under the receiver operator curve was calculated. RESULTS Mean T2 values could differentiate solid tumor regions of lower grade gliomas from metastases (mean, 172 ± 53 ms, and 105 ± 27 ms, respectively; P = .004, significant after Bonferroni correction). The mean T1 of peritumoral white matter surrounding lower grade gliomas differed from peritumoral white matter around glioblastomas (mean, 1066 ± 218 ms, and 1578 ± 331 ms, respectively; P = .004, significant after Bonferroni correction). Logistic regression analysis revealed that the mean T2 of solid tumor offered the best separation between glioblastomas and metastases with an area under the curve of 0.86 (95% CI, 0.69-1.00; P < .0001). CONCLUSIONS MR fingerprinting allows rapid simultaneous T1 and T2 measurement in brain tumors and surrounding tissues. MR fingerprinting-based relaxometry can identify quantitative differences between solid tumor regions of lower grade gliomas and metastases and between peritumoral regions of glioblastomas and lower grade gliomas.
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Affiliation(s)
- C Badve
- From the Department of Radiology (C.B., S.D., D.M., S.P., J.S., M.G., V.G.), University Hospitals Cleveland Medical Center and Case Western Reserve University, Cleveland, Ohio
| | - A Yu
- School of Medicine (A.Y., M.R., Z.L.)
| | - S Dastmalchian
- From the Department of Radiology (C.B., S.D., D.M., S.P., J.S., M.G., V.G.), University Hospitals Cleveland Medical Center and Case Western Reserve University, Cleveland, Ohio
| | - M Rogers
- School of Medicine (A.Y., M.R., Z.L.)
| | - D Ma
- From the Department of Radiology (C.B., S.D., D.M., S.P., J.S., M.G., V.G.), University Hospitals Cleveland Medical Center and Case Western Reserve University, Cleveland, Ohio
| | - Y Jiang
- Department of Biomedical Engineering (Y.J., M.G., V.G.)
| | - S Margevicius
- Department of Epidemiology and Biostatistics (S.M., M.S.), Case Western Reserve University, Cleveland, Ohio
| | - S Pahwa
- From the Department of Radiology (C.B., S.D., D.M., S.P., J.S., M.G., V.G.), University Hospitals Cleveland Medical Center and Case Western Reserve University, Cleveland, Ohio
| | - Z Lu
- School of Medicine (A.Y., M.R., Z.L.)
| | - M Schluchter
- Department of Epidemiology and Biostatistics (S.M., M.S.), Case Western Reserve University, Cleveland, Ohio
| | - J Sunshine
- From the Department of Radiology (C.B., S.D., D.M., S.P., J.S., M.G., V.G.), University Hospitals Cleveland Medical Center and Case Western Reserve University, Cleveland, Ohio
| | - M Griswold
- From the Department of Radiology (C.B., S.D., D.M., S.P., J.S., M.G., V.G.), University Hospitals Cleveland Medical Center and Case Western Reserve University, Cleveland, Ohio.,Department of Biomedical Engineering (Y.J., M.G., V.G.)
| | - A Sloan
- Departments of Neurosurgery and Pathology (A.S.), University Hospitals-Cleveland Medical Center, Seidman Cancer Center and the Case Comprehensive Cancer Center, Cleveland, Ohio
| | - V Gulani
- From the Department of Radiology (C.B., S.D., D.M., S.P., J.S., M.G., V.G.), University Hospitals Cleveland Medical Center and Case Western Reserve University, Cleveland, Ohio.,Department of Biomedical Engineering (Y.J., M.G., V.G.)
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47
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Analysis of fractional anisotropy facilitates differentiation of glioblastoma and brain metastases in a clinical setting. Eur J Radiol 2016; 85:2182-2187. [DOI: 10.1016/j.ejrad.2016.10.002] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2016] [Accepted: 10/01/2016] [Indexed: 01/17/2023]
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48
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Desmond KL, Mehrabian H, Chavez S, Sahgal A, Soliman H, Rola R, Stanisz GJ. Chemical exchange saturation transfer for predicting response to stereotactic radiosurgery in human brain metastasis. Magn Reson Med 2016; 78:1110-1120. [PMID: 27690156 DOI: 10.1002/mrm.26470] [Citation(s) in RCA: 48] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2016] [Revised: 08/23/2016] [Accepted: 08/29/2016] [Indexed: 12/19/2022]
Abstract
PURPOSE The purpose of this work was to determine the predictive value of chemical exchange saturation transfer (CEST) metrics in brain metastases treated with stereotactic radiosurgery (SRS). METHODS CEST spectra at a radiofrequency power of 0.52 µT were collected on a 3 Tesla (T) magnetic resonance imaging from 25 patients at three time points: pretreatment, 1 week, and 1 month post-treatment. Amide proton transfer-weighted images and maps of the amplitude and width of Lorentzian-shaped CEST peaks and the relaxation-compensated AREX metric were constructed at the offset frequencies of amide, amine, and relayed nuclear Overhauser effect (NOE) from aliphatic groups as well as the broad magnetization transfer effect. Pretreatment CEST metrics, as well as CEST metric changes at 1 week post-treatment, were compared to changes in tumor volume at 1 month. RESULTS Significant (P < 0.05) 1-week predictive metrics included NOE peak amplitude (R = 0.69) in normal-appearing white matter (NAWM) and width (R = -0.55) in tumor. Baseline NOE in contralateral NAWM was negatively correlated (R = -0.69) with volume changes at 1 month. Metrics-defined outside tumor margins had higher correlation with volume changes than tumor regions of interest. CONCLUSION CEST metrics, in particular, the NOE peak amplitude, can predict volume changes 1 month post-SRS. Magn Reson Med 78:1110-1120, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Kimberly L Desmond
- Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Hatef Mehrabian
- Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada.,Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Sofia Chavez
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Arjun Sahgal
- Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.,Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Hany Soliman
- Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.,Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Radoslaw Rola
- Department of Neurosurgery and Pediatric Neurosurgery, Medical University, Lublin, Poland
| | - Greg J Stanisz
- Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada.,Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.,Department of Neurosurgery and Pediatric Neurosurgery, Medical University, Lublin, Poland
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49
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Baris MM, Celik AO, Gezer NS, Ada E. Role of mass effect, tumor volume and peritumoral edema volume in the differential diagnosis of primary brain tumor and metastasis. Clin Neurol Neurosurg 2016; 148:67-71. [DOI: 10.1016/j.clineuro.2016.07.008] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2016] [Revised: 07/01/2016] [Accepted: 07/02/2016] [Indexed: 10/21/2022]
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50
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Huber T, Bette S, Wiestler B, Gempt J, Gerhardt J, Delbridge C, Barz M, Meyer B, Zimmer C, Kirschke JS. Fractional Anisotropy Correlates with Overall Survival in Glioblastoma. World Neurosurg 2016; 95:525-534.e1. [PMID: 27565465 DOI: 10.1016/j.wneu.2016.08.055] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2016] [Revised: 08/10/2016] [Accepted: 08/12/2016] [Indexed: 12/24/2022]
Abstract
OBJECTIVE Glioblastoma (GB) is an infiltrative disease that results in microstructural damage on a cellular level. Fractional anisotropy (FA) is an important estimate of diffusion tensor imaging (DTI) that can be used to assess microstructural integrity. The aim of this study was to examine the correlation between FA values and overall survival (OS) in patients with GB. METHODS This retrospective single-center study included 122 consecutive patients with GB (50 women; median age, 63 years) with preoperative MRI including fluid attenuated inversion recovery (FLAIR), contrast-enhanced T1-weighted sequences, and DTI. FA and apparent diffusion coefficient (ADC) values in contrast-enhancing lesions (FA-CEL, FA-ADC), nonenhancing lesions, and central tumor regions were correlated to histopathologic and clinical parameters. Univariate and multivariate survival analyses were performed. RESULTS Patients with low FA-CEL (median <0.31) showed significantly improved OS in univariate analysis (P = 0.028). FA-CEL also showed a positive correlation with Ki-67 proliferation index (P = 0.003). However, in a multivariate survival model, FA values could not be identified as independent prognostic parameters beside established factors such as age and Karnofsky performance scale score. FA values in nonenhancing lesions and central tumor regions and mean ADC values had no distinct influence on OS. CONCLUSIONS FA values can provide prognostic information regarding OS in patients with GB. There is a correlation between FA-CEL values and Ki-67 proliferation index, a marker for malignancy. Noninvasive identification of more aggressive GB growth patterns might be beneficial for preoperative risk evaluation and estimation of prognosis.
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Affiliation(s)
- Thomas Huber
- Department of Neuroradiology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
| | - Stefanie Bette
- Department of Neuroradiology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Benedikt Wiestler
- Department of Neuroradiology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Jens Gempt
- Department of Neurosurgery, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Julia Gerhardt
- Department of Neurosurgery, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Claire Delbridge
- Department of Neuropathology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Melanie Barz
- Department of Neurosurgery, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Bernhard Meyer
- Department of Neurosurgery, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Claus Zimmer
- Department of Neuroradiology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Jan S Kirschke
- Department of Neuroradiology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
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