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Whitman J, Adhikarla V, Tumyan L, Mortimer J, Huang W, Rockne R, Peterson JR, Cole J. Validation of Clinical Dynamic Contrast-Enhanced Magnetic Resonance Imaging Perfusion Modeling and Neoadjuvant Chemotherapy Response Prediction in Breast Cancer Using 18FDG and 64Cu-DOTA-Trastuzumab Positron Emission Tomography Studies. JCO Clin Cancer Inform 2025; 9:e2300248. [PMID: 39808751 PMCID: PMC11902905 DOI: 10.1200/cci.23.00248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Revised: 07/25/2024] [Accepted: 11/05/2024] [Indexed: 01/16/2025] Open
Abstract
PURPOSE Perfusion modeling presents significant opportunities for imaging biomarker development in breast cancer but has historically been held back by the need for data beyond the clinical standard of care (SoC) and uncertainty in the interpretability of results. We aimed to design a perfusion model applicable to breast cancer SoC dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) series with results stable to low temporal resolution imaging, comparable with published results using full-resolution DCE-MRI, and correlative with orthogonal imaging modalities indicative of biophysical markers. METHODS Subsampled high-temporal-resolution DCE-MRI series were run through our perfusion model and resulting fits were compared for consistency. The fits were also compared against previously published results from institutions using the full resolution series. The model was then evaluated on a separate cohort for validity of biomarker indications. Finally, the model was used as a fundamental part of predicting response to neoadjuvant chemotherapy (NACT). RESULTS Temporally subsampled DCE-MRI series yield perfusion fit variations on the scale of 1% of the tumor median value when input frames are varied. Fits generated from pseudoclinical series are within the variation range seen between imaging sites (ρ = 0.55), voxel-wise. The model also demonstrates significant correlations with orthogonal positron emission tomography imaging, indicating potential for use as a biomarker proxy. Specifically, using the perfusion fits as the grounding for a biophysical simulation of response, we correctly predict the pathologic complete response status after NACT in 15 of 18 patients, for an accuracy of 0.83, with a specificity and sensitivity of 0.83 as well. CONCLUSION Clinical DCE-MRI data may be leveraged to provide stable perfusion fit results and indirectly interrogate the tumor microenvironment. These fits can then be used downstream for prediction of response to NACT with high accuracy.
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Affiliation(s)
| | - Vikram Adhikarla
- Division of Mathematical Oncology and Computational Systems Biology, Beckman Research Institute, City of Hope
| | - Lusine Tumyan
- Department of Radiology, City of Hope National Medical Center
| | - Joanne Mortimer
- Department of Medical Oncology and Medical Therapeutics Research, City of Hope National Medical Center
| | - Wei Huang
- Advanced Imaging Research Center, Oregon Health and Science University
- Knight Cancer Institute, Oregon Health and Science University
| | - Russell Rockne
- Division of Mathematical Oncology and Computational Systems Biology, Beckman Research Institute, City of Hope
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Vaz SC, Woll JPP, Cardoso F, Groheux D, Cook GJR, Ulaner GA, Jacene H, Rubio IT, Schoones JW, Peeters MJV, Poortmans P, Mann RM, Graff SL, Dibble EH, de Geus-Oei LF. Joint EANM-SNMMI guideline on the role of 2-[ 18F]FDG PET/CT in no special type breast cancer : (endorsed by the ACR, ESSO, ESTRO, EUSOBI/ESR, and EUSOMA). Eur J Nucl Med Mol Imaging 2024; 51:2706-2732. [PMID: 38740576 PMCID: PMC11224102 DOI: 10.1007/s00259-024-06696-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Accepted: 03/20/2024] [Indexed: 05/16/2024]
Abstract
INTRODUCTION There is much literature about the role of 2-[18F]FDG PET/CT in patients with breast cancer (BC). However, there exists no international guideline with involvement of the nuclear medicine societies about this subject. PURPOSE To provide an organized, international, state-of-the-art, and multidisciplinary guideline, led by experts of two nuclear medicine societies (EANM and SNMMI) and representation of important societies in the field of BC (ACR, ESSO, ESTRO, EUSOBI/ESR, and EUSOMA). METHODS Literature review and expert discussion were performed with the aim of collecting updated information regarding the role of 2-[18F]FDG PET/CT in patients with no special type (NST) BC and summarizing its indications according to scientific evidence. Recommendations were scored according to the National Institute for Health and Care Excellence (NICE) criteria. RESULTS Quantitative PET features (SUV, MTV, TLG) are valuable prognostic parameters. In baseline staging, 2-[18F]FDG PET/CT plays a role from stage IIB through stage IV. When assessing response to therapy, 2-[18F]FDG PET/CT should be performed on certified scanners, and reported either according to PERCIST, EORTC PET, or EANM immunotherapy response criteria, as appropriate. 2-[18F]FDG PET/CT may be useful to assess early metabolic response, particularly in non-metastatic triple-negative and HER2+ tumours. 2-[18F]FDG PET/CT is useful to detect the site and extent of recurrence when conventional imaging methods are equivocal and when there is clinical and/or laboratorial suspicion of relapse. Recent developments are promising. CONCLUSION 2-[18F]FDG PET/CT is extremely useful in BC management, as supported by extensive evidence of its utility compared to other imaging modalities in several clinical scenarios.
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Affiliation(s)
- Sofia C Vaz
- Nuclear Medicine-Radiopharmacology, Champalimaud Clinical Center, Champalimaud Foundation, Lisbon, Portugal.
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.
| | | | - Fatima Cardoso
- Breast Unit, Champalimaud Clinical Center, Champalimaud Foundation, Lisbon, Portugal
| | - David Groheux
- Nuclear Medicine Department, Saint-Louis Hospital, Paris, France
- University Paris-Diderot, INSERM U976, Paris, France
- Centre d'Imagerie Radio-Isotopique (CIRI), La Rochelle, France
| | - Gary J R Cook
- Department of Cancer Imaging, King's College London, London, UK
- King's College London and Guy's & St Thomas' PET Centre, London, UK
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Gary A Ulaner
- Molecular Imaging and Therapy, Hoag Family Cancer Institute, Newport Beach, CA, USA
- University of Southern California, Los Angeles, CA, USA
| | - Heather Jacene
- Dana-Farber Cancer Institute/Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Isabel T Rubio
- Breast Surgical Oncology, Clinica Universidad de Navarra, Madrid, Cancer Center Clinica Universidad de Navarra, Navarra, Spain
| | - Jan W Schoones
- Directorate of Research Policy, Leiden University Medical Center, Leiden, The Netherlands
| | - Marie-Jeanne Vrancken Peeters
- Department of Surgical Oncology, Netherlands Cancer Institute, Amsterdam, The Netherlands
- Department of Surgery, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Philip Poortmans
- Department of Radiation Oncology, Iridium Netwerk, Antwerp, Belgium
- University of Antwerp, Wilrijk, Antwerp, Belgium
| | - Ritse M Mann
- Radiology Department, RadboudUMC, Nijmegen, The Netherlands
| | - Stephanie L Graff
- Lifespan Cancer Institute, Providence, Rhode Island, USA
- Legorreta Cancer Center at Brown University, Providence, Rhode Island, USA
| | - Elizabeth H Dibble
- Department of Diagnostic Imaging, The Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA.
| | - Lioe-Fee de Geus-Oei
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.
- Biomedical Photonic Imaging Group, University of Twente, Enschede, The Netherlands.
- Department of Radiation Science & Technology, Technical University of Delft, Delft, The Netherlands.
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Romero ÁB, Furtado FS, Sertic M, Goiffon RJ, Mahmood U, Catalano OA. Abdominal Positron Emission Tomography/Magnetic Resonance Imaging. Magn Reson Imaging Clin N Am 2023; 31:579-589. [PMID: 37741642 DOI: 10.1016/j.mric.2023.06.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/25/2023]
Abstract
Hybrid positron emission tomography (PET)/magnetic resonance imaging (MRI) is highly suited for abdominal pathologies. A precise co-registration of anatomic and metabolic data is possible thanks to the simultaneous acquisition, leading to accurate imaging. The literature shows that PET/MRI is at least as good as PET/CT and even superior for some indications, such as primary hepatic tumors, distant metastasis evaluation, and inflammatory bowel disease. PET/MRI allows whole-body staging in a single session, improving health care efficiency and patient comfort.
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Affiliation(s)
- Álvaro Badenes Romero
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Athinoula A Martinos Center for Biomedical Imaging, Harvard Medical School, Charlestown, MA, USA; Department of Nuclear Medicine, Joan XXIII Hospital, Tarragona, Spain
| | - Felipe S Furtado
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Athinoula A Martinos Center for Biomedical Imaging, Harvard Medical School, Charlestown, MA, USA
| | - Madaleine Sertic
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Reece J Goiffon
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Umar Mahmood
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Onofrio A Catalano
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Athinoula A Martinos Center for Biomedical Imaging, Harvard Medical School, Charlestown, MA, USA.
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Mainta IC, Sfakianaki I, Shiri I, Botsikas D, Garibotto V. The Clinical Added Value of Breast Cancer Imaging Using Hybrid PET/MR Imaging. Magn Reson Imaging Clin N Am 2023; 31:565-577. [PMID: 37741641 DOI: 10.1016/j.mric.2023.06.007] [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] [Indexed: 09/25/2023]
Abstract
Dedicated MR imaging is highly performant for the evaluation of the primary lesion and should regularly be added to whole-body PET/MR imaging for the initial staging. PET/MR imaging is highly sensitive for the detection of nodal involvement and could be combined with the high specificity of axillary second look ultrasound for the confirmation of the N staging. For M staging, with the exception of lung lesions, PET/MR imaging is superior to PET/computed tomography, at half the radiation dose. The predictive value of multiparametric imaging with PET/MR imaging holds promise to improve through radiomics and artificial intelligence.
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Affiliation(s)
- Ismini C Mainta
- Department of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals, Rue Gabrielle-Perret-Gentil 4, Geneva 1205, Switzerland.
| | - Ilektra Sfakianaki
- Department of Radiology, Geneva University Hospitals, Rue Gabrielle-Perret-Gentil 4, Geneva 1205, Switzerland
| | - Isaac Shiri
- Department of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals, Rue Gabrielle-Perret-Gentil 4, Geneva 1205, Switzerland
| | - Diomidis Botsikas
- Department of Radiology, Geneva University Hospitals, Rue Gabrielle-Perret-Gentil 4, Geneva 1205, Switzerland
| | - Valentina Garibotto
- Department of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals, Rue Gabrielle-Perret-Gentil 4, Geneva 1205, Switzerland; Faculty of Medicine, University of Geneva, Rue Michel Servet 1, Geneva 1211, Switzerland
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Xi Y, Sun L, Che X, Huang X, Liu H, Wang Q, Meng H, Miao Y, Qu Q, Hai W, Li B, Feng W. A comparative study of [ 68Ga]Ga-FAPI-04 PET/MR and [ 18F]FDG PET/CT in the diagnostic accuracy and resectability prediction of ovarian cancer. Eur J Nucl Med Mol Imaging 2023; 50:2885-2898. [PMID: 37093313 DOI: 10.1007/s00259-023-06235-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Accepted: 04/14/2023] [Indexed: 04/25/2023]
Abstract
PURPOSE To provide a theory for guiding clinical treatment by comparing the clinical application value of [18F]fluorodeoxyglucose ([18F]FDG) PET/CT and [68Ga]Ga-FAPI (fibroblast activating protein inhibitor) PET/MR in the diagnosis and evaluation of resectability of ovarian cancer. METHODS Thirty patients with high clinical suspicion of ovarian malignancies were enrolled from July 2021 to October 2022 and underwent [18F]FDG PET/CT and [68Ga]Ga-FAPI-04 PET/MR within 5 days. Twenty patients underwent [18F]FDG PET/MR at once completing [18F]FDG PET/CT for consistency checking. Images were analysed for comparing SUVs and for judging incomplete resectability according to the peritoneal cancer index (PCI) and SUIDAN scoring system. The expression of FAP, HK2 and Ki67 was analysed by immunohistochemistry staining. RESULTS There was no significant difference between PET/MR and PET/CT in SUVs-FDG at different locations (p > 0.05), and their diagnostic accuracies were similar. The diagnostic accuracy of [68Ga]Ga-FAPI-04 PET/MR had advantages for peritoneal metastasis since SUVsFAPI were higher (p < 0.01). The sensitivity of [68Ga]Ga-FAPI-04 PET/MR in the diagnosis of peridiaghragmatic metastases was higher because SUVmax in the liver was decreased (p < 0.001). [68Ga]Ga-FAPI-04 PET/MR might have advantages in diagnosing gastrointestinal invasion. In PCI score analysis, [68Ga]Ga-FAPI-04 PET/MR could partially correct missing or underestimated scores by [18F]FDG PET/CT, but the matching probability between left peri-intestinal metastasis scores was low and easy to overestimate. Interestingly, diaphragmatic metastasis detected by [68Ga]Ga-FAPI-04 PET/MR had the greatest correlation with the prediction of incomplete resectability (logistic regression p = 0.02). Through immunohistochemistry, the expression of FAP had a strong correlation with SUVmax-FAPI (p < 0.001), while the expression of HK2 was correlated with SUVmax-FDG (p < 0.01). In addition, SUVmax-FDG with Ki67 ≥ 20% was significantly higher than that with Ki67 < 20% (p < 0.05). CONCLUSIONS [68Ga]Ga-FAPI-04 PET/MR had obvious advantages for metastases diagnosis and could more accurately assess tumour load and predict incomplete resectability. SUVmax-FDG was conducive to evaluating the degree of tumour malignancy.
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Affiliation(s)
- Yun Xi
- Department of Nuclear Medicine, School of Medicine, Ruijin Hospital, Shanghai Jiaotong University, Shanghai, China
| | - Lili Sun
- Department of Obstetrics and Gynecology, School of Medicine, Ruijin Hospital, Shanghai Jiaotong University, No. 197, Ruijin Er Road, Shanghai, 200025, China
| | - Xiaoxia Che
- Department of Obstetrics and Gynecology, School of Medicine, Ruijin Hospital, Shanghai Jiaotong University, No. 197, Ruijin Er Road, Shanghai, 200025, China
| | - Xinyun Huang
- Department of Nuclear Medicine, School of Medicine, Ruijin Hospital, Shanghai Jiaotong University, Shanghai, China
| | - Hua Liu
- Department of Obstetrics and Gynecology, School of Medicine, Ruijin Hospital, Shanghai Jiaotong University, No. 197, Ruijin Er Road, Shanghai, 200025, China
| | - Qun Wang
- Department of Obstetrics and Gynecology, School of Medicine, Ruijin Hospital, Shanghai Jiaotong University, No. 197, Ruijin Er Road, Shanghai, 200025, China
| | - Hongping Meng
- Department of Nuclear Medicine, School of Medicine, Ruijin Hospital, Shanghai Jiaotong University, Shanghai, China
| | - Yuxin Miao
- Department of Nuclear Medicine, School of Medicine, Ruijin Hospital, Shanghai Jiaotong University, Shanghai, China
| | - Qian Qu
- Department of Nuclear Medicine, School of Medicine, Ruijin Hospital, Shanghai Jiaotong University, Shanghai, China
| | - Wangxi Hai
- Department of Nuclear Medicine, School of Medicine, Ruijin Hospital, Shanghai Jiaotong University, Shanghai, China
| | - Biao Li
- Department of Nuclear Medicine, School of Medicine, Ruijin Hospital, Shanghai Jiaotong University, Shanghai, China.
| | - Weiwei Feng
- Department of Obstetrics and Gynecology, School of Medicine, Ruijin Hospital, Shanghai Jiaotong University, No. 197, Ruijin Er Road, Shanghai, 200025, China.
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Clauser P, Rasul S, Kapetas P, Fueger BJ, Milos RI, Balber T, Berroterán-Infante N, Hacker M, Helbich TH, Baltzer PAT. Prospective validation of 18F-Fluoroethylcholine as a tracer in PET/MRI for the evaluation of breast lesions and prediction of lymph node status. LA RADIOLOGIA MEDICA 2023; 128:689-698. [PMID: 37221356 PMCID: PMC10264497 DOI: 10.1007/s11547-023-01633-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 04/19/2023] [Indexed: 05/25/2023]
Abstract
PURPOSE To assess 18F-Fluoroethylcholine (18F-FEC) as a PET/MRI tracer in the evaluation of breast lesions, breast cancer aggressiveness, and prediction of lymph node status. MATERIALS AND METHODS This prospective, monocentric study was approved by the ethics committee and patients gave written, informed consent. This clinical trial was registered in the EudraCT database (Number 2017-003089-29). Women who presented with suspicious breast lesions were included. Histopathology was used as reference standard. Simultaneous 18F-FEC PET/MRI of the breast was performed in a prone position with a dedicated breast coil. MRI was performed using a standard protocol before and after contrast agent administration. A simultaneous read by nuclear medicine physicians and radiologists collected the imaging data of MRI-detected lesions, including the maximum standardized 18F-FEC-uptake value of breast lesions (SUVmaxT) and axillary lymph nodes (SUVmaxLN). Differences in SUVmax were evaluated with the Mann-Whitney U test. To calculate diagnostic performance, the area under the receiver operating characteristics curve (ROC) was used. RESULTS There were 101 patients (mean age 52.3 years, standard deviation 12.0) with 117 breast lesions included (30 benign, 7 ductal carcinomas in situ, 80 invasive carcinomas). 18F-FEC was well tolerated by all patients. The ROC to distinguish benign from malignant breast lesions was 0.846. SUVmaxT was higher if lesions were malignant (p < 0.001), had a higher proliferation rate (p = 0.011), and were HER2-positive (p = 0.041). SUVmaxLN was higher in metastatic lymph nodes, with an ROC of 0.761 for SUVmaxT and of 0.793 for SUVmaxLN. CONCLUSION: Simultaneous 18F-FEC PET/MRI is safe and has the potential to be used for the evaluation of breast cancer aggressiveness, and prediction of lymph node status.
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Affiliation(s)
- Paola Clauser
- Department of Biomedical Imaging and Image-Guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria
| | - Sazan Rasul
- Department of Biomedical Imaging and Image-Guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Vienna, Austria
| | - Panagiotis Kapetas
- Department of Biomedical Imaging and Image-Guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria
| | - Barbara J Fueger
- Department of Biomedical Imaging and Image-Guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria
| | - Ruxandra-Iulia Milos
- Department of Biomedical Imaging and Image-Guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria
| | - Theresa Balber
- Department of Biomedical Imaging and Image-Guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Vienna, Austria
| | - Neydher Berroterán-Infante
- Department of Biomedical Imaging and Image-Guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Vienna, Austria
| | - Marcus Hacker
- Department of Biomedical Imaging and Image-Guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Vienna, Austria
| | - Thomas Hans Helbich
- Department of Biomedical Imaging and Image-Guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria
- Department of Biomedical Imaging and Image-Guided Therapy, Division of Molecular and Structural Preclinical Imaging, Medical University of Vienna, Vienna, Austria
| | - Pascal Andreas Thomas Baltzer
- Department of Biomedical Imaging and Image-Guided Therapy, Division of General and Pediatric Radiology, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria.
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Heitkamp A, Madesta F, Amberg S, Wahaj S, Schröder T, Bechstein M, Meyer L, Broocks G, Hanning U, Gauer T, Werner R, Fiehler J, Gellißen S, Kniep HC. Discordant and Converting Receptor Expressions in Brain Metastases from Breast Cancer: MRI-Based Non-Invasive Receptor Status Tracking. Cancers (Basel) 2023; 15:cancers15112880. [PMID: 37296843 DOI: 10.3390/cancers15112880] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 05/15/2023] [Accepted: 05/18/2023] [Indexed: 06/12/2023] Open
Abstract
Discordance and conversion of receptor expressions in metastatic lesions and primary tumors is often observed in patients with brain metastases from breast cancer. Therefore, personalized therapy requires continuous monitoring of receptor expressions and dynamic adaptation of applied targeted treatment options. Radiological in vivo techniques may allow receptor status tracking at high frequencies at low risk and cost. The present study aims to investigate the potential of receptor status prediction through machine-learning-based analysis of radiomic MR image features. The analysis is based on 412 brain metastases samples from 106 patients acquired between 09/2007 and 09/2021. Inclusion criteria were as follows: diagnosed cerebral metastases from breast cancer; histopathology reports on progesterone (PR), estrogen (ER), and human epidermal growth factor 2 (HER2) receptor status; and availability of MR imaging data. In total, 3367 quantitative features of T1 contrast-enhanced, T1 non-enhanced, and FLAIR images and corresponding patient age were evaluated utilizing random forest algorithms. Feature importance was assessed using Gini impurity measures. Predictive performance was tested using 10 permuted 5-fold cross-validation sets employing the 30 most important features of each training set. Receiver operating characteristic areas under the curves of the validation sets were 0.82 (95% confidence interval [0.78; 0.85]) for ER+, 0.73 [0.69; 0.77] for PR+, and 0.74 [0.70; 0.78] for HER2+. Observations indicate that MR image features employed in a machine learning classifier could provide high discriminatory accuracy in predicting the receptor status of brain metastases from breast cancer.
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Affiliation(s)
- Alexander Heitkamp
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
| | - Frederic Madesta
- Department of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
| | - Sophia Amberg
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
| | - Schohla Wahaj
- Department of Radiotherapy and Radiation Oncology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
| | - Tanja Schröder
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
| | - Matthias Bechstein
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
| | - Lukas Meyer
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
| | - Gabriel Broocks
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
| | - Uta Hanning
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
| | - Tobias Gauer
- Department of Radiotherapy and Radiation Oncology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
| | - René Werner
- Department of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
- Center for Biomedical Artificial Intelligence (bAIome), University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
| | - Jens Fiehler
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
| | - Susanne Gellißen
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
| | - Helge C Kniep
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
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Furtado FS, Mercaldo ND, Vahle T, Benkert T, Bradley WR, Ratanaprasatporn L, Seethamraju RT, Harisinghani MG, Lee S, Suarez-Weiss K, Umutlu L, Catana C, Pomykala KL, Domachevsky L, Bernstine H, Groshar D, Rosen BR, Catalano OA. Simultaneous multislice diffusion-weighted imaging versus standard diffusion-weighted imaging in whole-body PET/MRI. Eur Radiol 2023; 33:2536-2547. [PMID: 36460925 DOI: 10.1007/s00330-022-09275-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2022] [Revised: 10/20/2022] [Accepted: 10/26/2022] [Indexed: 12/04/2022]
Abstract
OBJECTIVE To compare standard (STD-DWI) single-shot echo-planar imaging DWI and simultaneous multislice (SMS) DWI during whole-body positron emission tomography (PET)/MRI regarding acquisition time, image quality, and lesion detection. METHODS Eighty-three adults (47 females, 57%), median age of 64 years (IQR 52-71), were prospectively enrolled from August 2018 to March 2020. Inclusion criteria were (a) abdominal or pelvic tumors and (b) PET/MRI referral from a clinician. Patients were excluded if whole-body acquisition of STD-DWI and SMS-DWI sequences was not completed. The evaluated sequences were axial STD-DWI at b-values 50-400-800 s/mm2 and the apparent diffusion coefficient (ADC), and axial SMS-DWI at b-values 50-300-800 s/mm2 and ADC, acquired with a 3-T PET/MRI scanner. Three radiologists rated each sequence's quality on a five-point scale. Lesion detection was quantified using the anatomic MRI sequences and PET as the reference standard. Regression models were constructed to quantify the association between all imaging outcomes/scores and sequence type. RESULTS The median whole-body STD-DWI acquisition time was 14.8 min (IQR 14.1-16.0) versus 7.0 min (IQR 6.7-7.2) for whole-body SMS-DWI, p < 0.001. SMS-DWI image quality scores were higher than STD-DWI in the abdomen (OR 5.31, 95% CI 2.76-10.22, p < 0.001), but lower in the cervicothoracic junction (OR 0.21, 95% CI 0.10-0.43, p < 0.001). There was no significant difference in the chest, mediastinum, pelvis, and rectum. STD-DWI detected 276/352 (78%) lesions while SMS-DWI located 296/352 (84%, OR 1.46, 95% CI 1.02-2.07, p = 0.038). CONCLUSIONS In cancer staging and restaging, SMS-DWI abbreviates acquisition while maintaining or improving the diagnostic yield in most anatomic regions. KEY POINTS • Simultaneous multislice diffusion-weighted imaging enables faster whole-body image acquisition. • Simultaneous multislice diffusion-weighted imaging maintains or improves image quality when compared to single-shot echo-planar diffusion-weighted imaging in most anatomical regions. • Simultaneous multislice diffusion-weighted imaging leads to superior lesion detection.
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Affiliation(s)
- Felipe S Furtado
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA, 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School, 149 13th Street, Charlestown, MA, 02129, USA
| | - Nathaniel D Mercaldo
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA, 02114, USA
| | - Thomas Vahle
- MR Application Predevelopment, Siemens Healthcare GmbH, Allee am Roethelheimpark 2, 91052, Erlangen, Germany
| | - Thomas Benkert
- MR Application Predevelopment, Siemens Healthcare GmbH, Allee am Roethelheimpark 2, 91052, Erlangen, Germany
| | - William R Bradley
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA, 02114, USA
| | - Lisa Ratanaprasatporn
- Brigham and Women's Hospital, Harvard Medical School, 75 Francis St, Boston, MA, 02115, USA
| | - Ravi Teja Seethamraju
- Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School, 149 13th Street, Charlestown, MA, 02129, USA
- MR Collaborations, Siemens Medical Solutions USA, Inc., 30 Jonathan Ln, Malden, MA, 02148, USA
| | - Mukesh G Harisinghani
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA, 02114, USA
| | - Susanna Lee
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA, 02114, USA
| | - Krista Suarez-Weiss
- Brigham and Women's Hospital, Harvard Medical School, 75 Francis St, Boston, MA, 02115, USA
| | - Lale Umutlu
- Universitätsmedizin Essen, Hufelandstraße 55, 45147, Essen, Germany
| | - Ciprian Catana
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA, 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School, 149 13th Street, Charlestown, MA, 02129, USA
| | | | - Liran Domachevsky
- Sheba Medical Center, Derech Sheba 2, Ramat Gan, Israel
- Tel Aviv University, 6997801, Tel Aviv-Yafo, Israel
| | - Hanna Bernstine
- Tel Aviv University, 6997801, Tel Aviv-Yafo, Israel
- Assuta Medical Center, HaBarzel 20 St, Ramat Hahayal, Tel Aviv, Israel
| | - David Groshar
- Tel Aviv University, 6997801, Tel Aviv-Yafo, Israel
- Assuta Medical Center, HaBarzel 20 St, Ramat Hahayal, Tel Aviv, Israel
| | - Bruse R Rosen
- Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School, 149 13th Street, Charlestown, MA, 02129, USA
| | - Onofrio Antonio Catalano
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA, 02114, USA.
- Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School, 149 13th Street, Charlestown, MA, 02129, USA.
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9
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Jannusch K, Bittner AK, Bruckmann NM, Morawitz J, Stieglitz C, Dietzel F, Quick HH, Baba HA, Herrmann K, Umutlu L, Antoch G, Kirchner J, Kasimir-Bauer S, Hoffmann O. Correlation between Imaging Markers Derived from PET/MRI and Invasive Acquired Biomarkers in Newly Diagnosed Breast Cancer. Cancers (Basel) 2023; 15:cancers15061651. [PMID: 36980537 PMCID: PMC10046153 DOI: 10.3390/cancers15061651] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 03/06/2023] [Indexed: 03/30/2023] Open
Abstract
PURPOSE Evaluate the diagnostic potential of [18F]FDG-PET/MRI data compared with invasive acquired biomarkers in newly diagnosed early breast cancer (BC). METHODS Altogether 169 women with newly diagnosed BC were included. All underwent a breast- and whole-body [18F]FDG-PET/MRI for initial staging. A tumor-adapted volume of interest was placed in the primaries and defined bone regions on each standard uptake value (SUV)/apparent diffusion coefficient (ADC) dataset. Immunohistochemical markers, molecular subtype, tumor grading, and disseminated tumor cells (DTCs) of each patient were assessed after ultrasound-guided biopsy of the primaries and bone marrow (BM) aspiration. Correlation analysis and group comparisons were assessed. RESULTS A significant inverse correlation of estrogen-receptor (ER) expression and progesterone-receptor (PR) expression towards SUVmax was found (ER: r = 0.27, p < 0.01; PR: r = 0.19, p < 0.05). HER2-receptor expression showed no significant correlation towards SUV and ADC values. A significant positive correlation between Ki67 and SUVmax and SUVmean (r = 0.42 p < 0.01; r = 0.19 p < 0.05) was shown. Tumor grading significantly correlated with SUVmax and SUVmean (ρ = 0.36 and ρ = 0.39, both p's < 0.01). There were no group differences between SUV/ADC values of DTC-positive/-negative patients. CONCLUSIONS [18F]FDG-PET/MRI may give a first impression of BC-receptor status and BC-tumor biology during initial staging by measuring glucose metabolism but cannot distinguish between DTC-positive/-negative patients and replace biopsy.
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Affiliation(s)
- Kai Jannusch
- Department of Diagnostic and Interventional Radiology, University Dusseldorf, Medical Faculty, 40225 Dusseldorf, Germany
| | - Ann-Kathrin Bittner
- Department Gynecology and Obstetrics, University Hospital Essen, University of Duisburg-Essen, 45147 Essen, Germany
| | - Nils Martin Bruckmann
- Department of Diagnostic and Interventional Radiology, University Dusseldorf, Medical Faculty, 40225 Dusseldorf, Germany
| | - Janna Morawitz
- Department of Diagnostic and Interventional Radiology, University Dusseldorf, Medical Faculty, 40225 Dusseldorf, Germany
| | - Cleo Stieglitz
- Department of Diagnostic and Interventional Radiology, University Dusseldorf, Medical Faculty, 40225 Dusseldorf, Germany
| | - Frederic Dietzel
- Department of Diagnostic and Interventional Radiology, University Dusseldorf, Medical Faculty, 40225 Dusseldorf, Germany
| | - Harald H Quick
- High-Field and Hybrid MR Imaging, University Hospital Essen, University Duisburg-Essen, 45147 Essen, Germany
- Erwin L. Hahn Institute for Magnetic Resonance Imaging, University Duisburg-Essen, 45141 Essen, Germany
| | - Hideo A Baba
- Institute of Pathology, University Hospital Essen, University of Duisburg-Essen, 45147 Essen, Germany
| | - Ken Herrmann
- Department of Nuclear Medicine, University Hospital Essen, University of Duisburg-Essen, 45147 Essen, Germany
| | - Lale Umutlu
- Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, University of Duisburg-Essen, 45147 Essen, Germany
| | - Gerald Antoch
- Department of Diagnostic and Interventional Radiology, University Dusseldorf, Medical Faculty, 40225 Dusseldorf, Germany
| | - Julian Kirchner
- Department of Diagnostic and Interventional Radiology, University Dusseldorf, Medical Faculty, 40225 Dusseldorf, Germany
| | - Sabine Kasimir-Bauer
- Department Gynecology and Obstetrics, University Hospital Essen, University of Duisburg-Essen, 45147 Essen, Germany
| | - Oliver Hoffmann
- Department Gynecology and Obstetrics, University Hospital Essen, University of Duisburg-Essen, 45147 Essen, Germany
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10
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Romeo V, Helbich TH, Pinker K. Breast PET/MRI Hybrid Imaging and Targeted Tracers. J Magn Reson Imaging 2023; 57:370-386. [PMID: 36165348 PMCID: PMC10074861 DOI: 10.1002/jmri.28431] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 09/01/2022] [Accepted: 09/02/2022] [Indexed: 01/20/2023] Open
Abstract
The recent introduction of hybrid positron emission tomography/magnetic resonance imaging (PET/MRI) as a promising imaging modality for breast cancer assessment has prompted fervent research activity on its clinical applications. The current knowledge regarding the possible clinical applications of hybrid PET/MRI is constantly evolving, thanks to the development and clinical availability of hybrid scanners, the development of new PET tracers and the rise of artificial intelligence (AI) techniques. In this state-of-the-art review on the use of hybrid breast PET/MRI, the most promising advanced MRI techniques (diffusion-weighted imaging, dynamic contrast-enhanced MRI, magnetic resonance spectroscopy, and chemical exchange saturation transfer) are discussed. Current and experimental PET tracers (18 F-FDG, 18 F-NaF, choline, 18 F-FES, 18 F-FES, 89 Zr-trastuzumab, choline derivatives, 18 F-FLT, and 68 Ga-FAPI-46) are described in order to provide an overview on their molecular mechanisms of action and corresponding clinical applications. New perspectives represented by the use of radiomics and AI techniques are discussed. Furthermore, the current strengths and limitations of hybrid PET/MRI in the real world are highlighted. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Valeria Romeo
- Department of Advanced Biomedical Sciences, University of Naples Federico II, Naples, Italy
| | - Thomas H Helbich
- Division of General and Pediatric Radiology, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Wien, Austria
| | - Katja Pinker
- Division of General and Pediatric Radiology, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Wien, Austria.,Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, New York, New York, USA
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11
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Ruan D, Sun L. Diagnostic Performance of PET/MRI in Breast Cancer: A Systematic Review and Bayesian Bivariate Meta-analysis. Clin Breast Cancer 2023; 23:108-124. [PMID: 36549970 DOI: 10.1016/j.clbc.2022.11.010] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 11/07/2022] [Accepted: 11/26/2022] [Indexed: 12/04/2022]
Abstract
INTRODUCTION By performing a systematic review and meta-analysis, the diagnostic value of 18F-FDG PET/MRI in breast lesions, lymph nodes, and distant metastases was assessed, and the merits and demerits of PET/MRI in the application of breast cancer were comprehensively reviewed. METHODS Breast cancer-related studies using 18F-FDG PET/MRI as a diagnostic tool published before September 12, 2022 were included. The pooled sensitivity, specificity, log diagnostic odds ratio (LDOR), and area under the curve (AUC) were calculated using Bayesian bivariate meta-analysis in a lesion-based and patient-based manner. RESULTS We ultimately included 24 studies (including 1723 patients). Whether on a lesion-based or patient-based analysis, PET/MRI showed superior overall pooled sensitivity (0.95 [95% CI: 0.92-0.98] & 0.93 [95% CI: 0.88-0.98]), specificity (0.94 [95% CI: 0.90-0.97] & 0.94 [95% CI: 0.92-0.97]), LDOR (5.79 [95% CI: 4.95-6.86] & 5.64 [95% CI: 4.58-7.03]) and AUC (0.98 [95% CI: 0.94-0.99] & 0.98[95% CI: 0.92-0.99]) for diagnostic applications in breast cancer. In the specific subgroup analysis, PET/MRI had high pooled sensitivity and specificity for the diagnosis of breast lesions and distant metastatic lesions and was especially excellent for bone lesions. PET/MRI performed poorly for diagnosing axillary lymph nodes but was better than for lymph nodes at other sites (pooled sensitivity, specificity, LDOR, AUC: 0.86 vs. 0.58, 0.90 vs. 0.82, 4.09 vs. 1.98, 0.89 vs. 0.84). CONCLUSION 18F-FDG PET/MRI performed excellently in diagnosing breast lesions and distant metastases. It can be applied to the initial diagnosis of suspicious breast lesions, accurate staging of breast cancer patients, and accurate restaging of patients with suspected recurrence.
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Affiliation(s)
- Dan Ruan
- Department of Nuclear Medicine, Zhongshan Hospital (Xiamen), Fudan University, Xiamen, China
| | - Long Sun
- Department of Nuclear Medicine and Minnan PET Center, Xiamen Cancer Hospital, The First Affiliated Hospital of Xiamen University, Xiamen, China.
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12
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Radiogenomics, Breast Cancer Diagnosis and Characterization: Current Status and Future Directions. Methods Protoc 2022; 5:mps5050078. [PMID: 36287050 PMCID: PMC9611546 DOI: 10.3390/mps5050078] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Revised: 09/23/2022] [Accepted: 09/27/2022] [Indexed: 12/05/2022] Open
Abstract
Breast cancer (BC) is a heterogeneous disease, affecting millions of women every year. Early diagnosis is crucial to increasing survival. The clinical workup of BC diagnosis involves diagnostic imaging and bioptic characterization. In recent years, technical advances in image processing allowed for the application of advanced image analysis (radiomics) to clinical data. Furthermore, -omics technologies showed their potential in the characterization of BC. Combining information provided by radiomics with -omics data can be important to personalize diagnostic and therapeutic work up in a clinical context for the benefit of the patient. In this review, we analyzed the recent literature, highlighting innovative approaches to combine imaging and biochemical/biological data, with the aim of identifying recent advances in radiogenomics applied to BC. The results of radiogenomic studies are encouraging approaches in a clinical setting. Despite this, as radiogenomics is an emerging area, the optimal approach has to face technical limitations and needs to be applied to large cohorts including all the expression profiles currently available for BC subtypes (e.g., besides markers from transcriptomics, proteomics and miRNomics, also other non-coding RNA profiles).
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13
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Wu J, Mayer AT, Li R. Integrated imaging and molecular analysis to decipher tumor microenvironment in the era of immunotherapy. Semin Cancer Biol 2022; 84:310-328. [PMID: 33290844 PMCID: PMC8319834 DOI: 10.1016/j.semcancer.2020.12.005] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2019] [Revised: 11/29/2020] [Accepted: 12/02/2020] [Indexed: 02/07/2023]
Abstract
Radiological imaging is an integral component of cancer care, including diagnosis, staging, and treatment response monitoring. It contains rich information about tumor phenotypes that are governed not only by cancer cellintrinsic biological processes but also by the tumor microenvironment, such as the composition and function of tumor-infiltrating immune cells. By analyzing the radiological scans using a quantitative radiomics approach, robust relations between specific imaging and molecular phenotypes can be established. Indeed, a number of studies have demonstrated the feasibility of radiogenomics for predicting intrinsic molecular subtypes and gene expression signatures in breast cancer based on MRI. In parallel, promising results have been shown for inferring the amount of tumor-infiltrating lymphocytes, a key factor for the efficacy of cancer immunotherapy, from standard-of-care radiological images. Compared with the biopsy-based approach, radiogenomics offers a unique avenue to profile the molecular makeup of the tumor and immune microenvironment as well as its evolution in a noninvasive and holistic manner through longitudinal imaging scans. Here, we provide a systematic review of the state of the art radiogenomics studies in the era of immunotherapy and discuss emerging paradigms and opportunities in AI and deep learning approaches. These technical advances are expected to transform the radiogenomics field, leading to the discovery of reliable imaging biomarkers. This will pave the way for their clinical translation to guide precision cancer therapy.
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Affiliation(s)
- Jia Wu
- Department of Imaging Physics, MD Anderson Cancer Center, Texas, 77030, USA; Department of Thoracic/Head & Neck Medical Oncology, MD Anderson Cancer Center, Texas, 77030, USA.
| | - Aaron T Mayer
- Department of Bioengineering, Stanford University, Stanford, California, 94305, USA; Department of Radiology, Stanford University, Stanford, California, 94305, USA; Molecular Imaging Program at Stanford, Stanford University, Stanford, California, 94305, USA; BioX Program at Stanford, Stanford University, Stanford, California, 94305, USA
| | - Ruijiang Li
- Department of Radiation Oncology, Stanford University, Stanford, California, 94305, USA
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14
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Crafa F, Vanella S, Catalano OA, Pomykala KL, Baiamonte M. Role of one-step nucleic acid amplification in colorectal cancer lymph node metastases detection. World J Gastroenterol 2022; 28:4019-4043. [PMID: 36157105 PMCID: PMC9403438 DOI: 10.3748/wjg.v28.i30.4019] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/26/2022] [Revised: 06/03/2022] [Accepted: 07/22/2022] [Indexed: 02/06/2023] Open
Abstract
Current histopathological staging procedures in colorectal cancer (CRC) depend on midline division of the lymph nodes (LNs) with one section of hematoxylin and eosin staining. Cancer cells outside this transection line may be missed, which could lead to understaging of Union for International Cancer Control Stage II high-risk patients. The one-step nucleic acid amplification (OSNA) assay has emerged as a rapid molecular diagnostic tool for LN metastases detection. It is a molecular technique that can analyze the entire LN tissue using a reverse-transcriptase loop-mediated isothermal amplification reaction to detect tumor-specific cytokeratin 19 mRNA. Our findings suggest that the OSNA assay has a high diagnostic accuracy in detecting metastatic LNs in CRC and a high negative predictive value. OSNA is a standardized, observer-independent technique, which may lead to more accurate staging. It has been suggested that in stage II CRC, the upstaging can reach 25% and these patients can access postoperative adjuvant chemotherapy. Moreover, intraoperative OSNA sentinel node evaluation may allow early CRC to be treated with organ-preserving surgery, while in more advanced-stage disease, a tailored lymphadenectomy can be performed considering the presence of aberrant lymphatic drainage and skip metastases.
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Affiliation(s)
- Francesco Crafa
- Division of General and Surgical Oncology, St. Giuseppe Moscati Hospital, Center of National Excellence and High Specialty, Avellino 83100, Italy
| | - Serafino Vanella
- Division of General and Surgical Oncology, St. Giuseppe Moscati Hospital, Center of National Excellence and High Specialty, Avellino 83100, Italy
| | - Onofrio A Catalano
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, United States
| | - Kelsey L Pomykala
- Department of Nuclear Medicine, Department of Radiological Sciences, David Geffen School of Medicine at University of California, Los Angeles, University Hospital Essen, University of Duisburg-Essen, Essen 45141, Germany
| | - Mario Baiamonte
- Division of General and Surgical Oncology, St. Giuseppe Moscati Hospital, Center of National Excellence and High Specialty, Avellino 83100, Italy
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15
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Koori N, Miyati T, Ohno N, Kawashima H, Nishikawa H. Sigmoid model analysis of breast dynamic contrast-enhanced MRI: Distinguishing between benign and malignant breast masses and breast cancer subtype prediction. J Appl Clin Med Phys 2022; 23:e13651. [PMID: 35594028 PMCID: PMC9195041 DOI: 10.1002/acm2.13651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2021] [Revised: 04/25/2022] [Accepted: 04/29/2022] [Indexed: 11/23/2022] Open
Abstract
Dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI) is performed to distinguish between benign and malignant lesions by evaluating the changes in signal intensity of the acquired image (kinetic curve). This study aimed to verify whether the existing breast DCE‐MRI analyzed by the sigmoid model can accurately distinguish between benign and invasive ductal carcinoma (IDC) and predict the subtype. A total of 154 patients who underwent breast MRI for detailed breast mass examinations were included in this study (38 with benign masses and 116 with IDC. The sigmoid model involved the acquisition of images at seven timepoints in 1‐min intervals to determine the change in signal intensity before and after contrast injection. From this curve, the magnitude of the increase in signal intensity in the early phase, the time to reach the maximum increase, and the slopes in the early and late phases were calculated. The Mann–Whitney U‐test was used for the statistical analysis. The IDC group exhibited a significantly larger and faster signal increase in the early phase and a significantly smaller rate of increase in the late phase than the benign group (P < 0.001). The luminal A‐like group demonstrated a significantly longer time to reach the maximum signal increase rate than other IDC subtypes (P < 0.05). The sigmoid model analysis of breast DCE‐MRI can distinguish between benign lesions and IDC and may also help in predicting luminal A‐like breast cancer.
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Affiliation(s)
- Norikazu Koori
- Department of Radiology, Komaki City Hospital, Komaki, Aichi, Japan.,Division of Health Sciences, Kanazawa University Graduate School of Medical Sciences, Kanazawa, Ishikawa, Japan
| | - Tosiaki Miyati
- Division of Health Sciences, Kanazawa University Graduate School of Medical Sciences, Kanazawa, Ishikawa, Japan
| | - Naoki Ohno
- Division of Health Sciences, Kanazawa University Graduate School of Medical Sciences, Kanazawa, Ishikawa, Japan
| | - Hiroko Kawashima
- Division of Health Sciences, Kanazawa University Graduate School of Medical Sciences, Kanazawa, Ishikawa, Japan
| | - Hiroko Nishikawa
- Department of Radiology, Komaki City Hospital, Komaki, Aichi, Japan
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16
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Kazama T, Takahara T, Hashimoto J. Breast Cancer Subtypes and Quantitative Magnetic Resonance Imaging: A Systemic Review. Life (Basel) 2022; 12:life12040490. [PMID: 35454981 PMCID: PMC9028183 DOI: 10.3390/life12040490] [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: 01/23/2022] [Revised: 02/20/2022] [Accepted: 03/08/2022] [Indexed: 12/12/2022] Open
Abstract
Magnetic resonance imaging (MRI) is the most sensitive imaging modality for breast cancer detection. This systematic review investigated the role of quantitative MRI features in classifying molecular subtypes of breast cancer. We performed a literature search of articles published on the application of quantitative MRI features in invasive breast cancer molecular subtype classification in PubMed from 1 January 2002 to 30 September 2021. Of the 1275 studies identified, 106 studies with a total of 12,989 patients fulfilled the inclusion criteria. Bias was assessed based using the Quality Assessment of Diagnostic Studies. All studies were case-controlled and research-based. Most studies assessed quantitative MRI features using dynamic contrast-enhanced (DCE) kinetic features and apparent diffusion coefficient (ADC) values. We present a summary of the quantitative MRI features and their correlations with breast cancer subtypes. In DCE studies, conflicting results have been reported; therefore, we performed a meta-analysis. Significant differences in the time intensity curve patterns were observed between receptor statuses. In 10 studies, including a total of 1276 lesions, the pooled difference in proportions of type Ⅲ curves (wash-out) between oestrogen receptor-positive and -negative cancers was not significant (95% confidence interval (CI): [−0.10, 0.03]). In nine studies, including a total of 1070 lesions, the pooled difference in proportions of type 3 curves between human epidermal growth factor receptor 2-positive and -negative cancers was significant (95% CI: [0.01, 0.14]). In six studies including a total of 622 lesions, the pooled difference in proportions of type 3 curves between the high and low Ki-67 groups was significant (95% CI: [0.17, 0.44]). However, the type 3 curve itself is a nonspecific finding in breast cancer. Many studies have examined the relationship between mean ADC and breast cancer subtypes; however, the ADC values overlapped significantly between subtypes. The heterogeneity of ADC using kurtosis or difference, diffusion tensor imaging parameters, and relaxation time was reported recently with promising results; however, current evidence is limited, and further studies are required to explore these potential applications.
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Affiliation(s)
- Toshiki Kazama
- Department of Diagnostic Radiology, Tokai University School of Medicine, Isehara 259-1193, Japan;
- Correspondence: ; Tel.: +81-463-93-1121
| | - Taro Takahara
- Department of Biomedical Engineering, Tokai University School of Engineering, Hiratsuka 259-1207, Japan;
| | - Jun Hashimoto
- Department of Diagnostic Radiology, Tokai University School of Medicine, Isehara 259-1193, Japan;
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17
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Bruckmann NM, Morawitz J, Fendler WP, Ruckhäberle E, Bittner AK, Giesel FL, Herrmann K, Antoch G, Umutlu L, Kirchner J. A Role of PET/MR in Breast Cancer? Semin Nucl Med 2022; 52:611-618. [DOI: 10.1053/j.semnuclmed.2022.01.003] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2022] [Accepted: 01/26/2022] [Indexed: 01/18/2023]
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18
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A Complex Radiomic Signature in Luminal Breast Cancer from a Weighted Statistical Framework: A Pilot Study. Diagnostics (Basel) 2022; 12:diagnostics12020499. [PMID: 35204589 PMCID: PMC8871349 DOI: 10.3390/diagnostics12020499] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 02/08/2022] [Accepted: 02/12/2022] [Indexed: 01/27/2023] Open
Abstract
Radiomics is rapidly advancing in precision diagnostics and cancer treatment. However, there are several challenges that need to be addressed before translation to clinical use. This study presents an ad-hoc weighted statistical framework to explore radiomic biomarkers for a better characterization of the radiogenomic phenotypes in breast cancer. Thirty-six female patients with breast cancer were enrolled in this study. Radiomic features were extracted from MRI and PET imaging techniques for malignant and healthy lesions in each patient. To reduce within-subject bias, the ratio of radiomic features extracted from both lesions was calculated for each patient. Radiomic features were further normalized, comparing the z-score, quantile, and whitening normalization methods to reduce between-subjects bias. After feature reduction by Spearman’s correlation, a methodological approach based on a principal component analysis (PCA) was applied. The results were compared and validated on twenty-seven patients to investigate the tumor grade, Ki-67 index, and molecular cancer subtypes using classification methods (LogitBoost, random forest, and linear discriminant analysis). The classification techniques achieved high area-under-the-curve values with one PC that was calculated by normalizing the radiomic features via the quantile method. This pilot study helped us to establish a robust framework of analysis to generate a combined radiomic signature, which may lead to more precise breast cancer prognosis.
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19
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Meyer HJ, Wienke A, Surov A. Diffusion-Weighted Imaging of Different Breast Cancer Molecular Subtypes: A Systematic Review and Meta-Analysis. Breast Care (Basel) 2022; 17:47-54. [PMID: 35355697 PMCID: PMC8914237 DOI: 10.1159/000514407] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Accepted: 01/08/2021] [Indexed: 02/03/2023] Open
Abstract
Background Magnetic resonance imaging can be used to diagnose breast cancer (BC). Diffusion-weighted imaging (DWI) and the apparent diffusion coefficient (ADC) can be used to reflect tumor microstructure. Objectives This analysis aimed to compare ADC values between molecular subtypes of BC based on a large sample of patients. Method The MEDLINE library and Scopus database were screened for the associations between ADC and molecular subtypes of BC up to April 2020. The primary end point of the systematic review was the ADC value in different BC subtypes. Overall, 28 studies were included. Results The included studies comprised a total of 2,990 tumors. Luminal A type was diagnosed in 865 cases (28.9%), luminal B in 899 (30.1%), human epidermal growth factor receptor (Her2)-enriched in 597 (20.0%), and triple-negative in 629 (21.0%). The mean ADC values of the subtypes were as follows: luminal A: 0.99 × 10-3 mm2/s (95% CI 0.94-1.04), luminal B: 0.97 × 10-3 mm2/s (95% CI 0.89-1.05), Her2-enriched: 1.02 × 10-3 mm2/s (95% CI 0.95-1.08), and triple-negative: 0.99 × 10-3 mm2/s (95% CI 0.91-1.07). Conclusions ADC values cannot be used to discriminate between molecular subtypes of BC.
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Affiliation(s)
- Hans-Jonas Meyer
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Leipzig, Germany
| | - Andreas Wienke
- Institute of Medical Epidemiology, Biostatistics, and Informatics, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
| | - Alexey Surov
- Department of Radiology and Nuclear Medicine, University of Magdeburg, Magdeburg, Germany
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20
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Bu L, Tu N, Wang K, Zhou Y, Xie X, Han X, Lin H, Feng H. Relationship between 18F-FDG PET/CT Semi-Quantitative Parameters and International Association for the Study of Lung Cancer, American Thoracic Society/European Respiratory Society Classification in Lung Adenocarcinomas. Korean J Radiol 2022; 23:112-123. [PMID: 34983098 PMCID: PMC8743143 DOI: 10.3348/kjr.2021.0455] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Revised: 08/30/2021] [Accepted: 09/26/2021] [Indexed: 12/24/2022] Open
Abstract
Objective To investigate the relationship between 18F-FDG PET/CT semi-quantitative parameters and the International Association for the Study of Lung Cancer, American Thoracic Society/European Respiratory Society (IASLC/ATS/ERS) histopathologic classification, including histological subtypes, proliferation activity, and somatic mutations. Materials and Methods This retrospective study included 419 patients (150 males, 269 females; median age, 59.0 years; age range, 23.0–84.0 years) who had undergone surgical removal of stage IA–IIIA lung adenocarcinoma and had preoperative PET/CT data of lung tumors. The maximum standardized uptake values (SUVmax), background-subtracted volume (BSV), and background-subtracted lesion activity (BSL) derived from PET/CT were measured. The IASLC/ATS/ERS subtypes, Ki67 score, and epidermal growth factor/anaplastic lymphoma kinase (EGFR/ALK) mutation status were evaluated. The PET/CT semi-quantitative parameters were compared between the tumor subtypes using the Mann–Whitney U test or the Kruskal–Wallis test. The optimum cutoff values of the PET/CT semi-quantitative parameters for distinguishing the IASLC/ATS/ERS subtypes were calculated using receiver operating characteristic curve analysis. The correlation between the PET/CT semi-quantitative parameters and pathological parameters was analyzed using Spearman’s correlation. Statistical significance was set at p < 0.05. Results SUVmax, BSV, and BSL values were significantly higher in invasive adenocarcinoma (IA) than in minimally IA (MIA), and the values were higher in MIA than in adenocarcinoma in situ (AIS) (all p < 0.05). Remarkably, an SUVmax of 0.90 and a BSL of 3.62 were shown to be the optimal cutoff values for differentiating MIA from AIS, manifesting as pure ground-glass nodules with 100% sensitivity and specificity. Metabolic-volumetric parameters (BSV and BSL) were better potential independent factors than metabolic parameters (SUVmax) in differentiating growth patterns. SUVmax and BSL, rather than BSV, were strongly or moderately correlated with Ki67 in most subtypes, except for the micropapillary and solid predominant groups. PET/CT parameters were not correlated with EGFR/ALK mutation status. Conclusion As noninvasive surrogates, preoperative PET/CT semi-quantitative parameters could imply IASLC/ATS/ERS subtypes and Ki67 index and thus may contribute to improved management of precise surgery and postoperative adjuvant therapy.
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Affiliation(s)
- Lihong Bu
- PET/CT/MRI and Molecular Imaging Center, Renmin Hospital of Wuhan University, Wuhan, China
| | - Ning Tu
- PET/CT/MRI and Molecular Imaging Center, Renmin Hospital of Wuhan University, Wuhan, China
| | - Ke Wang
- PET/CT/MRI and Molecular Imaging Center, Renmin Hospital of Wuhan University, Wuhan, China
| | - Ying Zhou
- PET/CT/MRI and Molecular Imaging Center, Renmin Hospital of Wuhan University, Wuhan, China
| | - Xinli Xie
- Department of Nuclear Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xingmin Han
- Department of Nuclear Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Huiqin Lin
- Department of Thoracic Surgery, Renmin Hospital of Wuhan University, Wuhan, China
| | - Hongyan Feng
- PET/CT/MRI and Molecular Imaging Center, Renmin Hospital of Wuhan University, Wuhan, China.
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21
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Fowler AM, Strigel RM. Clinical advances in PET-MRI for breast cancer. Lancet Oncol 2022; 23:e32-e43. [PMID: 34973230 PMCID: PMC9673821 DOI: 10.1016/s1470-2045(21)00577-5] [Citation(s) in RCA: 50] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2021] [Revised: 09/20/2021] [Accepted: 10/01/2021] [Indexed: 01/03/2023]
Abstract
Imaging is paramount for the early detection and clinical staging of breast cancer, as well as to inform management decisions and direct therapy. PET-MRI is a quantitative hybrid imaging technology that combines metabolic and functional PET data with anatomical detail and functional perfusion information from MRI. The clinical applicability of PET-MRI for breast cancer is an active area of research. In this Review, we discuss the rationale and summarise the clinical evidence for the use of PET-MRI in the diagnosis, staging, prognosis, tumour phenotyping, and assessment of treatment response in breast cancer. The continued development and approval of targeted radiopharmaceuticals, together with radiomics and automated analysis tools, will further expand the opportunity for PET-MRI to provide added value for breast cancer imaging and patient care.
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Affiliation(s)
- Amy M Fowler
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; University of Wisconsin Carbone Cancer Center, Madison, WI, USA.
| | - Roberta M Strigel
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; University of Wisconsin Carbone Cancer Center, Madison, WI, USA
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22
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PET/MRI for Staging the Axilla in Breast Cancer: Current Evidence and the Rationale for SNB vs. PET/MRI Trials. Cancers (Basel) 2021; 13:cancers13143571. [PMID: 34298781 PMCID: PMC8303241 DOI: 10.3390/cancers13143571] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2021] [Revised: 07/05/2021] [Accepted: 07/12/2021] [Indexed: 01/03/2023] Open
Abstract
Simple Summary PET/MRI is a relatively new, hybrid imaging tool that allows practitioners to obtain both a local and systemic staging in breast cancer patients in a single exam. To date, the available evidence is not sufficient to determine the role of PET/MRI in breast cancer management. The aims of this paper are to provide an overview of the current literature on PET/MRI in breast cancer, and to illustrate two ongoing trials aimed at defining the eventual role of PET/MRI in axillary staging in two different settings: patients with early breast cancer and patients with positive axillary nodes that are candidates for primary systemic therapy. In both cases, findings from PET/MRI will be compared with the final pathology and could be helpful to better tailor axillary surgery in the future. Abstract Axillary surgery in breast cancer (BC) is no longer a therapeutic procedure but has become a purely staging procedure. The progressive improvement in imaging techniques has paved the way to the hypothesis that prognostic information on nodal status deriving from surgery could be obtained with an accurate diagnostic exam. Positron emission tomography/magnetic resonance imaging (PET/MRI) is a relatively new imaging tool and its role in breast cancer patients is still under investigation. We reviewed the available literature on PET/MRI in BC patients. This overview showed that PET/MRI yields a high diagnostic performance for the primary tumor and distant lesions of liver, brain and bone. In particular, the results of PET/MRI in staging the axilla are promising. This provided the rationale for two prospective comparative trials between axillary surgery and PET/MRI that could lead to a further de-escalation of surgical treatment of BC. • SNB vs. PET/MRI 1 trial compares PET/MRI and axillary surgery in staging the axilla of BC patients undergoing primary systemic therapy (PST). • SNB vs. PET/MRI 2 trial compares PET/MRI and sentinel node biopsy (SNB) in staging the axilla of early BC patients who are candidates for upfront surgery. Finally, these ongoing studies will help clarify the role of PET/MRI in BC and establish whether it represents a useful diagnostic tool that could guide, or ideally replace, axillary surgery in the future.
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23
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Molecular subtypes of invasive breast cancer: correlation between PET/computed tomography and MRI findings. Nucl Med Commun 2021; 41:810-816. [PMID: 32427700 DOI: 10.1097/mnm.0000000000001220] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVE The aim of the study was to investigate the diagnostic value of fluorodeoxyglucose-18 (FDG)-PET/computed tomography (CT) and MRI parameters in determining the molecular subtypes of invasive breast cancer. METHODS Data from 55 primary invasive breast cancer masses in 51 female patients who underwent pre-treatment PET/CT and MRI scans, and histopathological diagnosis at the authors' center were retrospectively reviewed. The relationship between FDG-PET/CT and MRI parameters, including maximum and mean standard uptake values (SUVmax and SUVmean, respectively), mean metabolic index (MImean) and metabolic tumor volume (MTV) values obtained from FDG-PET, and shape, margin, internal contrast-enhancement characteristics, kinetic curve types, functional tumor volume (FTV), apparent diffusion coefficient (ADC) values obtained from MRI was evaluated. Subsequently, differences among molecular subtypes (i.e. luminal A, luminal B, c-erbB-2 positive, and triple-negative) in terms of PET/CT and MRI parameters were evaluated. RESULTS The luminal B subtype of invasive breast cancer had higher SUVmax and SUVmean (P = 0.002 and P = 0.017, respectively) values than the luminal A subtype. In addition, the triple-negative subtype had a higher SUVmax (P = 0.028) than the luminal A subtype. There was a statistically significant positive correlation between pathological tumor volume (PTV) and SUVmean (P = 0.019, r = 0.720). SUVmax and ADC were negatively correlated (P = 0.001; r = -0.384). A very strong positive correlation was detected between MTV and FTV (P = 0.000; r = 0.857), and between MTV and PTV (P = 0.006, r = 0.796), and between FTV and PTV (P = 0.006, r = 0.921). CONCLUSION Results of the present study suggest that SUVmax was superior to MRI findings in predicting molecular subtypes and that MRI was superior to PET/CT in predicting PTV.
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Morawitz J, Kirchner J, Martin O, Bruckmann NM, Dietzel F, Li Y, Rischpler C, Herrmann K, Umutlu L, Bittner AK, Mohrmann S, Ingenwerth M, Häberle L, Esposito I, Antoch G, Buchbender C, Sawicki LM. Prospective Correlation of Prognostic Immunohistochemical Markers With SUV and ADC Derived From Dedicated Hybrid Breast 18F-FDG PET/MRI in Women With Newly Diagnosed Breast Cancer. Clin Nucl Med 2021; 46:201-205. [PMID: 33351505 DOI: 10.1097/rlu.0000000000003488] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
PURPOSE The aim of this study was to correlate prognostically relevant immunohistochemical parameters of breast cancer with simultaneously acquired SUVs and apparent diffusion coefficient (ADC) values derived from hybrid breast PET/MRI. PATIENTS AND METHODS Fifty-six women with newly diagnosed, therapy-naive, histologically proven breast cancer (mean age, 54.1 ± 12.0 years) underwent dedicated prone 18F-FDG breast PET/MRI. Diffusion-weighted imaging (b-values: 0, 500, 1000 s/mm2) was performed simultaneously with the PET acquisition. A region of interest encompassing the entire primary tumor on each patient's PET/MRI scan was used to determine the glucose metabolism represented by maximum and mean SUV as well as into corresponding ADC maps to assess tumor cellularity represented by mean and minimum ADC values. Histopathological tumor grading and prognostically relevant immunohistochemical markers, that is, Ki67, progesterone receptor, estrogen receptor, and human epidermal growth factor receptor 2 (HER2), were assessed. Pearson correlation coefficients were calculated to compare SUV and ADC values as well as the immunohistochemically markers and molecular subtype. For the comparison with the tumor grading, a Wilcoxon test was used. RESULTS A significant inverse correlation between SUV and ADC values derived from breast PET/MRI (r = -0.49 for SUVmean vs ADCmean; r = -0.43 for SUVmax vs ADCmin; both P's < 0.001) was found. Tumor grading and Ki67 both showed a positive correlation with SUVmean from breast PET/MRI (r = 0.37 and r = 0.32, P < 0.01). For immunohistochemical markers, HER2 showed an inverse correlation with ADC values from breast PET/MRI (r = -0.35, P < 0.01). Molecular subtypes significantly correlate with SUVmax and SUVmean (r = 0.52 and r = 0.42, both P's < 0.05). In addition, estrogen receptor expression showed an inverse correlation with SUVmax and SUVmean from breast PET/MRI (r = -0.45 and r = -0.42, P < 0.001). CONCLUSIONS The present data show a correlation between increased glucose metabolism, cellularity, tumor grading, estrogen and HER2 expression, as well as molecular subtype of breast cancer primaries. Hence, simultaneous 18F-FDG PET and diffusion-weighted imaging from hybrid breast PET/MRI may serve as a predictive tool for identifying high-risk breast cancer patients in initial staging and guide-targeted therapy.
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Affiliation(s)
- Janna Morawitz
- From the Department of Diagnostic and Interventional Radiology, Medical Faculty, University Düsseldorf, Düsseldorf
| | - Julian Kirchner
- From the Department of Diagnostic and Interventional Radiology, Medical Faculty, University Düsseldorf, Düsseldorf
| | - Ole Martin
- From the Department of Diagnostic and Interventional Radiology, Medical Faculty, University Düsseldorf, Düsseldorf
| | - Nils-Martin Bruckmann
- From the Department of Diagnostic and Interventional Radiology, Medical Faculty, University Düsseldorf, Düsseldorf
| | - Frederic Dietzel
- From the Department of Diagnostic and Interventional Radiology, Medical Faculty, University Düsseldorf, Düsseldorf
| | - Yan Li
- Departments of Diagnostic and Interventional Radiology and Neuroradiology
| | | | | | - Lale Umutlu
- Departments of Diagnostic and Interventional Radiology and Neuroradiology
| | - Ann-Kathrin Bittner
- Gynecology and Obstetrics, Essen University Hospital, University of Duisburg-Essen, Essen
| | - Svjetlana Mohrmann
- Department of Gynecology, Medical Faculty, University Düsseldorf, Düsseldorf
| | - Marc Ingenwerth
- Institute of Pathology, West German Cancer Center, Essen University Hospital, University Duisburg-Essen and the German Cancer Consortium (DKTK), Essen
| | - Lena Häberle
- Institute of Pathology, Medical Faculty, Heinrich Heine University and University Hospital Duesseldorf, Duesseldorf, Germany
| | - Irene Esposito
- Institute of Pathology, Medical Faculty, Heinrich Heine University and University Hospital Duesseldorf, Duesseldorf, Germany
| | - Gerald Antoch
- From the Department of Diagnostic and Interventional Radiology, Medical Faculty, University Düsseldorf, Düsseldorf
| | - Christian Buchbender
- From the Department of Diagnostic and Interventional Radiology, Medical Faculty, University Düsseldorf, Düsseldorf
| | - Lino M Sawicki
- From the Department of Diagnostic and Interventional Radiology, Medical Faculty, University Düsseldorf, Düsseldorf
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Yeh JCY, Yu WH, Yang CK, Chien LI, Lin KH, Huang WS, Hsu PK. Predicting aggressive histopathological features in esophageal cancer with positron emission tomography using a deep convolutional neural network. ANNALS OF TRANSLATIONAL MEDICINE 2021; 9:37. [PMID: 33553330 PMCID: PMC7859760 DOI: 10.21037/atm-20-1419] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Background The presence of lymphovascular invasion (LVI) and perineural invasion (PNI) are of great prognostic importance in esophageal squamous cell carcinoma. Currently, positron emission tomography (PET) scans are the only means of functional assessment prior to treatment. We aimed to predict the presence of LVI and PNI in esophageal squamous cell carcinoma using PET imaging data by training a three-dimensional convolution neural network (3D-CNN). Methods Seven hundred and ninety-eight PET scans of patients with esophageal squamous cell carcinoma and 309 PET scans of patients with stage I lung cancer were collected. In the first part of this study, we built a 3D-CNN based on a residual network, ResNet, for a task to classify the scans into esophageal cancer or lung cancer. In the second stage, we collected the PET scans of 278 patients undergoing esophagectomy for a task to classify and predict the presence of LVI/PNI. Results In the first part, the model performance attained an area under the receiver operating characteristic curve (AUC) of 0.860. In the second part, we randomly split 80%, 10%, and 10% of our dataset into training set, validation set and testing set, respectively, for a task to classify the scans into the presence of LVI/PNI and evaluated the model performance on the testing set. Our 3D-CNN model attained an AUC of 0.668 in the testing set, which shows a better discriminative ability than random guessing. Conclusions A 3D-CNN can be trained, using PET imaging datasets, to predict LNV/PNI in esophageal cancer with acceptable accuracy.
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Affiliation(s)
| | | | | | - Ling-I Chien
- Department of Nursing, Taipei Veterans General Hospital, Taipei
| | - Ko-Han Lin
- Department of Nuclear Medicine, Taipei Veterans General Hospital, Taipei
| | - Wen-Sheng Huang
- Department of Nuclear Medicine, Taipei Veterans General Hospital, Taipei
| | - Po-Kuei Hsu
- Division of Thoracic Surgery, Department of Surgery, Taipei Veterans General Hospital and School of Medicine, National Yang-Ming University, Taipei
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Du S, Gao S, Zhang L, Yang X, Qi X, Li S. Improved discrimination of molecular subtypes in invasive breast cancer: Comparison of multiple quantitative parameters from breast MRI. Magn Reson Imaging 2020; 77:148-158. [PMID: 33309922 DOI: 10.1016/j.mri.2020.12.001] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2020] [Revised: 11/21/2020] [Accepted: 12/06/2020] [Indexed: 12/17/2022]
Abstract
PURPOSE To compare multiple quantitative parameters from breast magnetic resonance imaging (MRI) with the synthetic MRI sequence included for discrimination of molecular subtypes of invasive breast cancer. MATERIALS AND METHODS Between March 2019 and September 2020, two hundred breast cancer patients underwent preoperative breast multiparametric MRI examinations including synthetic MRI, diffusion weighted imaging (DWI) and dynamic contrast enhancement (DCE)-MRI sequences. MRI morphological features, T1 and T2 relaxation times (T1, T2) and proton density (PD) values from synthetic MRI, Ktrans, Kep, and Ve from DCE-MRI, mean apparent diffusion coefficient (ADC) from DWI and tumor volume were measured. Quantitative parameters were compared according to molecular markers and subtypes. Logistic regression were performed to find the related MRI parameters and establish combined parameters. The comparison between single and combined quantitative parameters by using DeLong tests. RESULTS T1, T2 values were significantly higher in hormone receptor (HR)- negative and Ki67 > 14% tumors (p < 0.05). Human epidermal growth factor receptor 2 (HER2)-positive tumors demonstrated significantly higher Ktrans and Kep (p < 0.01). Mean ADC values were significantly decreased in HR-positive and Ki67 > 14% tumors (p < 0.01). Tumor volumes were significantly higher in HER2-positive and Ki67 > 14% tumors (p < 0.05). Independent influencing factors were lower T2 values (p < 0.001), smaller tumor volume (p = 0.031) and higher mean ADC (p = 0.002) associated with luminal A subtype, while T1 values (p = 0.007) was the only quantitative parameter associated with triple-negative subtype. The diagnostic efficiency of combined parameters (T2 + mean ADC + volume) (AUC = 0.765) was significantly higher than that of mean ADC (AUC = 0.666, p = 0.031 by DeLong test) and volume (AUC = 0.650, p = 0.008 by DeLong test) for separating luminal A subtype. CONCLUSIONS MRI quantitative parameters could help distinguish molecular markers and subtypes. The emerging synthetic MRI parameters - T1 values were associated with the TN subtype, and combined parameters with added T2 values might improve the discrimination of the luminal A subtype. Application of synthetic MRI can enrich quantitative descriptors from breast MRI.
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Affiliation(s)
- Siyao Du
- Department of Radiology, the First Affiliated Hospital of China Medical University, Shenyang 110001, China
| | - Si Gao
- Department of Radiology, the First Affiliated Hospital of China Medical University, Shenyang 110001, China
| | - Lina Zhang
- Department of Radiology, the First Affiliated Hospital of China Medical University, Shenyang 110001, China.
| | - Xiaoping Yang
- Department of Radiology, the First Affiliated Hospital of China Medical University, Shenyang 110001, China
| | - Xixun Qi
- Department of Radiology, the First Affiliated Hospital of China Medical University, Shenyang 110001, China
| | - Shu Li
- Department of Radiology, the First Affiliated Hospital of China Medical University, Shenyang 110001, China
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Incoronato M, Mirabelli P, Grimaldi AM, Soricelli A, Salvatore M. Correlating imaging parameters with molecular data: An integrated approach to improve the management of breast cancer patients. Int J Biol Markers 2020; 35:47-50. [PMID: 32079469 DOI: 10.1177/1724600819899665] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
The goal of this review is to provide an overview of the studies aimed at integrating imaging parameters with molecular biomarkers for improving breast cancer patient's diagnosis and prognosis. The use of diagnostic imaging to extract quantitative parameters related to the morphology, metabolism, and functionality of tumors, as well as their correlation with cancer tissue biomarkers is an emerging research topic. Thanks to the development of imaging biobanks and the technological tools required for extraction of imaging parameters including radiomic features, it is possible to integrate imaging markers with genetic data. This new field of study represents the evolution of radiology-pathology correlation from an anatomic-histologic level to a genetic level, which paves new interesting perspectives for breast cancer management.
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Affiliation(s)
| | | | | | - Andrea Soricelli
- IRCCS SDN, Naples, Italy.,Department of Motor Sciences & Healthiness, University of Naples Parthenope, Naples, Italy
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Vidiri A, Gangemi E, Ruberto E, Pasqualoni R, Sciuto R, Sanguineti G, Farneti A, Benevolo M, Rollo F, Sperati F, Spasiano F, Pellini R, Marzi S. Correlation between histogram-based DCE-MRI parameters and 18F-FDG PET values in oropharyngeal squamous cell carcinoma: Evaluation in primary tumors and metastatic nodes. PLoS One 2020; 15:e0229611. [PMID: 32119697 PMCID: PMC7051076 DOI: 10.1371/journal.pone.0229611] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2019] [Accepted: 02/10/2020] [Indexed: 12/11/2022] Open
Abstract
OBJECTIVES To investigate the correlation between histogram-based Dynamic Contrast-Enhanced magnetic resonance imaging (DCE-MRI) parameters and positron emission tomography with 18F-fluorodeoxyglucose (18F-FDG-PET) values in oropharyngeal squamous cell carcinoma (OPSCC), both in primary tumors (PTs) and in metastatic lymph nodes (LNs). METHODS 52 patients with a new pathologically-confirmed OPSCC were included in the present retrospective cohort study. Imaging including DCE-MRI and 18F-FDG PET/CT scans were acquired in all patients. Both PTs and the largest LN, if present, were volumetrically contoured. Quantitative parameters, including the transfer constants, Ktrans and Kep, and the volume of extravascular extracellular space, ve, were calculated from DCE-MRI. The percentiles (P), P10, P25, P50, P75, P90, and skewness, kurtosis and entropy were obtained from the histogram-based analysis of each perfusion parameter. Standardized uptake values (SUV), SUVmax, SUVpeak, SUVmean, metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were calculated applying a SUV threshold of 40%. The correlations between all variables were investigated with the Spearman-rank correlation test. To exclude false positive results under multiple testing, the Benjamini-Hockberg procedure was applied. RESULTS No significant correlations were found between any parameters in PTs, while significant associations emerged between Ktrans and 18F-FDG PET parameters in LNs. CONCLUSIONS Evident relationships emerged between DCE-MRI and 18F-FDG PET parameters in OPSCC LNs, while no association was found in PTs. The complex relationships between perfusion and metabolic biomarkers should be interpreted separately for primary tumors and lymph-nodes. A multiparametric approach to analyze PTs and LNs before treatment is advisable in head and neck squamous cell carcinoma (HNSCC).
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Affiliation(s)
- Antonello Vidiri
- Radiology and Diagnostic Imaging Department, IRCCS Regina Elena National Cancer Institute, Rome, Italy
| | - Emma Gangemi
- Radiology and Diagnostic Imaging Department, IRCCS Regina Elena National Cancer Institute, Rome, Italy
- Departmental Faculty of Medicine and Surgery, Center for Integrated Research, University Campus Bio-Medico of Rome, Rome, Italy
- * E-mail:
| | - Emanuela Ruberto
- Radiology and Diagnostic Imaging Department, IRCCS Regina Elena National Cancer Institute, Rome, Italy
| | - Rosella Pasqualoni
- Department of Nuclear Medicine, IRCCS Regina Elena National Cancer Institute, Rome, Italy
| | - Rosa Sciuto
- Department of Nuclear Medicine, IRCCS Regina Elena National Cancer Institute, Rome, Italy
| | - Giuseppe Sanguineti
- Department of Radiotherapy, IRCCS Regina Elena National Cancer Institute, Rome, Italy
| | - Alessia Farneti
- Department of Radiotherapy, IRCCS Regina Elena National Cancer Institute, Rome, Italy
| | - Maria Benevolo
- Department of Pathology, IRCCS Regina Elena National Cancer Institute, Rome, Italy
| | - Francesca Rollo
- Department of Pathology, IRCCS Regina Elena National Cancer Institute, Rome, Italy
| | - Francesca Sperati
- Biostatistics-Scientific Direction, IRCCS Regina Elena National Cancer Institute, Rome, Italy
| | - Filomena Spasiano
- Department of Radiotherapy, IRCCS Regina Elena National Cancer Institute, Rome, Italy
| | - Raul Pellini
- Department of Otolaryngology & Head and Neck Surgery, IRCCS Regina Elena National Cancer Institute, Rome, Italy
| | - Simona Marzi
- Medical Physics Laboratory, IRCCS Regina Elena National Cancer Institute, Rome, Italy
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Correlation Between Semiquantitative Metabolic Parameters After PET/CT and Histologic Prognostic Factors in Laryngeal and Pharyngeal Carcinoma. Head Neck Pathol 2019; 14:724-732. [PMID: 31873933 PMCID: PMC7413956 DOI: 10.1007/s12105-019-01116-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2019] [Accepted: 12/17/2019] [Indexed: 12/11/2022]
Abstract
Positron emission tomography/computed tomography (PET/CT) has shown prognostic significance in head and neck cancer patients. The underlying pathologic features that could explain the mechanisms associated with this observation are not clear. To analyze the correlation between 18-F-fluoro-2-deoxy-D-glucose (18F-FDG) uptake assessed by PET/CT in head and neck cancer and histopathologic prognostic factors. Ninety-nine patients with laryngeal and pharyngeal squamous cell carcinoma were retrospectively reviewed for pretreatment PET/CT measurements, namely standardized uptake value (SUV), metabolic tumor volume (MTV), and total lesion glycolysis (TLG). The corresponding histologic material was evaluated for tumor stroma-related prognostic factors such as the amount and type of stroma, lymphocytic response, tumor budding activity, and size of tumor cell nests in the tumor core area and tumor front. TLG and MTV were associated with tumor localization, as they were higher in oropharyngeal tumors. These values were also associated with tumor cell nest size in the tumor core with higher values corresponding to tumors with smaller nests. MTV40% was marginally associated with fibroblastic stroma type and higher budding activity. SUVmax was not associated with the histological factors in the whole sample, but higher values trended with higher tumor budding activity and stroma-rich tumors of the oropharynx. 18F-FDG PET measurements in head and neck squamous cell carcinomas are associated with prognostic histopathologic factors and suggest a possible correlation of glucose metabolism to epithelial-to-mesenchymal transition.
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Incoronato M, Grimaldi AM, Mirabelli P, Cavaliere C, Parente CA, Franzese M, Staibano S, Ilardi G, Russo D, Soricelli A, Catalano OA, Salvatore M. Circulating miRNAs in Untreated Breast Cancer: An Exploratory Multimodality Morpho-Functional Study. Cancers (Basel) 2019; 11:E876. [PMID: 31234535 PMCID: PMC6628327 DOI: 10.3390/cancers11060876] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2019] [Revised: 06/17/2019] [Accepted: 06/20/2019] [Indexed: 12/24/2022] Open
Abstract
The aim of this study was to identify new disease-related circulating miRNAs with high diagnostic accuracy for breast cancer (BC) and to correlate their deregulation with the morpho-functional characteristics of the tumour, as assessed in vivo by positron emission tomography/magnetic resonance (PET/MR) imaging. A total of 77 untreated female BC patients underwent same-day PET/MR and blood collection, and 78 healthy donors were recruited as negative controls. The expression profile of 84 human miRNAs was screened by using miRNA PCR arrays and validated by real-time PCR. The validated miRNAs were correlated with the quantitative imaging parameters extracted from the primary BC samples. Circulating miR-125b-5p and miR-143-3p were upregulated in BC plasma and able to discriminate BC patients from healthy subjects (miR-125-5p area under the receiver operating characteristic ROC curve (AUC) = 0.85 and miR-143-3p AUC = 0.80). Circulating CA15-3, a soluble form of the transmembrane glycoprotein Mucin 1 (MUC-1) that is upregulated in epithelial cancer cells of different origins, was combined with miR-125b-5p and improved the diagnostic accuracy from 70% (CA15-3 alone) to 89% (CA15-3 plus miR-125b-5p). MiR-143-3p showed a strong and significant correlation with the stage of the disease, apparent diffusion coefficient (ADCmean), reverse efflux volume transfer constant (Kepmean) and maximum standardized uptake value (SUVmax), and it might represent a biomarker of tumour aggressiveness. Similarly, miR-125b-5p was correlated with stage and grade 2 but inversely correlated with the forward volume transfer constant (Ktransmean) and proliferation index (Ki67), suggesting a potential role as a biomarker of a relatively more favourable prognosis. In situ hybridization (ISH) experiments revealed that miR-143-3p was expressed in endothelial tumour cells, miR-125-5p in cancer-associated fibroblasts, and neither in epithelial tumour cells. Our results suggested that miR-125-5p and miR-143-3p are potential biomarkers for the risk stratification of BC, and Kaplan-Maier plots confirmed this hypothesis. In addition, the combined use of miR-125-b-5p and CA15-3 enhanced the diagnostic accuracy up to 89%. This is the first study that correlates circulating miRNAs with in vivo quantified tumour biology through PET/MR biomarkers. This integration elucidates the link between the plasmatic increase in these two potential circulating biomarkers and the biology of untreated BC. In conclusion, while miR-143-3b and miR-125b-5p provide valuable information for prognosis, a combination of miR-125b-5p with the tumour marker CA15-3 improves sensitivity for BC detection, which warrants consideration by further validation studies.
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Affiliation(s)
| | | | | | | | | | | | - Stefania Staibano
- Department of Advanced Biomedical Sciences, Federico II University, 80131 Naples, Italy.
| | - Gennaro Ilardi
- Department of Advanced Biomedical Sciences, Federico II University, 80131 Naples, Italy.
| | - Daniela Russo
- Department of Advanced Biomedical Sciences, Federico II University, 80131 Naples, Italy.
| | - Andrea Soricelli
- IRCCS SDN, 80143 Naples, Italy.
- Department of Motor Sciences & Wellness, University of Naples Parthenope, 80133 Naples, Italy.
| | - Onofrio Antonio Catalano
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA.
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MR Imaging-Histology Correlation by Tailored 3D-Printed Slicer in Oncological Assessment. CONTRAST MEDIA & MOLECULAR IMAGING 2019; 2019:1071453. [PMID: 31275082 PMCID: PMC6560325 DOI: 10.1155/2019/1071453] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Accepted: 05/12/2019] [Indexed: 12/14/2022]
Abstract
3D printing and reverse engineering are innovative technologies that are revolutionizing scientific research in the health sciences and related clinical practice. Such technologies are able to improve the development of various custom-made medical devices while also lowering design and production costs. Recent advances allow the printing of particularly complex prototypes whose geometry is drawn from precise computer models designed on in vivo imaging data. This review summarizes a new method for histological sample processing (applicable to e.g., the brain, prostate, liver, and renal mass) which employs a personalized mold developed from diagnostic images through computer-aided design software and 3D printing. Through positioning the custom mold in a coherent manner with respect to the organ of interest (as delineated by in vivo imaging data), the cutting instrument can be precisely guided in order to obtain blocks of tissue which correspond with high accuracy to the slices imaged. This approach appeared crucial for validation of new quantitative imaging tools, for an accurate imaging-histopathological correlation and for the assessment of radiogenomic features extracted from oncological lesions. The aim of this review is to define and describe 3D printing technologies which are applicable to oncological assessment and slicer design, highlighting the radiological and pathological perspective as well as recent applications of this approach for the histological validation of and correlation with MR images.
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Mikó E, Kovács T, Sebő É, Tóth J, Csonka T, Ujlaki G, Sipos A, Szabó J, Méhes G, Bai P. Microbiome-Microbial Metabolome-Cancer Cell Interactions in Breast Cancer-Familiar, but Unexplored. Cells 2019; 8:E293. [PMID: 30934972 PMCID: PMC6523810 DOI: 10.3390/cells8040293] [Citation(s) in RCA: 135] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2019] [Revised: 03/22/2019] [Accepted: 03/26/2019] [Indexed: 12/18/2022] Open
Abstract
Breast cancer is a leading cause of death among women worldwide. Dysbiosis, an aberrant composition of the microbiome, characterizes breast cancer. In this review we discuss the changes to the metabolism of breast cancer cells, as well as the composition of the breast and gut microbiome in breast cancer. The role of the breast microbiome in breast cancer is unresolved, nevertheless it seems that the gut microbiome does have a role in the pathology of the disease. The gut microbiome secretes bioactive metabolites (reactivated estrogens, short chain fatty acids, amino acid metabolites, or secondary bile acids) that modulate breast cancer. We highlight the bacterial species or taxonomical units that generate these metabolites, we show their mode of action, and discuss how the metabolites affect mitochondrial metabolism and other molecular events in breast cancer. These metabolites resemble human hormones, as they are produced in a "gland" (in this case, the microbiome) and they are subsequently transferred to distant sites of action through the circulation. These metabolites appear to be important constituents of the tumor microenvironment. Finally, we discuss how bacterial dysbiosis interferes with breast cancer treatment through interfering with chemotherapeutic drug metabolism and availability.
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Affiliation(s)
- Edit Mikó
- Department of Medical Chemistry, University of Debrecen, 4032 Debrecen, Hungary.
- Department of Microbiology, Faculty of Medicine, University of Debrecen, 4032 Debrecen, Hungary.
| | - Tünde Kovács
- Department of Medical Chemistry, University of Debrecen, 4032 Debrecen, Hungary.
| | - Éva Sebő
- Kenézy Breast Center, Kenézy Gyula County Hospital, 4032 Debrecen, Hungary.
| | - Judit Tóth
- Kenézy Breast Center, Kenézy Gyula County Hospital, 4032 Debrecen, Hungary.
| | - Tamás Csonka
- Department of Pathology, Faculty of Medicine, University of Debrecen, 4032 Debrecen, Hungary.
| | - Gyula Ujlaki
- Department of Medical Chemistry, University of Debrecen, 4032 Debrecen, Hungary.
| | - Adrienn Sipos
- Department of Medical Chemistry, University of Debrecen, 4032 Debrecen, Hungary.
| | - Judit Szabó
- Department of Microbiology, Faculty of Medicine, University of Debrecen, 4032 Debrecen, Hungary.
| | - Gábor Méhes
- Department of Pathology, Faculty of Medicine, University of Debrecen, 4032 Debrecen, Hungary.
| | - Péter Bai
- Department of Medical Chemistry, University of Debrecen, 4032 Debrecen, Hungary.
- MTA-DE Lendület Laboratory of Cellular Metabolism, 4032 Debrecen, Hungary.
- Research Center for Molecular Medicine, Faculty of Medicine, University of Debrecen, 4032 Debrecen, Hungary.
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Schiano C, Soricelli A, De Nigris F, Napoli C. New challenges in integrated diagnosis by imaging and osteo-immunology in bone lesions. Expert Rev Clin Immunol 2019; 15:289-301. [PMID: 30570412 DOI: 10.1080/1744666x.2019.1561283] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
INTRODUCTION High-resolution imaging is the gold standard to measure the functional and biological features of bone lesions. Imaging markers have allowed the characterization both of tumour heterogeneity and metabolic data. Besides, ongoing studies are evaluating a combined use of 'imaging markers', such as SUVs, MATV, TLG, ADC from PET and MRI techniques respectively, and several 'biomarkers' spanning from chemokine immune-modulators, such as PD-1, RANK/RANKL, CXCR4/CXCL12 to transcription factors, such as TP53, RB1, MDM2, RUNX family, EZH2, YY1, MAD2. Osteoimmunology may improve diagnosis and prognosis leading to precision medicine in bone lesion treatment. Areas covered: We investigated modalities (molecular and imaging approach) useful to identify bone lesions deriving both from primary bone tumours and from osteotropic tumours, which have a higher incidence, prevalence and prognosis. Here, we summarized the recent advances in imaging techniques and osteoimmunology biomarkers which could play a pivotal role in personalized treatment. Expert commentary: Although imaging and molecular integration could allow both early diagnosis and stratification of cancer prognosis, large scale clinical trials will be necessary to translate pilot studies in the current clinical setting. ABBREVIATIONS ADC: apparent diffusion coefficient; ALCAM: Activated Leukocyte Cell Adhesion Molecule; ALP: Alkaline phosphatases; BC: Breast cancer; BSAP: B-Cell Lineage Specific Activator; BSAP: bone-specific alkaline phosphatase; BSP: bone sialoprotein; CRIP1: cysteine-rich intestinal protein 1; CD44: cluster of differentiation 44; CT: computed tomography; CXCL12: C-X-C motif ligand 12; CXCR4: C-X-C C-X-C chemokine receptor type 4; CTLA-4: Cytotoxic T-lymphocyte antigen 4; CTX-1: C-terminal end of the telopeptide of type I collagen; DC: dendritic cell; DWI: Diffusion-weighted MR image; EMT: mesenchymal transition; ET-1: endothelin-1; FDA: Food and Drug Administration; FDG: 18F-2-fluoro-2-deoxy-D-glucose; FGF: fibroblast growth factor; FOXC2: forkhead box protein C2: HK-2: hexokinase-2; ICTP: carboxyterminal cross-linked telopeptide of type I collagen; IGF-1R: Insulin Like Growth Factor 1 Receptor; ILC: innate lymphocytes cells; LC: lung cancer; IL-1: interleukin-1; LYVE1: lymphatic vessel endothelial hyaluronic acid receptor 1; MAD2: mitotic arrest deficient 2; MATV: metabolically active tumour volume; M-CSF: macrophage colony stimulating factor; MM: multiple myeloma; MIP1a: macrophage inflammatory protein 1a; MSC: mesenchymal stem cell; MRI: magnetic resonance imaging; PC: prostate cancer; NRP2: neuropilin 2; OPG: osteoprotogerin; PDGF: platelet-derived growth factor; PD-1: Programmed Cell Death 1; PET: positron emission tomography; PINP: procollagen type I N propeptide; PROX1: prospero homeobox protein 1; PSA: Prostate-specific antigen; PTH: parathyroid hormone; RANK: Receptor activator of NF-kB ligand; RECK: Reversion-inducing-cysteine-rich protein; SEMAs: semaphorins; SPECT: single photon computed tomography; SUV: standard uptake value; TLG: total lesion glycolysis; TP53: tumour protein 53; VCAM-1: vascular endothelial molecule-1; VOI: volume of interest; YY1: Yin Yang 1.
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Affiliation(s)
- Concetta Schiano
- a Department of Biochemical and Clinical Diagnostic , IRCCS SDN , Naples , Italy
| | - Andrea Soricelli
- a Department of Biochemical and Clinical Diagnostic , IRCCS SDN , Naples , Italy.,b Department of Motor Sciences and Healthiness , University of Naples Parthenope , Naples , Italy
| | - Filomena De Nigris
- c Department of Precision Medicine , University of Campania "Luigi Vanvitelli" , Naples , Italy
| | - Claudio Napoli
- a Department of Biochemical and Clinical Diagnostic , IRCCS SDN , Naples , Italy.,d Department of Medical, Surgical, Neurological, Metabolic and Geriatric Sciences , University of Campania "Luigi Vanvitelli" , Naples , Italy
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