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Byeon Y, Park YW, Lee S, Park D, Shin H, Han K, Chang JH, Kim SH, Lee SK, Ahn SS, Hwang D. Interpretable multimodal transformer for prediction of molecular subtypes and grades in adult-type diffuse gliomas. NPJ Digit Med 2025; 8:140. [PMID: 40044878 PMCID: PMC11883078 DOI: 10.1038/s41746-025-01530-4] [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: 09/12/2024] [Accepted: 02/19/2025] [Indexed: 03/09/2025] Open
Abstract
Molecular subtyping and grading of adult-type diffuse gliomas are essential for treatment decisions and patient prognosis. We introduce GlioMT, an interpretable multimodal transformer that integrates imaging and clinical data to predict the molecular subtype and grade of adult-type diffuse gliomas according to the 2021 WHO classification. GlioMT is trained on multiparametric MRI data from an institutional set of 1053 patients with adult-type diffuse gliomas to predict the IDH mutation status, 1p/19q codeletion status, and tumor grade. External validation on the TCGA (200 patients) and UCSF (477 patients) shows that GlioMT outperforms conventional CNNs and visual transformers, achieving AUCs of 0.915 (TCGA) and 0.981 (UCSF) for IDH mutation, 0.854 (TCGA) and 0.806 (UCSF) for 1p/19q codeletion, and 0.862 (TCGA) and 0.960 (UCSF) for grade prediction. GlioMT enhances the reliability of clinical decision-making by offering interpretability through attention maps and contributions of imaging and clinical data.
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Affiliation(s)
- Yunsu Byeon
- School of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Yae Won Park
- Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Soohyun Lee
- School of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Doohyun Park
- School of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - HyungSeob Shin
- School of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Kyunghwa Han
- Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Jong Hee Chang
- Department of Neurosurgery, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Se Hoon Kim
- Department of Pathology, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Seung-Koo Lee
- Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Sung Soo Ahn
- Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Republic of Korea.
| | - Dosik Hwang
- School of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea.
- Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Republic of Korea.
- Artificial Intelligence and Robotics Institute, Korea Institute of Science and Technology, Seoul, Republic of Korea.
- Department of Oral and Maxillofacial Radiology, Yonsei University College of Dentistry, Seoul, Republic of Korea.
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Nichelli L, Cadin C, Lazzari P, Mathon B, Touat M, Sanson M, Bielle F, Marjańska M, Lehéricy S, Branzoli F. Incorporation of Edited MRS into Clinical Practice May Improve Care of Patients with IDH-Mutant Glioma. AJNR Am J Neuroradiol 2025; 46:113-120. [PMID: 38997123 PMCID: PMC11735446 DOI: 10.3174/ajnr.a8413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Accepted: 07/02/2024] [Indexed: 07/14/2024]
Abstract
BACKGROUND AND PURPOSE Isocitrate dehydrogenase (IDH) mutation and 1p/19q codeletion classify adult-type diffuse gliomas into 3 tumor subtypes with distinct prognoses. We aimed to evaluate the performance of edited MR spectroscopy for glioma subtyping in a clinical setting, via the quantification of D-2-hydroxyglutarate (2HG) and cystathionine. The delay between this noninvasive classification and the integrated histomolecular analysis was also quantified. MATERIALS AND METHODS Subjects with presumed low-grade gliomas eligible for surgery (cohort 1) and subjects with IDH-mutant gliomas previously treated and with progressive disease (cohort 2) were prospectively examined with a single-voxel Mescher-Garwood point-resolved spectroscopy sequence at 3T. Spectra were quantified using LCModel. The Cramér-Rao lower bounds threshold was set to 20%. Integrated histomolecular analysis according to the 2021 WHO classification was considered as ground truth. RESULTS Thirty-four consecutive subjects were enrolled. Due to poor spectra quality and lack of histologic specimens, data from 26 subjects were analyzed. Twenty-one belonged to cohort 1 (11 women; median age, 42 years); and 5, to cohort 2 (3 women; median age, 48 years). Edited MR spectroscopy showed 100% specificity for detection of IDH-mutation and 91% specificity for the prediction of 1p/19q-codeletion status. Sensitivities for the prediction of IDH and 1p/19q codeletion were 69% and 33%, respectively. The median Cramér-Rao lower bounds values were 16% (13%-28%) for IDH-mutant and 572% (554%-999%) for IDH wild type tumors. The time between MR spectroscopy and surgery was longer for low-grade than for high-grade gliomas (P = .03), yet the time between MR spectroscopy and WHO diagnosis did not differ between grades (P = .07), possibly reflecting molecular analyses-induced delays in high-grade gliomas. CONCLUSIONS Our results, acquired in a clinic setting, confirmed that edited MR spectroscopy is highly specific for both IDH-mutation and 1p/19q-codeletion predictions and can provide a faster prognosis stratification. In the upcoming IDH-inhibitor treatment era, incorporation of edited MR spectroscopy into clinical workflow is desirable.
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Affiliation(s)
- Lucia Nichelli
- From the Department of Neuroradiology (L.N., P.L., S.L.), La Pitié Salpêtrière University Hospital, Assistance publique-hôpitaux de Paris, Paris, France
- The Paris Brain Institute (L.N., C.C., B.M., M.T., M.S., F. Bielle, S.L., F. Branzoli), Sorbonne University, Institut national de la santé et de la Recherche Médicale 1127, Centre National de la Recherche Scientifique, Joint Research Unit 7225, Equipe Labellisée Ligue Nationale Contre le Cancer, Paris, France
| | - Capucine Cadin
- The Paris Brain Institute (L.N., C.C., B.M., M.T., M.S., F. Bielle, S.L., F. Branzoli), Sorbonne University, Institut national de la santé et de la Recherche Médicale 1127, Centre National de la Recherche Scientifique, Joint Research Unit 7225, Equipe Labellisée Ligue Nationale Contre le Cancer, Paris, France
| | - Patrizia Lazzari
- From the Department of Neuroradiology (L.N., P.L., S.L.), La Pitié Salpêtrière University Hospital, Assistance publique-hôpitaux de Paris, Paris, France
- Department of Radiology (P.L.), University of Modena and Reggio Emilia, AOU Policlinico di Modena, Modena, Italy
| | - Bertrand Mathon
- Department of Neurosurgery (B.M.), La Pitié Salpêtrière University Hospital, Paris, France
- The Paris Brain Institute (L.N., C.C., B.M., M.T., M.S., F. Bielle, S.L., F. Branzoli), Sorbonne University, Institut national de la santé et de la Recherche Médicale 1127, Centre National de la Recherche Scientifique, Joint Research Unit 7225, Equipe Labellisée Ligue Nationale Contre le Cancer, Paris, France
| | - Mehdi Touat
- Department of Neuro-oncology (M.T., M.S.), La Pitié Salpêtrière University Hospital, Paris, France
- The Paris Brain Institute (L.N., C.C., B.M., M.T., M.S., F. Bielle, S.L., F. Branzoli), Sorbonne University, Institut national de la santé et de la Recherche Médicale 1127, Centre National de la Recherche Scientifique, Joint Research Unit 7225, Equipe Labellisée Ligue Nationale Contre le Cancer, Paris, France
| | - Marc Sanson
- Department of Neuro-oncology (M.T., M.S.), La Pitié Salpêtrière University Hospital, Paris, France
- The Paris Brain Institute (L.N., C.C., B.M., M.T., M.S., F. Bielle, S.L., F. Branzoli), Sorbonne University, Institut national de la santé et de la Recherche Médicale 1127, Centre National de la Recherche Scientifique, Joint Research Unit 7225, Equipe Labellisée Ligue Nationale Contre le Cancer, Paris, France
| | - Franck Bielle
- The Paris Brain Institute (L.N., C.C., B.M., M.T., M.S., F. Bielle, S.L., F. Branzoli), Sorbonne University, Institut national de la santé et de la Recherche Médicale 1127, Centre National de la Recherche Scientifique, Joint Research Unit 7225, Equipe Labellisée Ligue Nationale Contre le Cancer, Paris, France
- Department of Neuropathology (F. Bielle), La Pitié Salpêtrière University Hospital, Paris, France
| | - Małgorzata Marjańska
- Center for Magnetic Resonance Research (M.M.), Department of Radiology, University of innesota, Minneapolis, Minnesota
| | - Stéphane Lehéricy
- From the Department of Neuroradiology (L.N., P.L., S.L.), La Pitié Salpêtrière University Hospital, Assistance publique-hôpitaux de Paris, Paris, France
- Center for NeuroImaging Research (S.L.), Paris Brain Institute, Paris, France
- The Paris Brain Institute (L.N., C.C., B.M., M.T., M.S., F. Bielle, S.L., F. Branzoli), Sorbonne University, Institut national de la santé et de la Recherche Médicale 1127, Centre National de la Recherche Scientifique, Joint Research Unit 7225, Equipe Labellisée Ligue Nationale Contre le Cancer, Paris, France
| | - Francesca Branzoli
- The Paris Brain Institute (L.N., C.C., B.M., M.T., M.S., F. Bielle, S.L., F. Branzoli), Sorbonne University, Institut national de la santé et de la Recherche Médicale 1127, Centre National de la Recherche Scientifique, Joint Research Unit 7225, Equipe Labellisée Ligue Nationale Contre le Cancer, Paris, France
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3
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Nakhate V, Lasica AB, Wen PY. The Role of Mutant IDH Inhibitors in the Treatment of Glioma. Curr Neurol Neurosci Rep 2024; 24:631-643. [PMID: 39302605 DOI: 10.1007/s11910-024-01378-3] [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] [Accepted: 09/06/2024] [Indexed: 09/22/2024]
Abstract
PURPOSE OF REVIEW The identification of isocitrate dehydrogenase (IDH) mutations has led to a transformation in our understanding of gliomas and has paved the way to a new era of targeted therapy. In this article, we review the classification of IDH-mutant glioma, standard of care treatment options, clinical evidence for mutant IDH (mIDH) inhibitors, and practical implications of the recent landmark INDIGO trial. RECENT FINDINGS In the phase 3 randomized placebo-controlled INDIGO trial, mIDH1/2 inhibitor vorasidenib increased progression-free survival among non-enhancing grade 2 IDH-mutant gliomas following surgery. This marks the first positive randomized trial of targeted therapy in IDH-mutant glioma, and led to the US Food and Drug Administration's approval of vorasidenib in August 2024 for grade 2 IDH-mutant glioma. Vorasidenib is a well-tolerated treatment that can benefit a subset of patients with IDH-mutant glioma. Targeting mIDH also remains a promising strategy for select groups of patients excluded from the INDIGO trial. Ongoing and future studies, including with new agents and with combination therapy approaches, may expand the benefit and unlock the potential of mIDH inhibitors.
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Affiliation(s)
- Vihang Nakhate
- Center for Neuro-Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
- Harvard Medical School, Boston, MA, USA.
- Pappas Center for Neuro-Oncology, Massachusetts General Hospital, Boston, MA, USA.
| | - Aleksandra B Lasica
- Center for Neuro-Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Patrick Y Wen
- Center for Neuro-Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
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van den Bent MJ, French PJ, Brat D, Tonn JC, Touat M, Ellingson BM, Young RJ, Pallud J, von Deimling A, Sahm F, Figarella Branger D, Huang RY, Weller M, Mellinghoff IK, Cloughsey TF, Huse JT, Aldape K, Reifenberger G, Youssef G, Karschnia P, Noushmehr H, Peters KB, Ducray F, Preusser M, Wen PY. The biological significance of tumor grade, age, enhancement, and extent of resection in IDH-mutant gliomas: How should they inform treatment decisions in the era of IDH inhibitors? Neuro Oncol 2024; 26:1805-1822. [PMID: 38912846 PMCID: PMC11449017 DOI: 10.1093/neuonc/noae107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2024] [Indexed: 06/25/2024] Open
Abstract
The 2016 and 2021 World Health Organization 2021 Classification of central nervous system tumors have resulted in a major improvement in the classification of isocitrate dehydrogenase (IDH)-mutant gliomas. With more effective treatments many patients experience prolonged survival. However, treatment guidelines are often still based on information from historical series comprising both patients with IDH wild-type and IDH-mutant tumors. They provide recommendations for radiotherapy and chemotherapy for so-called high-risk patients, usually based on residual tumor after surgery and age over 40. More up-to-date studies give a better insight into clinical, radiological, and molecular factors associated with the outcome of patients with IDH-mutant glioma. These insights should be used today for risk stratification and for treatment decisions. In many patients with IDH-mutant grades 2 and 3 glioma, if carefully monitored postponing radiotherapy and chemotherapy is safe, and will not jeopardize the overall outcome of patients. With the INDIGO trial showing patient benefit from the IDH inhibitor vorasidenib, there is a sizable population in which it seems reasonable to try this class of agents before recommending radio-chemotherapy with its delayed adverse event profile affecting quality of survival. Ongoing trials should help to further identify the patients that are benefiting from this treatment.
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Affiliation(s)
| | - Pim J French
- Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Daniel Brat
- Department of Pathology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Joerg C Tonn
- Department of Neurosurgery, Ludwig-Maximilians-University, Munich, Germany
- German Cancer Consortium (DKTK), Partner Site Munich, Germany
| | - Mehdi Touat
- Department of Neurology, Brigham and Women’s Hospital, Boston, Massachusetts, USA
- Sorbonne Université, Inserm, CNRS, UMR S 1127, Institut du Cerveau, Paris Brain Institute, ICM, AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Service de Neurologie 2-Mazarin, Paris, France
| | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory, Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, USA
| | - Robert J Young
- Neuroradiology Service, Department of Radiology, Memorial Sloan Kettering Cancer, New York, New York, USA
| | - Johan Pallud
- Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, IMA-Brain, Université Paris Cité, Paris, France
- Service de Neurochirurgie, GHU-Paris Psychiatrie et Neurosciences, Site Sainte Anne, Paris, France
| | - Andreas von Deimling
- Department of Neuropathology, University Hospital Medicine and CCU Neuropathology, German Consortium for Translational Cancer Research (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Felix Sahm
- Department of Neuropathology, University Hospital Medicine and CCU Neuropathology, German Consortium for Translational Cancer Research (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Dominique Figarella Branger
- DFB Aix-Marseille Univ, APHM, CNRS, INP, Inst Neurophysiopathol, CHU Timone, Service d’Anatomie Pathologique et de Neuropathologie, Marseille, France
| | - Raymond Y Huang
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Michael Weller
- Department of Neurology & Brain Tumor Center, University Hospital Zurich & University of Zurich, Zurich, Switzerland
| | - Ingo K Mellinghoff
- Department of Neurology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Tim F Cloughsey
- Department of Neurology, TC David Geffen School of Medicine at UCLA, Los Angeles, USA
| | - Jason T Huse
- Departments of Pathology and Translational Molecular Pathology, University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Kenneth Aldape
- Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Guido Reifenberger
- Institute of Neuropathology, Medical Faculty, Heinrich Heine University and University Hospital Düsseldorf, and German Cancer Consortium (DKTK), Partner Site Essen/Düsseldorf, Düsseldorf, Germany
| | - Gilbert Youssef
- Center For Neuro-Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts, USA
| | - Philipp Karschnia
- German Cancer Consortium (DKTK), Partner Site Munich, Germany
- Department of Neurosurgery, Ludwig-Maximilians-University, Munich, Germany
| | - Houtan Noushmehr
- Department of Neurosurgery, Henry Ford Hospital+Michigan State University, Detroit, Michigan, USA
| | - Katherine B Peters
- Department of Neurosurgery, Preston Robert Tisch Brain Tumor Center, Duke University, Durham, North Carolina, USA
| | - Francois Ducray
- Inserm U1052, CNRS UMR5286, Université Claude Bernard Lyon, Lyon, France
- Hospices Civils de Lyon, Service de neuro-oncologie, LabEx Dev2CAN, Centre de Recherche en Cancérologie de Lyon, France
| | - Matthias Preusser
- Department of Medicine I, Division of Oncology, Medical University of Vienna, Vienna, Austria
| | - Patrick Y Wen
- Center For Neuro-Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts, USA
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Batool SM, Escobedo AK, Hsia T, Ekanayake E, Khanna SK, Gamblin AS, Zheng H, Skog J, Miller JJ, Stemmer-Rachamimov AO, Cahill DP, Balaj L, Carter BS. Clinical utility of a blood based assay for the detection of IDH1.R132H-mutant gliomas. Nat Commun 2024; 15:7074. [PMID: 39152110 PMCID: PMC11329733 DOI: 10.1038/s41467-024-51332-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2024] [Accepted: 08/05/2024] [Indexed: 08/19/2024] Open
Abstract
Glioma represents the most common central nervous system neoplasm in adults. Current classification scheme utilizes molecular alterations, particularly IDH1.R132H, to stratify lesions into distinct prognostic groups. Identification of the single nucleotide variant through traditional tissue biopsy assessment poses procedural risks and does not fully reflect the heterogeneous and evolving tumor landscape. Here, we introduce a liquid biopsy assay, mt-IDH1dx. The blood-based test allows minimally invasive detection of tumor-derived extracellular vesicle RNA using only 2 ml plasma volume. We perform rigorous, blinded validation testing across the study population (n = 133), comprising of IDH1.R132H patients (n = 80), IDH1 wild-type gliomas (n = 44), and age matched healthy controls (n = 9). Results from our plasma testing demonstrate an overall sensitivity of 75.0% (95% CI: 64.1%-84.0%), specificity 88.7% (95% CI: 77.0%-95.7%), positive predictive value 90.9%, and negative predictive value 70.1% compared to the tissue gold standard. In addition to fundamental diagnostic applications, the study also highlights the utility of mt-IDH1dx platform for blood-based monitoring and surveillance, offering valuable prognostic information. Finally, the optimized workflow enables rapid and efficient completion of both tumor tissue and plasma testing in under 4 hours from the time of sampling.
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Affiliation(s)
- Syeda Maheen Batool
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Ana K Escobedo
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Tiffaney Hsia
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Emil Ekanayake
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Sirena K Khanna
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Austin S Gamblin
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Hui Zheng
- Center for Biostatistics, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Johan Skog
- Exosome Diagnostics, a Bio-Techne Brand, Waltham, MA, USA
| | - Julie J Miller
- Translational Neuro-Oncology Laboratory, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Center for Neuro-Oncology, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Daniel P Cahill
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Leonora Balaj
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
| | - Bob S Carter
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
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Pons-Escoda A, Naval-Baudin P, Viveros M, Flores-Casaperalta S, Martinez-Zalacaín I, Plans G, Vidal N, Cos M, Majos C. DSC-PWI presurgical differentiation of grade 4 astrocytoma and glioblastoma in young adults: rCBV percentile analysis across enhancing and non-enhancing regions. Neuroradiology 2024; 66:1267-1277. [PMID: 38834877 PMCID: PMC11246293 DOI: 10.1007/s00234-024-03385-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 05/29/2024] [Indexed: 06/06/2024]
Abstract
PURPOSE The presurgical discrimination of IDH-mutant astrocytoma grade 4 from IDH-wildtype glioblastoma is crucial for patient management, especially in younger adults, aiding in prognostic assessment, guiding molecular diagnostics and surgical planning, and identifying candidates for IDH-targeted trials. Despite its potential, the full capabilities of DSC-PWI remain underexplored. This research evaluates the differentiation ability of relative-cerebral-blood-volume (rCBV) percentile values for the enhancing and non-enhancing tumor regions compared to the more commonly used mean or maximum preselected rCBV values. METHODS This retrospective study, spanning 2016-2023, included patients under 55 years (age threshold based on World Health Organization recommendations) with grade 4 astrocytic tumors and known IDH status, who underwent presurgical MR with DSC-PWI. Enhancing and non-enhancing regions were 3D-segmented to calculate voxel-level rCBV, deriving mean, maximum, and percentile values. Statistical analyses were conducted using the Mann-Whitney U test and AUC-ROC. RESULTS The cohort consisted of 59 patients (mean age 46; 34 male): 11 astrocytoma-4 and 48 glioblastoma. While glioblastoma showed higher rCBV in enhancing regions, the differences were not significant. However, non-enhancing astrocytoma-4 regions displayed notably higher rCBV, particularly in lower percentiles. The 30th rCBV percentile for non-enhancing regions was 0.705 in astrocytoma-4, compared to 0.458 in glioblastoma (p = 0.001, AUC-ROC = 0.811), outperforming standard mean and maximum values. CONCLUSION Employing an automated percentile-based approach for rCBV selection enhances differentiation capabilities, with non-enhancing regions providing more insightful data. Elevated rCBV in lower percentiles of non-enhancing astrocytoma-4 is the most distinguishable characteristic and may indicate lowly vascularized infiltrated edema, contrasting with glioblastoma's pure edema.
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Affiliation(s)
- Albert Pons-Escoda
- Radiology Department, Hospital Universitari de Bellvitge, Barcelona, Spain.
- Neuro-oncology Unit, Institut d'Investigació Biomèdica de Bellvitge- IDIBELL, Barcelona, Spain.
- Facultat de Medicina i Ciències de La Salut, Universitat de Barcelona (UB), Barcelona, Spain.
| | - Pablo Naval-Baudin
- Radiology Department, Hospital Universitari de Bellvitge, Barcelona, Spain
- Facultat de Medicina i Ciències de La Salut, Universitat de Barcelona (UB), Barcelona, Spain
- Diagnostic Imaging and Nuclear Medicine Research Group, Institut d'Investigació Biomèdica de Bellvitge- IDIBELL, Barcelona, Spain
| | - Mildred Viveros
- Radiology Department, Hospital Universitari de Bellvitge, Barcelona, Spain
| | | | - Ignacio Martinez-Zalacaín
- Radiology Department, Hospital Universitari de Bellvitge, Barcelona, Spain
- Diagnostic Imaging and Nuclear Medicine Research Group, Institut d'Investigació Biomèdica de Bellvitge- IDIBELL, Barcelona, Spain
| | - Gerard Plans
- Neuro-oncology Unit, Institut d'Investigació Biomèdica de Bellvitge- IDIBELL, Barcelona, Spain
- Neurosurgery Department, Hospital Universitari de Bellvitge, Barcelona, Spain
| | - Noemi Vidal
- Neuro-oncology Unit, Institut d'Investigació Biomèdica de Bellvitge- IDIBELL, Barcelona, Spain
- Pathology Department, Hospital Universitari de Bellvitge, Barcelona, Spain
| | - Monica Cos
- Radiology Department, Hospital Universitari de Bellvitge, Barcelona, Spain
| | - Carles Majos
- Radiology Department, Hospital Universitari de Bellvitge, Barcelona, Spain
- Neuro-oncology Unit, Institut d'Investigació Biomèdica de Bellvitge- IDIBELL, Barcelona, Spain
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7
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Lavrador JP, Mirallave-Pescador A, Soumpasis C, Díaz Baamonde A, Aliaga-Arias J, Baig Mirza A, Patel S, David Siado Mosquera J, Gullan R, Ashkan K, Bhangoo R, Vergani F. Transcranial Magnetic Stimulation-Based Machine Learning Prediction of Tumor Grading in Motor-Eloquent Gliomas. Neurosurgery 2024; 95:347-356. [PMID: 38511960 DOI: 10.1227/neu.0000000000002902] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2023] [Accepted: 01/04/2024] [Indexed: 03/22/2024] Open
Abstract
BACKGROUND Navigated transcranial magnetic stimulation (nTMS) is a well-established preoperative mapping tool for motor-eloquent glioma surgery. Machine learning (ML) and nTMS may improve clinical outcome prediction and histological correlation. METHODS This was a retrospective cohort study of patients who underwent surgery for motor-eloquent gliomas between 2018 and 2022. Ten healthy subjects were included. Preoperative nTMS-derived variables were collected: resting motor threshold (RMT), interhemispheric RMT ratio (iRMTr)-abnormal if above 10%-and cortical excitability score-number of abnormal iRMTrs. World Health Organization (WHO) grade and molecular profile were collected to characterize each tumor. ML models were fitted to the data after statistical feature selection to predict tumor grade. RESULTS A total of 177 patients were recruited: WHO grade 2-32 patients, WHO grade 3-65 patients, and WHO grade 4-80 patients. For the upper limb, abnormal iRMTr were identified in 22.7% of WHO grade 2, 62.5% of WHO grade 3, and 75.4% of WHO grade 4 patients. For the lower limb, iRMTr was abnormal in 23.1% of WHO grade 2, 67.6% of WHO grade 3%, and 63.6% of WHO grade 4 patients. Cortical excitability score ( P = .04) was statistically significantly related with WHO grading. Using these variables as predictors, the ML model had an accuracy of 0.57 to predict WHO grade 4 lesions. In subgroup analysis of high-grade gliomas vs low-grade gliomas, the accuracy for high-grade gliomas prediction increased to 0.83. The inclusion of molecular data into the model-IDH mutation and 1p19q codeletion status-increases the accuracy of the model in predicting tumor grading (0.95 and 0.74, respectively). CONCLUSION ML algorithms based on nTMS-derived interhemispheric excitability assessment provide accurate predictions of HGGs affecting the motor pathway. Their accuracy is further increased when molecular data are fitted onto the model paving the way for a joint preoperative approach with radiogenomics.
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Affiliation(s)
- José Pedro Lavrador
- Department of Neurosurgery, King's College Hospital Foundation Trust, London , UK
| | - Ana Mirallave-Pescador
- Department of Neurosurgery, King's College Hospital Foundation Trust, London , UK
- Department of Clinical Neurophysiology, King's College Hospital Foundation Trust, London , UK
| | - Christos Soumpasis
- Department of Neurosurgery, King's College Hospital Foundation Trust, London , UK
| | - Alba Díaz Baamonde
- Department of Neurosurgery, King's College Hospital Foundation Trust, London , UK
- Department of Clinical Neurophysiology, King's College Hospital Foundation Trust, London , UK
| | - Jahard Aliaga-Arias
- Department of Neurosurgery, King's College Hospital Foundation Trust, London , UK
| | - Asfand Baig Mirza
- Department of Neurosurgery, King's College Hospital Foundation Trust, London , UK
| | - Sabina Patel
- Department of Neurosurgery, King's College Hospital Foundation Trust, London , UK
| | - José David Siado Mosquera
- Department of Neurosurgery, King's College Hospital Foundation Trust, London , UK
- Department of Clinical Neurophysiology, King's College Hospital Foundation Trust, London , UK
| | - Richard Gullan
- Department of Neurosurgery, King's College Hospital Foundation Trust, London , UK
| | - Keyoumars Ashkan
- Department of Neurosurgery, King's College Hospital Foundation Trust, London , UK
| | - Ranjeev Bhangoo
- Department of Neurosurgery, King's College Hospital Foundation Trust, London , UK
| | - Francesco Vergani
- Department of Neurosurgery, King's College Hospital Foundation Trust, London , UK
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Lee DY, Choi KE, Han K, Choi SH, Lee N, Ahn SS, Chang JH, Kim SH, Lee SK, Park YW. Revisiting oligodendroglioma grading in the 2021 WHO classification: calcification and larger contrast-enhancing tumor volume may predict higher oligodendroglioma grade. Neuroradiology 2024:10.1007/s00234-024-03430-y. [PMID: 39014271 DOI: 10.1007/s00234-024-03430-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2024] [Accepted: 07/09/2024] [Indexed: 07/18/2024]
Abstract
PURPOSE To investigate whether qualitative and quantitative imaging phenotypes can predict the grade of oligodendroglioma. METHODS Retrospective chart and imaging reviews were conducted on 180 adults with oligodendroglioma (IDH-mutant and 1p/19q codeleted) between 2005 and 2021. Qualitative imaging characteristics including tumor location, calcification, gliomatosis cerebri, cystic change, necrosis, and infiltrative pattern were analyzed. Quantitative imaging assessment was performed from the tumor mask via automatic segmentation to calculate total, contrast-enhancing (CE), non-enhancing (NE), and necrotic tumor volumes. Logistic analyses were conducted to determine predictors of oligodendroglioma grade. RESULTS This study included 180 patients (84 [46.7%] with grade 2 and 96 [53.3%] with grade 3 oligodendrogliomas), with a median age of 42 years (range 23-76 years), comprising 91 females and 89 males. On univariable analysis, calcification (odds ratio [OR] = 6.00, P < 0.001), necrosis (OR = 21.84, P = 0.003), presence of CE tumor (OR = 7.86, P < 0.001), larger total (OR = 1.01, P < 0.001), larger CE (OR = 2.22, P = 0.010), and larger NE (OR = 1.01, P < 0.001) tumor volumes were predictors of grade 3 oligodendroglioma. On multivariable analysis, calcification (OR = 3.79, P < 0.001) and larger CE tumor volume (OR = 2.70, P = 0.043) remained as independent predictors of grade 3 oligodendroglioma. The multivariable model exhibited an AUC, accuracy, sensitivity, specificity of 0.78 (95% confidence interval 0.72-0.84), 72.8%, 79.2%, 69.1%, respectively. CONCLUSION Presence of calcification and larger CE tumor volume may serve as useful imaging biomarkers for prediction of oligodendroglioma grade. CLINICAL RELEVANCE STATEMENT Assessment of intratumoral calcification and CE tumor volume may facilitate accurate preoperative estimation of oligodendroglioma grade. Presence of intratumoral calcification and larger contrast-enhancing tumor volume were the significant predictors of higher grade oligodendroglioma based on the 2021 WHO classification.
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Affiliation(s)
- Doo Young Lee
- Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Republic of Korea
| | - Ka Eum Choi
- Department of Statistics and Data Science, Yonsei University, Seoul, Korea
| | - Kyunghwa Han
- Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Republic of Korea
| | - Seo Hee Choi
- Department of Radiation Oncology, Yonsei University College of Medicine, Seoul, Korea
| | - Narae Lee
- Department of Nuclear Medicine, Catholic University of Korea Seoul St. Mary's Hospital, Seoul, Korea
| | - Sung Soo Ahn
- Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Republic of Korea
| | - Jong Hee Chang
- Department of Neurosurgery, Yonsei University College of Medicine, Seoul, Korea
| | - Se Hoon Kim
- Department of Pathology, Yonsei University College of Medicine, Seoul, Korea
| | - Seung-Koo Lee
- Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Republic of Korea
| | - Yae Won Park
- Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Republic of Korea.
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9
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Wang Y, Xing H, Guo X, Chen W, Wang Y, Liang T, Wang H, Li Y, Jin S, Shi Y, Liu D, Yang T, Xia Y, Li J, Wu J, Liu Q, Qu T, Guo S, Li H, Zhang K, Wang Y, Ma W. Clinical features, MRI, molecular alternations, and prognosis of astrocytoma based on WHO 2021 classification of central nervous system tumors: A single-center retrospective study. Cancer Med 2024; 13:e7369. [PMID: 38970209 PMCID: PMC11226410 DOI: 10.1002/cam4.7369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 05/19/2024] [Accepted: 05/27/2024] [Indexed: 07/08/2024] Open
Abstract
BACKGROUND The diagnosis of glioma has advanced since the release of the WHO 2021 classification with more molecular alterations involved in the integrated diagnostic pathways. Our study aimed to present our experience with the clinical features and management of astrocytoma, IDH mutant based on the latest WHO classification. METHODS Patients diagnosed with astrocytoma, IDH-mutant based on the WHO 5th edition classification of CNS tumors at our center from January 2009 to January 2022 were included. Patients were divided into WHO 2-3 grade group and WHO 4 grade group. Integrate diagnoses were retrospectively confirmed according to WHO 2016 and 2021 classification. Clinical and MRI characteristics were reviewed, and survival analysis was performed. RESULTS A total of 60 patients were enrolled. 21.67% (13/60) of all patients changed tumor grade from WHO 4th edition classification to WHO 5th edition. Of these, 21.43% (6/28) of grade II astrocytoma and 58.33% (7/12) of grade III astrocytoma according to WHO 4th edition classification changed to grade 4 according to WHO 5th edition classification. Sex (p = 0.042), recurrent glioma (p = 0.006), and Ki-67 index (p < 0.001) of pathological examination were statistically different in the WHO grade 2-3 group (n = 27) and WHO grade 4 group (n = 33). CDK6 (p = 0.004), FGFR2 (p = 0.003), and MYC (p = 0.004) alterations showed an enrichment in the WHO grade 4 group. Patients with higher grade showed shorter mOS (mOS = 75.9 m, 53.6 m, 26.4 m for grade 2, 3, and 4, respectively, p = 0.01). CONCLUSIONS Patients diagnosed as WHO grade 4 according to the 5th edition WHO classification based on molecular alterations are more likely to have poorer prognosis. Therefore, treatment should be tailored to their individual needs. Further research is needed for the management of IDH-mutant astrocytoma is needed in the future.
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Affiliation(s)
- Yuekun Wang
- Department of Neurosurgery, Center for Malignant Brain Tumors, National Glioma MDT AlliancePeking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Hao Xing
- Department of Neurosurgery, Center for Malignant Brain Tumors, National Glioma MDT AlliancePeking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Xiaopeng Guo
- Department of Neurosurgery, Center for Malignant Brain Tumors, National Glioma MDT AlliancePeking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- China Anti‐Cancer Association Specialty Committee of GliomaBeijingChina
| | - Wenlin Chen
- Department of Neurosurgery, Center for Malignant Brain Tumors, National Glioma MDT AlliancePeking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Yaning Wang
- Department of Neurosurgery, Center for Malignant Brain Tumors, National Glioma MDT AlliancePeking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Tingyu Liang
- Department of Neurosurgery, Center for Malignant Brain Tumors, National Glioma MDT AlliancePeking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Hai Wang
- Department of Neurosurgery, Center for Malignant Brain Tumors, National Glioma MDT AlliancePeking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Yilin Li
- Department of Neurosurgery, Center for Malignant Brain Tumors, National Glioma MDT AlliancePeking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- '4+4' Medical Doctor ProgramChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Shanmu Jin
- Department of Neurosurgery, Center for Malignant Brain Tumors, National Glioma MDT AlliancePeking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- '4+4' Medical Doctor ProgramChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Yixin Shi
- Department of Neurosurgery, Center for Malignant Brain Tumors, National Glioma MDT AlliancePeking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- Eight‐year Medical Doctor ProgramChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Delin Liu
- Department of Neurosurgery, Center for Malignant Brain Tumors, National Glioma MDT AlliancePeking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- Eight‐year Medical Doctor ProgramChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Tianrui Yang
- Department of Neurosurgery, Center for Malignant Brain Tumors, National Glioma MDT AlliancePeking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- Eight‐year Medical Doctor ProgramChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Yu Xia
- Department of Neurosurgery, Center for Malignant Brain Tumors, National Glioma MDT AlliancePeking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- Eight‐year Medical Doctor ProgramChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Junlin Li
- Department of Neurosurgery, Center for Malignant Brain Tumors, National Glioma MDT AlliancePeking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- Eight‐year Medical Doctor ProgramChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Jiaming Wu
- Department of Neurosurgery, Center for Malignant Brain Tumors, National Glioma MDT AlliancePeking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- Eight‐year Medical Doctor ProgramChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Qianshu Liu
- Department of Neurosurgery, Center for Malignant Brain Tumors, National Glioma MDT AlliancePeking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- Eight‐year Medical Doctor ProgramChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Tian Qu
- Department of Neurosurgery, Center for Malignant Brain Tumors, National Glioma MDT AlliancePeking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- Eight‐year Medical Doctor ProgramChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Siying Guo
- Department of Neurosurgery, Center for Malignant Brain Tumors, National Glioma MDT AlliancePeking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- Tsinghua University Ringgold standard institution School of Medicine, Tsinghua UniversityBeijingChina
| | - Huanzhang Li
- Department of Neurosurgery, Center for Malignant Brain Tumors, National Glioma MDT AlliancePeking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- Eight‐year Medical Doctor ProgramChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Kun Zhang
- Department of Neurosurgery, Center for Malignant Brain Tumors, National Glioma MDT AlliancePeking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- Eight‐year Medical Doctor ProgramChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Yu Wang
- Department of Neurosurgery, Center for Malignant Brain Tumors, National Glioma MDT AlliancePeking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- China Anti‐Cancer Association Specialty Committee of GliomaBeijingChina
| | - Wenbin Ma
- Department of Neurosurgery, Center for Malignant Brain Tumors, National Glioma MDT AlliancePeking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- China Anti‐Cancer Association Specialty Committee of GliomaBeijingChina
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Pons-Escoda A, Majos C, Smits M, Oleaga L. Presurgical diagnosis of diffuse gliomas in adults: Post-WHO 2021 practical perspectives from radiologists in neuro-oncology units. RADIOLOGIA 2024; 66:260-277. [PMID: 38908887 DOI: 10.1016/j.rxeng.2024.03.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Accepted: 10/31/2023] [Indexed: 06/24/2024]
Abstract
The 2021 World Health Organization classification of CNS tumours was greeted with enthusiasm as well as an initial potential overwhelm. However, with time and experience, our understanding of its key aspects has notably improved. Using our collective expertise gained in neuro-oncology units in hospitals in different countries, we have compiled a practical guide for radiologists that clarifies the classification criteria for diffuse gliomas in adults. Its format is clear and concise to facilitate its incorporation into everyday clinical practice. The document includes a historical overview of the classifications and highlights the most important recent additions. It describes the main types in detail with an emphasis on their appearance on imaging. The authors also address the most debated issues in recent years. It will better prepare radiologists to conduct accurate presurgical diagnoses and collaborate effectively in clinical decision making, thus impacting decisions on treatment, prognosis, and overall patient care.
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Affiliation(s)
- A Pons-Escoda
- Radiology Department, Hospital Universitari de Bellvitge, Barcelona, Spain; Facultat de Medicina i Ciencies de La Salut, Universitat de Barcelona (UB), Barcelona, Spain.
| | - C Majos
- Radiology Department, Hospital Universitari de Bellvitge, Barcelona, Spain; Neuro-Oncology Unit, Institut d'Investigació Biomèdica de Bellvitge-IDIBELL, Barcelona, Spain; Diagnostic Imaging and Nuclear Medicine Research Group, Institut d'Investigació Biomèdica de Bellvitge-IDIBELL, Barcelona, Spain
| | - M Smits
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands; Erasmus MC Cancer Institute, Erasmus MC, Rotterdam, The Netherlands; Medical Delta, Delft, The Netherlands
| | - L Oleaga
- Radiology Department, Hospital Clínic Barcelona, Barcelona, Spain
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11
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She Y, Liu X, Jiang J, Wang X, Niu Q, Zhou J. The role of apparent diffusion coefficient in the grading of adult isocitrate dehydrogenase-mutant astrocytomas: relationship with the Ki-67 proliferation index. Acta Radiol 2024; 65:489-498. [PMID: 38644751 DOI: 10.1177/02841851241242653] [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: 04/23/2024]
Abstract
BACKGROUND The grading of adult isocitrate dehydrogenase (IDH)-mutant astrocytomas is a crucial prognostic factor. PURPOSE To investigate the value of conventional magnetic resonance imaging (MRI) features and apparent diffusion coefficient (ADC) in the grading of adult IDH-mutant astrocytomas, and to analyze the correlation between ADC and the Ki-67 proliferation index. MATERIAL AND METHODS The clinical and MRI data of 82 patients with adult IDH-mutant astrocytoma who underwent surgical resection and molecular genetic testing with IDH and 1p/19q were retrospectively analyzed. The conventional MRI features, ADCmin, ADCmean, and nADC of the tumors were compared using the Kruskal-Wallis single factor ANOVA and chi-square tests. Receiver operating characteristic (ROC) curves were drawn to evaluate conventional MRI and ADC accuracy in differentiating tumor grades. Pearson correlation analysis was performed to determine the correlation between ADC and the Ki-67 proliferation index. RESULTS The difference in enhancement, ADCmin, ADCmean, and nADC among WHO grade 2, 3, and 4 tumors was statistically significant (all P <0.05). ADCmin showed the preferable diagnostic accuracy for grading WHO grade 2 and 3 tumors (AUC=0.724, sensitivity=63.4%, specificity=80%, positive predictive value (PPV)=62.0%; negative predictive value (NPV)=82.5%), and distinguishing grade 3 from grade 4 tumors (AUC=0.764, sensitivity=70%, specificity=76.2%, PPV=75.0%, NPV=71.4%). Enhancement + ADC model showed an optimal predictive accuracy (grade 2 vs. 3: AUC = 0.759; grade 3 vs. 4: AUC = 0.799). The Ki-67 proliferation index was negatively correlated with ADCmin, ADCmean, and nADC (all P <0.05), and positively correlated with tumor grade. CONCLUSION Conventional MRI features and ADC are valuable to predict pathological grading of adult IDH-mutant astrocytomas.
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Affiliation(s)
- Yingxia She
- Radiology of Department, Lanzhou University Second Hospital, Lanzhou, PR China
- Key Laboratory of Medical Imaging of Gansu Province, Lanzhou University Second Hospital, Lanzhou, PR China
- Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou University Second Hospital, Lanzhou, PR China
| | - Xianwang Liu
- Radiology of Department, Lanzhou University Second Hospital, Lanzhou, PR China
- Key Laboratory of Medical Imaging of Gansu Province, Lanzhou University Second Hospital, Lanzhou, PR China
- Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou University Second Hospital, Lanzhou, PR China
| | - Jian Jiang
- Radiology of Department, Lanzhou University Second Hospital, Lanzhou, PR China
- Key Laboratory of Medical Imaging of Gansu Province, Lanzhou University Second Hospital, Lanzhou, PR China
- Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou University Second Hospital, Lanzhou, PR China
| | - Xuwen Wang
- Radiology of Department, Lanzhou University Second Hospital, Lanzhou, PR China
- Key Laboratory of Medical Imaging of Gansu Province, Lanzhou University Second Hospital, Lanzhou, PR China
- Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou University Second Hospital, Lanzhou, PR China
| | - Qian Niu
- Pathology of Department, Lanzhou University Second Hospital, Lanzhou, PR China
| | - Junlin Zhou
- Radiology of Department, Lanzhou University Second Hospital, Lanzhou, PR China
- Key Laboratory of Medical Imaging of Gansu Province, Lanzhou University Second Hospital, Lanzhou, PR China
- Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou University Second Hospital, Lanzhou, PR China
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Nafe R, Porto L, Samp PF, You SJ, Hattingen E. Adult-type and Pediatric-type Diffuse Gliomas : What the Neuroradiologist Should Know. Clin Neuroradiol 2023; 33:611-624. [PMID: 36941392 PMCID: PMC10449995 DOI: 10.1007/s00062-023-01277-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Accepted: 02/03/2023] [Indexed: 03/22/2023]
Abstract
The classification of diffuse gliomas into the adult type and the pediatric type is the new basis for the diagnosis and clinical evaluation. The knowledge for the neuroradiologist should not remain limited to radiological aspects but should be based additionally on the current edition of the World Health Organization (WHO) classification of tumors of the central nervous system (CNS). This classification defines the 11 entities of diffuse gliomas, which are included in the 3 large groups of adult-type diffuse gliomas, pediatric-type diffuse low-grade gliomas, and pediatric-type diffuse high-grade gliomas. This article provides a detailed overview of important molecular, morphological, and clinical aspects for all 11 entities, such as typical genetic alterations, age distribution, variability of the tumor localization, variability of histopathological and radiological findings within each entity, as well as currently available statistical information on prognosis and outcome. Important differential diagnoses are also discussed.
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Affiliation(s)
- Reinhold Nafe
- Dept. Neuroradiology, Clinics of Johann Wolfgang-Goethe University, Schleusenweg 2-16, 60528, Frankfurt am Main, Germany.
| | - Luciana Porto
- Dept. Neuroradiology, Clinics of Johann Wolfgang-Goethe University, Schleusenweg 2-16, 60528, Frankfurt am Main, Germany
| | - Patrick-Felix Samp
- Dept. Neuroradiology, Clinics of Johann Wolfgang-Goethe University, Schleusenweg 2-16, 60528, Frankfurt am Main, Germany
| | - Se-Jong You
- Dept. Neuroradiology, Clinics of Johann Wolfgang-Goethe University, Schleusenweg 2-16, 60528, Frankfurt am Main, Germany
| | - Elke Hattingen
- Dept. Neuroradiology, Clinics of Johann Wolfgang-Goethe University, Schleusenweg 2-16, 60528, Frankfurt am Main, Germany
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13
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Picca A, Bruno F, Nichelli L, Sanson M, Rudà R. Advances in molecular and imaging biomarkers in lower-grade gliomas. Expert Rev Neurother 2023; 23:1217-1231. [PMID: 37982735 DOI: 10.1080/14737175.2023.2285472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Accepted: 11/15/2023] [Indexed: 11/21/2023]
Abstract
INTRODUCTION Lower-grade (grade 2-3) gliomas (LGGs) constitutes a group of primary brain tumors with variable clinical behaviors and treatment responses. Recent advancements in molecular biology have redefined their classification, and novel imaging modalities emerged for the noninvasive diagnosis and follow-up. AREAS COVERED This review comprehensively analyses the current knowledge on molecular and imaging biomarkers in LGGs. Key molecular alterations, such as IDH mutations and 1p/19q codeletion, are discussed for their prognostic and predictive implications in guiding treatment decisions. Moreover, the authors explore theranostic biomarkers for the potential of tailored therapies. Additionally, they also describe the utility of advanced imaging modalities, including widely available techniques, as dynamic susceptibility contrast perfusion-weighted imaging and less validated, emerging approaches, for the noninvasive LGGs characterization and follow-up. EXPERT OPINION The integration of molecular markers enhanced the stratification of LGGs, leading to the new concept of integrated histomolecular classification. While the IDH mutation is an established key prognostic and predictive marker, recent results from IDH inhibitors trials showed its potential value as a theranostic marker. In this setting, advanced MRI techniques such as 2-D-hydroxyglutarate spectroscopy are very promising for the noninvasive diagnosis and monitoring of LGGs. This progress offers exciting prospects for personalized medicine and improved treatment outcomes in LGGs.
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Affiliation(s)
- Alberto Picca
- Service de Neurologie 2 Mazarin, Hôpital Universitaire Pitié-Salpêtrière, AP-HP, Paris, France
- Sorbonne Université, Inserm, CNRS, UMRS1127, Institut du Cerveau-Paris Brain Institute-ICM, AP-HP, Paris, France
| | - Francesco Bruno
- Division of Neuro-Oncology, Department of Neuroscience "Rita Levi Montalcini", University and City of Health and Science University Hospital, Turin, Italy
| | - Lucia Nichelli
- Service de Neuroradiologie, Hôpital Universitaire Pitié-Salpêtrière, AP-HP, Paris, France
| | - Marc Sanson
- Service de Neurologie 2 Mazarin, Hôpital Universitaire Pitié-Salpêtrière, AP-HP, Paris, France
- Sorbonne Université, Inserm, CNRS, UMRS1127, Institut du Cerveau-Paris Brain Institute-ICM, AP-HP, Paris, France
| | - Roberta Rudà
- Division of Neuro-Oncology, Department of Neuroscience "Rita Levi Montalcini", University and City of Health and Science University Hospital, Turin, Italy
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Griessmair M, Delbridge C, Ziegenfeuter J, Bernhardt D, Gempt J, Schmidt-Graf F, Kertels O, Thomas M, Meyer HS, Zimmer C, Meyer B, Combs SE, Yakushev I, Wiestler B, Metz MC. Imaging the WHO 2021 Brain Tumor Classification: Fully Automated Analysis of Imaging Features of Newly Diagnosed Gliomas. Cancers (Basel) 2023; 15:2355. [PMID: 37190283 PMCID: PMC10136825 DOI: 10.3390/cancers15082355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2023] [Revised: 03/13/2023] [Accepted: 04/14/2023] [Indexed: 05/17/2023] Open
Abstract
BACKGROUND The fifth version of the World Health Organization (WHO) classification of tumors of the central nervous system (CNS) in 2021 brought substantial changes. Driven by the enhanced implementation of molecular characterization, some diagnoses were adapted while others were newly introduced. How these changes are reflected in imaging features remains scarcely investigated. MATERIALS AND METHODS We retrospectively analyzed 226 treatment-naive primary brain tumor patients from our institution who received extensive molecular characterization by epigenome-wide methylation microarray and were diagnosed according to the 2021 WHO brain tumor classification. From multimodal preoperative 3T MRI scans, we extracted imaging metrics via a fully automated, AI-based image segmentation and processing pipeline. Subsequently, we examined differences in imaging features between the three main glioma entities (glioblastoma, astrocytoma, and oligodendroglioma) and particularly investigated new entities such as astrocytoma, WHO grade 4. RESULTS Our results confirm prior studies that found significantly higher median CBV (p = 0.00003, ANOVA) and lower median ADC in contrast-enhancing areas of glioblastomas, compared to astrocytomas and oligodendrogliomas (p = 0.41333, ANOVA). Interestingly, molecularly defined glioblastoma, which usually does not contain contrast-enhancing areas, also shows significantly higher CBV values in the non-enhancing tumor than common glioblastoma and astrocytoma grade 4 (p = 0.01309, ANOVA). CONCLUSIONS This work provides extensive insights into the imaging features of gliomas in light of the new 2021 WHO CNS tumor classification. Advanced imaging shows promise in visualizing tumor biology and improving the diagnosis of brain tumor patients.
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Affiliation(s)
- Michael Griessmair
- Department of Neuroradiology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
| | - Claire Delbridge
- Department of Pathology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
| | - Julian Ziegenfeuter
- Department of Neuroradiology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
| | - Denise Bernhardt
- Department of Radiation Oncology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
| | - Jens Gempt
- Department of Neurosurgery, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany
| | | | - Olivia Kertels
- Department of Neuroradiology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
| | - Marie Thomas
- Department of Neuroradiology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
| | - Hanno S. Meyer
- Department of Neurosurgery, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany
| | - Claus Zimmer
- Department of Neuroradiology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
| | - Bernhard Meyer
- Department of Neurosurgery, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
| | - Stephanie E. Combs
- Department of Radiation Oncology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
| | - Igor Yakushev
- Department of Nuclear Medicine, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
| | - Benedikt Wiestler
- Department of Neuroradiology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
- TranslaTUM, TU Munich, 81675 Munich, Germany
| | - Marie-Christin Metz
- Department of Neuroradiology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
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Ke X, Zhao J, Liu X, Zhou Q, Cheng W, Zhang P, Zhou J. Apparent diffusion coefficient values effectively predict cell proliferation and determine oligodendroglioma grade. Neurosurg Rev 2023; 46:83. [PMID: 37022533 DOI: 10.1007/s10143-023-01989-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Revised: 02/27/2023] [Accepted: 03/27/2023] [Indexed: 04/07/2023]
Abstract
This study aims to evaluate the value of conventional magnetic resonance imaging (MRI) features and apparent diffusion coefficient (ADC) values in differentiating oligodendroglioma of various grades and explore the correlation between ADC and Ki-67. The preoperative MRI data of 99 patients with World Health Organization (WHO) grades 2 (n = 42) and 3 (n = 57) oligodendroglioma confirmed by surgery and pathology were retrospectively analyzed. Conventional MRI features, ADCmean, ADCmin, and normalized ADC (nADC) were compared between the two groups. A receiver operating characteristic curve was used to evaluate each parameter's diagnostic efficacy in differentiating the two tumor types. Each tumor's Ki-67 proliferation index was also measured to explore its relationship with the ADC value. Compared with WHO2 grade tumors, WHO3 grade tumors had a larger maximum diameter and more significant cystic degeneration/necrosis, edema, and moderate/severe enhancement (all P < 0.05). The ADCmin, ADCmean, and nADC values of the WHO3 and WHO2 grade tumors were significantly different, and the ADCmin value most accurately distinguished the two tumor types, yielding an area under the curve value of 0.980. When 0.96 × 10-3 mm2/s was used as the differential diagnosis threshold, the sensitivity, specificity, and accuracy of the two groups were 100%, 93.00%, and 96.96%, respectively. The ADCmin (r = -0.596), ADCmean (r = - 0.590), nADC (r = - 0.577), and Ki-67 proliferation index values had significantly negative correlations (all P < 0.05). Conventional MRI features and ADC values are beneficial in the noninvasive prediction of the WHO grade and tumor proliferation rate of oligodendroglioma.
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Affiliation(s)
- Xiaoai Ke
- Department of Radiology, Lanzhou University Second Hospital, Chengguan District, Cuiyingmen No.82, Lanzhou, 730030, Gansu, People's Republic of China
- Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, China
- Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, China
| | - Jun Zhao
- Department of Radiology, Lanzhou University Second Hospital, Chengguan District, Cuiyingmen No.82, Lanzhou, 730030, Gansu, People's Republic of China
- Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, China
- Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, China
- Second Clinical School, Lanzhou University, Lanzhou, China
| | - Xianwang Liu
- Department of Radiology, Lanzhou University Second Hospital, Chengguan District, Cuiyingmen No.82, Lanzhou, 730030, Gansu, People's Republic of China
- Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, China
- Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, China
- Second Clinical School, Lanzhou University, Lanzhou, China
| | - Qing Zhou
- Department of Radiology, Lanzhou University Second Hospital, Chengguan District, Cuiyingmen No.82, Lanzhou, 730030, Gansu, People's Republic of China
- Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, China
- Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, China
- Second Clinical School, Lanzhou University, Lanzhou, China
| | - Wen Cheng
- Department of Radiology, Lanzhou University Second Hospital, Chengguan District, Cuiyingmen No.82, Lanzhou, 730030, Gansu, People's Republic of China
- Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, China
- Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, China
| | - Peng Zhang
- Department of Pathology, Lanzhou University Second Hospital, Lanzhou, Gansu, China
| | - Junlin Zhou
- Department of Radiology, Lanzhou University Second Hospital, Chengguan District, Cuiyingmen No.82, Lanzhou, 730030, Gansu, People's Republic of China.
- Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, China.
- Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, China.
- Second Clinical School, Lanzhou University, Lanzhou, China.
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Willman M, Willman J, Figg J, Dioso E, Sriram S, Olowofela B, Chacko K, Hernandez J, Lucke-Wold B. Update for astrocytomas: medical and surgical management considerations. EXPLORATION OF NEUROSCIENCE 2023:1-26. [PMID: 36935776 PMCID: PMC10019464 DOI: 10.37349/en.2023.00009] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 12/10/2022] [Indexed: 02/25/2023]
Abstract
Astrocytomas include a wide range of tumors with unique mutations and varying grades of malignancy. These tumors all originate from the astrocyte, a star-shaped glial cell that plays a major role in supporting functions of the central nervous system (CNS), including blood-brain barrier (BBB) development and maintenance, water and ion regulation, influencing neuronal synaptogenesis, and stimulating the immunological response. In terms of epidemiology, glioblastoma (GB), the most common and malignant astrocytoma, generally occur with higher rates in Australia, Western Europe, and Canada, with the lowest rates in Southeast Asia. Additionally, significantly higher rates of GB are observed in males and non-Hispanic whites. It has been suggested that higher levels of testosterone observed in biological males may account for the increased rates of GB. Hereditary syndromes such as Cowden, Lynch, Turcot, Li-Fraumeni, and neurofibromatosis type 1 have been linked to increased rates of astrocytoma development. While there are a number of specific gene mutations that may influence malignancy or be targeted in astrocytoma treatment, O6-methylguanine-DNA methyltransferase (MGMT) gene function is an important predictor of astrocytoma response to chemotherapeutic agent temozolomide (TMZ). TMZ for primary and bevacizumab in the setting of recurrent tumor formation are two of the main chemotherapeutic agents currently approved in the treatment of astrocytomas. While stereotactic radiosurgery (SRS) has debatable implications for increased survival in comparison to whole-brain radiotherapy (WBRT), SRS demonstrates increased precision with reduced radiation toxicity. When considering surgical resection of astrocytoma, the extent of resection (EoR) is taken into consideration. Subtotal resection (STR) spares the margins of the T1 enhanced magnetic resonance imaging (MRI) region, gross total resection (GTR) includes the margins, and supramaximal resection (SMR) extends beyond the margin of the T1 and into the T2 region. Surgical resection, radiation, and chemotherapy are integral components of astrocytoma treatment.
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Affiliation(s)
- Matthew Willman
- College of Medicine, University of Florida, Gainesville, FL 32610, USA
| | - Jonathan Willman
- College of Medicine, University of Florida, Gainesville, FL 32610, USA
| | - John Figg
- College of Medicine, University of Florida, Gainesville, FL 32610, USA
| | - Emma Dioso
- School of Medicine, University of Utah, Salt Lake City, UT 84132, USA
| | - Sai Sriram
- College of Medicine, University of Florida, Gainesville, FL 32610, USA
| | - Bankole Olowofela
- College of Medicine, University of Florida, Gainesville, FL 32610, USA
| | - Kevin Chacko
- College of Medicine, University of Florida, Gainesville, FL 32610, USA
| | - Jairo Hernandez
- College of Medicine, University of Florida, Gainesville, FL 32610, USA
| | - Brandon Lucke-Wold
- Department of Neurosurgery, University of Florida, Gainesville, FL 32608, USA
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