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Śledzińska P, Furtak J, Bebyn M, Serafin Z. Beyond conventional imaging: Advancements in MRI for glioma malignancy prediction and molecular profiling. Magn Reson Imaging 2024:S0730-725X(24)00175-9. [PMID: 38914147 DOI: 10.1016/j.mri.2024.06.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Revised: 05/20/2024] [Accepted: 06/20/2024] [Indexed: 06/26/2024]
Abstract
This review examines the advancements in magnetic resonance imaging (MRI) techniques and their pivotal role in diagnosing and managing gliomas, the most prevalent primary brain tumors. The paper underscores the importance of integrating modern MRI modalities, such as diffusion-weighted imaging and perfusion MRI, which are essential for assessing glioma malignancy and predicting tumor behavior. Special attention is given to the 2021 WHO Classification of Tumors of the Central Nervous System, emphasizing the integration of molecular diagnostics in glioma classification, significantly impacting treatment decisions. The review also explores radiogenomics, which correlates imaging features with molecular markers to tailor personalized treatment strategies. Despite technological progress, MRI protocol standardization and result interpretation challenges persist, affecting diagnostic consistency across different settings. Furthermore, the review addresses MRI's capacity to distinguish between tumor recurrence and pseudoprogression, which is vital for patient management. The necessity for greater standardization and collaborative research to harness MRI's full potential in glioma diagnosis and personalized therapy is highlighted, advocating for an enhanced understanding of glioma biology and more effective treatment approaches.
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Affiliation(s)
- Paulina Śledzińska
- Department of Radiology, 10th Military Research Hospital and Polyclinic, 85-681 Bydgoszcz, Poland.
| | - Jacek Furtak
- Department of Clinical Medicine, Faculty of Medicine, University of Science and Technology, , Bydgoszcz, Poland; Department of Neurosurgery, 10th Military Research Hospital and Polyclinic, 85-681 Bydgoszcz, Poland
| | - Marek Bebyn
- Department of Neurosurgery, 10th Military Research Hospital and Polyclinic, 85-681 Bydgoszcz, Poland
| | - Zbigniew Serafin
- Department of Radiology and Diagnostic Imaging, Nicolaus Copernicus University, Collegium Medicum, Bydgoszcz, Poland
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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 2024:10.1007/s00234-024-03385-0. [PMID: 38834877 DOI: 10.1007/s00234-024-03385-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 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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Cadrien C, Sharma S, Lazen P, Licandro R, Furtner J, Lipka A, Niess E, Hingerl L, Motyka S, Gruber S, Strasser B, Kiesel B, Mischkulnig M, Preusser M, Roetzer-Pejrimovsky T, Wöhrer A, Weber M, Dorfer C, Trattnig S, Rössler K, Bogner W, Widhalm G, Hangel G. 7 Tesla magnetic resonance spectroscopic imaging predicting IDH status and glioma grading. Cancer Imaging 2024; 24:67. [PMID: 38802883 PMCID: PMC11129458 DOI: 10.1186/s40644-024-00704-9] [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: 09/13/2023] [Accepted: 04/27/2024] [Indexed: 05/29/2024] Open
Abstract
INTRODUCTION With the application of high-resolution 3D 7 Tesla Magnetic Resonance Spectroscopy Imaging (MRSI) in high-grade gliomas, we previously identified intratumoral metabolic heterogeneities. In this study, we evaluated the potential of 3D 7 T-MRSI for the preoperative noninvasive classification of glioma grade and isocitrate dehydrogenase (IDH) status. We demonstrated that IDH mutation and glioma grade are detectable by ultra-high field (UHF) MRI. This technique might potentially optimize the perioperative management of glioma patients. METHODS We prospectively included 36 patients with WHO 2021 grade 2-4 gliomas (20 IDH mutated, 16 IDH wildtype). Our 7 T 3D MRSI sequence provided high-resolution metabolic maps (e.g., choline, creatine, glutamine, and glycine) of these patients' brains. We employed multivariate random forest and support vector machine models to voxels within a tumor segmentation, for classification of glioma grade and IDH mutation status. RESULTS Random forest analysis yielded an area under the curve (AUC) of 0.86 for multivariate IDH classification based on metabolic ratios. We distinguished high- and low-grade tumors by total choline (tCho) / total N-acetyl-aspartate (tNAA) ratio difference, yielding an AUC of 0.99. Tumor categorization based on other measured metabolic ratios provided comparable accuracy. CONCLUSIONS We successfully classified IDH mutation status and high- versus low-grade gliomas preoperatively based on 7 T MRSI and clinical tumor segmentation. With this approach, we demonstrated imaging based tumor marker predictions at least as accurate as comparable studies, highlighting the potential application of MRSI for pre-operative tumor classifications.
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Affiliation(s)
- Cornelius Cadrien
- Department of Biomedical Imaging and Image-Guided Therapy, High-Field MR Center, Medical University of Vienna, Vienna, Austria
- Department of Neurosurgery, Medical University of Vienna, Währinger Gürtel 18-20, Vienna, A-1090, Austria
| | - Sukrit Sharma
- Department of Biomedical Imaging and Image-Guided Therapy, High-Field MR Center, Medical University of Vienna, Vienna, Austria
| | - Philipp Lazen
- Department of Biomedical Imaging and Image-Guided Therapy, High-Field MR Center, Medical University of Vienna, Vienna, Austria
- Department of Neurosurgery, Medical University of Vienna, Währinger Gürtel 18-20, Vienna, A-1090, Austria
| | - Roxane Licandro
- A.A. Martinos Center for Biomedical Imaging, Laboratory for Computational Neuroimaging, Massachusetts General Hospital / Harvard Medical School, Charlestown, USA
- Department of Biomedical Imaging and Image-Guided Therapy, Computational Imaging Research Lab (CIR), Medical University of Vienna, Vienna, Austria
| | - Julia Furtner
- Division of Neuroradiology and Musculoskeletal Radiology, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
- Center for Medical Image Analysis and Artificial Intelligence (MIAAI), Danube Private University, Krems, Austria
| | - Alexandra Lipka
- Department of Biomedical Imaging and Image-Guided Therapy, High-Field MR Center, Medical University of Vienna, Vienna, Austria
| | - Eva Niess
- Department of Biomedical Imaging and Image-Guided Therapy, High-Field MR Center, Medical University of Vienna, Vienna, Austria
| | - Lukas Hingerl
- Department of Biomedical Imaging and Image-Guided Therapy, High-Field MR Center, Medical University of Vienna, Vienna, Austria
| | - Stanislav Motyka
- Department of Biomedical Imaging and Image-Guided Therapy, High-Field MR Center, Medical University of Vienna, Vienna, Austria
| | - Stephan Gruber
- Department of Biomedical Imaging and Image-Guided Therapy, High-Field MR Center, Medical University of Vienna, Vienna, Austria
| | - Bernhard Strasser
- Department of Biomedical Imaging and Image-Guided Therapy, High-Field MR Center, Medical University of Vienna, Vienna, Austria
| | - Barbara Kiesel
- Department of Neurosurgery, Medical University of Vienna, Währinger Gürtel 18-20, Vienna, A-1090, Austria
| | - Mario Mischkulnig
- Department of Neurosurgery, Medical University of Vienna, Währinger Gürtel 18-20, Vienna, A-1090, Austria
| | - Matthias Preusser
- Division of Oncology, Department of Internal Medicine I, Medical University of Vienna, Vienna, Austria
| | - Thomas Roetzer-Pejrimovsky
- Division of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Adelheid Wöhrer
- Division of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Michael Weber
- Department of Biomedical Imaging and Image-Guided Therapy, Computational Imaging Research Lab (CIR), Medical University of Vienna, Vienna, Austria
| | - Christian Dorfer
- Department of Neurosurgery, Medical University of Vienna, Währinger Gürtel 18-20, Vienna, A-1090, Austria
| | - Siegfried Trattnig
- Department of Biomedical Imaging and Image-Guided Therapy, High-Field MR Center, Medical University of Vienna, Vienna, Austria
- Institute for Clinical Molecular MRI, Karl Landsteiner Society, St. Pölten, Austria
- Christian Doppler Laboratory for MR Imaging Biomarkers, Vienna, Austria
| | - Karl Rössler
- Department of Neurosurgery, Medical University of Vienna, Währinger Gürtel 18-20, Vienna, A-1090, Austria
- Christian Doppler Laboratory for MR Imaging Biomarkers, Vienna, Austria
| | - Wolfgang Bogner
- Department of Biomedical Imaging and Image-Guided Therapy, High-Field MR Center, Medical University of Vienna, Vienna, Austria
- Christian Doppler Laboratory for MR Imaging Biomarkers, Vienna, Austria
| | - Georg Widhalm
- Department of Neurosurgery, Medical University of Vienna, Währinger Gürtel 18-20, Vienna, A-1090, Austria
| | - Gilbert Hangel
- Department of Biomedical Imaging and Image-Guided Therapy, High-Field MR Center, Medical University of Vienna, Vienna, Austria.
- Department of Neurosurgery, Medical University of Vienna, Währinger Gürtel 18-20, Vienna, A-1090, Austria.
- Christian Doppler Laboratory for MR Imaging Biomarkers, Vienna, Austria.
- Medical Imaging Cluster, Medical University of Vienna, Vienna, Austria.
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Rudà R, Horbinski C, van den Bent M, Preusser M, Soffietti R. IDH inhibition in gliomas: from preclinical models to clinical trials. Nat Rev Neurol 2024:10.1038/s41582-024-00967-7. [PMID: 38760442 DOI: 10.1038/s41582-024-00967-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/26/2024] [Indexed: 05/19/2024]
Abstract
Gliomas are the most common malignant primary brain tumours in adults and cannot usually be cured with standard cancer treatments. Gliomas show intratumoural and intertumoural heterogeneity at the histological and molecular levels, and they frequently contain mutations in the isocitrate dehydrogenase 1 (IDH1) or IDH2 gene. IDH-mutant adult-type diffuse gliomas are subdivided into grade 2, 3 or 4 IDH-mutant astrocytomas and grade 2 or 3 IDH-mutant, 1p19q-codeleted oligodendrogliomas. The product of the mutated IDH genes, D-2-hydroxyglutarate (D-2-HG), induces global DNA hypermethylation and interferes with immunity, leading to stimulation of tumour growth. Selective inhibitors of mutant IDH, such as ivosidenib and vorasidenib, have been shown to reduce D-2-HG levels and induce cellular differentiation in preclinical models and to induce MRI-detectable responses in early clinical trials. The phase III INDIGO trial has demonstrated superiority of vorasidenib, a brain-penetrant pan-mutant IDH inhibitor, over placebo in people with non-enhancing grade 2 IDH-mutant gliomas following surgery. In this Review, we describe the pathway of development of IDH inhibitors in IDH-mutant low-grade gliomas from preclinical models to clinical trials. We discuss the practice-changing implications of the INDIGO trial and consider new avenues of investigation in the field of IDH-mutant gliomas.
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Affiliation(s)
- Roberta Rudà
- Division of Neuro-Oncology, Department of Neuroscience 'Rita Levi Montalcini', University of Turin, Turin, Italy.
| | - Craig Horbinski
- Department of Pathology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Department of Neurological Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Martin van den Bent
- Brain Tumour Center at Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Matthias Preusser
- Division of Oncology, Department of Medicine I, Medical University of Vienna, Vienna, Austria
| | - Riccardo Soffietti
- Division of Neuro-Oncology, Department of Neuroscience 'Rita Levi Montalcini', University of Turin, Turin, Italy
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Bauer J, Raum HN, Kugel H, Müther M, Mannil M, Heindel W. 2-Hydroxyglutarate as an MR spectroscopic predictor of an IDH mutation in gliomas. ROFO-FORTSCHR RONTG 2024. [PMID: 38648790 DOI: 10.1055/a-2285-4923] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/25/2024]
Abstract
The mutated enzyme isocitrate dehydrogenase (IDH) 1 and 2 has been detected in various tumor entities such as gliomas and can convert α-ketoglutarate into the oncometabolite 2-hydroxyglutarate (2-HG). This neuro-oncologically significant metabolic product can be detected by MR spectroscopy and is therefore suitable for noninvasive glioma classification and therapy monitoring.This paper provides an up-to-date overview of the methodology and relevance of 1H-MR spectroscopy (MRS) in the oncological primary and follow-up diagnosis of gliomas. The possibilities and limitations of this MR spectroscopic examination are evaluated on the basis of the available literature.By detecting 2-HG, MRS can in principle offer a noninvasive alternative to immunohistological analysis thus avoiding surgical intervention in some cases. However, in addition to an adapted and optimized examination protocol, the individual measurement conditions in the examination region are of decisive importance. Due to the inherently small signal of 2-HG, unfavorable measurement conditions can influence the reliability of detection. · MR spectroscopy enables the non-invasive detection of 2-hydroxyglutarate.. · The measurement of this metabolite allows the detection of an IDH mutation in gliomas.. · The choice of MR examination method is particularly important.. · Detection reliability is influenced by glioma size, necrotic tissue and the existing measurement conditions.. · Bauer J, Raum HN, Kugel H et al. 2-Hydroxyglutarate as an MR spectroscopic predictor of an IDH mutation in gliomas. Fortschr Röntgenstr 2024; DOI 10.1055/a-2285-4923.
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Affiliation(s)
- Jochen Bauer
- Clinic for Radiology, University of Münster and University Hospital Münster, Münster, Germany
| | - Heiner N Raum
- Clinic for Radiology, University of Münster and University Hospital Münster, Münster, Germany
| | - Harald Kugel
- Clinic for Radiology, University of Münster and University Hospital Münster, Münster, Germany
| | - Michael Müther
- Department of Neurosurgery, University of Münster and University Hospital Münster, Münster, Germany
| | - Manoj Mannil
- Clinic for Radiology, University of Münster and University Hospital Münster, Münster, Germany
- Institute for Diagnostic and Interventional Radiology, Caritas Hospital Bad Mergentheim, Bad Mergentheim, Germany
| | - Walter Heindel
- Clinic for Radiology, University of Münster and University Hospital Münster, Münster, Germany
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Yasuda S, Yano H, Ikegame Y, Ikuta S, Maruyama T, Kumagai M, Muragaki Y, Iwama T, Shinoda J, Izumo T. Predicting Isocitrate Dehydrogenase Status in Non-Contrast-Enhanced Adult-Type Astrocytic Tumors Using Diffusion Tensor Imaging and 11C-Methionine, 11C-Choline, and 18F-Fluorodeoxyglucose PET. Cancers (Basel) 2024; 16:1543. [PMID: 38672625 PMCID: PMC11048577 DOI: 10.3390/cancers16081543] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2024] [Revised: 04/16/2024] [Accepted: 04/16/2024] [Indexed: 04/28/2024] Open
Abstract
We aimed to differentiate the isocitrate dehydrogenase (IDH) status among non-enhanced astrocytic tumors using preoperative MRI and PET. We analyzed 82 patients with non-contrast-enhanced, diffuse, supratentorial astrocytic tumors (IDH mutant [IDH-mut], 55 patients; IDH-wildtype [IDH-wt], 27 patients) who underwent MRI and PET between May 2012 and December 2022. We calculated the fractional anisotropy (FA) and mean diffusivity (MD) values using diffusion tensor imaging. We evaluated the tumor/normal brain uptake (T/N) ratios using 11C-methionine, 11C-choline, and 18F-fluorodeoxyglucose PET; extracted the parameters with significant differences in distinguishing the IDH status; and verified their diagnostic accuracy. Patients with astrocytomas were significantly younger than those with glioblastomas. The following MRI findings were significant predictors of IDH-wt instead of IDH-mut: thalamus invasion, contralateral cerebral hemisphere invasion, location adjacent to the ventricular walls, higher FA value, and lower MD value. The T/N ratio for all tracers was significantly higher for IDH-wt than for IDH-mut. In a composite diagnosis based on nine parameters, including age, 84.4% of cases with 0-4 points were of IDH-mut; conversely, 100% of cases with 6-9 points were of IDH-wt. Composite diagnosis using all parameters, including MRI and PET findings with significant differences, may help guide treatment decisions for early-stage gliomas.
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Affiliation(s)
- Shoji Yasuda
- Department of Neurosurgery, Chubu Medical Center for Prolonged Traumatic Brain Dysfunction, Minokamo 505-0034, Japan; (H.Y.); (Y.I.); (M.K.); (J.S.)
- Department of Neurosurgery, Chubu Neurorehabilitation Hospital, Minokamo 505-0034, Japan
- Department of Neurosurgery, Gifu University Graduate School of Medicine, Gifu 501-1194, Japan;
| | - Hirohito Yano
- Department of Neurosurgery, Chubu Medical Center for Prolonged Traumatic Brain Dysfunction, Minokamo 505-0034, Japan; (H.Y.); (Y.I.); (M.K.); (J.S.)
- Department of Neurosurgery, Chubu Neurorehabilitation Hospital, Minokamo 505-0034, Japan
- Department of Clinical Brain Sciences, Gifu University Graduate School of Medicine, Gifu 501-1194, Japan
| | - Yuka Ikegame
- Department of Neurosurgery, Chubu Medical Center for Prolonged Traumatic Brain Dysfunction, Minokamo 505-0034, Japan; (H.Y.); (Y.I.); (M.K.); (J.S.)
- Department of Neurosurgery, Chubu Neurorehabilitation Hospital, Minokamo 505-0034, Japan
| | - Soko Ikuta
- Department of Neurosurgery, Tokyo Women’s Medical University, Tokyo 162-8666, Japan; (S.I.); (T.M.); (Y.M.)
| | - Takashi Maruyama
- Department of Neurosurgery, Tokyo Women’s Medical University, Tokyo 162-8666, Japan; (S.I.); (T.M.); (Y.M.)
| | - Morio Kumagai
- Department of Neurosurgery, Chubu Medical Center for Prolonged Traumatic Brain Dysfunction, Minokamo 505-0034, Japan; (H.Y.); (Y.I.); (M.K.); (J.S.)
- Department of Neurosurgery, Chubu Neurorehabilitation Hospital, Minokamo 505-0034, Japan
| | - Yoshihiro Muragaki
- Department of Neurosurgery, Tokyo Women’s Medical University, Tokyo 162-8666, Japan; (S.I.); (T.M.); (Y.M.)
| | - Toru Iwama
- Department of Neurosurgery, Gifu Municipal Hospital, Gifu 500-8513, Japan;
| | - Jun Shinoda
- Department of Neurosurgery, Chubu Medical Center for Prolonged Traumatic Brain Dysfunction, Minokamo 505-0034, Japan; (H.Y.); (Y.I.); (M.K.); (J.S.)
- Department of Neurosurgery, Chubu Neurorehabilitation Hospital, Minokamo 505-0034, Japan
- Department of Clinical Brain Sciences, Gifu University Graduate School of Medicine, Gifu 501-1194, Japan
| | - Tsuyoshi Izumo
- Department of Neurosurgery, Gifu University Graduate School of Medicine, Gifu 501-1194, Japan;
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Yu M, Ge Y, Wang Z, Zhang Y, Hou X, Chen H, Chen X, Ji N, Li X, Shen H. The diagnostic efficiency of integration of 2HG MRS and IVIM versus individual parameters for predicting IDH mutation status in gliomas in clinical scenarios: A retrospective study. J Neurooncol 2024; 167:305-313. [PMID: 38424338 DOI: 10.1007/s11060-024-04609-2] [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: 01/15/2024] [Accepted: 02/16/2024] [Indexed: 03/02/2024]
Abstract
PURPOSE Currently, there remains a scarcity of established preoperative tests to accurately predict the isocitrate dehydrogenase (IDH) mutation status in clinical scenarios, with limited research has explored the potential synergistic diagnostic performance among metabolite, perfusion, and diffusion parameters. To address this issue, we aimed to develop an imaging protocol that integrated 2-hydroxyglutarate (2HG) magnetic resonance spectroscopy (MRS) and intravoxel incoherent motion (IVIM) by comprehensively assessing metabolic, cellular, and angiogenic changes caused by IDH mutations, and explored the diagnostic efficiency of this imaging protocol for predicting IDH mutation status in clinical scenarios. METHODS Patients who met the inclusion criteria were categorized into two groups: IDH-wild type (IDH-WT) group and IDH-mutant (IDH-MT) group. Subsequently, we quantified the 2HG concentration, the relative apparent diffusion coefficient (rADC), the relative true diffusion coefficient value (rD), the relative pseudo-diffusion coefficient (rD*) and the relative perfusion fraction value (rf). Intergroup differences were estimated using t-test and Mann-Whitney U test. Finally, we performed receiver operating characteristic (ROC) curve and DeLong's test to evaluate and compare the diagnostic performance of individual parameters and their combinations. RESULTS 64 patients (female, 21; male, 43; age, 47.0 ± 13.7 years) were enrolled. Compared with IDH-WT gliomas, IDH-MT gliomas had higher 2HG concentration, rADC and rD (P < 0.001), and lower rD* (P = 0.013). The ROC curve demonstrated that 2HG + rD + rD* exhibited the highest areas under curve (AUC) value (0.967, 95%CI 0.889-0.996) for discriminating IDH mutation status. Compared with each individual parameter, the predictive efficiency of 2HG + rADC + rD* and 2HG + rD + rD* shows a statistically significant enhancement (DeLong's test: P < 0.05). CONCLUSIONS The integration of 2HG MRS and IVIM significantly improves the diagnostic efficiency for predicting IDH mutation status in clinical scenarios.
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Affiliation(s)
- Meimei Yu
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, No.119 South Fourth Ring West Road, Fengtai District, Beijing, 100070, China
- Department of Radiology, The First People's Hospital of Longquanyi District, Chengdu, Sichuan Province, China
| | - Ying Ge
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, No.119 South Fourth Ring West Road, Fengtai District, Beijing, 100070, China
- Department of Radiology, Beijing Huimin Hospital, Beijing, China
| | - Zixuan Wang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yang Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xinyi Hou
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, No.119 South Fourth Ring West Road, Fengtai District, Beijing, 100070, China
| | - Hongyan Chen
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, No.119 South Fourth Ring West Road, Fengtai District, Beijing, 100070, China
| | - Xuzhu Chen
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, No.119 South Fourth Ring West Road, Fengtai District, Beijing, 100070, China
| | - Nan Ji
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xin Li
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Huicong Shen
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, No.119 South Fourth Ring West Road, Fengtai District, Beijing, 100070, China.
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Majós C, Pons-Escoda A, Naval P, Güell A, Lucas A, Vidal N, Cos M, Bruna J. Proton MR spectroscopy shows improved performance to segregate high-grade astrocytoma subgroups when defined with the new 2021 World Health Organization classification of central nervous system tumors. Eur Radiol 2024; 34:2174-2182. [PMID: 37740778 DOI: 10.1007/s00330-023-10138-9] [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: 04/18/2023] [Revised: 06/24/2023] [Accepted: 07/06/2023] [Indexed: 09/25/2023]
Abstract
OBJECTIVES The 2021 World Health Organization (WHO) classification of central nervous system (CNS) tumors prioritizes isocitrate dehydrogenase (IDH) mutation to define tumor types in diffuse gliomas, in contrast to the 2016 classification, which prioritized histological features. Our objective was to investigate the influence of this change in the performance of proton MR spectroscopy (1H-MRS) in segregating high-grade diffuse astrocytoma subgroups. METHODS Patients with CNS WHO grade 3 and 4 diffuse astrocytoma, known IDH mutation status, and available 1H-MRS were retrospectively retrieved and divided into 4 groups based on IDH mutation status and histological grade. Differences in 1H-MRS between groups were analyzed with the Kruskal-Wallis test. The points on the spectrum that showed the greatest differences were chosen to evaluate the performance of 1H-MRS in discriminating between grades 3 and 4 tumors (WHO 2016 defined), and between IDH-mutant and IDH-wildtype tumors (WHO 2021). ROC curves were constructed with these points, and AUC values were calculated and compared. RESULTS The study included 223 patients with high-grade diffuse astrocytoma. Discrimination between IDH-mutant and IDH-wildtype tumors showed higher AUC values (highest AUC short TE, 0.943; long TE, 0.864) and more noticeable visual differences than the discrimination between grade 3 and 4 tumors (short TE, 0.885; long TE, 0.838). CONCLUSION Our findings suggest that 1H-MRS is more applicable to classify high-grade astrocytomas defined with the 2021 criteria. Improved metabolomic robustness and more homogeneous groups yielded better tumor type discrimination by 1H-MRS with the new criteria. CLINICAL RELEVANCE STATEMENT The 2021 World Health Organization classification of brain tumors empowers molecular criteria to improve tumor characterization. This derives in greater segregation of high-grade diffuse astrocytoma subgroups by MR spectroscopy and warrants further development of brain tumor classification tools with spectroscopy. KEY POINTS • The new 2021 updated World Health Organization classification of central nervous system tumors maximizes the role of molecular diagnosis in the classification of brain tumors. • Proton MR spectroscopy performs better to segregate high-grade astrocytoma subgroups when defined with the new criteria. • The study provides additional evidence of improved metabolic characterization of brain tumor subgroups with the new criteria.
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Affiliation(s)
- Carles Majós
- Radiology Department, Institut deDiagnòstic Per LaImatge (IDI), Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat, Barcelona, Spain.
- Neurooncology Unit, Institutd'InvestigacióBiomèdica deBellvitge-IDIBELL, L'Hospitalet de Llobregat, Barcelona, Spain.
- Centro de Investigación Biomédica en Red, BioingenieríaBiomateriales y Nanomedicina (CIBER-BBN), Cerdanyola del Vallès, Spain.
| | - Albert Pons-Escoda
- Radiology Department, Institut deDiagnòstic Per LaImatge (IDI), Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat, Barcelona, Spain
- Neurooncology Unit, Institutd'InvestigacióBiomèdica deBellvitge-IDIBELL, L'Hospitalet de Llobregat, Barcelona, Spain
| | - Pablo Naval
- Radiology Department, Institut deDiagnòstic Per LaImatge (IDI), Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat, Barcelona, Spain
| | - Anna Güell
- Radiology Department, Institut deDiagnòstic Per LaImatge (IDI), Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat, Barcelona, Spain
| | - Anna Lucas
- Neurooncology Unit, Institutd'InvestigacióBiomèdica deBellvitge-IDIBELL, L'Hospitalet de Llobregat, Barcelona, Spain
- Radiation Oncology Department, Institut Català d'Oncologia (ICO), Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat, Barcelona, Spain
| | - Noemí Vidal
- Neurooncology Unit, Institutd'InvestigacióBiomèdica deBellvitge-IDIBELL, L'Hospitalet de Llobregat, Barcelona, Spain
- Pathology Department, Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat, Barcelona, Spain
| | - Mònica Cos
- Radiology Department, Institut deDiagnòstic Per LaImatge (IDI), Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat, Barcelona, Spain
| | - Jordi Bruna
- Neurooncology Unit, Institutd'InvestigacióBiomèdica deBellvitge-IDIBELL, L'Hospitalet de Llobregat, Barcelona, Spain
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Kasap DNG, Mora NGN, Blömer DA, Akkurt BH, Heindel WL, Mannil M, Musigmann M. Comparison of MRI Sequences to Predict IDH Mutation Status in Gliomas Using Radiomics-Based Machine Learning. Biomedicines 2024; 12:725. [PMID: 38672080 PMCID: PMC11048271 DOI: 10.3390/biomedicines12040725] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Revised: 02/24/2024] [Accepted: 03/21/2024] [Indexed: 04/28/2024] Open
Abstract
OBJECTIVES Regarding the 2021 World Health Organization (WHO) classification of central nervous system (CNS) tumors, the isocitrate dehydrogenase (IDH) mutation status is one of the most important factors for CNS tumor classification. The aim of our study is to analyze which of the commonly used magnetic resonance imaging (MRI) sequences is best suited to obtain this information non-invasively using radiomics-based machine learning models. We developed machine learning models based on different MRI sequences and determined which of the MRI sequences analyzed yields the highest discriminatory power in predicting the IDH mutation status. MATERIAL AND METHODS In our retrospective IRB-approved study, we used the MRI images of 106 patients with histologically confirmed gliomas. The MRI images were acquired using the T1 sequence with and without administration of a contrast agent, the T2 sequence, and the Fluid-Attenuated Inversion Recovery (FLAIR) sequence. To objectively compare performance in predicting the IDH mutation status as a function of the MRI sequence used, we included only patients in our study cohort for whom MRI images of all four sequences were available. Seventy-one of the patients had an IDH mutation, and the remaining 35 patients did not have an IDH mutation (IDH wild-type). For each of the four MRI sequences used, 107 radiomic features were extracted from the corresponding MRI images by hand-delineated regions of interest. Data partitioning into training data and independent test data was repeated 100 times to avoid random effects associated with the data partitioning. Feature preselection and subsequent model development were performed using Random Forest, Lasso regression, LDA, and Naïve Bayes. The performance of all models was determined with independent test data. RESULTS Among the different approaches we examined, the T1-weighted contrast-enhanced sequence was found to be the most suitable for predicting IDH mutations status using radiomics-based machine learning models. Using contrast-enhanced T1-weighted MRI images, our seven-feature model developed with Lasso regression achieved a mean area under the curve (AUC) of 0.846, a mean accuracy of 0.792, a mean sensitivity of 0.847, and a mean specificity of 0.681. The administration of contrast agents resulted in a significant increase in the achieved discriminatory power. CONCLUSIONS Our analyses show that for the prediction of the IDH mutation status using radiomics-based machine learning models, among the MRI images acquired with the commonly used MRI sequences, the contrast-enhanced T1-weighted images are the most suitable.
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Su X, Yang X, Sun H, Liu Y, Chen N, Li S, Huang Z, Shao H, Zhang S, Gong Q, Yue Q. Evaluation of Key Molecular Markers in Adult Diffuse Gliomas Based on a Novel Combination of Diffusion and Perfusion MRI and MR Spectroscopy. J Magn Reson Imaging 2024; 59:628-638. [PMID: 37246748 DOI: 10.1002/jmri.28793] [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: 03/08/2023] [Revised: 05/08/2023] [Accepted: 05/08/2023] [Indexed: 05/30/2023] Open
Abstract
BACKGROUND Preoperative identification of isocitrate dehydrogenase (IDH) mutation and 1p/19q codeletion status could help clinicians select the optimal therapy in patients with diffuse glioma. Although, the value of multimodal intersection was underutilized. PURPOSE To evaluate the value of quantitative MRI biomarkers for the identification of IDH mutation and 1p/19q codeletion in adult patients with diffuse glioma. STUDY TYPE Retrospective. POPULATION Two hundred sixteen adult diffuse gliomas with known genetic test results, divided into training (N = 130), test (N = 43), and validation (N = 43) groups. SEQUENCE/FIELD STRENGTH Diffusion/perfusion-weighted-imaging sequences and multivoxel MR spectroscopy (MRS), all 3.0 T using three different scanners. ASSESSMENT The apparent diffusion coefficient (ADC) and cerebral blood volume (CBV) of the core tumor were calculated to identify IDH-mutant and 1p/19q-codeleted statuses and to determine cut-off values. ADC models were built based on the 30th percentile and lower, CBV models were built based on the 75th centile and higher (both in five centile steps). The optimal tumor region was defined and the metabolite concentrations of MRS voxels that overlapped with the ADC/CBV optimal region were calculated and added to the best-performing diagnostic models. STATISTICAL TESTS DeLong's test, diagnostic test, and decision curve analysis were performed. A P value <0.05 was considered to be statistically significant. RESULTS Almost all ADC models achieved good performance in identifying IDH mutation status, among which ADC_15th was the most valuable parameter (threshold = 1.186; Youden index = 0.734; AUC_train = 0.896). The differential power of CBV histogram metrics for predicting 1p/19q codeletion outperformed ADC histogram metrics, and the CBV_80th-related model performed best (threshold = 1.435; Youden index = 0.458; AUC_train = 0.724). The AUCs of ADC_15th and CBV_80th models in the validation set were 0.857 and 0.733. These models tended to improve after incorporation of N-acetylaspartate/total_creatine and glutamate-plus-glutamine/total_creatine, respectively. DATA CONCLUSION The intersection of ADC-, CBV-based histogram and MRS provide a reliable paradigm for identifying the key molecular markers in adult diffuse gliomas. EVIDENCE LEVEL 3 TECHNICAL EFFICACY: Stage 3.
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Affiliation(s)
- Xiaorui Su
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
- Huaxi Glioma Center, West China Hospital of Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Xibiao Yang
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Huaiqiang Sun
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Yanhui Liu
- Huaxi Glioma Center, West China Hospital of Sichuan University, Chengdu, China
- Department of Neurosurgery, West China Hospital of Sichuan University, Chengdu, China
| | - Ni Chen
- Huaxi Glioma Center, West China Hospital of Sichuan University, Chengdu, China
- Department of Pathology, West China Hospital of Sichuan University, Chengdu, China
| | - Shuang Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Zongyao Huang
- Department of Pathology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, China
| | - Hanbing Shao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Simin Zhang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, Chengdu, China
- Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian, China
| | - Qiang Yue
- Huaxi Glioma Center, West China Hospital of Sichuan University, Chengdu, China
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
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11
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Wamelink IJHG, Azizova A, Booth TC, Mutsaerts HJMM, Ogunleye A, Mankad K, Petr J, Barkhof F, Keil VC. Brain Tumor Imaging without Gadolinium-based Contrast Agents: Feasible or Fantasy? Radiology 2024; 310:e230793. [PMID: 38319162 PMCID: PMC10902600 DOI: 10.1148/radiol.230793] [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: 03/29/2023] [Revised: 08/07/2023] [Accepted: 08/14/2023] [Indexed: 02/07/2024]
Abstract
Gadolinium-based contrast agents (GBCAs) form the cornerstone of current primary brain tumor MRI protocols at all stages of the patient journey. Though an imperfect measure of tumor grade, GBCAs are repeatedly used for diagnosis and monitoring. In practice, however, radiologists will encounter situations where GBCA injection is not needed or of doubtful benefit. Reducing GBCA administration could improve the patient burden of (repeated) imaging (especially in vulnerable patient groups, such as children), minimize risks of putative side effects, and benefit costs, logistics, and the environmental footprint. On the basis of the current literature, imaging strategies to reduce GBCA exposure for pediatric and adult patients with primary brain tumors will be reviewed. Early postoperative MRI and fixed-interval imaging of gliomas are examples of GBCA exposure with uncertain survival benefits. Half-dose GBCAs for gliomas and T2-weighted imaging alone for meningiomas are among options to reduce GBCA use. While most imaging guidelines recommend using GBCAs at all stages of diagnosis and treatment, non-contrast-enhanced sequences, such as the arterial spin labeling, have shown a great potential. Artificial intelligence methods to generate synthetic postcontrast images from decreased-dose or non-GBCA scans have shown promise to replace GBCA-dependent approaches. This review is focused on pediatric and adult gliomas and meningiomas. Special attention is paid to the quality and real-life applicability of the reviewed literature.
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Affiliation(s)
- Ivar J. H. G. Wamelink
- From the Department of Radiology and Nuclear Medicine, Amsterdam
University Medical Center, VUMC Site, De Boelelaan 1117, Amsterdam 1081 HV, the
Netherlands (I.J.H.G.W., A.A., H.J.M.M.M., J.P., F.B., V.C.K.); Department of
Imaging and Biomarkers, Cancer Center Amsterdam, Amsterdam, the Netherlands
(I.J.H.G.W., A.A., H.J.M.M.M., V.C.K.); School of Biomedical Engineering and
Imaging Sciences, King’s College London, London, United Kingdom (T.C.B.);
Department of Neuroradiology, King’s College Hospital, NHS Foundation
Trust, London, UK (T.C.B.); Department of Brain Imaging, Amsterdam Neuroscience,
Amsterdam, the Netherlands (H.J.M.M.M., F.B., V.C.K.); Department of Radiology,
Lagos State University Teaching Hospital, Ikeja, Nigeria Radiology (A.O.);
Department of Radiology, Great Ormond Street Hospital for Children, NHS
Foundation Trust, London, United Kingdom (K.M.); Institute of
Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf,
Dresden, Germany (J.P.); and Queen Square Institute of Neurology and Centre for
Medical Image Computing, University College London, London, United Kingdom
(F.B.)
| | - Aynur Azizova
- From the Department of Radiology and Nuclear Medicine, Amsterdam
University Medical Center, VUMC Site, De Boelelaan 1117, Amsterdam 1081 HV, the
Netherlands (I.J.H.G.W., A.A., H.J.M.M.M., J.P., F.B., V.C.K.); Department of
Imaging and Biomarkers, Cancer Center Amsterdam, Amsterdam, the Netherlands
(I.J.H.G.W., A.A., H.J.M.M.M., V.C.K.); School of Biomedical Engineering and
Imaging Sciences, King’s College London, London, United Kingdom (T.C.B.);
Department of Neuroradiology, King’s College Hospital, NHS Foundation
Trust, London, UK (T.C.B.); Department of Brain Imaging, Amsterdam Neuroscience,
Amsterdam, the Netherlands (H.J.M.M.M., F.B., V.C.K.); Department of Radiology,
Lagos State University Teaching Hospital, Ikeja, Nigeria Radiology (A.O.);
Department of Radiology, Great Ormond Street Hospital for Children, NHS
Foundation Trust, London, United Kingdom (K.M.); Institute of
Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf,
Dresden, Germany (J.P.); and Queen Square Institute of Neurology and Centre for
Medical Image Computing, University College London, London, United Kingdom
(F.B.)
| | - Thomas C. Booth
- From the Department of Radiology and Nuclear Medicine, Amsterdam
University Medical Center, VUMC Site, De Boelelaan 1117, Amsterdam 1081 HV, the
Netherlands (I.J.H.G.W., A.A., H.J.M.M.M., J.P., F.B., V.C.K.); Department of
Imaging and Biomarkers, Cancer Center Amsterdam, Amsterdam, the Netherlands
(I.J.H.G.W., A.A., H.J.M.M.M., V.C.K.); School of Biomedical Engineering and
Imaging Sciences, King’s College London, London, United Kingdom (T.C.B.);
Department of Neuroradiology, King’s College Hospital, NHS Foundation
Trust, London, UK (T.C.B.); Department of Brain Imaging, Amsterdam Neuroscience,
Amsterdam, the Netherlands (H.J.M.M.M., F.B., V.C.K.); Department of Radiology,
Lagos State University Teaching Hospital, Ikeja, Nigeria Radiology (A.O.);
Department of Radiology, Great Ormond Street Hospital for Children, NHS
Foundation Trust, London, United Kingdom (K.M.); Institute of
Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf,
Dresden, Germany (J.P.); and Queen Square Institute of Neurology and Centre for
Medical Image Computing, University College London, London, United Kingdom
(F.B.)
| | - Henk J. M. M. Mutsaerts
- From the Department of Radiology and Nuclear Medicine, Amsterdam
University Medical Center, VUMC Site, De Boelelaan 1117, Amsterdam 1081 HV, the
Netherlands (I.J.H.G.W., A.A., H.J.M.M.M., J.P., F.B., V.C.K.); Department of
Imaging and Biomarkers, Cancer Center Amsterdam, Amsterdam, the Netherlands
(I.J.H.G.W., A.A., H.J.M.M.M., V.C.K.); School of Biomedical Engineering and
Imaging Sciences, King’s College London, London, United Kingdom (T.C.B.);
Department of Neuroradiology, King’s College Hospital, NHS Foundation
Trust, London, UK (T.C.B.); Department of Brain Imaging, Amsterdam Neuroscience,
Amsterdam, the Netherlands (H.J.M.M.M., F.B., V.C.K.); Department of Radiology,
Lagos State University Teaching Hospital, Ikeja, Nigeria Radiology (A.O.);
Department of Radiology, Great Ormond Street Hospital for Children, NHS
Foundation Trust, London, United Kingdom (K.M.); Institute of
Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf,
Dresden, Germany (J.P.); and Queen Square Institute of Neurology and Centre for
Medical Image Computing, University College London, London, United Kingdom
(F.B.)
| | - Afolabi Ogunleye
- From the Department of Radiology and Nuclear Medicine, Amsterdam
University Medical Center, VUMC Site, De Boelelaan 1117, Amsterdam 1081 HV, the
Netherlands (I.J.H.G.W., A.A., H.J.M.M.M., J.P., F.B., V.C.K.); Department of
Imaging and Biomarkers, Cancer Center Amsterdam, Amsterdam, the Netherlands
(I.J.H.G.W., A.A., H.J.M.M.M., V.C.K.); School of Biomedical Engineering and
Imaging Sciences, King’s College London, London, United Kingdom (T.C.B.);
Department of Neuroradiology, King’s College Hospital, NHS Foundation
Trust, London, UK (T.C.B.); Department of Brain Imaging, Amsterdam Neuroscience,
Amsterdam, the Netherlands (H.J.M.M.M., F.B., V.C.K.); Department of Radiology,
Lagos State University Teaching Hospital, Ikeja, Nigeria Radiology (A.O.);
Department of Radiology, Great Ormond Street Hospital for Children, NHS
Foundation Trust, London, United Kingdom (K.M.); Institute of
Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf,
Dresden, Germany (J.P.); and Queen Square Institute of Neurology and Centre for
Medical Image Computing, University College London, London, United Kingdom
(F.B.)
| | - Kshitij Mankad
- From the Department of Radiology and Nuclear Medicine, Amsterdam
University Medical Center, VUMC Site, De Boelelaan 1117, Amsterdam 1081 HV, the
Netherlands (I.J.H.G.W., A.A., H.J.M.M.M., J.P., F.B., V.C.K.); Department of
Imaging and Biomarkers, Cancer Center Amsterdam, Amsterdam, the Netherlands
(I.J.H.G.W., A.A., H.J.M.M.M., V.C.K.); School of Biomedical Engineering and
Imaging Sciences, King’s College London, London, United Kingdom (T.C.B.);
Department of Neuroradiology, King’s College Hospital, NHS Foundation
Trust, London, UK (T.C.B.); Department of Brain Imaging, Amsterdam Neuroscience,
Amsterdam, the Netherlands (H.J.M.M.M., F.B., V.C.K.); Department of Radiology,
Lagos State University Teaching Hospital, Ikeja, Nigeria Radiology (A.O.);
Department of Radiology, Great Ormond Street Hospital for Children, NHS
Foundation Trust, London, United Kingdom (K.M.); Institute of
Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf,
Dresden, Germany (J.P.); and Queen Square Institute of Neurology and Centre for
Medical Image Computing, University College London, London, United Kingdom
(F.B.)
| | - Jan Petr
- From the Department of Radiology and Nuclear Medicine, Amsterdam
University Medical Center, VUMC Site, De Boelelaan 1117, Amsterdam 1081 HV, the
Netherlands (I.J.H.G.W., A.A., H.J.M.M.M., J.P., F.B., V.C.K.); Department of
Imaging and Biomarkers, Cancer Center Amsterdam, Amsterdam, the Netherlands
(I.J.H.G.W., A.A., H.J.M.M.M., V.C.K.); School of Biomedical Engineering and
Imaging Sciences, King’s College London, London, United Kingdom (T.C.B.);
Department of Neuroradiology, King’s College Hospital, NHS Foundation
Trust, London, UK (T.C.B.); Department of Brain Imaging, Amsterdam Neuroscience,
Amsterdam, the Netherlands (H.J.M.M.M., F.B., V.C.K.); Department of Radiology,
Lagos State University Teaching Hospital, Ikeja, Nigeria Radiology (A.O.);
Department of Radiology, Great Ormond Street Hospital for Children, NHS
Foundation Trust, London, United Kingdom (K.M.); Institute of
Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf,
Dresden, Germany (J.P.); and Queen Square Institute of Neurology and Centre for
Medical Image Computing, University College London, London, United Kingdom
(F.B.)
| | - Frederik Barkhof
- From the Department of Radiology and Nuclear Medicine, Amsterdam
University Medical Center, VUMC Site, De Boelelaan 1117, Amsterdam 1081 HV, the
Netherlands (I.J.H.G.W., A.A., H.J.M.M.M., J.P., F.B., V.C.K.); Department of
Imaging and Biomarkers, Cancer Center Amsterdam, Amsterdam, the Netherlands
(I.J.H.G.W., A.A., H.J.M.M.M., V.C.K.); School of Biomedical Engineering and
Imaging Sciences, King’s College London, London, United Kingdom (T.C.B.);
Department of Neuroradiology, King’s College Hospital, NHS Foundation
Trust, London, UK (T.C.B.); Department of Brain Imaging, Amsterdam Neuroscience,
Amsterdam, the Netherlands (H.J.M.M.M., F.B., V.C.K.); Department of Radiology,
Lagos State University Teaching Hospital, Ikeja, Nigeria Radiology (A.O.);
Department of Radiology, Great Ormond Street Hospital for Children, NHS
Foundation Trust, London, United Kingdom (K.M.); Institute of
Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf,
Dresden, Germany (J.P.); and Queen Square Institute of Neurology and Centre for
Medical Image Computing, University College London, London, United Kingdom
(F.B.)
| | - Vera C. Keil
- From the Department of Radiology and Nuclear Medicine, Amsterdam
University Medical Center, VUMC Site, De Boelelaan 1117, Amsterdam 1081 HV, the
Netherlands (I.J.H.G.W., A.A., H.J.M.M.M., J.P., F.B., V.C.K.); Department of
Imaging and Biomarkers, Cancer Center Amsterdam, Amsterdam, the Netherlands
(I.J.H.G.W., A.A., H.J.M.M.M., V.C.K.); School of Biomedical Engineering and
Imaging Sciences, King’s College London, London, United Kingdom (T.C.B.);
Department of Neuroradiology, King’s College Hospital, NHS Foundation
Trust, London, UK (T.C.B.); Department of Brain Imaging, Amsterdam Neuroscience,
Amsterdam, the Netherlands (H.J.M.M.M., F.B., V.C.K.); Department of Radiology,
Lagos State University Teaching Hospital, Ikeja, Nigeria Radiology (A.O.);
Department of Radiology, Great Ormond Street Hospital for Children, NHS
Foundation Trust, London, United Kingdom (K.M.); Institute of
Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf,
Dresden, Germany (J.P.); and Queen Square Institute of Neurology and Centre for
Medical Image Computing, University College London, London, United Kingdom
(F.B.)
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Levis B, Snell KIE, Damen JAA, Hattle M, Ensor J, Dhiman P, Andaur Navarro CL, Takwoingi Y, Whiting PF, Debray TPA, Reitsma JB, Moons KGM, Collins GS, Riley RD. Risk of bias assessments in individual participant data meta-analyses of test accuracy and prediction models: a review shows improvements are needed. J Clin Epidemiol 2024; 165:111206. [PMID: 37925059 DOI: 10.1016/j.jclinepi.2023.10.022] [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: 07/24/2023] [Revised: 10/19/2023] [Accepted: 10/30/2023] [Indexed: 11/06/2023]
Abstract
OBJECTIVES Risk of bias assessments are important in meta-analyses of both aggregate and individual participant data (IPD). There is limited evidence on whether and how risk of bias of included studies or datasets in IPD meta-analyses (IPDMAs) is assessed. We review how risk of bias is currently assessed, reported, and incorporated in IPDMAs of test accuracy and clinical prediction model studies and provide recommendations for improvement. STUDY DESIGN AND SETTING We searched PubMed (January 2018-May 2020) to identify IPDMAs of test accuracy and prediction models, then elicited whether each IPDMA assessed risk of bias of included studies and, if so, how assessments were reported and subsequently incorporated into the IPDMAs. RESULTS Forty-nine IPDMAs were included. Nineteen of 27 (70%) test accuracy IPDMAs assessed risk of bias, compared to 5 of 22 (23%) prediction model IPDMAs. Seventeen of 19 (89%) test accuracy IPDMAs used Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2), but no tool was used consistently among prediction model IPDMAs. Of IPDMAs assessing risk of bias, 7 (37%) test accuracy IPDMAs and 1 (20%) prediction model IPDMA provided details on the information sources (e.g., the original manuscript, IPD, primary investigators) used to inform judgments, and 4 (21%) test accuracy IPDMAs and 1 (20%) prediction model IPDMA provided information or whether assessments were done before or after obtaining the IPD of the included studies or datasets. Of all included IPDMAs, only seven test accuracy IPDMAs (26%) and one prediction model IPDMA (5%) incorporated risk of bias assessments into their meta-analyses. For future IPDMA projects, we provide guidance on how to adapt tools such as Prediction model Risk Of Bias ASsessment Tool (for prediction models) and QUADAS-2 (for test accuracy) to assess risk of bias of included primary studies and their IPD. CONCLUSION Risk of bias assessments and their reporting need to be improved in IPDMAs of test accuracy and, especially, prediction model studies. Using recommended tools, both before and after IPD are obtained, will address this.
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Affiliation(s)
- Brooke Levis
- Centre for Prognosis Research, School of Medicine, Keele University, Keele, Staffordshire, UK; Centre for Clinical Epidemiology, Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Canada.
| | - Kym I E Snell
- Institute of Applied Health Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK; National Institute for Health and Care Research (NIHR) Birmingham Biomedical Research Centre, Birmingham, UK
| | - Johanna A A Damen
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Miriam Hattle
- Institute of Applied Health Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK; National Institute for Health and Care Research (NIHR) Birmingham Biomedical Research Centre, Birmingham, UK
| | - Joie Ensor
- Institute of Applied Health Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK; National Institute for Health and Care Research (NIHR) Birmingham Biomedical Research Centre, Birmingham, UK
| | - Paula Dhiman
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Constanza L Andaur Navarro
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Yemisi Takwoingi
- Institute of Applied Health Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK; National Institute for Health and Care Research (NIHR) Birmingham Biomedical Research Centre, Birmingham, UK
| | - Penny F Whiting
- School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Thomas P A Debray
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Johannes B Reitsma
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Karel G M Moons
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Gary S Collins
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Richard D Riley
- Institute of Applied Health Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK; National Institute for Health and Care Research (NIHR) Birmingham Biomedical Research Centre, Birmingham, UK.
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13
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Santos-Pinheiro F, Graber JJ. Neuro-oncology Treatment Strategies for Primary Glial Tumors. Semin Neurol 2023; 43:889-896. [PMID: 38096849 DOI: 10.1055/s-0043-1776764] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
Primary brain tumors underwent reclassification in the 2021 World Health Organization update, relying on molecular findings (especially isocitrate dehydrogenase mutations and chromosomal changes in 1p, 19q, gain of chromosome 7 and loss of chromosome 10). Newer entities have also been described including histone 3 mutant midline gliomas. These updated pathologic classifications improve prognostication and reliable diagnosis, but may confuse interpretation of prior clinical trials and require reclassification of patients diagnosed in the past. For patients over seventy, multiple studies have now confirmed the utility of shorter courses of radiation, and the risk of post-operative delirium. Ongoing studies are comparing proton to photon radiation. Long term follow up of prior clinical trials have confirmed the roles and length of chemotherapy (mainly temozolomide) in different tumors, as well as the wearable novottf device. New oral isocitrate dehydrogenase inhibitors have also shown efficacy in clinical trials.
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Affiliation(s)
| | - Jerome J Graber
- Department of Neurology and Neurosurgery, University of Washington, Alvord Brain Tumor Center, Seattle, Washington
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14
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de Godoy LL, Lim KC, Rajan A, Verma G, Hanaoka M, O’Rourke DM, Lee JYK, Desai A, Chawla S, Mohan S. Non-Invasive Assessment of Isocitrate Dehydrogenase-Mutant Gliomas Using Optimized Proton Magnetic Resonance Spectroscopy on a Routine Clinical 3-Tesla MRI. Cancers (Basel) 2023; 15:4453. [PMID: 37760422 PMCID: PMC10526791 DOI: 10.3390/cancers15184453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2023] [Revised: 08/22/2023] [Accepted: 08/31/2023] [Indexed: 09/29/2023] Open
Abstract
PURPOSE The isocitrate dehydrogenase (IDH) mutation has become one of the most important prognostic biomarkers in glioma management, indicating better treatment response and prognosis. IDH mutations confer neomorphic activity leading to the conversion of alpha-ketoglutarate (α-KG) to 2-hydroxyglutarate (2HG). The purpose of this study was to investigate the clinical potential of proton MR spectroscopy (1H-MRS) in identifying IDH-mutant gliomas by detecting characteristic resonances of 2HG and its complex interplay with other clinically relevant metabolites. MATERIALS AND METHODS Thirty-two patients with suspected infiltrative glioma underwent a single-voxel (SVS, n = 17) and/or single-slice-multivoxel (1H-MRSI, n = 15) proton MR spectroscopy (1H-MRS) sequence with an optimized echo-time (97 ms) on 3T-MRI. Spectroscopy data were analyzed using the linear combination (LC) model. Cramér-Rao lower bound (CRLB) values of <40% were considered acceptable for detecting 2HG and <20% for other metabolites. Immunohistochemical analyses for determining IDH mutational status were subsequently performed from resected tumor specimens and findings were compared with the results from spectral data. Mann-Whitney and chi-squared tests were performed to ascertain differences in metabolite levels between IDH-mutant and IDH-wild-type gliomas. Receiver operating characteristic (ROC) curve analyses were also performed. RESULTS Data from eight cases were excluded due to poor spectral quality or non-tumor-related etiology, and final data analyses were performed from 24 cases. Of these cases, 9/12 (75%) were correctly identified as IDH-mutant or IDH-wildtype gliomas through SVS and 10/12 (83%) through 1H-MRSI with an overall concordance rate of 79% (19/24). The sensitivity, specificity, positive predictive value, and negative predictive value were 80%, 77%, 86%, and 70%, respectively. The metabolite 2HG was found to be significant in predicting IDH-mutant gliomas through the chi-squared test (p < 0.01). The IDH-mutant gliomas also had a significantly higher NAA/Cr ratio (1.20 ± 0.09 vs. 0.75 ± 0.12 p = 0.016) and lower Glx/Cr ratio (0.86 ± 0.078 vs. 1.88 ± 0.66; p = 0.029) than those with IDH wild-type gliomas. The areas under the ROC curves for NAA/Cr and Glx/Cr were 0.808 and 0.786, respectively. CONCLUSIONS Noninvasive optimized 1H-MRS may be useful in predicting IDH mutational status and 2HG may serve as a valuable diagnostic and prognostic biomarker in patients with gliomas.
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Affiliation(s)
- Laiz Laura de Godoy
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA; (L.L.d.G.); (A.R.); (M.H.); (S.M.)
| | - Kheng Choon Lim
- Department of Neuroradiology, Singapore General Hospital, Singapore 169609, Singapore;
| | - Archith Rajan
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA; (L.L.d.G.); (A.R.); (M.H.); (S.M.)
| | - Gaurav Verma
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA;
| | - Mauro Hanaoka
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA; (L.L.d.G.); (A.R.); (M.H.); (S.M.)
| | - Donald M. O’Rourke
- Department of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA; (D.M.O.); (J.Y.K.L.)
- Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA;
- Glioblastoma Translational Center of Excellence, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19014, USA
| | - John Y. K. Lee
- Department of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA; (D.M.O.); (J.Y.K.L.)
- Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA;
- Glioblastoma Translational Center of Excellence, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19014, USA
| | - Arati Desai
- Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA;
- Glioblastoma Translational Center of Excellence, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19014, USA
| | - Sanjeev Chawla
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA; (L.L.d.G.); (A.R.); (M.H.); (S.M.)
| | - Suyash Mohan
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA; (L.L.d.G.); (A.R.); (M.H.); (S.M.)
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15
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Jahanshahi A, Salarinejad S, Oraee-Yazdani S, Chehresonboll Y, Morsali S, Jafarizadeh A, Falahatian M, Rahimi F, Jaberinezhad M. Gliomatosis cerebri with blindness: A case report with literature review. Radiol Case Rep 2023; 18:2884-2894. [PMID: 37388536 PMCID: PMC10300258 DOI: 10.1016/j.radcr.2023.05.037] [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: 03/16/2023] [Revised: 05/10/2023] [Accepted: 05/12/2023] [Indexed: 07/01/2023] Open
Abstract
Cerebral gliomatosis (GC) is a rare diffuse infiltrative growth pattern of glioma with nonspecific clinical manifestations like visual impairment that may involve bilateral temporal lobes. Herpes simplex encephalitis (HSE) and limbic encephalitis (LE) can also lead to temporal lobe involvement. Differentiating these entities is necessary for patients with misleading presentations and imaging findings. To the best of our knowledge, this is the third case of GC presenting with blindness. The patient was a 35 years-old male in a drug rehabilitation center for heroin addiction. He presented with a headache, a single episode of seizure, and a 2-month history of bilateral decrease in visual acuity, which had acutely worsened. Magnetic resonance imaging (MRI) and computed tomography (CT) showed bilateral temporal lobe involvement. Ophthalmological studies showed bilateral papilledema, absence of visual evoked potential, and thickening of the retinal nerve fiber layer. Due to this clinical presentation, normal laboratory data, and suspicious MRI findings, further investigation with magnetic resonance spectroscopy (MRS) was performed. Results showed a greatly increased ratio of choline to creatinine(Cr) or N-acetyl aspartate (NAA), suggesting a neoplastic nature of the disease. Subsequently, the patient was referred for a brain tissue biopsy with a suspicion of malignancy. The pathology results revealed adult-type diffuse glioma with isocitrate dehydrogenase (IDH) mutation. Bilateral blindness, as well as bilateral temporal lobe involvement, each has many different causes. However, as demonstrated in this study, adult-type diffuse glioma must be considered a rare cause of concomitant bilateral temporal lobe involvement and blindness.
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Affiliation(s)
- Amirreza Jahanshahi
- Department of Radiology, Emam Reza Hospital, Tabriz University of Medical Sciences, Tabriz, Iran
- Medical Radiation Sciences Research Group, Imam Reza Hosptial, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Sareh Salarinejad
- Department of Pathology, Faculty of Medicine, Shohada-e-Tajrish Hospital, Shahid Beheshti University of Medical Science, Tehran, Iran
| | - Saeed Oraee-Yazdani
- Functional Neurosurgery Research Center, Shohada Tajrish Comprehensive Neurosurgical Center of Excellence, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Yasaman Chehresonboll
- Department of Surgical and Clinical Pathology, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Soroush Morsali
- Neuroscience Research Center (NSRC), Tabriz University of Medical Sciences, Tabriz, Iran
| | - Ali Jafarizadeh
- Nikookari Eye Center, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Masih Falahatian
- Medical Radiation Sciences Research Group, Imam Reza Hosptial, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Faezeh Rahimi
- Department of Radiology, Zanjan University of Medical Sciences, Zanjan, Iran
| | - Mehran Jaberinezhad
- Clinical Research Development Unit of Tabriz Valiasr Hospital, Tabriz University of Medical Sciences, Tabriz, Iran
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16
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Park YW, Vollmuth P, Foltyn-Dumitru M, Sahm F, Ahn SS, Chang JH, Kim SH. The 2021 WHO Classification for Gliomas and Implications on Imaging Diagnosis: Part 1-Key Points of the Fifth Edition and Summary of Imaging Findings on Adult-Type Diffuse Gliomas. J Magn Reson Imaging 2023; 58:677-689. [PMID: 37069792 DOI: 10.1002/jmri.28743] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 03/31/2023] [Accepted: 04/03/2023] [Indexed: 04/19/2023] Open
Abstract
The fifth edition of the World Health Organization (WHO) classification of central nervous system tumors published in 2021 advances the role of molecular diagnostics in the classification of gliomas by emphasizing integrated diagnoses based on histopathology and molecular information and grouping tumors based on genetic alterations. Importantly, molecular biomarkers that provide important prognostic information are now a parameter for establishing tumor grades in gliomas. Understanding the 2021 WHO classification is crucial for radiologists for daily imaging interpretation as well as communication with clinicians. Although imaging features are not included in the 2021 WHO classification, imaging can serve as a powerful tool to impact the clinical practice not only prior to tissue confirmation but beyond. This review represents the first of a three-installment review series on the 2021 WHO classification for gliomas, glioneuronal tumors, and neuronal tumors and implications on imaging diagnosis. This Part 1 Review focuses on the major changes to the classification of gliomas and imaging findings on adult-type diffuse gliomas. EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 3.
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Affiliation(s)
- 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, Korea
| | - Philipp Vollmuth
- Section for Computational Neuroimaging, Department of Neuroradiology, Heidelberg University College of Medicine, Heidelberg, Germany
| | - Martha Foltyn-Dumitru
- Section for Computational Neuroimaging, Department of Neuroradiology, Heidelberg University College of Medicine, Heidelberg, Germany
| | - Felix Sahm
- Department of Neuropathology, Heidelberg University College of Medicine, Heidelberg, Germany
| | - 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, 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
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17
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Zhang H, Fan X, Zhang J, Wei Z, Feng W, Hu Y, Ni J, Yao F, Zhou G, Wan C, Zhang X, Wang J, Liu Y, You Y, Yu Y. Deep-learning and conventional radiomics to predict IDH genotyping status based on magnetic resonance imaging data in adult diffuse glioma. Front Oncol 2023; 13:1143688. [PMID: 37711207 PMCID: PMC10499353 DOI: 10.3389/fonc.2023.1143688] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Accepted: 08/17/2023] [Indexed: 09/16/2023] Open
Abstract
Objectives In adult diffuse glioma, preoperative detection of isocitrate dehydrogenase (IDH) status helps clinicians develop surgical strategies and evaluate patient prognosis. Here, we aim to identify an optimal machine-learning model for prediction of IDH genotyping by combining deep-learning (DL) signatures and conventional radiomics (CR) features as model predictors. Methods In this study, a total of 486 patients with adult diffuse gliomas were retrospectively collected from our medical center (n=268) and the public database (TCGA, n=218). All included patients were randomly divided into the training and validation sets by using nested 10-fold cross-validation. A total of 6,736 CR features were extracted from four MRI modalities in each patient, namely T1WI, T1CE, T2WI, and FLAIR. The LASSO algorithm was performed for CR feature selection. In each MRI modality, we applied a CNN+LSTM-based neural network to extract DL features and integrate these features into a DL signature after the fully connected layer with sigmoid activation. Eight classic machine-learning models were analyzed and compared in terms of their prediction performance and stability in IDH genotyping by combining the LASSO-selected CR features and integrated DL signatures as model predictors. In the validation sets, the prediction performance was evaluated by using accuracy and the area under the curve (AUC) of the receiver operating characteristics, while the model stability was analyzed by using the relative standard deviation of the AUC (RSDAUC). Subgroup analyses of DL signatures and CR features were also individually conducted to explore their independent prediction values. Results Logistic regression (LR) achieved favorable prediction performance (AUC: 0.920 ± 0.043, accuracy: 0.843 ± 0.044), whereas support vector machine with the linear kernel (l-SVM) displayed low prediction performance (AUC: 0.812 ± 0.052, accuracy: 0.821 ± 0.050). With regard to stability, LR also showed high robustness against data perturbation (RSDAUC: 4.7%). Subgroup analyses showed that DL signatures outperformed CR features (DL, AUC: 0.915 ± 0.054, accuracy: 0.835 ± 0.061, RSDAUC: 5.9%; CR, AUC: 0.830 ± 0.066, accuracy: 0.771 ± 0.051, RSDAUC: 8.0%), while DL and DL+CR achieved similar prediction results. Conclusion In IDH genotyping, LR is a promising machine-learning classification model. Compared with CR features, DL signatures exhibit markedly superior prediction values and discriminative capability.
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Affiliation(s)
- Hongjian Zhang
- Department of Medical Informatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Xiao Fan
- Department of Neurosurgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Junxia Zhang
- Department of Neurosurgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Zhiyuan Wei
- Department of Medical Informatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Wei Feng
- Department of Medical Informatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yifang Hu
- Department of Geriatric Endocrinology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Jiaying Ni
- Department of Medical Informatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Fushen Yao
- Department of Medical Informatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Gaoxin Zhou
- Department of Medical Informatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, China
- Institute of Medical Informatics and Management, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Cheng Wan
- Department of Medical Informatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, China
- Institute of Medical Informatics and Management, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Xin Zhang
- Department of Medical Informatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, China
- Institute of Medical Informatics and Management, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Junjie Wang
- Department of Medical Informatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, China
- Institute of Medical Informatics and Management, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yun Liu
- Department of Medical Informatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, China
- Institute of Medical Informatics and Management, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yongping You
- Department of Neurosurgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yun Yu
- Department of Medical Informatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, China
- Institute of Medical Informatics and Management, Nanjing Medical University, Nanjing, Jiangsu, China
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18
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van Dijken BRJ, Jeltema HR, Kłos J, van Laar PJ, Enting RH, Maatman RGHJ, Bijsterveld K, Den Dunnen WFA, Dierckx RA, Sijens PE, van der Hoorn A. The Correlation of In Vivo MR Spectroscopy and Ex Vivo 2-Hydroxyglutarate Concentration for the Prediction of Isocitrate Dehydrogenase Mutation Status in Diffuse Glioma. Diagnostics (Basel) 2023; 13:2791. [PMID: 37685329 PMCID: PMC10487112 DOI: 10.3390/diagnostics13172791] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 08/27/2023] [Accepted: 08/28/2023] [Indexed: 09/10/2023] Open
Abstract
Isocitrate dehydrogenase (IDH) mutation status is an important biomarker in the glioma-defining subtype and corresponding prognosis. This study proposes a straightforward method for 2-hydroxyglutarate (2-HG) quantification by MR spectroscopy for IDH mutation status detection and directly compares in vivo 2-HG MR spectroscopy with ex vivo 2-HG concentration measured in resected tumor tissue. Eleven patients with suspected lower-grade glioma (ten IDH1; one IDHwt) were prospectively included. Preoperatively, 3T point-resolved spectroscopy (PRESS) was acquired; 2-HG was measured as the percentage elevation of Glx3 (the sum of 2-HG and Glx) compared to Glx4. IDH mutation status was assessed by immunochemistry or direct sequencing. The ex vivo 2-HG concentration was determined in surgically obtained tissue specimens using gas chromatography-mass spectrometry. Pearson correlation was used for assessing the correlation between in vivo MR spectroscopy and ex vivo 2-HG concentration. MR spectroscopy was positive for 2-HG in eight patients, all of whom had IDH1 tumors. A strong correlation (r = 0.80, p = 0.003) between 2-HG MR spectroscopy and the ex vivo 2-HG concentration was found. This study shows in vivo 2-HG MR spectroscopy can non-invasively determine IDH status in glioma and demonstrates a strong correlation with ex vivo 2-HG concentration in patients with lower-grade glioma.
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Affiliation(s)
- Bart R. J. van Dijken
- Department of Radiology, Medical Imaging Center (MIC), University Medical Center Groningen (UMCG), 9700 RB Groningen, The Netherlands
| | - Hanne-Rinck Jeltema
- Department of Neurosurgery, University Medical Center Groningen (UMCG), 9700 RB Groningen, The Netherlands
| | - Justyna Kłos
- Department of Radiology, Medical Imaging Center (MIC), University Medical Center Groningen (UMCG), 9700 RB Groningen, The Netherlands
| | - Peter Jan van Laar
- Department of Radiology, Hospital Group Twente (ZGT), 7600 SZ Almelo, The Netherlands
| | - Roelien H. Enting
- Department of Neurology, University Medical Center Groningen (UMCG), 9700 RB Groningen, The Netherlands
| | - Ronald G. H. J. Maatman
- Department of Laboratory Medicine, University Medical Center Groningen (UMCG), 9700 RB Groningen, The Netherlands
| | - Klaas Bijsterveld
- Department of Laboratory Medicine, University Medical Center Groningen (UMCG), 9700 RB Groningen, The Netherlands
| | - Wilfred F. A. Den Dunnen
- Department of Pathology, University Medical Center Groningen (UMCG), 9700 RB Groningen, The Netherlands
| | - Rudi A. Dierckx
- Department of Radiology, Medical Imaging Center (MIC), University Medical Center Groningen (UMCG), 9700 RB Groningen, The Netherlands
- Department of Nuclear Medicine, Medical Imaging Center (MIC), University Medical Center Groningen (UMCG), 9700 RB Groningen, The Netherlands
| | - Paul E. Sijens
- Department of Radiology, Medical Imaging Center (MIC), University Medical Center Groningen (UMCG), 9700 RB Groningen, The Netherlands
| | - Anouk van der Hoorn
- Department of Radiology, Medical Imaging Center (MIC), University Medical Center Groningen (UMCG), 9700 RB Groningen, The Netherlands
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19
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Gallus M, Kwok D, Lakshmanachetty S, Yamamichi A, Okada H. Immunotherapy Approaches in Isocitrate-Dehydrogenase-Mutant Low-Grade Glioma. Cancers (Basel) 2023; 15:3726. [PMID: 37509387 PMCID: PMC10378701 DOI: 10.3390/cancers15143726] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 07/17/2023] [Accepted: 07/20/2023] [Indexed: 07/30/2023] Open
Abstract
Low-grade gliomas (LGGs) are slow-growing tumors in the central nervous system (CNS). Patients characteristically show the onset of seizures or neurological deficits due to the predominant LGG location in high-functional brain areas. As a molecular hallmark, LGGs display mutations in the isocitrate dehydrogenase (IDH) enzymes, resulting in an altered cellular energy metabolism and the production of the oncometabolite D-2-hydroxyglutarate. Despite the remarkable progress in improving the extent of resection and adjuvant radiotherapy and chemotherapy, LGG remains incurable, and secondary malignant transformation is often observed. Therefore, novel therapeutic approaches are urgently needed. In recent years, immunotherapeutic strategies have led to tremendous success in various cancer types, but the effect of immunotherapy against glioma has been limited due to several challenges, such as tumor heterogeneity and the immunologically "cold" tumor microenvironment. Nevertheless, recent preclinical and clinical findings from immunotherapy trials are encouraging and offer a glimmer of hope for treating IDH-mutant LGG patients. Here, we aim to review the lessons learned from trials involving vaccines, T-cell therapies, and IDH-mutant inhibitors and discuss future approaches to enhance the efficacy of immunotherapies in IDH-mutant LGG.
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Affiliation(s)
- Marco Gallus
- Department of Neurological Surgery, University of California, San Francisco, CA 94143, USA
- Department of Neurosurgery, University Hospital Muenster, 48149 Muenster, Germany
| | - Darwin Kwok
- Department of Neurological Surgery, University of California, San Francisco, CA 94143, USA
| | | | - Akane Yamamichi
- Department of Neurological Surgery, University of California, San Francisco, CA 94143, USA
| | - Hideho Okada
- Department of Neurological Surgery, University of California, San Francisco, CA 94143, USA
- Parker Institute for Cancer Immunotherapy, San Francisco, CA 94129, USA
- Helen Diller Family Comprehensive Cancer Center, San Francisco, CA 94143, USA
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20
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Yano H, Miwa K, Nakayama N, Maruyama T, Ohe N, Ikuta S, Ikegame Y, Yamada T, Takei H, Owashi E, Ohmura K, Yokoyama K, Kumagai M, Muragaki Y, Iwama T, Shinoda J. Differentiation of astrocytoma between grades II and III using a combination of methionine positron emission tomography and magnetic resonance spectroscopy. World Neurosurg X 2023; 19:100193. [PMID: 37123626 PMCID: PMC10141501 DOI: 10.1016/j.wnsx.2023.100193] [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: 10/05/2022] [Accepted: 04/04/2023] [Indexed: 05/02/2023] Open
Abstract
Objective This study aimed to establish a method for differentiating between grades II and III astrocytomas using preoperative imaging. Methods We retrospectively analyzed astrocytic tumors, including 18 grade II astrocytomas (isocitrate dehydrogenase (IDH)-mutant: IDH-wildtype = 8:10) and 56 grade III anaplastic astrocytomas (37:19). We recorded the maximum methionine (MET) uptake ratios (tumor-to-normal: T/N) on positron emission tomography (PET) and three MRS peak ratios: choline (Cho)/creatine (Cr), N-acetyl aspartate (NAA)/Cr, and Cho/NAA, between June 2015 and June 2020. We then evaluated the cut-off values to differentiate between grades II and III. We compared the grading results between contrast enhancement effects on MR and combinational diagnostic methods (CDM) on a scatter chart using the cutoff values of the T/N ratio and MRS parameters. Results The IDH-mutant group showed significant differences in the Cho/NAA ratio between grades II and III using univariate analysis; however, multiple regression analysis results negated this. The IDH-wildtype group showed no significant differences between the groups. Contrast enhancement effects also showed no significant differences in IDH status. Accordingly, regardless of the IDH status, no statistically independent factors differentiated between grades II and III. However, CDMs showed higher sensitivity and negative predictive value in distinguishing them than MRI contrast examinations for both IDH statuses. We demonstrated a significantly higher diagnostic rate of grade III than of grade II with CDM, which was more striking in the IDH-mutant group than in the wild-type group. Conclusions CDM could be valuable in differentiating between grade II and III astrocytic tumors.
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Affiliation(s)
- Hirohito Yano
- Department of Neurosurgery and Chubu Medical Center for Prolonged Traumatic Brain Dysfunction, Chubu Neurorehabilitation Hospital, 630 Shimo-kobi, Kobi-cho, Minokamo, 505-0034, Japan
- Department of Clinical Brain Science, Gifu University Graduate School of Medicine, 1-1 Yanagido, Gifu City, 501-1194, Japan
- Corresponding author. Department of Neurosurgery and Chubu Medical Center for Prolonged Traumatic Brain Dysfunction, Chubu Neurorehabilitation Hospital, 630 Shimo-kobi, Kobi-cho, Minokamo, 505-0034, Japan.
| | - Kazuhiro Miwa
- Department of Neurosurgery, Central Japan International Medical Center, 1-1 Kenkou-no-machi, Minokamo City, 505-8510, Japan
| | - Noriyuki Nakayama
- Department of Neurosurgery, Gifu University Graduate School of Medicine, 1-1 Yanagido, Gifu City, 501-1194, Japan
| | - Takashi Maruyama
- Department of Neurosurgery, Tokyo Women's Medical University, 8-1 Kawada-cho, Shinjuku-ku, Tokyo, 162-8666, Japan
| | - Naoyuki Ohe
- Department of Neurosurgery, Gifu University Graduate School of Medicine, 1-1 Yanagido, Gifu City, 501-1194, Japan
| | - Soko Ikuta
- Department of Neurosurgery, Tokyo Women's Medical University, 8-1 Kawada-cho, Shinjuku-ku, Tokyo, 162-8666, Japan
| | - Yuka Ikegame
- Department of Neurosurgery and Chubu Medical Center for Prolonged Traumatic Brain Dysfunction, Chubu Neurorehabilitation Hospital, 630 Shimo-kobi, Kobi-cho, Minokamo, 505-0034, Japan
- Department of Clinical Brain Science, Gifu University Graduate School of Medicine, 1-1 Yanagido, Gifu City, 501-1194, Japan
| | - Tetsuya Yamada
- Department of Neurosurgery, Gifu University Graduate School of Medicine, 1-1 Yanagido, Gifu City, 501-1194, Japan
| | - Hiroaki Takei
- Department of Neurosurgery, Central Japan International Medical Center, 1-1 Kenkou-no-machi, Minokamo City, 505-8510, Japan
| | - Etsuko Owashi
- Department of Neurosurgery and Chubu Medical Center for Prolonged Traumatic Brain Dysfunction, Chubu Neurorehabilitation Hospital, 630 Shimo-kobi, Kobi-cho, Minokamo, 505-0034, Japan
| | - Kazufumi Ohmura
- Department of Neurosurgery and Chubu Medical Center for Prolonged Traumatic Brain Dysfunction, Chubu Neurorehabilitation Hospital, 630 Shimo-kobi, Kobi-cho, Minokamo, 505-0034, Japan
| | - Kazutoshi Yokoyama
- Department of Neurosurgery, Central Japan International Medical Center, 1-1 Kenkou-no-machi, Minokamo City, 505-8510, Japan
| | - Morio Kumagai
- Department of Neurosurgery and Chubu Medical Center for Prolonged Traumatic Brain Dysfunction, Chubu Neurorehabilitation Hospital, 630 Shimo-kobi, Kobi-cho, Minokamo, 505-0034, Japan
| | - Yoshihiro Muragaki
- Department of Neurosurgery, Tokyo Women's Medical University, 8-1 Kawada-cho, Shinjuku-ku, Tokyo, 162-8666, Japan
| | - Toru Iwama
- Department of Neurosurgery, Gifu University Graduate School of Medicine, 1-1 Yanagido, Gifu City, 501-1194, Japan
| | - Jun Shinoda
- Department of Neurosurgery and Chubu Medical Center for Prolonged Traumatic Brain Dysfunction, Chubu Neurorehabilitation Hospital, 630 Shimo-kobi, Kobi-cho, Minokamo, 505-0034, Japan
- Department of Clinical Brain Science, Gifu University Graduate School of Medicine, 1-1 Yanagido, Gifu City, 501-1194, Japan
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21
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Hangel G, Schmitz‐Abecassis B, Sollmann N, Pinto J, Arzanforoosh F, Barkhof F, Booth T, Calvo‐Imirizaldu M, Cassia G, Chmelik M, Clement P, Ercan E, Fernández‐Seara MA, Furtner J, Fuster‐Garcia E, Grech‐Sollars M, Guven NT, Hatay GH, Karami G, Keil VC, Kim M, Koekkoek JAF, Kukran S, Mancini L, Nechifor RE, Özcan A, Ozturk‐Isik E, Piskin S, Schmainda KM, Svensson SF, Tseng C, Unnikrishnan S, Vos F, Warnert E, Zhao MY, Jancalek R, Nunes T, Hirschler L, Smits M, Petr J, Emblem KE. Advanced MR Techniques for Preoperative Glioma Characterization: Part 2. J Magn Reson Imaging 2023; 57:1676-1695. [PMID: 36912262 PMCID: PMC10947037 DOI: 10.1002/jmri.28663] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 02/08/2023] [Accepted: 02/09/2023] [Indexed: 03/14/2023] Open
Abstract
Preoperative clinical MRI protocols for gliomas, brain tumors with dismal outcomes due to their infiltrative properties, still rely on conventional structural MRI, which does not deliver information on tumor genotype and is limited in the delineation of diffuse gliomas. The GliMR COST action wants to raise awareness about the state of the art of advanced MRI techniques in gliomas and their possible clinical translation. This review describes current methods, limits, and applications of advanced MRI for the preoperative assessment of glioma, summarizing the level of clinical validation of different techniques. In this second part, we review magnetic resonance spectroscopy (MRS), chemical exchange saturation transfer (CEST), susceptibility-weighted imaging (SWI), MRI-PET, MR elastography (MRE), and MR-based radiomics applications. The first part of this review addresses dynamic susceptibility contrast (DSC) and dynamic contrast-enhanced (DCE) MRI, arterial spin labeling (ASL), diffusion-weighted MRI, vessel imaging, and magnetic resonance fingerprinting (MRF). EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Gilbert Hangel
- Department of NeurosurgeryMedical University of ViennaViennaAustria
- High Field MR Centre, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
- Christian Doppler Laboratory for MR Imaging BiomarkersViennaAustria
- Medical Imaging ClusterMedical University of ViennaViennaAustria
| | - Bárbara Schmitz‐Abecassis
- Department of RadiologyLeiden University Medical CenterLeidenthe Netherlands
- Medical Delta FoundationDelftthe Netherlands
| | - Nico Sollmann
- Department of Diagnostic and Interventional RadiologyUniversity Hospital UlmUlmGermany
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der IsarTechnical University of MunichMunichGermany
- TUM‐Neuroimaging Center, Klinikum rechts der IsarTechnical University of MunichMunichGermany
| | - Joana Pinto
- Institute of Biomedical Engineering, Department of Engineering ScienceUniversity of OxfordOxfordUK
| | | | - Frederik Barkhof
- Department of Radiology & Nuclear MedicineAmsterdam UMC, Vrije UniversiteitAmsterdamNetherlands
- Queen Square Institute of Neurology and Centre for Medical Image ComputingUniversity College LondonLondonUK
| | - Thomas Booth
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
- Department of NeuroradiologyKing's College Hospital NHS Foundation TrustLondonUK
| | | | | | - Marek Chmelik
- Department of Technical Disciplines in Medicine, Faculty of Health CareUniversity of PrešovPrešovSlovakia
| | - Patricia Clement
- Department of Diagnostic SciencesGhent UniversityGhentBelgium
- Department of Medical ImagingGhent University HospitalGhentBelgium
| | - Ece Ercan
- Department of RadiologyLeiden University Medical CenterLeidenthe Netherlands
| | - Maria A. Fernández‐Seara
- Department of RadiologyClínica Universidad de NavarraPamplonaSpain
- IdiSNA, Instituto de Investigación Sanitaria de NavarraPamplonaSpain
| | - Julia Furtner
- Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
- Research Center of Medical Image Analysis and Artificial IntelligenceDanube Private UniversityAustria
| | - Elies Fuster‐Garcia
- Biomedical Data Science Laboratory, Instituto Universitario de Tecnologías de la Información y ComunicacionesUniversitat Politècnica de ValènciaValenciaSpain
| | - Matthew Grech‐Sollars
- Centre for Medical Image Computing, Department of Computer ScienceUniversity College LondonLondonUK
- Lysholm Department of Neuroradiology, National Hospital for Neurology and NeurosurgeryUniversity College London Hospitals NHS Foundation TrustLondonUK
| | - N. Tugay Guven
- Institute of Biomedical EngineeringBogazici University IstanbulIstanbulTurkey
| | - Gokce Hale Hatay
- Institute of Biomedical EngineeringBogazici University IstanbulIstanbulTurkey
| | - Golestan Karami
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
| | - Vera C. Keil
- Department of Radiology & Nuclear MedicineAmsterdam UMC, Vrije UniversiteitAmsterdamNetherlands
- Cancer Center AmsterdamAmsterdamNetherlands
| | - Mina Kim
- Centre for Medical Image Computing, Department of Medical Physics & Biomedical Engineering and Department of NeuroinflammationUniversity College LondonLondonUK
| | - Johan A. F. Koekkoek
- Department of NeurologyLeiden University Medical CenterLeidenthe Netherlands
- Department of NeurologyHaaglanden Medical CenterNetherlands
| | - Simran Kukran
- Department of BioengineeringImperial College LondonLondonUK
- Department of Radiotherapy and ImagingInstitute of Cancer ResearchUK
| | - Laura Mancini
- Lysholm Department of Neuroradiology, National Hospital for Neurology and NeurosurgeryUniversity College London Hospitals NHS Foundation TrustLondonUK
- Department of Brain Repair and Rehabilitation, Institute of NeurologyUniversity College LondonLondonUK
| | - Ruben Emanuel Nechifor
- Department of Clinical Psychology and Psychotherapy, International Institute for the Advanced Studies of Psychotherapy and Applied Mental HealthBabes‐Bolyai UniversityRomania
| | - Alpay Özcan
- Electrical and Electronics Engineering DepartmentBogazici University IstanbulIstanbulTurkey
| | - Esin Ozturk‐Isik
- Institute of Biomedical EngineeringBogazici University IstanbulIstanbulTurkey
| | - Senol Piskin
- Department of Mechanical Engineering, Faculty of Natural Sciences and EngineeringIstinye University IstanbulIstanbulTurkey
| | | | - Siri F. Svensson
- Department of Physics and Computational RadiologyOslo University HospitalOsloNorway
- Department of PhysicsUniversity of OsloOsloNorway
| | - Chih‐Hsien Tseng
- Medical Delta FoundationDelftthe Netherlands
- Department of Imaging PhysicsDelft University of TechnologyDelftthe Netherlands
| | - Saritha Unnikrishnan
- Faculty of Engineering and DesignAtlantic Technological University (ATU) SligoSligoIreland
- Mathematical Modelling and Intelligent Systems for Health and Environment (MISHE), ATU SligoSligoIreland
| | - Frans Vos
- Medical Delta FoundationDelftthe Netherlands
- Department of Radiology & Nuclear MedicineErasmus MCRotterdamNetherlands
- Department of Imaging PhysicsDelft University of TechnologyDelftthe Netherlands
| | - Esther Warnert
- Department of Radiology & Nuclear MedicineErasmus MCRotterdamNetherlands
| | - Moss Y. Zhao
- Department of RadiologyStanford UniversityStanfordCaliforniaUSA
- Stanford Cardiovascular InstituteStanford UniversityStanfordCaliforniaUSA
| | - Radim Jancalek
- Department of NeurosurgerySt. Anne's University HospitalBrnoCzechia
- Faculty of MedicineMasaryk UniversityBrnoCzechia
| | - Teresa Nunes
- Department of NeuroradiologyHospital Garcia de OrtaAlmadaPortugal
| | - Lydiane Hirschler
- C.J. Gorter MRI Center, Department of RadiologyLeiden University Medical CenterLeidenthe Netherlands
| | - Marion Smits
- Medical Delta FoundationDelftthe Netherlands
- Department of Radiology & Nuclear MedicineErasmus MCRotterdamNetherlands
- Brain Tumour CentreErasmus MC Cancer InstituteRotterdamthe Netherlands
| | - Jan Petr
- Helmholtz‐Zentrum Dresden‐RossendorfInstitute of Radiopharmaceutical Cancer ResearchDresdenGermany
| | - Kyrre E. Emblem
- Department of Physics and Computational RadiologyOslo University HospitalOsloNorway
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22
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Siakallis L, Topriceanu CC, Panovska-Griffiths J, Bisdas S. The role of DSC MR perfusion in predicting IDH mutation and 1p19q codeletion status in gliomas: meta-analysis and technical considerations. Neuroradiology 2023:10.1007/s00234-023-03154-5. [PMID: 37173578 DOI: 10.1007/s00234-023-03154-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Accepted: 04/18/2023] [Indexed: 05/15/2023]
Abstract
PURPOSE Isocitrate dehydrogenase (IDH) mutation and 1p19q codeletion status are important for managing glioma patients. However, current practice dictates invasive tissue sampling for histomolecular classification. We investigated the current value of dynamic susceptibility contrast (DSC) MR perfusion imaging as a tool for the non-invasive identification of these biomarkers. METHODS A systematic search of PubMed, Medline, and Embase up to 2023 was performed, and meta-analyses were conducted. We removed studies employing machine learning models or using multiparametric imaging. We used random-effects standardized mean difference (SMD) and bivariate sensitivity-specificity meta-analyses, calculated the area under the hierarchical summary receiver operating characteristic curve (AUC) and performed meta-regressions using technical acquisition parameters (e.g., time to echo [TE], repetition time [TR]) as moderators to explore sources of heterogeneity. For all estimates, 95% confidence intervals (CIs) are provided. RESULTS Sixteen eligible manuscripts comprising 1819 patients were included in the quantitative analyses. IDH mutant (IDHm) gliomas had lower rCBV values compared to their wild-type (IDHwt) counterparts. The highest SMD was observed for rCBVmean, rCBVmax, and rCBV 75th percentile (SMD≈ - 0.8, 95% CI ≈ [- 1.2, - 0.5]). In meta-regression, shorter TEs, shorter TRs, and smaller slice thicknesses were linked to higher absolute SMDs. When discriminating IDHm from IDHwt, the highest pooled specificity was observed for rCBVmean (82% [72, 89]), and the highest pooled sensitivity (i.e., 92% [86, 93]) and AUC (i.e., 0.91) for rCBV 10th percentile. In the bivariate meta-regression, shorter TEs and smaller slice gaps were linked to higher pooled sensitivities. In IDHm, 1p19q codeletion was associated with higher rCBVmean (SMD = 0.9 [0.2, 1.5]) and rCBV 90th percentile (SMD = 0.9 [0.1, 1.7]) values. CONCLUSIONS Identification of vascular signatures predictive of IDH and 1p19q status is a novel promising application of DSC perfusion. Standardization of acquisition protocols and post-processing of DSC perfusion maps are warranted before widespread use in clinical practice.
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Affiliation(s)
- Loizos Siakallis
- University College London (UCL) Queen Square Institute of Neurology, London, UK.
- Lysholm Department of Neuroradiology, The National Hospital for Neurology and Neurosurgery, University College London Hospitals (UCLH) NHS Foundation Trust, London, UK.
| | - Constantin-Cristian Topriceanu
- University College London (UCL) Queen Square Institute of Neurology, London, UK
- Lysholm Department of Neuroradiology, The National Hospital for Neurology and Neurosurgery, University College London Hospitals (UCLH) NHS Foundation Trust, London, UK
- UCL Institute of Cardiovascular Science, University College London, London, UK
| | - Jasmina Panovska-Griffiths
- The Big Data Institute and the Pandemic Sciences Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- The Queen's College, University of Oxford, Oxford, UK
| | - Sotirios Bisdas
- Lysholm Department of Neuroradiology, The National Hospital for Neurology and Neurosurgery, University College London Hospitals (UCLH) NHS Foundation Trust, London, UK
- Department of Brain Repair & Rehabilitation, Queen Square Institute of Neurology, University College London, London, UK
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23
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Neumaier F, Zlatopolskiy BD, Neumaier B. Mutated Isocitrate Dehydrogenase (mIDH) as Target for PET Imaging in Gliomas. Molecules 2023; 28:molecules28072890. [PMID: 37049661 PMCID: PMC10096429 DOI: 10.3390/molecules28072890] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 03/21/2023] [Accepted: 03/21/2023] [Indexed: 04/14/2023] Open
Abstract
Gliomas are the most common primary brain tumors in adults. A diffuse infiltrative growth pattern and high resistance to therapy make them largely incurable, but there are significant differences in the prognosis of patients with different subtypes of glioma. Mutations in isocitrate dehydrogenase (IDH) have been recognized as an important biomarker for glioma classification and a potential therapeutic target. However, current clinical methods for detecting mutated IDH (mIDH) require invasive tissue sampling and cannot be used for follow-up examinations or longitudinal studies. PET imaging could be a promising approach for non-invasive assessment of the IDH status in gliomas, owing to the availability of various mIDH-selective inhibitors as potential leads for the development of PET tracers. In the present review, we summarize the rationale for the development of mIDH-selective PET probes, describe their potential applications beyond the assessment of the IDH status and highlight potential challenges that may complicate tracer development. In addition, we compile the major chemical classes of mIDH-selective inhibitors that have been described to date and briefly consider possible strategies for radiolabeling of the most promising candidates. Where available, we also summarize previous studies with radiolabeled analogs of mIDH inhibitors and assess their suitability for PET imaging in gliomas.
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Affiliation(s)
- Felix Neumaier
- Forschungszentrum Jülich GmbH, Institute of Neuroscience and Medicine, Nuclear Chemistry (INM-5), Wilhelm-Johnen-Str., 52428 Jülich, Germany
- Institute of Radiochemistry and Experimental Molecular Imaging, Faculty of Medicine and University Hospital Cologne, University of Cologne, Kerpener Str. 62, 50937 Cologne, Germany
| | - Boris D Zlatopolskiy
- Forschungszentrum Jülich GmbH, Institute of Neuroscience and Medicine, Nuclear Chemistry (INM-5), Wilhelm-Johnen-Str., 52428 Jülich, Germany
- Institute of Radiochemistry and Experimental Molecular Imaging, Faculty of Medicine and University Hospital Cologne, University of Cologne, Kerpener Str. 62, 50937 Cologne, Germany
| | - Bernd Neumaier
- Forschungszentrum Jülich GmbH, Institute of Neuroscience and Medicine, Nuclear Chemistry (INM-5), Wilhelm-Johnen-Str., 52428 Jülich, Germany
- Institute of Radiochemistry and Experimental Molecular Imaging, Faculty of Medicine and University Hospital Cologne, University of Cologne, Kerpener Str. 62, 50937 Cologne, Germany
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24
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Nabavizadeh A, Barkovich MJ, Mian A, Ngo V, Kazerooni AF, Villanueva-Meyer JE. Current state of pediatric neuro-oncology imaging, challenges and future directions. Neoplasia 2023; 37:100886. [PMID: 36774835 PMCID: PMC9945752 DOI: 10.1016/j.neo.2023.100886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 01/20/2023] [Accepted: 02/05/2023] [Indexed: 02/12/2023]
Abstract
Imaging plays a central role in neuro-oncology including primary diagnosis, treatment planning, and surveillance of tumors. The emergence of quantitative imaging and radiomics provided an uprecedented opportunity to compile mineable databases that can be utilized in a variety of applications. In this review, we aim to summarize the current state of conventional and advanced imaging techniques, standardization efforts, fast protocols, contrast and sedation in pediatric neuro-oncologic imaging, radiomics-radiogenomics, multi-omics and molecular imaging approaches. We will also address the existing challenges and discuss future directions.
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Affiliation(s)
- Ali Nabavizadeh
- Department of Radiology, Hospital of University of Pennsylvania, Perelman School of Medicine of the University of Pennsylvania, Philadelphia, Pennsylvania, USA; Center for Data-Driven Discovery in Biomedicine (D3b), Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
| | - Matthew J Barkovich
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Ali Mian
- Division of Neuroradiology, Mallinckrodt Institute of Radiology, Washington University in St. Louis, Missouri, USA
| | - Van Ngo
- Saint Louis University School of Medicine, St. Louis, Missouri, USA
| | - Anahita Fathi Kazerooni
- Center for Data-Driven Discovery in Biomedicine (D3b), Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Javier E Villanueva-Meyer
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
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25
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Harris AD, Amiri H, Bento M, Cohen R, Ching CRK, Cudalbu C, Dennis EL, Doose A, Ehrlich S, Kirov II, Mekle R, Oeltzschner G, Porges E, Souza R, Tam FI, Taylor B, Thompson PM, Quidé Y, Wilde EA, Williamson J, Lin AP, Bartnik-Olson B. Harmonization of multi-scanner in vivo magnetic resonance spectroscopy: ENIGMA consortium task group considerations. Front Neurol 2023; 13:1045678. [PMID: 36686533 PMCID: PMC9845632 DOI: 10.3389/fneur.2022.1045678] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 12/06/2022] [Indexed: 01/06/2023] Open
Abstract
Magnetic resonance spectroscopy is a powerful, non-invasive, quantitative imaging technique that allows for the measurement of brain metabolites that has demonstrated utility in diagnosing and characterizing a broad range of neurological diseases. Its impact, however, has been limited due to small sample sizes and methodological variability in addition to intrinsic limitations of the method itself such as its sensitivity to motion. The lack of standardization from a data acquisition and data processing perspective makes it difficult to pool multiple studies and/or conduct multisite studies that are necessary for supporting clinically relevant findings. Based on the experience of the ENIGMA MRS work group and a review of the literature, this manuscript provides an overview of the current state of MRS data harmonization. Key factors that need to be taken into consideration when conducting both retrospective and prospective studies are described. These include (1) MRS acquisition issues such as pulse sequence, RF and B0 calibrations, echo time, and SNR; (2) data processing issues such as pre-processing steps, modeling, and quantitation; and (3) biological factors such as voxel location, age, sex, and pathology. Various approaches to MRS data harmonization are then described including meta-analysis, mega-analysis, linear modeling, ComBat and artificial intelligence approaches. The goal is to provide both novice and experienced readers with the necessary knowledge for conducting MRS data harmonization studies.
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Affiliation(s)
- Ashley D. Harris
- Department of Radiology, University of Calgary, Calgary, AB, Canada,Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Houshang Amiri
- Neuroscience Research Center, Institute of Neuropharmacology, Kerman University of Medical Sciences, Kerman, Iran
| | - Mariana Bento
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada,Department of Biomedical Engineering, Schulich School of Engineering, University of Calgary, Calgary, AB, Canada
| | - Ronald Cohen
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, United States
| | - Christopher R. K. Ching
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, Los Angeles, CA, United States
| | - Christina Cudalbu
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland,Animal Imaging and Technology, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Emily L. Dennis
- TBI and Concussion Center, Department of Neurology, University of Utah, Salt Lake City, UT, United States
| | - Arne Doose
- Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Stefan Ehrlich
- Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Ivan I. Kirov
- Department of Radiology, Center for Advanced Imaging Innovation and Research, New York University Grossman School of Medicine, New York, NY, United States
| | - Ralf Mekle
- Center for Stroke Research Berlin, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Georg Oeltzschner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Eric Porges
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, United States
| | - Roberto Souza
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada,Department of Electrical and Software Engineering, Schulich School of Engineering, University of Calgary, Calgary, AB, Canada
| | - Friederike I. Tam
- Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Brian Taylor
- Division of Diagnostic Imaging, Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Paul M. Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, Los Angeles, CA, United States
| | - Yann Quidé
- School of Psychology, University of New South Wales (UNSW), Sydney, NSW, Australia
| | - Elisabeth A. Wilde
- TBI and Concussion Center, Department of Neurology, University of Utah, Salt Lake City, UT, United States
| | - John Williamson
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, United States
| | - Alexander P. Lin
- Center for Clinical Spectroscopy, Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States
| | - Brenda Bartnik-Olson
- Department of Radiology, Loma Linda University Medical Center, Loma Linda, CA, United States,*Correspondence: Brenda Bartnik-Olson ✉
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26
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Di Stefano AL, Nichelli L, Berzero G, Valabregue R, Touat M, Capelle L, Pontoizeau C, Bielle F, Lerond J, Giry M, Villa C, Baussart B, Dehais C, Galanaud D, Baldini C, Savatovsky J, Dhermain F, Deelchand DK, Ottolenghi C, Lehéricy S, Marjańska M, Branzoli F, Sanson M. In Vivo 2-Hydroxyglutarate Monitoring With Edited MR Spectroscopy for the Follow-up of IDH-Mutant Diffuse Gliomas: The IDASPE Prospective Study. Neurology 2023; 100:e94-e106. [PMID: 36180241 PMCID: PMC9827125 DOI: 10.1212/wnl.0000000000201137] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2021] [Accepted: 07/05/2022] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND AND OBJECTIVES D-2-hydroxyglutarate (2HG) characterizes IDH-mutant gliomas and can be detected and quantified with edited MRS (MEGA-PRESS). In this study, we investigated the clinical, radiologic, and molecular parameters affecting 2HG levels. METHODS MEGA-PRESS data were acquired in 71 patients with glioma (24 untreated, 47 treated) on a 3 T system. Eighteen patients were followed during cytotoxic (n = 12) or targeted (n = 6) therapy. 2HG was measured in tumor samples using gas chromatography coupled to mass spectrometry (GCMS). RESULTS MEGA-PRESS detected 2HG with a sensitivity of 95% in untreated patients and 62% in treated patients. Sensitivity depended on tumor volume (>27 cm3; p = 0.02), voxel coverage (>75%; p = 0.002), and expansive presentation (defined by equal size of T1 and FLAIR abnormalities, p = 0.04). 2HG levels were positively correlated with IDH-mutant allelic fraction (p = 0.03) and total choline levels (p < 0.001) and were higher in IDH2-mutant compared with IDH1 R132H-mutant and non-R132H IDH1-mutant patients (p = 0.002). In patients receiving IDH inhibitors, 2HG levels decreased within a few days, demonstrating the on-target effect of the drug, but 2HG level decrease did not predict tumor response. Patients receiving cytotoxic treatments showed a slower decrease in 2HG levels, consistent with tumor response and occurring before any tumor volume change on conventional MRI. At progression, 1p/19q codeleted gliomas, but not the non-codeleted, showed detectable in vivo 2HG levels, pointing out to different modes of progression characterizing these 2 entities. DISCUSSION MEGA-PRESS edited MRS allows in vivo monitoring of 2-hydroxyglutarate, confirming efficacy of IDH inhibition and suggests different patterns of tumor progression in astrocytomas compared with oligodendrogliomas.
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Affiliation(s)
- Anna Luisa Di Stefano
- From the Sorbonne Université (A.L.D.S.,M.D.P.D., L.N., M.D.P.D., J.L., M.G., S.L., Francesca Branzoli), Inserm, CNRS, Paris Brain Institute-Institut du Cerveau (ICM), Paris, France. Equipe labellisée LNCC; Service de Neurologie 2-Mazarin (A.L.D.S.,M.D.P.D., M.D.P.D., C.D.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Neuroradiologie Diagnostique et Interventionnelle (L.N., D.G., S.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Neurology Unit (G.B.), IRCCS San Raffaele Scientific Institute, Milan, Italy; Centre de NeuroImagerie de Recherche (CENIR) (R.V., S.L., Francesca Branzoli), Institut du Cerveau (ICM), Paris, France; Service de Neurochirurgie (L.C., B.B.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Biochimie Métabolique (C.P.), AP-HP, Hôpital Necker, Paris, France; Laboratoire R Escourolle (J.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Drug Development Department (DITEP) (C.B.), Gustave Roussy, Villejuif, France; Service de Radiologie (J.S.), Fondation Ophtalmologique Adolphe de Rothschild, Paris, France; Radiotherapy Department (F.D.), Gustave Roussy University Hospital, Villejuif, Cedex, France; Center for Magnetic Resonance Research (D.K.D., M.M.), Department of Radiology, Minneapolis, MN; and OncoNeuroTek Tumor Bank (M.D.P.D.), Institut du Cerveau et de la Moelle épinière (ICM), Paris, France
| | - Lucia Nichelli
- From the Sorbonne Université (A.L.D.S.,M.D.P.D., L.N., M.D.P.D., J.L., M.G., S.L., Francesca Branzoli), Inserm, CNRS, Paris Brain Institute-Institut du Cerveau (ICM), Paris, France. Equipe labellisée LNCC; Service de Neurologie 2-Mazarin (A.L.D.S.,M.D.P.D., M.D.P.D., C.D.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Neuroradiologie Diagnostique et Interventionnelle (L.N., D.G., S.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Neurology Unit (G.B.), IRCCS San Raffaele Scientific Institute, Milan, Italy; Centre de NeuroImagerie de Recherche (CENIR) (R.V., S.L., Francesca Branzoli), Institut du Cerveau (ICM), Paris, France; Service de Neurochirurgie (L.C., B.B.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Biochimie Métabolique (C.P.), AP-HP, Hôpital Necker, Paris, France; Laboratoire R Escourolle (J.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Drug Development Department (DITEP) (C.B.), Gustave Roussy, Villejuif, France; Service de Radiologie (J.S.), Fondation Ophtalmologique Adolphe de Rothschild, Paris, France; Radiotherapy Department (F.D.), Gustave Roussy University Hospital, Villejuif, Cedex, France; Center for Magnetic Resonance Research (D.K.D., M.M.), Department of Radiology, Minneapolis, MN; and OncoNeuroTek Tumor Bank (M.D.P.D.), Institut du Cerveau et de la Moelle épinière (ICM), Paris, France
| | - Giulia Berzero
- From the Sorbonne Université (A.L.D.S.,M.D.P.D., L.N., M.D.P.D., J.L., M.G., S.L., Francesca Branzoli), Inserm, CNRS, Paris Brain Institute-Institut du Cerveau (ICM), Paris, France. Equipe labellisée LNCC; Service de Neurologie 2-Mazarin (A.L.D.S.,M.D.P.D., M.D.P.D., C.D.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Neuroradiologie Diagnostique et Interventionnelle (L.N., D.G., S.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Neurology Unit (G.B.), IRCCS San Raffaele Scientific Institute, Milan, Italy; Centre de NeuroImagerie de Recherche (CENIR) (R.V., S.L., Francesca Branzoli), Institut du Cerveau (ICM), Paris, France; Service de Neurochirurgie (L.C., B.B.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Biochimie Métabolique (C.P.), AP-HP, Hôpital Necker, Paris, France; Laboratoire R Escourolle (J.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Drug Development Department (DITEP) (C.B.), Gustave Roussy, Villejuif, France; Service de Radiologie (J.S.), Fondation Ophtalmologique Adolphe de Rothschild, Paris, France; Radiotherapy Department (F.D.), Gustave Roussy University Hospital, Villejuif, Cedex, France; Center for Magnetic Resonance Research (D.K.D., M.M.), Department of Radiology, Minneapolis, MN; and OncoNeuroTek Tumor Bank (M.D.P.D.), Institut du Cerveau et de la Moelle épinière (ICM), Paris, France
| | - Romain Valabregue
- From the Sorbonne Université (A.L.D.S.,M.D.P.D., L.N., M.D.P.D., J.L., M.G., S.L., Francesca Branzoli), Inserm, CNRS, Paris Brain Institute-Institut du Cerveau (ICM), Paris, France. Equipe labellisée LNCC; Service de Neurologie 2-Mazarin (A.L.D.S.,M.D.P.D., M.D.P.D., C.D.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Neuroradiologie Diagnostique et Interventionnelle (L.N., D.G., S.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Neurology Unit (G.B.), IRCCS San Raffaele Scientific Institute, Milan, Italy; Centre de NeuroImagerie de Recherche (CENIR) (R.V., S.L., Francesca Branzoli), Institut du Cerveau (ICM), Paris, France; Service de Neurochirurgie (L.C., B.B.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Biochimie Métabolique (C.P.), AP-HP, Hôpital Necker, Paris, France; Laboratoire R Escourolle (J.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Drug Development Department (DITEP) (C.B.), Gustave Roussy, Villejuif, France; Service de Radiologie (J.S.), Fondation Ophtalmologique Adolphe de Rothschild, Paris, France; Radiotherapy Department (F.D.), Gustave Roussy University Hospital, Villejuif, Cedex, France; Center for Magnetic Resonance Research (D.K.D., M.M.), Department of Radiology, Minneapolis, MN; and OncoNeuroTek Tumor Bank (M.D.P.D.), Institut du Cerveau et de la Moelle épinière (ICM), Paris, France
| | - Mehdi Touat
- From the Sorbonne Université (A.L.D.S.,M.D.P.D., L.N., M.D.P.D., J.L., M.G., S.L., Francesca Branzoli), Inserm, CNRS, Paris Brain Institute-Institut du Cerveau (ICM), Paris, France. Equipe labellisée LNCC; Service de Neurologie 2-Mazarin (A.L.D.S.,M.D.P.D., M.D.P.D., C.D.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Neuroradiologie Diagnostique et Interventionnelle (L.N., D.G., S.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Neurology Unit (G.B.), IRCCS San Raffaele Scientific Institute, Milan, Italy; Centre de NeuroImagerie de Recherche (CENIR) (R.V., S.L., Francesca Branzoli), Institut du Cerveau (ICM), Paris, France; Service de Neurochirurgie (L.C., B.B.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Biochimie Métabolique (C.P.), AP-HP, Hôpital Necker, Paris, France; Laboratoire R Escourolle (J.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Drug Development Department (DITEP) (C.B.), Gustave Roussy, Villejuif, France; Service de Radiologie (J.S.), Fondation Ophtalmologique Adolphe de Rothschild, Paris, France; Radiotherapy Department (F.D.), Gustave Roussy University Hospital, Villejuif, Cedex, France; Center for Magnetic Resonance Research (D.K.D., M.M.), Department of Radiology, Minneapolis, MN; and OncoNeuroTek Tumor Bank (M.D.P.D.), Institut du Cerveau et de la Moelle épinière (ICM), Paris, France
| | - Laurent Capelle
- From the Sorbonne Université (A.L.D.S.,M.D.P.D., L.N., M.D.P.D., J.L., M.G., S.L., Francesca Branzoli), Inserm, CNRS, Paris Brain Institute-Institut du Cerveau (ICM), Paris, France. Equipe labellisée LNCC; Service de Neurologie 2-Mazarin (A.L.D.S.,M.D.P.D., M.D.P.D., C.D.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Neuroradiologie Diagnostique et Interventionnelle (L.N., D.G., S.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Neurology Unit (G.B.), IRCCS San Raffaele Scientific Institute, Milan, Italy; Centre de NeuroImagerie de Recherche (CENIR) (R.V., S.L., Francesca Branzoli), Institut du Cerveau (ICM), Paris, France; Service de Neurochirurgie (L.C., B.B.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Biochimie Métabolique (C.P.), AP-HP, Hôpital Necker, Paris, France; Laboratoire R Escourolle (J.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Drug Development Department (DITEP) (C.B.), Gustave Roussy, Villejuif, France; Service de Radiologie (J.S.), Fondation Ophtalmologique Adolphe de Rothschild, Paris, France; Radiotherapy Department (F.D.), Gustave Roussy University Hospital, Villejuif, Cedex, France; Center for Magnetic Resonance Research (D.K.D., M.M.), Department of Radiology, Minneapolis, MN; and OncoNeuroTek Tumor Bank (M.D.P.D.), Institut du Cerveau et de la Moelle épinière (ICM), Paris, France
| | - Clément Pontoizeau
- From the Sorbonne Université (A.L.D.S.,M.D.P.D., L.N., M.D.P.D., J.L., M.G., S.L., Francesca Branzoli), Inserm, CNRS, Paris Brain Institute-Institut du Cerveau (ICM), Paris, France. Equipe labellisée LNCC; Service de Neurologie 2-Mazarin (A.L.D.S.,M.D.P.D., M.D.P.D., C.D.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Neuroradiologie Diagnostique et Interventionnelle (L.N., D.G., S.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Neurology Unit (G.B.), IRCCS San Raffaele Scientific Institute, Milan, Italy; Centre de NeuroImagerie de Recherche (CENIR) (R.V., S.L., Francesca Branzoli), Institut du Cerveau (ICM), Paris, France; Service de Neurochirurgie (L.C., B.B.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Biochimie Métabolique (C.P.), AP-HP, Hôpital Necker, Paris, France; Laboratoire R Escourolle (J.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Drug Development Department (DITEP) (C.B.), Gustave Roussy, Villejuif, France; Service de Radiologie (J.S.), Fondation Ophtalmologique Adolphe de Rothschild, Paris, France; Radiotherapy Department (F.D.), Gustave Roussy University Hospital, Villejuif, Cedex, France; Center for Magnetic Resonance Research (D.K.D., M.M.), Department of Radiology, Minneapolis, MN; and OncoNeuroTek Tumor Bank (M.D.P.D.), Institut du Cerveau et de la Moelle épinière (ICM), Paris, France
| | - Franck Bielle
- From the Sorbonne Université (A.L.D.S.,M.D.P.D., L.N., M.D.P.D., J.L., M.G., S.L., Francesca Branzoli), Inserm, CNRS, Paris Brain Institute-Institut du Cerveau (ICM), Paris, France. Equipe labellisée LNCC; Service de Neurologie 2-Mazarin (A.L.D.S.,M.D.P.D., M.D.P.D., C.D.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Neuroradiologie Diagnostique et Interventionnelle (L.N., D.G., S.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Neurology Unit (G.B.), IRCCS San Raffaele Scientific Institute, Milan, Italy; Centre de NeuroImagerie de Recherche (CENIR) (R.V., S.L., Francesca Branzoli), Institut du Cerveau (ICM), Paris, France; Service de Neurochirurgie (L.C., B.B.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Biochimie Métabolique (C.P.), AP-HP, Hôpital Necker, Paris, France; Laboratoire R Escourolle (J.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Drug Development Department (DITEP) (C.B.), Gustave Roussy, Villejuif, France; Service de Radiologie (J.S.), Fondation Ophtalmologique Adolphe de Rothschild, Paris, France; Radiotherapy Department (F.D.), Gustave Roussy University Hospital, Villejuif, Cedex, France; Center for Magnetic Resonance Research (D.K.D., M.M.), Department of Radiology, Minneapolis, MN; and OncoNeuroTek Tumor Bank (M.D.P.D.), Institut du Cerveau et de la Moelle épinière (ICM), Paris, France
| | - Julie Lerond
- From the Sorbonne Université (A.L.D.S.,M.D.P.D., L.N., M.D.P.D., J.L., M.G., S.L., Francesca Branzoli), Inserm, CNRS, Paris Brain Institute-Institut du Cerveau (ICM), Paris, France. Equipe labellisée LNCC; Service de Neurologie 2-Mazarin (A.L.D.S.,M.D.P.D., M.D.P.D., C.D.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Neuroradiologie Diagnostique et Interventionnelle (L.N., D.G., S.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Neurology Unit (G.B.), IRCCS San Raffaele Scientific Institute, Milan, Italy; Centre de NeuroImagerie de Recherche (CENIR) (R.V., S.L., Francesca Branzoli), Institut du Cerveau (ICM), Paris, France; Service de Neurochirurgie (L.C., B.B.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Biochimie Métabolique (C.P.), AP-HP, Hôpital Necker, Paris, France; Laboratoire R Escourolle (J.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Drug Development Department (DITEP) (C.B.), Gustave Roussy, Villejuif, France; Service de Radiologie (J.S.), Fondation Ophtalmologique Adolphe de Rothschild, Paris, France; Radiotherapy Department (F.D.), Gustave Roussy University Hospital, Villejuif, Cedex, France; Center for Magnetic Resonance Research (D.K.D., M.M.), Department of Radiology, Minneapolis, MN; and OncoNeuroTek Tumor Bank (M.D.P.D.), Institut du Cerveau et de la Moelle épinière (ICM), Paris, France
| | - Marine Giry
- From the Sorbonne Université (A.L.D.S.,M.D.P.D., L.N., M.D.P.D., J.L., M.G., S.L., Francesca Branzoli), Inserm, CNRS, Paris Brain Institute-Institut du Cerveau (ICM), Paris, France. Equipe labellisée LNCC; Service de Neurologie 2-Mazarin (A.L.D.S.,M.D.P.D., M.D.P.D., C.D.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Neuroradiologie Diagnostique et Interventionnelle (L.N., D.G., S.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Neurology Unit (G.B.), IRCCS San Raffaele Scientific Institute, Milan, Italy; Centre de NeuroImagerie de Recherche (CENIR) (R.V., S.L., Francesca Branzoli), Institut du Cerveau (ICM), Paris, France; Service de Neurochirurgie (L.C., B.B.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Biochimie Métabolique (C.P.), AP-HP, Hôpital Necker, Paris, France; Laboratoire R Escourolle (J.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Drug Development Department (DITEP) (C.B.), Gustave Roussy, Villejuif, France; Service de Radiologie (J.S.), Fondation Ophtalmologique Adolphe de Rothschild, Paris, France; Radiotherapy Department (F.D.), Gustave Roussy University Hospital, Villejuif, Cedex, France; Center for Magnetic Resonance Research (D.K.D., M.M.), Department of Radiology, Minneapolis, MN; and OncoNeuroTek Tumor Bank (M.D.P.D.), Institut du Cerveau et de la Moelle épinière (ICM), Paris, France
| | - Chiara Villa
- From the Sorbonne Université (A.L.D.S.,M.D.P.D., L.N., M.D.P.D., J.L., M.G., S.L., Francesca Branzoli), Inserm, CNRS, Paris Brain Institute-Institut du Cerveau (ICM), Paris, France. Equipe labellisée LNCC; Service de Neurologie 2-Mazarin (A.L.D.S.,M.D.P.D., M.D.P.D., C.D.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Neuroradiologie Diagnostique et Interventionnelle (L.N., D.G., S.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Neurology Unit (G.B.), IRCCS San Raffaele Scientific Institute, Milan, Italy; Centre de NeuroImagerie de Recherche (CENIR) (R.V., S.L., Francesca Branzoli), Institut du Cerveau (ICM), Paris, France; Service de Neurochirurgie (L.C., B.B.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Biochimie Métabolique (C.P.), AP-HP, Hôpital Necker, Paris, France; Laboratoire R Escourolle (J.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Drug Development Department (DITEP) (C.B.), Gustave Roussy, Villejuif, France; Service de Radiologie (J.S.), Fondation Ophtalmologique Adolphe de Rothschild, Paris, France; Radiotherapy Department (F.D.), Gustave Roussy University Hospital, Villejuif, Cedex, France; Center for Magnetic Resonance Research (D.K.D., M.M.), Department of Radiology, Minneapolis, MN; and OncoNeuroTek Tumor Bank (M.D.P.D.), Institut du Cerveau et de la Moelle épinière (ICM), Paris, France
| | - Bertrand Baussart
- From the Sorbonne Université (A.L.D.S.,M.D.P.D., L.N., M.D.P.D., J.L., M.G., S.L., Francesca Branzoli), Inserm, CNRS, Paris Brain Institute-Institut du Cerveau (ICM), Paris, France. Equipe labellisée LNCC; Service de Neurologie 2-Mazarin (A.L.D.S.,M.D.P.D., M.D.P.D., C.D.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Neuroradiologie Diagnostique et Interventionnelle (L.N., D.G., S.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Neurology Unit (G.B.), IRCCS San Raffaele Scientific Institute, Milan, Italy; Centre de NeuroImagerie de Recherche (CENIR) (R.V., S.L., Francesca Branzoli), Institut du Cerveau (ICM), Paris, France; Service de Neurochirurgie (L.C., B.B.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Biochimie Métabolique (C.P.), AP-HP, Hôpital Necker, Paris, France; Laboratoire R Escourolle (J.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Drug Development Department (DITEP) (C.B.), Gustave Roussy, Villejuif, France; Service de Radiologie (J.S.), Fondation Ophtalmologique Adolphe de Rothschild, Paris, France; Radiotherapy Department (F.D.), Gustave Roussy University Hospital, Villejuif, Cedex, France; Center for Magnetic Resonance Research (D.K.D., M.M.), Department of Radiology, Minneapolis, MN; and OncoNeuroTek Tumor Bank (M.D.P.D.), Institut du Cerveau et de la Moelle épinière (ICM), Paris, France
| | - Caroline Dehais
- From the Sorbonne Université (A.L.D.S.,M.D.P.D., L.N., M.D.P.D., J.L., M.G., S.L., Francesca Branzoli), Inserm, CNRS, Paris Brain Institute-Institut du Cerveau (ICM), Paris, France. Equipe labellisée LNCC; Service de Neurologie 2-Mazarin (A.L.D.S.,M.D.P.D., M.D.P.D., C.D.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Neuroradiologie Diagnostique et Interventionnelle (L.N., D.G., S.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Neurology Unit (G.B.), IRCCS San Raffaele Scientific Institute, Milan, Italy; Centre de NeuroImagerie de Recherche (CENIR) (R.V., S.L., Francesca Branzoli), Institut du Cerveau (ICM), Paris, France; Service de Neurochirurgie (L.C., B.B.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Biochimie Métabolique (C.P.), AP-HP, Hôpital Necker, Paris, France; Laboratoire R Escourolle (J.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Drug Development Department (DITEP) (C.B.), Gustave Roussy, Villejuif, France; Service de Radiologie (J.S.), Fondation Ophtalmologique Adolphe de Rothschild, Paris, France; Radiotherapy Department (F.D.), Gustave Roussy University Hospital, Villejuif, Cedex, France; Center for Magnetic Resonance Research (D.K.D., M.M.), Department of Radiology, Minneapolis, MN; and OncoNeuroTek Tumor Bank (M.D.P.D.), Institut du Cerveau et de la Moelle épinière (ICM), Paris, France
| | - Damien Galanaud
- From the Sorbonne Université (A.L.D.S.,M.D.P.D., L.N., M.D.P.D., J.L., M.G., S.L., Francesca Branzoli), Inserm, CNRS, Paris Brain Institute-Institut du Cerveau (ICM), Paris, France. Equipe labellisée LNCC; Service de Neurologie 2-Mazarin (A.L.D.S.,M.D.P.D., M.D.P.D., C.D.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Neuroradiologie Diagnostique et Interventionnelle (L.N., D.G., S.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Neurology Unit (G.B.), IRCCS San Raffaele Scientific Institute, Milan, Italy; Centre de NeuroImagerie de Recherche (CENIR) (R.V., S.L., Francesca Branzoli), Institut du Cerveau (ICM), Paris, France; Service de Neurochirurgie (L.C., B.B.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Biochimie Métabolique (C.P.), AP-HP, Hôpital Necker, Paris, France; Laboratoire R Escourolle (J.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Drug Development Department (DITEP) (C.B.), Gustave Roussy, Villejuif, France; Service de Radiologie (J.S.), Fondation Ophtalmologique Adolphe de Rothschild, Paris, France; Radiotherapy Department (F.D.), Gustave Roussy University Hospital, Villejuif, Cedex, France; Center for Magnetic Resonance Research (D.K.D., M.M.), Department of Radiology, Minneapolis, MN; and OncoNeuroTek Tumor Bank (M.D.P.D.), Institut du Cerveau et de la Moelle épinière (ICM), Paris, France
| | - Capucine Baldini
- From the Sorbonne Université (A.L.D.S.,M.D.P.D., L.N., M.D.P.D., J.L., M.G., S.L., Francesca Branzoli), Inserm, CNRS, Paris Brain Institute-Institut du Cerveau (ICM), Paris, France. Equipe labellisée LNCC; Service de Neurologie 2-Mazarin (A.L.D.S.,M.D.P.D., M.D.P.D., C.D.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Neuroradiologie Diagnostique et Interventionnelle (L.N., D.G., S.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Neurology Unit (G.B.), IRCCS San Raffaele Scientific Institute, Milan, Italy; Centre de NeuroImagerie de Recherche (CENIR) (R.V., S.L., Francesca Branzoli), Institut du Cerveau (ICM), Paris, France; Service de Neurochirurgie (L.C., B.B.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Biochimie Métabolique (C.P.), AP-HP, Hôpital Necker, Paris, France; Laboratoire R Escourolle (J.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Drug Development Department (DITEP) (C.B.), Gustave Roussy, Villejuif, France; Service de Radiologie (J.S.), Fondation Ophtalmologique Adolphe de Rothschild, Paris, France; Radiotherapy Department (F.D.), Gustave Roussy University Hospital, Villejuif, Cedex, France; Center for Magnetic Resonance Research (D.K.D., M.M.), Department of Radiology, Minneapolis, MN; and OncoNeuroTek Tumor Bank (M.D.P.D.), Institut du Cerveau et de la Moelle épinière (ICM), Paris, France
| | - Julien Savatovsky
- From the Sorbonne Université (A.L.D.S.,M.D.P.D., L.N., M.D.P.D., J.L., M.G., S.L., Francesca Branzoli), Inserm, CNRS, Paris Brain Institute-Institut du Cerveau (ICM), Paris, France. Equipe labellisée LNCC; Service de Neurologie 2-Mazarin (A.L.D.S.,M.D.P.D., M.D.P.D., C.D.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Neuroradiologie Diagnostique et Interventionnelle (L.N., D.G., S.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Neurology Unit (G.B.), IRCCS San Raffaele Scientific Institute, Milan, Italy; Centre de NeuroImagerie de Recherche (CENIR) (R.V., S.L., Francesca Branzoli), Institut du Cerveau (ICM), Paris, France; Service de Neurochirurgie (L.C., B.B.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Biochimie Métabolique (C.P.), AP-HP, Hôpital Necker, Paris, France; Laboratoire R Escourolle (J.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Drug Development Department (DITEP) (C.B.), Gustave Roussy, Villejuif, France; Service de Radiologie (J.S.), Fondation Ophtalmologique Adolphe de Rothschild, Paris, France; Radiotherapy Department (F.D.), Gustave Roussy University Hospital, Villejuif, Cedex, France; Center for Magnetic Resonance Research (D.K.D., M.M.), Department of Radiology, Minneapolis, MN; and OncoNeuroTek Tumor Bank (M.D.P.D.), Institut du Cerveau et de la Moelle épinière (ICM), Paris, France
| | - Frédéric Dhermain
- From the Sorbonne Université (A.L.D.S.,M.D.P.D., L.N., M.D.P.D., J.L., M.G., S.L., Francesca Branzoli), Inserm, CNRS, Paris Brain Institute-Institut du Cerveau (ICM), Paris, France. Equipe labellisée LNCC; Service de Neurologie 2-Mazarin (A.L.D.S.,M.D.P.D., M.D.P.D., C.D.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Neuroradiologie Diagnostique et Interventionnelle (L.N., D.G., S.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Neurology Unit (G.B.), IRCCS San Raffaele Scientific Institute, Milan, Italy; Centre de NeuroImagerie de Recherche (CENIR) (R.V., S.L., Francesca Branzoli), Institut du Cerveau (ICM), Paris, France; Service de Neurochirurgie (L.C., B.B.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Biochimie Métabolique (C.P.), AP-HP, Hôpital Necker, Paris, France; Laboratoire R Escourolle (J.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Drug Development Department (DITEP) (C.B.), Gustave Roussy, Villejuif, France; Service de Radiologie (J.S.), Fondation Ophtalmologique Adolphe de Rothschild, Paris, France; Radiotherapy Department (F.D.), Gustave Roussy University Hospital, Villejuif, Cedex, France; Center for Magnetic Resonance Research (D.K.D., M.M.), Department of Radiology, Minneapolis, MN; and OncoNeuroTek Tumor Bank (M.D.P.D.), Institut du Cerveau et de la Moelle épinière (ICM), Paris, France
| | - Dinesh K Deelchand
- From the Sorbonne Université (A.L.D.S.,M.D.P.D., L.N., M.D.P.D., J.L., M.G., S.L., Francesca Branzoli), Inserm, CNRS, Paris Brain Institute-Institut du Cerveau (ICM), Paris, France. Equipe labellisée LNCC; Service de Neurologie 2-Mazarin (A.L.D.S.,M.D.P.D., M.D.P.D., C.D.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Neuroradiologie Diagnostique et Interventionnelle (L.N., D.G., S.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Neurology Unit (G.B.), IRCCS San Raffaele Scientific Institute, Milan, Italy; Centre de NeuroImagerie de Recherche (CENIR) (R.V., S.L., Francesca Branzoli), Institut du Cerveau (ICM), Paris, France; Service de Neurochirurgie (L.C., B.B.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Biochimie Métabolique (C.P.), AP-HP, Hôpital Necker, Paris, France; Laboratoire R Escourolle (J.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Drug Development Department (DITEP) (C.B.), Gustave Roussy, Villejuif, France; Service de Radiologie (J.S.), Fondation Ophtalmologique Adolphe de Rothschild, Paris, France; Radiotherapy Department (F.D.), Gustave Roussy University Hospital, Villejuif, Cedex, France; Center for Magnetic Resonance Research (D.K.D., M.M.), Department of Radiology, Minneapolis, MN; and OncoNeuroTek Tumor Bank (M.D.P.D.), Institut du Cerveau et de la Moelle épinière (ICM), Paris, France
| | - Chris Ottolenghi
- From the Sorbonne Université (A.L.D.S.,M.D.P.D., L.N., M.D.P.D., J.L., M.G., S.L., Francesca Branzoli), Inserm, CNRS, Paris Brain Institute-Institut du Cerveau (ICM), Paris, France. Equipe labellisée LNCC; Service de Neurologie 2-Mazarin (A.L.D.S.,M.D.P.D., M.D.P.D., C.D.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Neuroradiologie Diagnostique et Interventionnelle (L.N., D.G., S.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Neurology Unit (G.B.), IRCCS San Raffaele Scientific Institute, Milan, Italy; Centre de NeuroImagerie de Recherche (CENIR) (R.V., S.L., Francesca Branzoli), Institut du Cerveau (ICM), Paris, France; Service de Neurochirurgie (L.C., B.B.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Biochimie Métabolique (C.P.), AP-HP, Hôpital Necker, Paris, France; Laboratoire R Escourolle (J.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Drug Development Department (DITEP) (C.B.), Gustave Roussy, Villejuif, France; Service de Radiologie (J.S.), Fondation Ophtalmologique Adolphe de Rothschild, Paris, France; Radiotherapy Department (F.D.), Gustave Roussy University Hospital, Villejuif, Cedex, France; Center for Magnetic Resonance Research (D.K.D., M.M.), Department of Radiology, Minneapolis, MN; and OncoNeuroTek Tumor Bank (M.D.P.D.), Institut du Cerveau et de la Moelle épinière (ICM), Paris, France
| | - Stéphane Lehéricy
- From the Sorbonne Université (A.L.D.S.,M.D.P.D., L.N., M.D.P.D., J.L., M.G., S.L., Francesca Branzoli), Inserm, CNRS, Paris Brain Institute-Institut du Cerveau (ICM), Paris, France. Equipe labellisée LNCC; Service de Neurologie 2-Mazarin (A.L.D.S.,M.D.P.D., M.D.P.D., C.D.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Neuroradiologie Diagnostique et Interventionnelle (L.N., D.G., S.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Neurology Unit (G.B.), IRCCS San Raffaele Scientific Institute, Milan, Italy; Centre de NeuroImagerie de Recherche (CENIR) (R.V., S.L., Francesca Branzoli), Institut du Cerveau (ICM), Paris, France; Service de Neurochirurgie (L.C., B.B.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Biochimie Métabolique (C.P.), AP-HP, Hôpital Necker, Paris, France; Laboratoire R Escourolle (J.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Drug Development Department (DITEP) (C.B.), Gustave Roussy, Villejuif, France; Service de Radiologie (J.S.), Fondation Ophtalmologique Adolphe de Rothschild, Paris, France; Radiotherapy Department (F.D.), Gustave Roussy University Hospital, Villejuif, Cedex, France; Center for Magnetic Resonance Research (D.K.D., M.M.), Department of Radiology, Minneapolis, MN; and OncoNeuroTek Tumor Bank (M.D.P.D.), Institut du Cerveau et de la Moelle épinière (ICM), Paris, France
| | - Małgorzata Marjańska
- From the Sorbonne Université (A.L.D.S.,M.D.P.D., L.N., M.D.P.D., J.L., M.G., S.L., Francesca Branzoli), Inserm, CNRS, Paris Brain Institute-Institut du Cerveau (ICM), Paris, France. Equipe labellisée LNCC; Service de Neurologie 2-Mazarin (A.L.D.S.,M.D.P.D., M.D.P.D., C.D.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Neuroradiologie Diagnostique et Interventionnelle (L.N., D.G., S.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Neurology Unit (G.B.), IRCCS San Raffaele Scientific Institute, Milan, Italy; Centre de NeuroImagerie de Recherche (CENIR) (R.V., S.L., Francesca Branzoli), Institut du Cerveau (ICM), Paris, France; Service de Neurochirurgie (L.C., B.B.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Biochimie Métabolique (C.P.), AP-HP, Hôpital Necker, Paris, France; Laboratoire R Escourolle (J.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Drug Development Department (DITEP) (C.B.), Gustave Roussy, Villejuif, France; Service de Radiologie (J.S.), Fondation Ophtalmologique Adolphe de Rothschild, Paris, France; Radiotherapy Department (F.D.), Gustave Roussy University Hospital, Villejuif, Cedex, France; Center for Magnetic Resonance Research (D.K.D., M.M.), Department of Radiology, Minneapolis, MN; and OncoNeuroTek Tumor Bank (M.D.P.D.), Institut du Cerveau et de la Moelle épinière (ICM), Paris, France
| | - Francesca Branzoli
- From the Sorbonne Université (A.L.D.S.,M.D.P.D., L.N., M.D.P.D., J.L., M.G., S.L., Francesca Branzoli), Inserm, CNRS, Paris Brain Institute-Institut du Cerveau (ICM), Paris, France. Equipe labellisée LNCC; Service de Neurologie 2-Mazarin (A.L.D.S.,M.D.P.D., M.D.P.D., C.D.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Neuroradiologie Diagnostique et Interventionnelle (L.N., D.G., S.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Neurology Unit (G.B.), IRCCS San Raffaele Scientific Institute, Milan, Italy; Centre de NeuroImagerie de Recherche (CENIR) (R.V., S.L., Francesca Branzoli), Institut du Cerveau (ICM), Paris, France; Service de Neurochirurgie (L.C., B.B.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Biochimie Métabolique (C.P.), AP-HP, Hôpital Necker, Paris, France; Laboratoire R Escourolle (J.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Drug Development Department (DITEP) (C.B.), Gustave Roussy, Villejuif, France; Service de Radiologie (J.S.), Fondation Ophtalmologique Adolphe de Rothschild, Paris, France; Radiotherapy Department (F.D.), Gustave Roussy University Hospital, Villejuif, Cedex, France; Center for Magnetic Resonance Research (D.K.D., M.M.), Department of Radiology, Minneapolis, MN; and OncoNeuroTek Tumor Bank (M.D.P.D.), Institut du Cerveau et de la Moelle épinière (ICM), Paris, France
| | - Marc Sanson
- From the Sorbonne Université (A.L.D.S.,M.D.P.D., L.N., M.D.P.D., J.L., M.G., S.L., Francesca Branzoli), Inserm, CNRS, Paris Brain Institute-Institut du Cerveau (ICM), Paris, France. Equipe labellisée LNCC; Service de Neurologie 2-Mazarin (A.L.D.S.,M.D.P.D., M.D.P.D., C.D.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Neuroradiologie Diagnostique et Interventionnelle (L.N., D.G., S.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Neurology Unit (G.B.), IRCCS San Raffaele Scientific Institute, Milan, Italy; Centre de NeuroImagerie de Recherche (CENIR) (R.V., S.L., Francesca Branzoli), Institut du Cerveau (ICM), Paris, France; Service de Neurochirurgie (L.C., B.B.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Service de Biochimie Métabolique (C.P.), AP-HP, Hôpital Necker, Paris, France; Laboratoire R Escourolle (J.L.), AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Paris, France; Drug Development Department (DITEP) (C.B.), Gustave Roussy, Villejuif, France; Service de Radiologie (J.S.), Fondation Ophtalmologique Adolphe de Rothschild, Paris, France; Radiotherapy Department (F.D.), Gustave Roussy University Hospital, Villejuif, Cedex, France; Center for Magnetic Resonance Research (D.K.D., M.M.), Department of Radiology, Minneapolis, MN; and OncoNeuroTek Tumor Bank (M.D.P.D.), Institut du Cerveau et de la Moelle épinière (ICM), Paris, France.
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MRI features predict tumor grade in isocitrate dehydrogenase (IDH)-mutant astrocytoma and oligodendroglioma. Neuroradiology 2023; 65:121-129. [PMID: 35953567 DOI: 10.1007/s00234-022-03038-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Accepted: 08/07/2022] [Indexed: 01/28/2023]
Abstract
PURPOSE Nearly all literature for predicting tumor grade in astrocytoma and oligodendroglioma pre-dates the molecular classification system. We investigated the association between contrast enhancement, ADC, and rCBV with tumor grade separately for IDH-mutant astrocytomas and molecularly-defined oligodendrogliomas. METHODS For this retrospective study, 44 patients with IDH-mutant astrocytomas (WHO grades II, III, or IV) and 39 patients with oligodendrogliomas (IDH-mutant and 1p/19q codeleted) (WHO grade II or III) were enrolled. Two readers independently assessed preoperative MRI for contrast enhancement, ADC, and rCBV. Inter-reader agreement was calculated, and statistical associations between MRI metrics and WHO grade were determined per reader. RESULTS For IDH-mutant astrocytomas, both readers found a stepwise positive association between contrast enhancement and WHO grade (Reader A: OR 7.79 [1.97, 30.80], p = 0.003; Reader B: OR 6.62 [1.70, 25.82], p = 0.006); both readers found that ADC was negatively associated with WHO grade (Reader A: OR 0.74 [0.61, 0.90], p = 0.002); Reader B: OR 0.80 [0.66, 0.96], p = 0.017), and both readers found that rCBV was positively associated with WHO grade (Reader A: OR 2.33 [1.35, 4.00], p = 0.002; Reader B: OR 2.13 [1.30, 3.57], p = 0.003). For oligodendrogliomas, both readers found a positive association between contrast enhancement and WHO grade (Reader A: OR 15.33 [2.56, 91.95], p = 0.003; Reader B: OR 20.00 [2.19, 182.45], p = 0.008), but neither reader found an association between ADC or rCBV and WHO grade. CONCLUSIONS Contrast enhancement predicts WHO grade for IDH-mutant astrocytomas and oligodendrogliomas. ADC and rCBV predict WHO grade for IDH-mutant astrocytomas, but not for oligodendrogliomas.
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Minami N, Hong D, Stevers N, Barger CJ, Radoul M, Hong C, Chen L, Kim Y, Batsios G, Gillespie AM, Pieper RO, Costello JF, Viswanath P, Ronen SM. Imaging biomarkers of TERT or GABPB1 silencing in TERT-positive glioblastoma. Neuro Oncol 2022; 24:1898-1910. [PMID: 35460557 PMCID: PMC9629440 DOI: 10.1093/neuonc/noac112] [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] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND TERT promoter mutations are observed in 80% of wild-type IDH glioblastoma (GBM). Moreover, the upstream TERT transcription factor GABPB1 was recently identified as a cancer-specific therapeutic target for tumors harboring a TERT promoter mutation. In that context, noninvasive imaging biomarkers are needed for the detection of TERT modulation. METHODS Multiple GBM models were investigated as cells and in vivo tumors and the impact of TERT silencing, either directly or by targeting GABPB1, was determined using 1H and hyperpolarized 13C magnetic resonance spectroscopy (MRS). Changes in associated metabolic enzymes were also investigated. RESULTS 1H-MRS revealed that lactate and glutathione (GSH) were the most significantly altered metabolites when either TERT or GABPB1 was silenced, and lactate and GSH levels were correlated with cellular TERT expression. Consistent with the drop in lactate, 13C-MRS showed that hyperpolarized [1-13C]lactate production from [1-13C]pyruvate was also reduced when TERT was silenced. Mechanistically, the reduction in GSH was associated with a reduction in pentose phosphate pathway flux, reduced activity of glucose-6-phosphate dehydrogenase, and reduced NADPH. The drop in lactate and hyperpolarized lactate were associated with reductions in glycolytic flux, NADH, and expression/activity of GLUT1, monocarboxylate transporters, and lactate dehydrogenase A. CONCLUSIONS Our study indicates that MRS-detectable GSH, lactate, and lactate production could serve as metabolic biomarkers of response to emerging TERT-targeted therapies for GBM with activating TERT promoter mutations. Importantly these biomarkers are readily translatable to the clinic, and thus could ultimately improve GBM patient management.
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Affiliation(s)
- Noriaki Minami
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Donghyun Hong
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Nicholas Stevers
- Department of Neurological Surgery, University of California, San Francisco, California, USA
| | - Carter J Barger
- Department of Neurological Surgery, University of California, San Francisco, California, USA
| | - Marina Radoul
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Chibo Hong
- Department of Neurological Surgery, University of California, San Francisco, California, USA
| | - Lee Chen
- Department of Neurological Surgery, University of California, San Francisco, California, USA
| | - Yaewon Kim
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Georgios Batsios
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Anne Marie Gillespie
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Russel O Pieper
- Department of Neurological Surgery, University of California, San Francisco, California, USA
| | - Joseph F Costello
- Department of Neurological Surgery, University of California, San Francisco, California, USA
| | - Pavithra Viswanath
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Sabrina M Ronen
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
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McCarthy L, Verma G, Hangel G, Neal A, Moffat BA, Stockmann JP, Andronesi OC, Balchandani P, Hadjipanayis CG. Application of 7T MRS to High-Grade Gliomas. AJNR Am J Neuroradiol 2022; 43:1378-1395. [PMID: 35618424 PMCID: PMC9575545 DOI: 10.3174/ajnr.a7502] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Accepted: 02/11/2022] [Indexed: 01/26/2023]
Abstract
MRS, including single-voxel spectroscopy and MR spectroscopic imaging, captures metabolites in high-grade gliomas. Emerging evidence indicates that 7T MRS may be more sensitive to aberrant metabolic activity than lower-field strength MRS. However, the literature on the use of 7T MRS to visualize high-grade gliomas has not been summarized. We aimed to identify metabolic information provided by 7T MRS, optimal spectroscopic sequences, and areas for improvement in and new applications for 7T MRS. Literature was found on PubMed using "high-grade glioma," "malignant glioma," "glioblastoma," "anaplastic astrocytoma," "7T," "MR spectroscopy," and "MR spectroscopic imaging." 7T MRS offers higher SNR, modestly improved spatial resolution, and better resolution of overlapping resonances. 7T MRS also yields reduced Cramér-Rao lower bound values. These features help to quantify D-2-hydroxyglutarate in isocitrate dehydrogenase 1 and 2 gliomas and to isolate variable glutamate, increased glutamine, and increased glycine with higher sensitivity and specificity. 7T MRS may better characterize tumor infiltration and treatment effect in high-grade gliomas, though further study is necessary. 7T MRS will benefit from increased sample size; reductions in field inhomogeneity, specific absorption rate, and acquisition time; and advanced editing techniques. These findings suggest that 7T MRS may advance understanding of high-grade glioma metabolism, with reduced Cramér-Rao lower bound values and better measurement of smaller metabolite signals. Nevertheless, 7T is not widely used clinically, and technical improvements are necessary. 7T MRS isolates metabolites that may be valuable therapeutic targets in high-grade gliomas, potentially resulting in wider ranging neuro-oncologic applications.
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Affiliation(s)
- L McCarthy
- From the Department of Neurosurgery (L.M., C.G.H.), Icahn School of Medicine at Mount Sinai, Mount Sinai Health System, New York, New York
| | - G Verma
- BioMedical Engineering and Imaging Institute (G.V., P.B.), Icahn School of Medicine at Mount Sinai, New York, New York
| | - G Hangel
- Department of Neurosurgery (G.H.)
- High-field MR Center (G.H.), Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - A Neal
- Department of Medicine (A.N.), Royal Melbourne Hospital, University of Melbourne, Melbourne, Australia
- Department of Neurology (A.N.), Royal Melbourne Hospital, Melbourne, Australia
| | - B A Moffat
- The Melbourne Brain Centre Imaging Unit (B.A.M.), Department of Radiology, The University of Melbourne, Melbourne, Australia
| | - J P Stockmann
- A. A. Martinos Center for Biomedical Imaging (J.P.S., O.C.A.), Massachusetts General Hospital, Charlestown, Massachusetts
- Harvard Medical School (J.P.S., O.C.A.), Boston, Massachusetts
| | - O C Andronesi
- A. A. Martinos Center for Biomedical Imaging (J.P.S., O.C.A.), Massachusetts General Hospital, Charlestown, Massachusetts
- Harvard Medical School (J.P.S., O.C.A.), Boston, Massachusetts
| | - P Balchandani
- BioMedical Engineering and Imaging Institute (G.V., P.B.), Icahn School of Medicine at Mount Sinai, New York, New York
| | - C G Hadjipanayis
- From the Department of Neurosurgery (L.M., C.G.H.), Icahn School of Medicine at Mount Sinai, Mount Sinai Health System, New York, New York
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Karabacak M, Ozkara BB, Mordag S, Bisdas S. Deep learning for prediction of isocitrate dehydrogenase mutation in gliomas: a critical approach, systematic review and meta-analysis of the diagnostic test performance using a Bayesian approach. Quant Imaging Med Surg 2022; 12:4033-4046. [PMID: 35919062 PMCID: PMC9338374 DOI: 10.21037/qims-22-34] [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: 01/13/2022] [Accepted: 05/25/2022] [Indexed: 11/08/2022]
Abstract
Background Conventionally, identifying isocitrate dehydrogenase (IDH) mutation in gliomas is based on histopathological analysis of tissue specimens acquired via stereotactic biopsy or definitive resection. Accurate pre-treatment prediction of IDH mutation status using magnetic resonance imaging (MRI) can guide clinical decision-making. We aim to evaluate the diagnostic performance of deep learning (DL) to determine IDH mutation status in gliomas. Methods A systematic search of Cochrane Library, Web of Science, Medline, and Scopus was conducted to identify relevant publications until August 1, 2021. Articles were included if all the following criteria were met: (I) patients with histopathologically confirmed World Health Organization (WHO) grade II, III, or IV gliomas; (II) histopathological examination with the IDH mutation; (III) DL was used to predict the IDH mutation status; (IV) sufficient data for reconstruction of confusion matrices in terms of the diagnostic performance of the DL algorithms; and (V) original research articles. Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) and Checklist for Artificial Intelligence in Medical Imaging (CLAIM) was used to assess the studies' quality. Bayes theorem was utilized to calculate the posttest probability. Results Four studies with a total of 1,295 patients were included. In the training set, the pooled sensitivity, specificity, and area under the summary receiver operating characteristic (SROC) curve were 93.9%, 90.9% and 0.958, respectively. In the validation set, the pooled sensitivity, specificity, and area under the SROC curve were 90.8%, 85.5% and 0.939, respectively. With a known pretest probability of 80.2%, the Bayes theorem yielded a posttest probability of 97.6% and 96.0% for a positive test and 27.0% and 30.6% for a negative test for training sets and validation sets, respectively. Discussion This is the first meta-analysis that summarizes the diagnostic performance of DL in predicting IDH mutation status in gliomas via the Bayes theorem. DL algorithms demonstrate excellent diagnostic performance in predicting IDH mutation in gliomas. Radiomic features associated with IDH mutation, and its underlying pathophysiology extracted from advanced MRI may improve prediction probability. However, more studies are required to optimize and increase its reliability. Limitations include obtaining some data via email and lack of training and test sets statistics.
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Affiliation(s)
- Mert Karabacak
- Cerrahpasa Faculty of Medicine, Istanbul University-Cerrahpasa, Cerrahpasa, Istanbul, Turkey
| | - Burak Berksu Ozkara
- Cerrahpasa Faculty of Medicine, Istanbul University-Cerrahpasa, Cerrahpasa, Istanbul, Turkey
| | - Seren Mordag
- Faculty of Medicine, Hacettepe University, Sihhiye, Ankara, Turkey
| | - Sotirios Bisdas
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, London, UK
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Yano H, Ikegame Y, Miwa K, Nakayama N, Maruyama T, Ikuta S, Yokoyama K, Muragaki Y, Iwama T, Shinoda J. Radiological Prediction of Isocitrate Dehydrogenase (IDH) Mutational Status and Pathological Verification for Lower-Grade Astrocytomas. Cureus 2022; 14:e27157. [PMID: 36017268 PMCID: PMC9393092 DOI: 10.7759/cureus.27157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/22/2022] [Indexed: 11/06/2022] Open
Abstract
Background and objective The isocitrate dehydrogenase (IDH) status of patients with World Health Organization (WHO) grade II or III astrocytoma is essential for understanding its biological features and determining therapeutic strategies. This study aimed to use radiological analysis to predict the IDH status of patients with lower-grade astrocytomas and to verify the pathological implications. Methods In this study, 47 patients with grade II (17 cases) or III astrocytomas (30 cases), based on 2016 WHO Classification, underwent methionine (MET) positron emission tomography (PET) and magnetic resonance spectroscopy (MRS) on the same day between January 2013 and June 2020. The patients were retrospectively assessed. Immunohistochemistry showed 23 cases of IDH-mutant and 24 of IDH-wildtype. Based on fluid-attenuated recovery inversion (FLAIR)/T2 imaging, three doctors blinded to clinical data independently allocated 18 patients to the clear boundary group between the tumor and the normal brain and 29 to the unclear boundary group. The peak ratios of N-acetylaspartate (NAA)/creatine (Cr), choline (Cho)/Cr, and Cho/NAA and the tumor-to-normal region (T/N) ratio for maximum accumulation in MET-PET were calculated. For statistical analysis, Fisher’s exact test was used to assess associations between two variables, and the Mann-Whitney U test to compare the values between the IDH-wildtype and IDH-mutant groups. The optimal cut-off values of MET T/N ratio and MRS parameters for discriminating IDH-wildtype from IDH-mutant were obtained using receiver operating characteristics curves. Results The unclear boundary group had significantly more IDH-wildtype cases than the clear boundary group (P<0.001). The IDH-wildtype group had significantly lower Cho/Cr (<1.84) and Cho/NAA (<1.62) ratios (P=0.02 and P=0.047, respectively) and a higher MET T/N ratio (>1.44, P=0.02) than the IDH-mutant group. The odds for the IDH-wildtype were 0.22 for patients who fulfilled none of the four criteria, including boundary status and three ratios, and 0.9 for all four criteria. Conclusions These results suggest that the combination of MRI, MRS, and MET-PET examination could be helpful for the prediction of IDH status in WHO grade II/III gliomas.
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Autry AW, Lafontaine M, Jalbert L, Phillips E, Phillips JJ, Villanueva-Meyer J, Berger MS, Chang SM, Li Y. Spectroscopic imaging of D-2-hydroxyglutarate and other metabolites in pre-surgical patients with IDH-mutant lower-grade gliomas. J Neurooncol 2022; 159:43-52. [PMID: 35672531 PMCID: PMC9325821 DOI: 10.1007/s11060-022-04042-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2022] [Accepted: 05/20/2022] [Indexed: 11/01/2022]
Abstract
Abstract
Purpose
Prognostically favorable IDH-mutant gliomas are known to produce oncometabolite D-2-hydroxyglutarate (2HG). In this study, we investigated metabolite-based features of patients with grade 2 and 3 glioma using 2HG-specific in vivo MR spectroscopy, to determine their relationship with image-guided tissue pathology and predictive role in progression-free survival (PFS).
Methods
Forty-five patients received pre-operative MRIs that included 3-D spectroscopy optimized for 2HG detection. Spectral data were reconstructed and quantified to compare metabolite levels according to molecular pathology (IDH1R132H, 1p/19q, and p53); glioma grade; histological subtype; and T2 lesion versus normal-appearing white matter (NAWM) ROIs. Levels of 2HG were correlated with other metabolites and pathological parameters (cellularity, MIB-1) from image-guided tissue samples using Pearson’s correlation test. Metabolites predictive of PFS were evaluated with Cox proportional hazards models.
Results
Quantifiable levels of 2HG in 39/42 (93%) IDH+ and 1/3 (33%) IDH– patients indicated a 91.1% apparent detection accuracy. Myo-inositol/total choline (tCho) showed reduced values in astrocytic (1p/19q-wildtype), p53-mutant, and grade 3 (vs. 2) IDH-mutant gliomas (p < 0.05), all of which exhibited higher proportions of astrocytomas. Compared to NAWM, T2 lesions displayed elevated 2HG+ γ-aminobutyric acid (GABA)/total creatine (tCr) (p < 0.001); reduced glutamate/tCr (p < 0.001); increased myo-inositol/tCr (p < 0.001); and higher tCho/tCr (p < 0.001). Levels of 2HG at sampled tissue locations were significantly associated with tCho (R = 0.62; p = 0.002), total NAA (R = − 0.61; p = 0.002) and cellularity (R = 0.37; p = 0.04) but not MIB-1. Increasing levels of 2HG/tCr (p = 0.0007, HR 5.594) and thresholding (≥ 0.905, median value; p = 0.02) predicted adverse PFS.
Conclusion
In vivo 2HG detection can reasonably be achieved on clinical scanners and increased levels may signal adverse PFS.
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Bumes E, Fellner C, Fellner FA, Fleischanderl K, Häckl M, Lenz S, Linker R, Mirus T, Oefner PJ, Paar C, Proescholdt MA, Riemenschneider MJ, Rosengarth K, Weis S, Wendl C, Wimmer S, Hau P, Gronwald W, Hutterer M. Validation Study for Non-Invasive Prediction of IDH Mutation Status in Patients with Glioma Using In Vivo 1H-Magnetic Resonance Spectroscopy and Machine Learning. Cancers (Basel) 2022; 14:cancers14112762. [PMID: 35681741 PMCID: PMC9179368 DOI: 10.3390/cancers14112762] [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: 04/30/2022] [Revised: 05/24/2022] [Accepted: 05/31/2022] [Indexed: 11/23/2022] Open
Abstract
Simple Summary The enzyme isocitrate dehydrogenase (IDH) affects glioma cell metabolism in multiple ways. Mutation of IDH is not only indicative of the presence of astrocytoma or oligodendroglioma but it also comes with a better prognosis and constitutes a promising therapeutic target. Therefore, determination of IDH mutation status is essential in clinical practice. In most patients, tissue can be obtained by resection or biopsy to determine IDH status histologically. However, in some cases, this is not possible for technical reasons. We recently showed in a small cohort of patients that non-invasive determination of IDH mutation status using proton magnetic resonance spectroscopy (1H-MRS) at 3.0 Tesla (T) together with machine learning techniques is feasible in a standard clinical setting and with acceptable effort. Here, we demonstrate that our approach showed comparably good results in sensitivity (82.6%) and specificity (72.7%) in a larger validation cohort employing 1H-MRS at 1.5 T in a retrospective, distinct setting. We concluded that our method works well regardless of the magnetic field strength and scanner used, and thus, may improve patient care. Abstract The isocitrate dehydrogenase (IDH) mutation status is an indispensable prerequisite for diagnosis of glioma (astrocytoma and oligodendroglioma) according to the WHO classification of brain tumors 2021 and is a potential therapeutic target. Usually, immunohistochemistry followed by sequencing of tumor tissue is performed for this purpose. In clinical routine, however, non-invasive determination of IDH mutation status is desirable in cases where tumor biopsy is not possible and for monitoring neuro-oncological therapies. In a previous publication, we presented reliable prediction of IDH mutation status employing proton magnetic resonance spectroscopy (1H-MRS) on a 3.0 Tesla (T) scanner and machine learning in a prospective cohort of 34 glioma patients. Here, we validated this approach in an independent cohort of 67 patients, for which 1H-MR spectra were acquired at 1.5 T between 2002 and 2007, using the same data analysis approach. Despite different technical conditions, a sensitivity of 82.6% (95% CI, 61.2–95.1%) and a specificity of 72.7% (95% CI, 57.2–85.0%) could be achieved. We concluded that our 1H-MRS based approach can be established in a routine clinical setting with affordable effort and time, independent of technical conditions employed. Therefore, the method provides a non-invasive tool for determining IDH status that is well-applicable in an everyday clinical setting.
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Affiliation(s)
- Elisabeth Bumes
- Department of Neurology and Wilhelm Sander-NeuroOncology Unit, Regensburg University Hospital, 93055 Regensburg, Germany; (R.L.); (P.H.); (M.H.)
- Correspondence: ; Tel.: +49-941-944-18751
| | - Claudia Fellner
- Department of Radiology and Division of Neuroradiology, Regensburg University Hospital, 93055 Regensburg, Germany; (C.F.); (C.W.)
| | - Franz A. Fellner
- Central Institute of Radiology, Kepler University Hospital, 4021 Linz, Austria;
| | - Karin Fleischanderl
- Division of Molecular Pathology, Neuromed Campus, Kepler University Hospital, 4020 Linz, Austria; (K.F.); (S.L.)
| | - Martina Häckl
- Institute of Functional Genomics, University of Regensburg, 93053 Regensburg, Germany; (M.H.); (T.M.); (P.J.O.); (W.G.)
| | - Stefan Lenz
- Division of Molecular Pathology, Neuromed Campus, Kepler University Hospital, 4020 Linz, Austria; (K.F.); (S.L.)
| | - Ralf Linker
- Department of Neurology and Wilhelm Sander-NeuroOncology Unit, Regensburg University Hospital, 93055 Regensburg, Germany; (R.L.); (P.H.); (M.H.)
| | - Tim Mirus
- Institute of Functional Genomics, University of Regensburg, 93053 Regensburg, Germany; (M.H.); (T.M.); (P.J.O.); (W.G.)
| | - Peter J. Oefner
- Institute of Functional Genomics, University of Regensburg, 93053 Regensburg, Germany; (M.H.); (T.M.); (P.J.O.); (W.G.)
| | - Christian Paar
- Institute of Laboratory Medicine, Kepler University Hospital, 4021 Linz, Austria;
| | | | | | - Katharina Rosengarth
- Department of Neurosurgery, Regensburg University Hospital, 93053 Regensburg, Germany; (M.A.P.); (K.R.)
| | - Serge Weis
- Division of Neuropathology, Neuromed Campus, Kepler University Hospital, 4020 Linz, Austria;
| | - Christina Wendl
- Department of Radiology and Division of Neuroradiology, Regensburg University Hospital, 93055 Regensburg, Germany; (C.F.); (C.W.)
| | - Sibylle Wimmer
- Institute of Neuroradiology, Neuromed Campus, Kepler University Hospital, 4020 Linz, Austria;
| | - Peter Hau
- Department of Neurology and Wilhelm Sander-NeuroOncology Unit, Regensburg University Hospital, 93055 Regensburg, Germany; (R.L.); (P.H.); (M.H.)
| | - Wolfram Gronwald
- Institute of Functional Genomics, University of Regensburg, 93053 Regensburg, Germany; (M.H.); (T.M.); (P.J.O.); (W.G.)
| | - Markus Hutterer
- Department of Neurology and Wilhelm Sander-NeuroOncology Unit, Regensburg University Hospital, 93055 Regensburg, Germany; (R.L.); (P.H.); (M.H.)
- Department of Neurology with Acute Geriatrics, Saint John of God Hospital Linz, 4021 Linz, Austria
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The Use of 18F-FET-PET-MRI in Neuro-Oncology: The Best of Both Worlds—A Narrative Review. Diagnostics (Basel) 2022; 12:diagnostics12051202. [PMID: 35626357 PMCID: PMC9140561 DOI: 10.3390/diagnostics12051202] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Revised: 04/22/2022] [Accepted: 04/28/2022] [Indexed: 02/05/2023] Open
Abstract
Gliomas are the most frequent primary tumors of the brain. They can be divided into grade II-IV astrocytomas and grade II-III oligodendrogliomas, based on their histomolecular profile. The prognosis and treatment is highly dependent on grade and well-identified prognostic and/or predictive molecular markers. Multi-parametric MRI, including diffusion weighted imaging, perfusion, and MR spectroscopy, showed increasing value in the non-invasive characterization of specific molecular subsets of gliomas. Radiolabeled amino-acid analogues, such as 18F-FET, have also been proven valuable in glioma imaging. These tracers not only contribute in the diagnostic process by detecting areas of dedifferentiation in diffuse gliomas, but this technique is also valuable in the follow-up of gliomas, as it can differentiate pseudo-progression from real tumor progression. Since multi-parametric MRI and 18F-FET PET are complementary imaging techniques, there may be a synergistic role for PET-MRI imaging in the neuro-oncological imaging of primary brain tumors. This could be of value for both primary staging, as well as during treatment and follow-up.
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Vagvala S, Guenette JP, Jaimes C, Huang RY. Imaging diagnosis and treatment selection for brain tumors in the era of molecular therapeutics. Cancer Imaging 2022; 22:19. [PMID: 35436952 PMCID: PMC9014574 DOI: 10.1186/s40644-022-00455-5] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 03/29/2022] [Indexed: 01/12/2023] Open
Abstract
Currently, most CNS tumors require tissue sampling to discern their molecular/genomic landscape. However, growing research has shown the powerful role imaging can play in non-invasively and accurately detecting the molecular signature of these tumors. The overarching theme of this review article is to provide neuroradiologists and neurooncologists with a framework of several important molecular markers, their associated imaging features and the accuracy of those features. A particular emphasis is placed on those tumors and mutations that have specific or promising imaging correlates as well as their respective therapeutic potentials.
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Affiliation(s)
- Saivenkat Vagvala
- Division of Neuroradiology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, 75 Francis St, Boston, MA, 02115, USA
| | - Jeffrey P Guenette
- Division of Neuroradiology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, 75 Francis St, Boston, MA, 02115, USA
| | - Camilo Jaimes
- Division of Neuroradiology, Boston Children's, 300 Longwood Ave., 2nd floor, Main Building, Boston, MA, 02115, USA
| | - Raymond Y Huang
- Division of Neuroradiology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, 75 Francis St, Boston, MA, 02115, USA.
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Masui K, Cavenee WK, Mischel PS, Shibata N. The metabolomic landscape plays a critical role in glioma oncogenesis. Cancer Sci 2022; 113:1555-1563. [PMID: 35271755 PMCID: PMC9128185 DOI: 10.1111/cas.15325] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Revised: 02/24/2022] [Accepted: 03/04/2022] [Indexed: 12/01/2022] Open
Abstract
Cancer cells depend on metabolic reprogramming for survival, undergoing profound shifts in nutrient sensing, nutrient uptake and flux through anabolic pathways, in order to drive nucleotide, lipid, and protein synthesis and provide key intermediates needed for those pathways. Although metabolic enzymes themselves can be mutated, including to generate oncometabolites, this is a relatively rare event in cancer. Usually, gene amplification, overexpression, and/or downstream signal transduction upregulate rate‐limiting metabolic enzymes and limit feedback loops, to drive persistent tumor growth. Recent molecular‐genetic advances have revealed discrete links between oncogenotypes and the resultant metabolic phenotypes. However, more comprehensive approaches are needed to unravel the dynamic spatio‐temporal regulatory map of enzymes and metabolites that enable cancer cells to adapt to their microenvironment to maximize tumor growth. Proteomic and metabolomic analyses are powerful tools for analyzing a repertoire of metabolic enzymes as well as intermediary metabolites, and in conjunction with other omics approaches could provide critical information in this regard. Here, we provide an overview of cancer metabolism, especially from an omics perspective and with a particular focus on the genomically well characterized malignant brain tumor, glioblastoma. We further discuss how metabolomics could be leveraged to improve the management of patients, by linking cancer cell genotype, epigenotype, and phenotype through metabolic reprogramming.
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Affiliation(s)
- Kenta Masui
- Department of Pathology, Tokyo Women's Medical University, Shinjuku, Tokyo, 162-8666, Japan
| | - Webster K Cavenee
- Ludwig Institute for Cancer Research, University of California San Diego, La Jolla, CA, 92093, USA
| | - Paul S Mischel
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, 94305, USA.,ChEM-H, Stanford University, Stanford, CA, 94305, USA
| | - Noriyuki Shibata
- Department of Pathology, Tokyo Women's Medical University, Shinjuku, Tokyo, 162-8666, Japan
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Yang Q, Hao J, Chi M, Wang Y, Li J, Huang J, Zhang J, Zhang M, Lu J, Zhou S, Yuan T, Shen Z, Zheng S, Guo C. D2HGDH-mediated D2HG catabolism enhances the anti-tumor activities of CAR-T cells in an immunosuppressive microenvironment. Mol Ther 2022; 30:1188-1200. [PMID: 35007759 PMCID: PMC8899596 DOI: 10.1016/j.ymthe.2022.01.007] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 08/31/2021] [Accepted: 01/05/2022] [Indexed: 10/19/2022] Open
Abstract
The effect of immunotherapy is limited by oncometabolite D-2-hydroxyglutarate (D2HG). D2HGDH is an inducible enzyme that converts D2HG into the endogenous metabolite 2-oxoglutarate. We aimed to evaluate the impairment of CD8 T lymphocyte function in the high-D2HG environment and to explore the phenotypic features and anti-tumor effect of D2HGDH-modified CAR-T cells. D2HG treatment inhibited the expansion of human CD8 T lymphocytes and CAR-T cells, increased their glucose uptake, suppressed effector cytokine production, and decreased the central memory cell proportion. D2HGDH-modified CAR-T cells displayed distinct phenotypes, as D2HGDH knock-out (KO) CAR-T cells exhibited a significant decrease in central memory cell differentiation and intracellular cytokine production, while D2HGDH over-expression (OE) CAR-T cells showed predominant killing efficacy against NALM6 cancer cells in high-D2HG medium. In vivo xenograft experiments confirmed that D2HGDH-OE CAR-T cells decreased serum D2HG and improved the overall survival of mice bearing NALM6 cancer cells with mutation IDH1. Our findings demonstrated that the immunosuppressive effect of D2HG and distinct phenotype of D2HGDH modified CAR-T cells. D2HGDH-OE CAR-T cells can take advantage of the catabolism of D2HG to foster T cell expansion, function, and anti-tumor effectiveness.
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Affiliation(s)
- Quanjun Yang
- Department of Pharmacy, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai 200233, China
| | - Juan Hao
- Department of Endocrinology, Shanghai Traditional Chinese Medicine-Integrated Hospital, Shanghai University of Traditional Chinese Medicine, 230 Baoding Road, Shanghai 200082, China
| | - Mengyi Chi
- Department of Pharmacy, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai 200233, China
| | - Yaxian Wang
- Department of Pharmacy, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai 200233, China
| | - Jie Li
- Department of Pharmacy, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai 200233, China
| | - Jinlu Huang
- Department of Pharmacy, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai 200233, China
| | - Jianping Zhang
- Department of Pharmacy, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai 200233, China
| | - Mengqi Zhang
- Department of Pharmacy, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai 200233, China
| | - Jin Lu
- Department of Pharmacy, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai 200233, China
| | - Shumin Zhou
- Institution of Microsurgery on Extremities, Shanghai Jiao Tong University affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai 200233, China
| | - Ting Yuan
- Department of Bone Oncology, Shanghai Jiao Tong University, affiliated Sixth People's Hospital, Shanghai, Shanghai 200233, China
| | - Zan Shen
- Department of Oncology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai 200233, China
| | - Shuier Zheng
- Department of Oncology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai 200233, China
| | - Cheng Guo
- Department of Pharmacy, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai 200233, China.
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Juskanič D, Mištinová JP, Hollý S, Sekerešová M, Koleják K, Pátrovič L. Diagnostic performance of edited 2HG MR spectroscopy of central glioma in the clinical environment. MAGMA (NEW YORK, N.Y.) 2022; 35:45-52. [PMID: 34985589 DOI: 10.1007/s10334-021-00989-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 12/09/2021] [Accepted: 12/12/2021] [Indexed: 06/14/2023]
Abstract
OBJECTIVE Oncometabolite D-2-hydroxyglutarate (2HG) is pooled in isocitrate dehydrogenase (IDH)-mutant glioma cells. Detecting 2HG by MR spectroscopy (MRS) has been proven viable in the last decade but has not entirely found its way into the clinical routine. This study aimed to explore the adoption of 2HG MRS while acknowledging factors that influence its performance in the clinical environment. METHODS Thirty-nine MR spectra were acquired and reported prospectively in patients with suspected glioma using a 3 T system with Mescher-Garwood point-resolved spectroscopy (MEGA-PRESS) sequence utilizing averaged free induction decay (FID) signals. Postprocessing and evaluation of spectra were performed with jMRUI and LCModel. 2HG concentration estimates, 2HG/Cr ratio, together with quality measures, including Cramér-Rao lower bounds (CRLBs), full-width at half-maximum (FWHM) values, and signal-to-noise ratio (SNR) were calculated using LCModel. Immunohistochemistry and genomic analysis results used as a ground truth were available for 15 patients. RESULTS The threshold for test positivity was set according to the ROC curve at 1 mM. Calculated sensitivity was 57.14% (95% CI 0.20-0.88), specificity 87.5% (95% CI 0.46-0.99), positive predictive value 80%, and negative predictive value 70%. Overall diagnostic accuracy was 73.33% (95% CI 0.45-0.92). The 2HG/Cr ratio with the cutoff value 0.085 significantly improved sensitivity and overall diagnostic accuracy [85.71%, 95% CI 0.42-1.00 and 86.67%, (95% CI 0.60-0.98), respectively]. CONCLUSION Multiple factors compromising spectral quality in the clinical adoption of edited 2HG MRS resulted in diminished sensitivity but clinically acceptable specificity. Furthermore, the 2HG/Cr ratio performs better than the sole 2HG concentration estimate in the pre-operative setting.
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Affiliation(s)
- Dominik Juskanič
- JESSENIUS-Diagnostic Center, Nitra, Slovakia.
- Medical Faculty, Comenius University in Bratislava, Bratislava, Slovakia.
- Faculty Hospital, Nitra, Slovakia.
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Stumpo V, Sebök M, van Niftrik CHB, Seystahl K, Hainc N, Kulcsar Z, Weller M, Regli L, Fierstra J. Feasibility of glioblastoma tissue response mapping with physiologic BOLD imaging using precise oxygen and carbon dioxide challenge. MAGMA (NEW YORK, N.Y.) 2022; 35:29-44. [PMID: 34874499 DOI: 10.1007/s10334-021-00980-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 11/15/2021] [Accepted: 11/19/2021] [Indexed: 12/15/2022]
Abstract
OBJECTIVES Innovative physiologic MRI development focuses on depiction of heterogenous vascular and metabolic features in glioblastoma. For this feasibility study, we employed blood oxygenation level-dependent (BOLD) MRI with standardized and precise carbon dioxide (CO2) and oxygen (O2) modulation to investigate specific tumor tissue response patterns in patients with newly diagnosed glioblastoma. MATERIALS AND METHODS Seven newly diagnosed untreated patients with suspected glioblastoma were prospectively included to undergo a BOLD study with combined CO2 and O2 standardized protocol. %BOLD signal change/mmHg during hypercapnic, hypoxic, and hyperoxic stimulus was calculated in the whole brain, tumor lesion and segmented volumes of interest (VOI) [contrast-enhancing (CE) - tumor, necrosis and edema] to analyze their tissue response patterns. RESULTS Quantification of BOLD signal change after gas challenges can be used to identify specific responses to standardized stimuli in glioblastoma patients. Integration of this approach with automatic VOI segmentation grants improved characterization of tumor subzones and edema. Magnitude of BOLD signal change during the 3 stimuli can be visualized at voxel precision through color-coded maps overlayed onto whole brain and identified VOIs. CONCLUSIONS Our preliminary investigation shows good feasibility of BOLD with standardized and precise CO2 and O2 modulation as an emerging physiologic imaging technique to detail specific glioblastoma characteristics. The unique tissue response patterns generated can be further investigated to better detail glioblastoma lesions and gauge treatment response.
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Affiliation(s)
- Vittorio Stumpo
- Department of Neurosurgery, University Hospital Zurich, Frauenklinikstrasse 10, 8091, Zurich, Switzerland. .,Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
| | - Martina Sebök
- Department of Neurosurgery, University Hospital Zurich, Frauenklinikstrasse 10, 8091, Zurich, Switzerland.,Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Christiaan Hendrik Bas van Niftrik
- Department of Neurosurgery, University Hospital Zurich, Frauenklinikstrasse 10, 8091, Zurich, Switzerland.,Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Katharina Seystahl
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland.,Department of Neurology, University Hospital Zurich, Zurich, Switzerland
| | - Nicolin Hainc
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland.,Department of Neuroradiology, University Hospital Zurich, Zurich, Switzerland
| | - Zsolt Kulcsar
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland.,Department of Neuroradiology, University Hospital Zurich, Zurich, Switzerland
| | - Michael Weller
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland.,Department of Neurology, University Hospital Zurich, Zurich, Switzerland
| | - Luca Regli
- Department of Neurosurgery, University Hospital Zurich, Frauenklinikstrasse 10, 8091, Zurich, Switzerland.,Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Jorn Fierstra
- Department of Neurosurgery, University Hospital Zurich, Frauenklinikstrasse 10, 8091, Zurich, Switzerland.,Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
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40
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Sun C, Fan L, Wang W, Wang W, Liu L, Duan W, Pei D, Zhan Y, Zhao H, Sun T, Liu Z, Hong X, Wang X, Guo Y, Li W, Cheng J, Li Z, Liu X, Zhang Z, Yan J. Radiomics and Qualitative Features From Multiparametric MRI Predict Molecular Subtypes in Patients With Lower-Grade Glioma. Front Oncol 2022; 11:756828. [PMID: 35127472 PMCID: PMC8814098 DOI: 10.3389/fonc.2021.756828] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Accepted: 12/28/2021] [Indexed: 11/13/2022] Open
Abstract
Background Isocitrate dehydrogenase (IDH) mutation and 1p19q codeletion status have been identified as significant markers for therapy and prognosis in lower-grade glioma (LGG). The current study aimed to construct a combined machine learning-based model for predicting the molecular subtypes of LGG, including (1) IDH wild-type astrocytoma (IDHwt), (2) IDH mutant and 1p19q non-codeleted astrocytoma (IDHmut-noncodel), and (3) IDH-mutant and 1p19q codeleted oligodendroglioma (IDHmut-codel), based on multiparametric magnetic resonance imaging (MRI) radiomics, qualitative features, and clinical factors. Methods A total of 335 patients with LGG (WHO grade II/III) were retrospectively enrolled. The sum of 5,929 radiomics features were extracted from multiparametric MRI. Selected robust, non-redundant, and relevant features were used to construct a random forest model based on a training cohort (n = 269) and evaluated on a testing cohort (n = 66). Meanwhile, preoperative MRIs of all patients were scored in accordance with Visually Accessible Rembrandt Images (VASARI) annotations and T2-fluid attenuated inversion recovery (T2-FLAIR) mismatch sign. By combining radiomics features, qualitative features (VASARI annotations and T2-FLAIR mismatch signs), and clinical factors, a combined prediction model for the molecular subtypes of LGG was built. Results The 17-feature radiomics model achieved area under the curve (AUC) values of 0.6557, 0.6830, and 0.7579 for IDHwt, IDHmut-noncodel, and IDHmut-codel, respectively, in the testing cohort. Incorporating qualitative features and clinical factors into the radiomics model resulted in improved AUCs of 0.8623, 0.8056, and 0.8036 for IDHwt, IDHmut-noncodel, and IDHmut-codel, with balanced accuracies of 0.8924, 0.8066, and 0.8095, respectively. Conclusion The combined machine learning algorithm can provide a method to non-invasively predict the molecular subtypes of LGG preoperatively with excellent predictive performance.
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Affiliation(s)
- Chen Sun
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Liyuan Fan
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Wenqing Wang
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Weiwei Wang
- Department of Pathology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Lei Liu
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Wenchao Duan
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Dongling Pei
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yunbo Zhan
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Haibiao Zhao
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Tao Sun
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Zhen Liu
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xuanke Hong
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xiangxiang Wang
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yu Guo
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Wencai Li
- Department of Pathology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jingliang Cheng
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Zhicheng Li
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Xianzhi Liu
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- *Correspondence: Jing Yan, ; Zhenyu Zhang, ; Xianzhi Liu,
| | - Zhenyu Zhang
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- *Correspondence: Jing Yan, ; Zhenyu Zhang, ; Xianzhi Liu,
| | - Jing Yan
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- *Correspondence: Jing Yan, ; Zhenyu Zhang, ; Xianzhi Liu,
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41
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Mancini L, Casagranda S, Gautier G, Peter P, Lopez B, Thorne L, McEvoy A, Miserocchi A, Samandouras G, Kitchen N, Brandner S, De Vita E, Torrealdea F, Rega M, Schmitt B, Liebig P, Sanverdi E, Golay X, Bisdas S. CEST MRI provides amide/amine surrogate biomarkers for treatment-naïve glioma sub-typing. Eur J Nucl Med Mol Imaging 2022; 49:2377-2391. [PMID: 35029738 PMCID: PMC9165287 DOI: 10.1007/s00259-022-05676-1] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Accepted: 12/31/2021] [Indexed: 11/24/2022]
Abstract
PURPOSE Accurate glioma classification affects patient management and is challenging on non- or low-enhancing gliomas. This study investigated the clinical value of different chemical exchange saturation transfer (CEST) metrics for glioma classification and assessed the diagnostic effect of the presence of abundant fluid in glioma subpopulations. METHODS Forty-five treatment-naïve glioma patients with known isocitrate dehydrogenase (IDH) mutation and 1p/19q codeletion status received CEST MRI (B1rms = 2μT, Tsat = 3.5 s) at 3 T. Magnetization transfer ratio asymmetry and CEST metrics (amides: offset range 3-4 ppm, amines: 1.5-2.5 ppm, amide/amine ratio) were calculated with two models: 'asymmetry-based' (AB) and 'fluid-suppressed' (FS). The presence of T2/FLAIR mismatch was noted. RESULTS IDH-wild type had higher amide/amine ratio than IDH-mutant_1p/19qcodel (p < 0.022). Amide/amine ratio and amine levels differentiated IDH-wild type from IDH-mutant (p < 0.0045) and from IDH-mutant_1p/19qret (p < 0.021). IDH-mutant_1p/19qret had higher amides and amines than IDH-mutant_1p/19qcodel (p < 0.035). IDH-mutant_1p/19qret with AB/FS mismatch had higher amines than IDH-mutant_1p/19qret without AB/FS mismatch ( < 0.016). In IDH-mutant_1p/19qret, the presence of AB/FS mismatch was closely related to the presence of T2/FLAIR mismatch (p = 0.014). CONCLUSIONS CEST-derived biomarkers for amides, amines, and their ratio can help with histomolecular staging in gliomas without intense contrast enhancement. T2/FLAIR mismatch is reflected in the presence of AB/FS CEST mismatch. The AB/FS CEST mismatch identifies glioma subgroups that may have prognostic and clinical relevance.
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Affiliation(s)
- Laura Mancini
- Box65, Lysholm Department of Neuroradiology, The National Hospital for Neurology & Neurosurgery, University College London Hospitals NHS Foundation Trust, 8-11 Queen Square, London, WC1N 3BG, UK.
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, London, UK.
| | | | | | | | | | - Lewis Thorne
- Department of Neurosurgery, The National Hospital for Neurology & Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
| | - Andrew McEvoy
- Department of Neurosurgery, The National Hospital for Neurology & Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
| | - Anna Miserocchi
- Department of Neurosurgery, The National Hospital for Neurology & Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
| | - George Samandouras
- Department of Neurosurgery, The National Hospital for Neurology & Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
| | - Neil Kitchen
- Department of Neurosurgery, The National Hospital for Neurology & Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
| | - Sebastian Brandner
- Division of Neuropathology, UCL Queen Square Institute of Neurology, London, UK
- The National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
| | - Enrico De Vita
- Box65, Lysholm Department of Neuroradiology, The National Hospital for Neurology & Neurosurgery, University College London Hospitals NHS Foundation Trust, 8-11 Queen Square, London, WC1N 3BG, UK
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, London, UK
| | - Francisco Torrealdea
- University College Hospital, University College of London Hospitals NHS Foundation Trust, London, UK
| | - Marilena Rega
- University College Hospital, University College of London Hospitals NHS Foundation Trust, London, UK
| | | | | | - Eser Sanverdi
- Box65, Lysholm Department of Neuroradiology, The National Hospital for Neurology & Neurosurgery, University College London Hospitals NHS Foundation Trust, 8-11 Queen Square, London, WC1N 3BG, UK
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, London, UK
| | - Xavier Golay
- Box65, Lysholm Department of Neuroradiology, The National Hospital for Neurology & Neurosurgery, University College London Hospitals NHS Foundation Trust, 8-11 Queen Square, London, WC1N 3BG, UK
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, London, UK
| | - Sotirios Bisdas
- Box65, Lysholm Department of Neuroradiology, The National Hospital for Neurology & Neurosurgery, University College London Hospitals NHS Foundation Trust, 8-11 Queen Square, London, WC1N 3BG, UK
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, London, UK
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Tyurina AN, Vikhrova NB, Batalov AI, Kalaeva DB, Shults EI, Postnov AA, Pronin IN. [Radiological biomarkers of brain gliomas]. ZHURNAL VOPROSY NEIROKHIRURGII IMENI N. N. BURDENKO 2022; 86:121-126. [PMID: 36534633 DOI: 10.17116/neiro202286061121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
The most important objective of modern neuroimaging is comparison of data on genotype and phenotype of brain gliomas. Radiogenomics as a new branch of science is devoted to searching for such relationships based on MRI and PET/CT parameters. The 2021 WHO classification of tumors of the central nervous system poses the most important tasks for physicians in assessment of biological behavior of tumors and their response to combined treatment. The review demonstrates the possibilities and prospects of preoperative MRI and PET/CT with amino acids in assessing the genetic profile of brain gliomas.
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Affiliation(s)
- A N Tyurina
- Burdenko Neurosurgery Center, Moscow, Russia
| | | | - A I Batalov
- Burdenko Neurosurgery Center, Moscow, Russia
| | - D B Kalaeva
- Burdenko Neurosurgery Center, Moscow, Russia
- Moscow Engineering Physics Institute, Moscow, Russia
| | - E I Shults
- Research Practical Clinical Center of Diagnosis and Telemedicine Technologies, Moscow, Russia
| | - A A Postnov
- Burdenko Neurosurgery Center, Moscow, Russia
- Moscow Engineering Physics Institute, Moscow, Russia
- Lebedev Physical Institute, Moscow, Russia
| | - I N Pronin
- Burdenko Neurosurgery Center, Moscow, Russia
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43
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Gonçalves FG, Viaene AN, Vossough A. Advanced Magnetic Resonance Imaging in Pediatric Glioblastomas. Front Neurol 2021; 12:733323. [PMID: 34858308 PMCID: PMC8631300 DOI: 10.3389/fneur.2021.733323] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Accepted: 10/12/2021] [Indexed: 12/26/2022] Open
Abstract
The shortly upcoming 5th edition of the World Health Organization Classification of Tumors of the Central Nervous System is bringing extensive changes in the terminology of diffuse high-grade gliomas (DHGGs). Previously "glioblastoma," as a descriptive entity, could have been applied to classify some tumors from the family of pediatric or adult DHGGs. However, now the term "glioblastoma" has been divested and is no longer applied to tumors in the family of pediatric types of DHGGs. As an entity, glioblastoma remains, however, in the family of adult types of diffuse gliomas under the insignia of "glioblastoma, IDH-wildtype." Of note, glioblastomas still can be detected in children when glioblastoma, IDH-wildtype is found in this population, despite being much more common in adults. Despite the separation from the family of pediatric types of DHGGs, what was previously labeled as "pediatric glioblastomas" still remains with novel labels and as new entities. As a result of advances in molecular biology, most of the previously called "pediatric glioblastomas" are now classified in one of the four family members of pediatric types of DHGGs. In this review, the term glioblastoma is still apocryphally employed mainly due to its historical relevance and the paucity of recent literature dealing with the recently described new entities. Therefore, "glioblastoma" is used here as an umbrella term in the attempt to encompass multiple entities such as astrocytoma, IDH-mutant (grade 4); glioblastoma, IDH-wildtype; diffuse hemispheric glioma, H3 G34-mutant; diffuse pediatric-type high-grade glioma, H3-wildtype and IDH-wildtype; and high grade infant-type hemispheric glioma. Glioblastomas are highly aggressive neoplasms. They may arise anywhere in the developing central nervous system, including the spinal cord. Signs and symptoms are non-specific, typically of short duration, and usually derived from increased intracranial pressure or seizure. Localized symptoms may also occur. The standard of care of "pediatric glioblastomas" is not well-established, typically composed of surgery with maximal safe tumor resection. Subsequent chemoradiation is recommended if the patient is older than 3 years. If younger than 3 years, surgery is followed by chemotherapy. In general, "pediatric glioblastomas" also have a poor prognosis despite surgery and adjuvant therapy. Magnetic resonance imaging (MRI) is the imaging modality of choice for the evaluation of glioblastomas. In addition to the typical conventional MRI features, i.e., highly heterogeneous invasive masses with indistinct borders, mass effect on surrounding structures, and a variable degree of enhancement, the lesions may show restricted diffusion in the solid components, hemorrhage, and increased perfusion, reflecting increased vascularity and angiogenesis. In addition, magnetic resonance spectroscopy has proven helpful in pre- and postsurgical evaluation. Lastly, we will refer to new MRI techniques, which have already been applied in evaluating adult glioblastomas, with promising results, yet not widely utilized in children.
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Affiliation(s)
- Fabrício Guimarães Gonçalves
- Division of Neuroradiology, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, United States
| | - Angela N Viaene
- Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, United States.,Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Arastoo Vossough
- Division of Neuroradiology, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, United States.,Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
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Ma R, Taphoorn MJB, Plaha P. Advances in the management of glioblastoma. J Neurol Neurosurg Psychiatry 2021; 92:1103-1111. [PMID: 34162730 DOI: 10.1136/jnnp-2020-325334] [Citation(s) in RCA: 55] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Accepted: 06/08/2021] [Indexed: 01/08/2023]
Abstract
Glioblastoma (GB) is the most common and most malignant primary brain tumour in adults. Despite much effort, gold standard therapy has not changed since the introduction of adjuvant temozolomide in 2005 and prognosis remains poor. Despite this, there has been significant improvement in the surgical technology and technique, that has allowed for increased rates of safe maximal resection of the tumour. In addition, our increased knowledge of the biology of GB has revealed more potential targets, especially in the field of immunotherapy, which has been successful in revolutionising treatment of other cancers. We review the current best practice for the treatment of GB and explore some of the more recent advances in GB management from both a surgical and molecular therapeutic perspective.
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Affiliation(s)
- Ruichong Ma
- Department of Neurosurgery, Oxford University Hospitals NHS Foundation Trust, Oxford, Oxfordshire, UK.,Human Immunology Unit, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.,Nuffield Department of Surgery, University of Oxford, Oxford, UK
| | - Martin J B Taphoorn
- Neurology, Leiden University Medical Center, Leiden, The Netherlands.,Neurology, Medical Center Haaglanden, The Hague, The Netherlands
| | - Puneet Plaha
- Department of Neurosurgery, Oxford University Hospitals NHS Foundation Trust, Oxford, Oxfordshire, UK .,Nuffield Department of Surgery, University of Oxford, Oxford, UK.,Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
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Neurosurgical Advances for Malignant Gliomas: Intersection of Biology and Technology. ACTA ACUST UNITED AC 2021; 27:364-370. [PMID: 34570450 DOI: 10.1097/ppo.0000000000000548] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
ABSTRACT The intersection of biology and technology has led to many advancements for the field of neurosurgery. Molecular developments have led to the identification of specific mutations, allowing for more accurate discussions in regard to prognosis and treatment effect. Even amid the progress from basic science benchwork, malignant gliomas continue to have a bleak natural history in lieu of the resistance to chemotherapy and the diffuse nature of the disease, leaving room for further research to discover more effective treatment modalities. Novel imaging methods, including the emerging field of radiogenomics, involve the merging of molecular and radiographic data, enabling earlier, detailed molecular diagnoses and improved surveillance of this pathology. Furthermore, surgical advancements have led to safer and more extensive resections. This review aims to delineate the various advancements in the many facets that are used daily in the care of our glioma population, specifically pertaining to its biology, imaging modalities, and perioperative adjuncts used in the operating room.
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46
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Abstract
This article reviews recent advances in the use of standard and advanced imaging techniques for diagnosis and treatment of central nervous system (CNS) tumors, including glioma and brain metastasis. Following the recent transition from a histology-based approach in classifying CNS tumors to one that integrates histology with the molecular information of tumor, the approaches for imaging CNS tumors have also been adapted to this new framework. Some challenges related to the diagnosis and treatment of CNS tumors, such as differentiating tumor from treatment-related imaging changes, require further progress to implement advanced imaging for clinical use.
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Affiliation(s)
- Raymond Y Huang
- Department of Neuroradiology, Brigham and Women's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA.
| | - Whitney B Pope
- Radiology, Section of Neuroradiology, Brain Tumor Imaging, UCLA Medical Center, Los Angeles, CA, USA; Department of Radiological Sciences, David Geffen School of Medicine, University of California-Los Angeles, 924 Westwood Boulevard, Suite 615, Los Angeles, CA 90024, USA; Department of Neurology, David Geffen School of Medicine, University of California-Los Angeles, 924 Westwood Boulevard, Suite 615, Los Angeles, CA 90024, USA
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47
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Shams Z, van der Kemp WJM, Emir U, Dankbaar JW, Snijders TJ, de Vos FYF, Klomp DWJ, Wijnen JP, Wiegers EC. Comparison of 2-Hydroxyglutarate Detection With sLASER and MEGA-sLASER at 7T. Front Neurol 2021; 12:718423. [PMID: 34557149 PMCID: PMC8452903 DOI: 10.3389/fneur.2021.718423] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Accepted: 08/05/2021] [Indexed: 12/15/2022] Open
Abstract
The onco-metabolite 2-hydroxyglutarate (2HG), a biomarker of IDH-mutant gliomas, can be detected with 1H MR spectroscopy (1H-MRS). Recent studies showed measurements of 2HG at 7T with substantial gain in signal to noise ratio (SNR) and spectral resolution, offering higher specificity and sensitivity for 2HG detection. In this study, we assessed the sensitivity of semi-localized by adiabatic selective refocusing (sLASER) and J-difference MEsher-GArwood-semi-LASER (MEGA-sLASER) for 2HG detection at 7T. We performed spectral editing at long TE using a TE-optimized sLASER sequence (110 ms) and J-difference spectroscopy using MEGA-sLASER (TE = 74ms) in phantoms with different 2HG concentrations to assess the sensitivity of 2HG detection. The robustness of the methods against B0 inhomogeneity was investigated. Moreover, the performance of these two techniques was evaluated in four patients with IDH1-mutated glioma. In contrary to MEGA-sLASER, sLASER was able to detect 2HG concentration as low as 0.5 mM. In case of a composite phantom containing 2HG with overlapping metabolites, MEGA-sLASER provided a clean 2HG signal with higher fitting reliability (lower %CRLB). The results demonstrate that sLASER is more robust against field inhomogeneities and experimental or motion-related artifacts which promotes to adopt sLASER in clinical implementations.
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Affiliation(s)
- Zahra Shams
- Department of Radiology, University Medical Center Utrecht, Utrecht, Netherlands
| | | | - Uzay Emir
- School of Health Sciences, Purdue University, West Lafayette, IN, United States
| | - Jan Willem Dankbaar
- Department of Radiology, University Medical Center Utrecht, Utrecht, Netherlands
| | - Tom J Snijders
- Department of Neurology & Neurosurgery, University Medical Center Utrecht/UMC Utrecht Brain Center, Utrecht, Netherlands
| | - Filip Y F de Vos
- Department of Medical Oncology, University Medical Center Utrecht, Utrecht, Netherlands
| | - Dennis W J Klomp
- Department of Radiology, University Medical Center Utrecht, Utrecht, Netherlands
| | - Jannie P Wijnen
- Department of Radiology, University Medical Center Utrecht, Utrecht, Netherlands
| | - Evita C Wiegers
- Department of Radiology, University Medical Center Utrecht, Utrecht, Netherlands
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Ellingson BM, Wen PY, Cloughesy TF. Therapeutic Response Assessment of High-Grade Gliomas During Early-Phase Drug Development in the Era of Molecular and Immunotherapies. Cancer J 2021; 27:395-403. [PMID: 34570454 PMCID: PMC8480435 DOI: 10.1097/ppo.0000000000000543] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
ABSTRACT Several new therapeutic strategies have emerged over the past decades to address unmet clinical needs in high-grade gliomas, including targeted molecular agents and various forms of immunotherapy. Each of these strategies requires addressing fundamental questions, depending on the stage of drug development, including ensuring drug penetration into the brain, engagement of the drug with the desired target, biologic effects downstream from the target including metabolic and/or physiologic changes, and identifying evidence of clinical activity that could be expanded upon to increase the likelihood of a meaningful survival benefit. The current review article highlights these strategies and outlines how imaging technology can be used for therapeutic response evaluation in both targeted and immunotherapies in early phases of drug development in high-grade gliomas.
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Affiliation(s)
- Benjamin M. Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
| | - Patrick Y. Wen
- Center for Neuro-Oncology, Dana-Farber Cancer Institute, Harvard University, Boston, MA
| | - Timothy F. Cloughesy
- UCLA Neuro Oncology Program, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
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Polvoy I, Qin H, Flavell RR, Gordon J, Viswanath P, Sriram R, Ohliger MA, Wilson DM. Deuterium Metabolic Imaging-Rediscovery of a Spectroscopic Tool. Metabolites 2021; 11:570. [PMID: 34564385 PMCID: PMC8470013 DOI: 10.3390/metabo11090570] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Accepted: 08/18/2021] [Indexed: 01/31/2023] Open
Abstract
The growing demand for metabolism-specific imaging techniques has rekindled interest in Deuterium (2H) Metabolic Imaging (DMI), a robust method based on administration of a substrate (glucose, acetate, fumarate, etc.) labeled with the stable isotope of hydrogen and the observation of its metabolic fate in three-dimensions. This technique allows the investigation of multiple metabolic processes in both healthy and diseased states. Despite its low natural abundance, the short relaxation time of deuterium allows for rapid radiofrequency (RF) pulses without saturation and efficient image acquisition. In this review, we provide a comprehensive picture of the evolution of DMI over the course of recent decades, with a special focus on its potential clinical applications.
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Affiliation(s)
- Ilona Polvoy
- Department of Radiology and Biomedical Imaging, University of California, 185 Berry St., San Francisco, CA 94158, USA; (I.P.); (H.Q.); (R.R.F.); (J.G.); (P.V.); (R.S.); (M.A.O.)
| | - Hecong Qin
- Department of Radiology and Biomedical Imaging, University of California, 185 Berry St., San Francisco, CA 94158, USA; (I.P.); (H.Q.); (R.R.F.); (J.G.); (P.V.); (R.S.); (M.A.O.)
| | - Robert R. Flavell
- Department of Radiology and Biomedical Imaging, University of California, 185 Berry St., San Francisco, CA 94158, USA; (I.P.); (H.Q.); (R.R.F.); (J.G.); (P.V.); (R.S.); (M.A.O.)
| | - Jeremy Gordon
- Department of Radiology and Biomedical Imaging, University of California, 185 Berry St., San Francisco, CA 94158, USA; (I.P.); (H.Q.); (R.R.F.); (J.G.); (P.V.); (R.S.); (M.A.O.)
| | - Pavithra Viswanath
- Department of Radiology and Biomedical Imaging, University of California, 185 Berry St., San Francisco, CA 94158, USA; (I.P.); (H.Q.); (R.R.F.); (J.G.); (P.V.); (R.S.); (M.A.O.)
| | - Renuka Sriram
- Department of Radiology and Biomedical Imaging, University of California, 185 Berry St., San Francisco, CA 94158, USA; (I.P.); (H.Q.); (R.R.F.); (J.G.); (P.V.); (R.S.); (M.A.O.)
| | - Michael A. Ohliger
- Department of Radiology and Biomedical Imaging, University of California, 185 Berry St., San Francisco, CA 94158, USA; (I.P.); (H.Q.); (R.R.F.); (J.G.); (P.V.); (R.S.); (M.A.O.)
- Department of Radiology, Zuckerberg San Francisco General Hospital, San Francisco, CA 94110, USA
| | - David M. Wilson
- Department of Radiology and Biomedical Imaging, University of California, 185 Berry St., San Francisco, CA 94158, USA; (I.P.); (H.Q.); (R.R.F.); (J.G.); (P.V.); (R.S.); (M.A.O.)
- Department of Radiology and Biomedical Imaging, University of California, 505 Parnassus Ave, San Francisco, CA 94143, USA
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Abstract
The central role of MRI in neuro-oncology is undisputed. The technique is used, both in clinical practice and in clinical trials, to diagnose and monitor disease activity, support treatment decision-making, guide the use of focused treatments and determine response to treatment. Despite recent substantial advances in imaging technology and image analysis techniques, clinical MRI is still primarily used for the qualitative subjective interpretation of macrostructural features, as opposed to quantitative analyses that take into consideration multiple pathophysiological features. However, the field of quantitative imaging and imaging biomarker development is maturing. The European Imaging Biomarkers Alliance (EIBALL) and Quantitative Imaging Biomarkers Alliance (QIBA) are setting standards for biomarker development, validation and implementation, as well as promoting the use of quantitative imaging and imaging biomarkers by demonstrating their clinical value. In parallel, advanced imaging techniques are reaching the clinical arena, providing quantitative, commonly physiological imaging parameters that are driving the discovery, validation and implementation of quantitative imaging and imaging biomarkers in the clinical routine. Additionally, computational analysis techniques are increasingly being used in the research setting to convert medical images into objective high-dimensional data and define radiomic signatures of disease states. Here, I review the definition and current state of MRI biomarkers in neuro-oncology, and discuss the clinical potential of quantitative image analysis techniques.
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