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Gue R, Lakhani DA. The 2021 World Health Organization Central Nervous System Tumor Classification: The Spectrum of Diffuse Gliomas. Biomedicines 2024; 12:1349. [PMID: 38927556 PMCID: PMC11202067 DOI: 10.3390/biomedicines12061349] [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: 05/13/2024] [Revised: 06/07/2024] [Accepted: 06/11/2024] [Indexed: 06/28/2024] Open
Abstract
The 2021 edition of the World Health Organization (WHO) classification of central nervous system tumors introduces significant revisions across various tumor types. These updates, encompassing changes in diagnostic techniques, genomic integration, terminology, and grading, are crucial for radiologists, who play a critical role in interpreting brain tumor imaging. Such changes impact the diagnosis and management of nearly all central nervous system tumor categories, including the reclassification, addition, and removal of specific tumor entities. Given their pivotal role in patient care, radiologists must remain conversant with these revisions to effectively contribute to multidisciplinary tumor boards and collaborate with peers in neuro-oncology, neurosurgery, radiation oncology, and neuropathology. This knowledge is essential not only for accurate diagnosis and staging, but also for understanding the molecular and genetic underpinnings of tumors, which can influence treatment decisions and prognostication. This review, therefore, focuses on the most pertinent updates concerning the classification of adult diffuse gliomas, highlighting the aspects most relevant to radiological practice. Emphasis is placed on the implications of new genetic information on tumor behavior and imaging findings, providing necessary tools to stay abreast of advancements in the field. This comprehensive overview aims to enhance the radiologist's ability to integrate new WHO classification criteria into everyday practice, ultimately improving patient outcomes through informed and precise imaging assessments.
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Affiliation(s)
- Racine Gue
- Department of Neuroradiology, West Virginia University, Morgantown, WV 26506, USA
| | - Dhairya A. Lakhani
- Department of Neuroradiology, West Virginia University, Morgantown, WV 26506, USA
- Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD 21218, USA
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Shelton WJ, Zandpazandi S, Nix JS, Gokden M, Bauer M, Ryan KR, Wardell CP, Vaske OM, Rodriguez A. Long-read sequencing for brain tumors. Front Oncol 2024; 14:1395985. [PMID: 38915364 PMCID: PMC11194609 DOI: 10.3389/fonc.2024.1395985] [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: 03/05/2024] [Accepted: 05/27/2024] [Indexed: 06/26/2024] Open
Abstract
Brain tumors and genomics have a long-standing history given that glioblastoma was the first cancer studied by the cancer genome atlas. The numerous and continuous advances through the decades in sequencing technologies have aided in the advanced molecular characterization of brain tumors for diagnosis, prognosis, and treatment. Since the implementation of molecular biomarkers by the WHO CNS in 2016, the genomics of brain tumors has been integrated into diagnostic criteria. Long-read sequencing, also known as third generation sequencing, is an emerging technique that allows for the sequencing of longer DNA segments leading to improved detection of structural variants and epigenetics. These capabilities are opening a way for better characterization of brain tumors. Here, we present a comprehensive summary of the state of the art of third-generation sequencing in the application for brain tumor diagnosis, prognosis, and treatment. We discuss the advantages and potential new implementations of long-read sequencing into clinical paradigms for neuro-oncology patients.
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Affiliation(s)
- William J. Shelton
- Department of Neurosurgery, College of Medicine, University of Arkansas for Medical Sciences, Little Rock, AR, United States
| | - Sara Zandpazandi
- Department of Neurosurgery, Medical University of South Carolina, Charleston, SC, United States
| | - J Stephen Nix
- Department of Pathology, University of Arkansas for Medical Sciences, Little Rock, AR, United States
| | - Murat Gokden
- Department of Pathology, University of Arkansas for Medical Sciences, Little Rock, AR, United States
| | - Michael Bauer
- Department of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR, United States
| | - Katie Rose Ryan
- Department of Biochemistry and Molecular Biology, University of Arkansas for Medical Sciences, Little Rock, AR, United States
| | - Christopher P. Wardell
- Department of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR, United States
| | - Olena Morozova Vaske
- Department of Molecular, Cell and Developmental Biology, University of California Santa Cruz, Santa Cruz, CA, United States
| | - Analiz Rodriguez
- Department of Neurosurgery, College of Medicine, University of Arkansas for Medical Sciences, Little Rock, AR, United States
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Pandey A, Chandla A, Mekonnen M, Hovis GEA, Teton ZE, Patel KS, Everson RG, Wadehra M, Yang I. Safety and Efficacy of Laser Interstitial Thermal Therapy as Upfront Therapy in Primary Glioblastoma and IDH-Mutant Astrocytoma: A Meta-Analysis. Cancers (Basel) 2024; 16:2131. [PMID: 38893250 PMCID: PMC11171930 DOI: 10.3390/cancers16112131] [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: 05/01/2024] [Revised: 05/24/2024] [Accepted: 05/28/2024] [Indexed: 06/21/2024] Open
Abstract
Although primary studies have reported the safety and efficacy of LITT as a primary treatment in glioma, they are limited by sample sizes and institutional variation in stereotactic parameters such as temperature and laser power. The current literature has yet to provide pooled statistics on outcomes solely for primary brain tumors according to the 2021 WHO Classification of Tumors of the Central Nervous System (WHO CNS5). In the present study, we identify recent articles on primary CNS neoplasms treated with LITT without prior intervention, focusing on relationships with molecular profile, PFS, and OS. This meta-analysis includes the extraction of data from primary sources across four databases using the Covidence systematic review manager. The pooled data suggest LITT may be a safe primary management option with tumor ablation rates of 94.8% and 84.6% in IDH-wildtype glioblastoma multiforme (GBM) and IDH-mutant astrocytoma, respectively. For IDH-wildtype GBM, the pooled PFS and OS were 5.0 and 9.0 months, respectively. Similar to rates reported in the prior literature, the neurologic and non-neurologic complication rates for IDH-wildtype GBM were 10.3% and 4.8%, respectively. The neurologic and non-neurologic complication rates were somewhat higher in the IDH-mutant astrocytoma cohort at 33% and 8.3%, likely due to a smaller cohort size.
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Affiliation(s)
- Aryan Pandey
- Department of Neurosurgery, University of California Los Angeles (UCLA), Los Angeles, CA 90095, USA (M.M.)
| | - Anubhav Chandla
- Department of Neurosurgery, University of California Los Angeles (UCLA), Los Angeles, CA 90095, USA (M.M.)
| | - Mahlet Mekonnen
- Department of Neurosurgery, University of California Los Angeles (UCLA), Los Angeles, CA 90095, USA (M.M.)
| | - Gabrielle E. A. Hovis
- Department of Neurosurgery, University of California Los Angeles (UCLA), Los Angeles, CA 90095, USA (M.M.)
| | - Zoe E. Teton
- Department of Neurosurgery, University of California Los Angeles (UCLA), Los Angeles, CA 90095, USA (M.M.)
- Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Kunal S. Patel
- Department of Neurosurgery, University of California Los Angeles (UCLA), Los Angeles, CA 90095, USA (M.M.)
- Jonsson Comprehensive Cancer Center, Los Angeles, CA 90095, USA
| | - Richard G. Everson
- Department of Neurosurgery, University of California Los Angeles (UCLA), Los Angeles, CA 90095, USA (M.M.)
- Jonsson Comprehensive Cancer Center, Los Angeles, CA 90095, USA
- Department of Radiation Oncology, University of California Los Angeles (UCLA), Los Angeles, CA 90095, USA
- The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
- Ronald Reagan UCLA Medical Center, Los Angeles, CA 90095, USA
| | - Madhuri Wadehra
- Jonsson Comprehensive Cancer Center, Los Angeles, CA 90095, USA
- Department of Pathology and Laboratory Medicine, University of California Los Angeles (UCLA), Los Angeles, CA 90095, USA
| | - Isaac Yang
- Department of Neurosurgery, University of California Los Angeles (UCLA), Los Angeles, CA 90095, USA (M.M.)
- Harbor-UCLA Medical Center, Torrance, CA 90502, USA
- Jonsson Comprehensive Cancer Center, Los Angeles, CA 90095, USA
- Department of Radiation Oncology, University of California Los Angeles (UCLA), Los Angeles, CA 90095, USA
- The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
- Ronald Reagan UCLA Medical Center, Los Angeles, CA 90095, USA
- Department of Head and Neck Surgery, University of California Los Angeles (UCLA), Los Angeles, CA 90095, USA
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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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Indira Chandran V, Gopala S, Venkat EH, Kjolby M, Nejsum P. Extracellular vesicles in glioblastoma: a challenge and an opportunity. NPJ Precis Oncol 2024; 8:103. [PMID: 38760427 PMCID: PMC11101656 DOI: 10.1038/s41698-024-00600-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Accepted: 05/03/2024] [Indexed: 05/19/2024] Open
Abstract
Glioblastoma is a highly heterogeneous tumor whose pathophysiological complexities dictate both the diagnosis of disease severity as well as response to therapy. Conventional diagnostic tools and standard treatment regimens have only managed to achieve limited success in the management of patients suspected of glioblastoma. Extracellular vesicles are an emerging liquid biopsy tool that has shown great promise in resolving the limitations presented by the heterogeneous nature of glioblastoma. Here we discuss the contrasting yet interdependent dual role of extracellular vesicles as communication agents that contribute to the progression of glioblastoma by creating a heterogeneous microenvironment and as a liquid biopsy tool providing an opportunity to accurately identify the disease severity and progression.
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Affiliation(s)
- Vineesh Indira Chandran
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.
- Department of Infectious Diseases, Aarhus University Hospital, Aarhus, Denmark.
| | - Srinivas Gopala
- Department of Biochemistry, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala, India
| | - Easwer Hariharan Venkat
- Department of Neurosurgery, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala, India
| | - Mads Kjolby
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- Department of Clinical Pharmacology and Steno Diabetes Centre, Aarhus University Hospital, Aarhus, Denmark
| | - Peter Nejsum
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Department of Infectious Diseases, Aarhus University Hospital, Aarhus, Denmark
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Pons-Escoda A, Majos C, Smits M, Oleaga L. Presurgical diagnosis of diffuse gliomas in adults: Post-WHO 2021 practical perspectives from radiologists in neuro-oncology units. RADIOLOGIA 2024; 66:260-277. [PMID: 38908887 DOI: 10.1016/j.rxeng.2024.03.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Accepted: 10/31/2023] [Indexed: 06/24/2024]
Abstract
The 2021 World Health Organization classification of CNS tumours was greeted with enthusiasm as well as an initial potential overwhelm. However, with time and experience, our understanding of its key aspects has notably improved. Using our collective expertise gained in neuro-oncology units in hospitals in different countries, we have compiled a practical guide for radiologists that clarifies the classification criteria for diffuse gliomas in adults. Its format is clear and concise to facilitate its incorporation into everyday clinical practice. The document includes a historical overview of the classifications and highlights the most important recent additions. It describes the main types in detail with an emphasis on their appearance on imaging. The authors also address the most debated issues in recent years. It will better prepare radiologists to conduct accurate presurgical diagnoses and collaborate effectively in clinical decision making, thus impacting decisions on treatment, prognosis, and overall patient care.
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Affiliation(s)
- A Pons-Escoda
- Radiology Department, Hospital Universitari de Bellvitge, Barcelona, Spain; Facultat de Medicina i Ciencies de La Salut, Universitat de Barcelona (UB), Barcelona, Spain.
| | - C Majos
- Radiology Department, Hospital Universitari de Bellvitge, Barcelona, Spain; Neuro-Oncology Unit, Institut d'Investigació Biomèdica de Bellvitge-IDIBELL, Barcelona, Spain; Diagnostic Imaging and Nuclear Medicine Research Group, Institut d'Investigació Biomèdica de Bellvitge-IDIBELL, Barcelona, Spain
| | - M Smits
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands; Erasmus MC Cancer Institute, Erasmus MC, Rotterdam, The Netherlands; Medical Delta, Delft, The Netherlands
| | - L Oleaga
- Radiology Department, Hospital Clínic Barcelona, Barcelona, Spain
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Martín-Noguerol T, Cabrera-Zubizarreta A, Luna A. Standardized reporting systems for (which?) brain tumors from in the dark: cons of the BT-RADS. Eur Radiol 2024:10.1007/s00330-024-10715-6. [PMID: 38583125 DOI: 10.1007/s00330-024-10715-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 01/12/2024] [Accepted: 01/25/2024] [Indexed: 04/08/2024]
Affiliation(s)
| | | | - Antonio Luna
- MRI Unit, Radiology Department, HT Medica, Carmelo Torres 2, 23007, Jaén, Spain
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Malik P, Soliman R, Chen YA, Munoz DG, Das S, Bharatha A, Mathur S. Patterns of T2-FLAIR discordance across a cohort of adult-type diffuse gliomas and deviations from the classic T2-FLAIR mismatch sign. Neuroradiology 2024; 66:521-530. [PMID: 38347151 DOI: 10.1007/s00234-024-03297-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Accepted: 01/25/2024] [Indexed: 03/14/2024]
Abstract
PURPOSE T2-FLAIR mismatch serves as a highly specific but insensitive marker for IDH-mutant (IDHm) astrocytoma with potential limitations in real-world application. We aimed to assess the utility of a broader definition of T2-FLAIR discordance across a cohort of adult-type diffuse lower-grade gliomas (LrGG) to see if specific patterns emerge and additionally examine factors determining deviation from the classic T2-FLAIR mismatch sign. METHODS Preoperative MRIs of non-enhancing adult-type diffuse LrGGs were reviewed. Relevant demographic, molecular, and MRI data were compared across tumor subgroups. RESULTS Eighty cases satisfied the inclusion criteria. Highest discordance prevalence and > 50% T2-FLAIR discordance volume were noted with IDHm astrocytomas (P < 0.001), while < 25% discordance volume was associated with oligodendrogliomas (P = 0.03) and IDH-wildtype (IDHw) LrGG (P = 0.004). "T2-FLAIR matched pattern" was associated with IDHw LrGG (P < 0.001) and small or minimal areas of discordance with oligodendrogliomas (P = 0.03). Sensitivity and specificity of classic mismatch sign for IDHm astrocytoma were 25.7% and 100%, respectively (P = 0.06). Retained ATRX expression and/or non-canonical IDH mutation (n = 10) emerged as a significant factor associated with absence of classic T2-FLAIR mismatch sign in IDHm astrocytomas (100%, P = 0.02) and instead had minimal discordance or matched pattern (40%, P = 0.04). CONCLUSION T2-FLAIR discordance patterns in adult-type diffuse LrGGs exist on a diverging but distinct spectrum of classic mismatch to T2-FLAIR matched patterns. Specific molecular markers may play a role in deviations from classic mismatch sign.
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Affiliation(s)
- Prateek Malik
- Division of Neuroradiology, Department of Medical Imaging, St. Michael's Hospital, University of Toronto, 30 Bond St., Toronto, ON, M5B 1W8, Canada
| | - Radwa Soliman
- Diagnostic and Interventional Radiology Department, Assiut University, Asyut, Egypt
| | - Yingming Amy Chen
- Division of Neuroradiology, Department of Medical Imaging, St. Michael's Hospital, University of Toronto, 30 Bond St., Toronto, ON, M5B 1W8, Canada
| | - David G Munoz
- Department of Pathology, St. Michael's Hospital, University of Toronto, Toronto, Canada
| | - Sunit Das
- Division of Neurosurgery, St. Michael's Hospital, University of Toronto, Toronto, Canada
| | - Aditya Bharatha
- Division of Neuroradiology, Department of Medical Imaging, St. Michael's Hospital, University of Toronto, 30 Bond St., Toronto, ON, M5B 1W8, Canada
| | - Shobhit Mathur
- Division of Neuroradiology, Department of Medical Imaging, St. Michael's Hospital, University of Toronto, 30 Bond St., Toronto, ON, M5B 1W8, Canada.
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Wagner MW, Jabehdar Maralani P, Bennett J, Nobre L, Lim-Fat MJ, Dirks P, Laughlin S, Tabori U, Ramaswamy V, Hawkins C, Ertl-Wagner BB. Brain Tumor Imaging in Adolescents and Young Adults: 2021 WHO Updates for Molecular-based Tumor Types. Radiology 2024; 310:e230777. [PMID: 38349246 DOI: 10.1148/radiol.230777] [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: 02/15/2024]
Abstract
Published in 2021, the fifth edition of the World Health Organization (WHO) classification of tumors of the central nervous system (CNS) introduced new molecular criteria for tumor types that commonly occur in either pediatric or adult age groups. Adolescents and young adults (AYAs) are at the intersection of adult and pediatric care, and both pediatric-type and adult-type CNS tumors occur at that age. Mortality rates for AYAs with CNS tumors have increased by 0.6% per year for males and 1% per year for females from 2007 to 2016. To best serve patients, it is crucial that both pediatric and adult radiologists who interpret neuroimages are familiar with the various pediatric- and adult-type brain tumors and their typical imaging morphologic characteristics. Gliomas account for approximately 80% of all malignant CNS tumors in the AYA age group, with the most common types observed being diffuse astrocytic and glioneuronal tumors. Ependymomas and medulloblastomas also occur in the AYA population but are seen less frequently. Importantly, biologic behavior and progression of distinct molecular subgroups of brain tumors differ across ages. This review discusses newly added or revised gliomas in the fifth edition of the CNS WHO classification, as well as other CNS tumor types common in the AYA population.
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Affiliation(s)
- Matthias W Wagner
- From the Division of Neuroradiology, Department of Diagnostic Imaging (M.W.W., S.L., B.B.E.W.), Division of Hematology/Oncology (J.B., L.N., U.T., V.R.), Department of Paediatric Laboratory Medicine, Division of Pathology (C.H.), Division of Neurosurgery (P.D.), and Division of Pediatric Neuroradiology (M.W.W.), The Hospital for Sick Children, 555 University Ave, Toronto, ON, Canada M5G 1X8; Neurosciences & Mental Health Research Program, SickKids Research Institute, Toronto, Canada (M.W.W., B.B.E.W.); Department of Medical Imaging, University of Toronto, Toronto, Canada (M.W.W., P.J.M., B.B.E.W.); Department of Diagnostic and Interventional Neuroradiology, University Hospital Augsburg, Augsburg, Germany (M.W.W.); Divisions of Neuroradiology (P.J.M.) and Neurooncology (M.J.L.F.), Sunnybrook Health Science Centre, Toronto, Canada; and Department of Medical Oncology and Hematology, Princess Margaret Cancer Centre, Toronto, Canada (J.B.)
| | - Pejman Jabehdar Maralani
- From the Division of Neuroradiology, Department of Diagnostic Imaging (M.W.W., S.L., B.B.E.W.), Division of Hematology/Oncology (J.B., L.N., U.T., V.R.), Department of Paediatric Laboratory Medicine, Division of Pathology (C.H.), Division of Neurosurgery (P.D.), and Division of Pediatric Neuroradiology (M.W.W.), The Hospital for Sick Children, 555 University Ave, Toronto, ON, Canada M5G 1X8; Neurosciences & Mental Health Research Program, SickKids Research Institute, Toronto, Canada (M.W.W., B.B.E.W.); Department of Medical Imaging, University of Toronto, Toronto, Canada (M.W.W., P.J.M., B.B.E.W.); Department of Diagnostic and Interventional Neuroradiology, University Hospital Augsburg, Augsburg, Germany (M.W.W.); Divisions of Neuroradiology (P.J.M.) and Neurooncology (M.J.L.F.), Sunnybrook Health Science Centre, Toronto, Canada; and Department of Medical Oncology and Hematology, Princess Margaret Cancer Centre, Toronto, Canada (J.B.)
| | - Julie Bennett
- From the Division of Neuroradiology, Department of Diagnostic Imaging (M.W.W., S.L., B.B.E.W.), Division of Hematology/Oncology (J.B., L.N., U.T., V.R.), Department of Paediatric Laboratory Medicine, Division of Pathology (C.H.), Division of Neurosurgery (P.D.), and Division of Pediatric Neuroradiology (M.W.W.), The Hospital for Sick Children, 555 University Ave, Toronto, ON, Canada M5G 1X8; Neurosciences & Mental Health Research Program, SickKids Research Institute, Toronto, Canada (M.W.W., B.B.E.W.); Department of Medical Imaging, University of Toronto, Toronto, Canada (M.W.W., P.J.M., B.B.E.W.); Department of Diagnostic and Interventional Neuroradiology, University Hospital Augsburg, Augsburg, Germany (M.W.W.); Divisions of Neuroradiology (P.J.M.) and Neurooncology (M.J.L.F.), Sunnybrook Health Science Centre, Toronto, Canada; and Department of Medical Oncology and Hematology, Princess Margaret Cancer Centre, Toronto, Canada (J.B.)
| | - Liana Nobre
- From the Division of Neuroradiology, Department of Diagnostic Imaging (M.W.W., S.L., B.B.E.W.), Division of Hematology/Oncology (J.B., L.N., U.T., V.R.), Department of Paediatric Laboratory Medicine, Division of Pathology (C.H.), Division of Neurosurgery (P.D.), and Division of Pediatric Neuroradiology (M.W.W.), The Hospital for Sick Children, 555 University Ave, Toronto, ON, Canada M5G 1X8; Neurosciences & Mental Health Research Program, SickKids Research Institute, Toronto, Canada (M.W.W., B.B.E.W.); Department of Medical Imaging, University of Toronto, Toronto, Canada (M.W.W., P.J.M., B.B.E.W.); Department of Diagnostic and Interventional Neuroradiology, University Hospital Augsburg, Augsburg, Germany (M.W.W.); Divisions of Neuroradiology (P.J.M.) and Neurooncology (M.J.L.F.), Sunnybrook Health Science Centre, Toronto, Canada; and Department of Medical Oncology and Hematology, Princess Margaret Cancer Centre, Toronto, Canada (J.B.)
| | - Mary Jane Lim-Fat
- From the Division of Neuroradiology, Department of Diagnostic Imaging (M.W.W., S.L., B.B.E.W.), Division of Hematology/Oncology (J.B., L.N., U.T., V.R.), Department of Paediatric Laboratory Medicine, Division of Pathology (C.H.), Division of Neurosurgery (P.D.), and Division of Pediatric Neuroradiology (M.W.W.), The Hospital for Sick Children, 555 University Ave, Toronto, ON, Canada M5G 1X8; Neurosciences & Mental Health Research Program, SickKids Research Institute, Toronto, Canada (M.W.W., B.B.E.W.); Department of Medical Imaging, University of Toronto, Toronto, Canada (M.W.W., P.J.M., B.B.E.W.); Department of Diagnostic and Interventional Neuroradiology, University Hospital Augsburg, Augsburg, Germany (M.W.W.); Divisions of Neuroradiology (P.J.M.) and Neurooncology (M.J.L.F.), Sunnybrook Health Science Centre, Toronto, Canada; and Department of Medical Oncology and Hematology, Princess Margaret Cancer Centre, Toronto, Canada (J.B.)
| | - Peter Dirks
- From the Division of Neuroradiology, Department of Diagnostic Imaging (M.W.W., S.L., B.B.E.W.), Division of Hematology/Oncology (J.B., L.N., U.T., V.R.), Department of Paediatric Laboratory Medicine, Division of Pathology (C.H.), Division of Neurosurgery (P.D.), and Division of Pediatric Neuroradiology (M.W.W.), The Hospital for Sick Children, 555 University Ave, Toronto, ON, Canada M5G 1X8; Neurosciences & Mental Health Research Program, SickKids Research Institute, Toronto, Canada (M.W.W., B.B.E.W.); Department of Medical Imaging, University of Toronto, Toronto, Canada (M.W.W., P.J.M., B.B.E.W.); Department of Diagnostic and Interventional Neuroradiology, University Hospital Augsburg, Augsburg, Germany (M.W.W.); Divisions of Neuroradiology (P.J.M.) and Neurooncology (M.J.L.F.), Sunnybrook Health Science Centre, Toronto, Canada; and Department of Medical Oncology and Hematology, Princess Margaret Cancer Centre, Toronto, Canada (J.B.)
| | - Suzanne Laughlin
- From the Division of Neuroradiology, Department of Diagnostic Imaging (M.W.W., S.L., B.B.E.W.), Division of Hematology/Oncology (J.B., L.N., U.T., V.R.), Department of Paediatric Laboratory Medicine, Division of Pathology (C.H.), Division of Neurosurgery (P.D.), and Division of Pediatric Neuroradiology (M.W.W.), The Hospital for Sick Children, 555 University Ave, Toronto, ON, Canada M5G 1X8; Neurosciences & Mental Health Research Program, SickKids Research Institute, Toronto, Canada (M.W.W., B.B.E.W.); Department of Medical Imaging, University of Toronto, Toronto, Canada (M.W.W., P.J.M., B.B.E.W.); Department of Diagnostic and Interventional Neuroradiology, University Hospital Augsburg, Augsburg, Germany (M.W.W.); Divisions of Neuroradiology (P.J.M.) and Neurooncology (M.J.L.F.), Sunnybrook Health Science Centre, Toronto, Canada; and Department of Medical Oncology and Hematology, Princess Margaret Cancer Centre, Toronto, Canada (J.B.)
| | - Uri Tabori
- From the Division of Neuroradiology, Department of Diagnostic Imaging (M.W.W., S.L., B.B.E.W.), Division of Hematology/Oncology (J.B., L.N., U.T., V.R.), Department of Paediatric Laboratory Medicine, Division of Pathology (C.H.), Division of Neurosurgery (P.D.), and Division of Pediatric Neuroradiology (M.W.W.), The Hospital for Sick Children, 555 University Ave, Toronto, ON, Canada M5G 1X8; Neurosciences & Mental Health Research Program, SickKids Research Institute, Toronto, Canada (M.W.W., B.B.E.W.); Department of Medical Imaging, University of Toronto, Toronto, Canada (M.W.W., P.J.M., B.B.E.W.); Department of Diagnostic and Interventional Neuroradiology, University Hospital Augsburg, Augsburg, Germany (M.W.W.); Divisions of Neuroradiology (P.J.M.) and Neurooncology (M.J.L.F.), Sunnybrook Health Science Centre, Toronto, Canada; and Department of Medical Oncology and Hematology, Princess Margaret Cancer Centre, Toronto, Canada (J.B.)
| | - Vijay Ramaswamy
- From the Division of Neuroradiology, Department of Diagnostic Imaging (M.W.W., S.L., B.B.E.W.), Division of Hematology/Oncology (J.B., L.N., U.T., V.R.), Department of Paediatric Laboratory Medicine, Division of Pathology (C.H.), Division of Neurosurgery (P.D.), and Division of Pediatric Neuroradiology (M.W.W.), The Hospital for Sick Children, 555 University Ave, Toronto, ON, Canada M5G 1X8; Neurosciences & Mental Health Research Program, SickKids Research Institute, Toronto, Canada (M.W.W., B.B.E.W.); Department of Medical Imaging, University of Toronto, Toronto, Canada (M.W.W., P.J.M., B.B.E.W.); Department of Diagnostic and Interventional Neuroradiology, University Hospital Augsburg, Augsburg, Germany (M.W.W.); Divisions of Neuroradiology (P.J.M.) and Neurooncology (M.J.L.F.), Sunnybrook Health Science Centre, Toronto, Canada; and Department of Medical Oncology and Hematology, Princess Margaret Cancer Centre, Toronto, Canada (J.B.)
| | - Cynthia Hawkins
- From the Division of Neuroradiology, Department of Diagnostic Imaging (M.W.W., S.L., B.B.E.W.), Division of Hematology/Oncology (J.B., L.N., U.T., V.R.), Department of Paediatric Laboratory Medicine, Division of Pathology (C.H.), Division of Neurosurgery (P.D.), and Division of Pediatric Neuroradiology (M.W.W.), The Hospital for Sick Children, 555 University Ave, Toronto, ON, Canada M5G 1X8; Neurosciences & Mental Health Research Program, SickKids Research Institute, Toronto, Canada (M.W.W., B.B.E.W.); Department of Medical Imaging, University of Toronto, Toronto, Canada (M.W.W., P.J.M., B.B.E.W.); Department of Diagnostic and Interventional Neuroradiology, University Hospital Augsburg, Augsburg, Germany (M.W.W.); Divisions of Neuroradiology (P.J.M.) and Neurooncology (M.J.L.F.), Sunnybrook Health Science Centre, Toronto, Canada; and Department of Medical Oncology and Hematology, Princess Margaret Cancer Centre, Toronto, Canada (J.B.)
| | - Birgit B Ertl-Wagner
- From the Division of Neuroradiology, Department of Diagnostic Imaging (M.W.W., S.L., B.B.E.W.), Division of Hematology/Oncology (J.B., L.N., U.T., V.R.), Department of Paediatric Laboratory Medicine, Division of Pathology (C.H.), Division of Neurosurgery (P.D.), and Division of Pediatric Neuroradiology (M.W.W.), The Hospital for Sick Children, 555 University Ave, Toronto, ON, Canada M5G 1X8; Neurosciences & Mental Health Research Program, SickKids Research Institute, Toronto, Canada (M.W.W., B.B.E.W.); Department of Medical Imaging, University of Toronto, Toronto, Canada (M.W.W., P.J.M., B.B.E.W.); Department of Diagnostic and Interventional Neuroradiology, University Hospital Augsburg, Augsburg, Germany (M.W.W.); Divisions of Neuroradiology (P.J.M.) and Neurooncology (M.J.L.F.), Sunnybrook Health Science Centre, Toronto, Canada; and Department of Medical Oncology and Hematology, Princess Margaret Cancer Centre, Toronto, Canada (J.B.)
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10
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Zhang K, Khosravi B, Vahdati S, Erickson BJ. FDA Review of Radiologic AI Algorithms: Process and Challenges. Radiology 2024; 310:e230242. [PMID: 38165243 DOI: 10.1148/radiol.230242] [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: 01/03/2024]
Abstract
A Food and Drug Administration (FDA)-cleared artificial intelligence (AI) algorithm misdiagnosed a finding as an intracranial hemorrhage in a patient, who was finally diagnosed with an ischemic stroke. This scenario highlights a notable failure mode of AI tools, emphasizing the importance of human-machine interaction. In this report, the authors summarize the review processes by the FDA for software as a medical device and the unique regulatory designs for radiologic AI/machine learning algorithms to ensure their safety in clinical practice. Then the challenges in maximizing the efficacy of these tools posed by their clinical implementation are discussed.
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Affiliation(s)
- Kuan Zhang
- From the Department of Radiology, Mayo Clinic, 200 1st St SW, Rochester, MN 55905
| | - Bardia Khosravi
- From the Department of Radiology, Mayo Clinic, 200 1st St SW, Rochester, MN 55905
| | - Sanaz Vahdati
- From the Department of Radiology, Mayo Clinic, 200 1st St SW, Rochester, MN 55905
| | - Bradley J Erickson
- From the Department of Radiology, Mayo Clinic, 200 1st St SW, Rochester, MN 55905
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11
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Karlberg A, Pedersen LK, Vindstad BE, Skjulsvik AJ, Johansen H, Solheim O, Skogen K, Kvistad KA, Bogsrud TV, Myrmel KS, Giskeødegård GF, Ingebrigtsen T, Berntsen EM, Eikenes L. Diagnostic accuracy of anti-3-[ 18F]-FACBC PET/MRI in gliomas. Eur J Nucl Med Mol Imaging 2024; 51:496-509. [PMID: 37776502 PMCID: PMC10774221 DOI: 10.1007/s00259-023-06437-4] [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: 06/22/2023] [Accepted: 09/06/2023] [Indexed: 10/02/2023]
Abstract
PURPOSE The primary aim was to evaluate whether anti-3-[18F]FACBC PET combined with conventional MRI correlated better with histomolecular diagnosis (reference standard) than MRI alone in glioma diagnostics. The ability of anti-3-[18F]FACBC to differentiate between molecular and histopathological entities in gliomas was also evaluated. METHODS In this prospective study, patients with suspected primary or recurrent gliomas were recruited from two sites in Norway and examined with PET/MRI prior to surgery. Anti-3-[18F]FACBC uptake (TBRpeak) was compared to histomolecular features in 36 patients. PET results were then added to clinical MRI readings (performed by two neuroradiologists, blinded for histomolecular results and PET data) to assess the predicted tumor characteristics with and without PET. RESULTS Histomolecular analyses revealed two CNS WHO grade 1, nine grade 2, eight grade 3, and 17 grade 4 gliomas. All tumors were visible on MRI FLAIR. The sensitivity of contrast-enhanced MRI and anti-3-[18F]FACBC PET was 61% (95%CI [45, 77]) and 72% (95%CI [58, 87]), respectively, in the detection of gliomas. Median TBRpeak was 7.1 (range: 1.4-19.2) for PET positive tumors. All CNS WHO grade 1 pilocytic astrocytomas/gangliogliomas, grade 3 oligodendrogliomas, and grade 4 glioblastomas/astrocytomas were PET positive, while 25% of grade 2-3 astrocytomas and 56% of grade 2-3 oligodendrogliomas were PET positive. Generally, TBRpeak increased with malignancy grade for diffuse gliomas. A significant difference in PET uptake between CNS WHO grade 2 and 4 gliomas (p < 0.001) and between grade 3 and 4 gliomas (p = 0.002) was observed. Diffuse IDH wildtype gliomas had significantly higher TBRpeak compared to IDH1/2 mutated gliomas (p < 0.001). Adding anti-3-[18F]FACBC PET to MRI improved the accuracy of predicted glioma grades, types, and IDH status, and yielded 13.9 and 16.7 percentage point improvement in the overall diagnoses for both readers, respectively. CONCLUSION Anti-3-[18F]FACBC PET demonstrated high uptake in the majority of gliomas, especially in IDH wildtype gliomas, and improved the accuracy of preoperatively predicted glioma diagnoses. CLINICAL TRIAL REGISTRATION ClinicalTrials.gov ID: NCT04111588, URL: https://clinicaltrials.gov/study/NCT04111588.
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Affiliation(s)
- Anna Karlberg
- Department of Radiology and Nuclear Medicine, St. Olavs Hospital, Trondheim University Hospital, Prinsesse Kristinas gate 3, N-7030, Trondheim, Norway.
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway.
| | | | - Benedikte Emilie Vindstad
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway
| | - Anne Jarstein Skjulsvik
- Department of Pathology, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
- Department of Clinical and Molecular Medicine, Faculty of Medical and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Håkon Johansen
- Department of Radiology and Nuclear Medicine, St. Olavs Hospital, Trondheim University Hospital, Prinsesse Kristinas gate 3, N-7030, Trondheim, Norway
| | - Ole Solheim
- Department of Neurosurgery, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
- Department of Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway
| | - Karoline Skogen
- Department of Radiology and Nuclear Medicine, Oslo University Hospitals, Oslo, Norway
| | - Kjell Arne Kvistad
- Department of Radiology and Nuclear Medicine, St. Olavs Hospital, Trondheim University Hospital, Prinsesse Kristinas gate 3, N-7030, Trondheim, Norway
| | - Trond Velde Bogsrud
- PET-Centre, University Hospital of North Norway, Tromsø, Norway
- Department of Nuclear Medicine and PET-Centre, Aarhus University Hospital, Aarhus, Denmark
| | | | - Guro F Giskeødegård
- Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
| | - Tor Ingebrigtsen
- Department of Neurosurgery, University Hospital of North Norway, Tromsø, Norway
- Department of Clinical Medicine, Faculty of Health Sciences, UiT the Arctic University of Norway, Tromsø, Norway
| | - Erik Magnus Berntsen
- Department of Radiology and Nuclear Medicine, St. Olavs Hospital, Trondheim University Hospital, Prinsesse Kristinas gate 3, N-7030, Trondheim, Norway
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway
| | - Live Eikenes
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway
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12
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Campion A, Iv M. Brain Tumor Imaging: Review of Conventional and Advanced Techniques. Semin Neurol 2023; 43:867-888. [PMID: 37963581 DOI: 10.1055/s-0043-1776765] [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: 11/16/2023]
Abstract
Approaches to central nervous system (CNS) tumor classification and evaluation have undergone multiple iterations over the past few decades, in large part due to our growing understanding of the influence of genetics on tumor behavior and our refinement of brain tumor imaging techniques. Computed tomography and magnetic resonance imaging (MRI) both play a critical role in the diagnosis and monitoring of brain tumors, although MRI has become especially important due to its superior soft tissue resolution. The purpose of this article will be to briefly review the fundamentals of conventional and advanced techniques used in brain tumor imaging. We will also highlight the applications of these imaging tools in the context of commonly encountered tumors based on the most recently updated 2021 World Health Organization (WHO) classification of CNS tumors framework.
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Affiliation(s)
- Andrew Campion
- Department of Radiology (Neuroradiology), Stanford University, Stanford, California
| | - Michael Iv
- Department of Radiology (Neuroradiology), Stanford University, Stanford, California
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13
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Guo J, Fu X, Li Y, Ming H, Lin Y, Yu S, Wei H, Sun C, Zhang K, Yang X. Ultra high b-value diffusion weighted imaging enables better molecular grading stratification over histological grading in adult-type diffuse glioma. Eur J Radiol 2023; 168:111140. [PMID: 37832200 DOI: 10.1016/j.ejrad.2023.111140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 09/22/2023] [Accepted: 10/05/2023] [Indexed: 10/15/2023]
Abstract
PURPOSE Accurate preoperative radiological staging of adult-type diffuse glioma is crucial for effective prognostic stratification and selection of appropriate therapeutic interventions. The purpose of this study was to compare the effectiveness of apparent diffusion coefficient (ADC) maps generated from ultrahigh b-value diffusion-weighted imaging (DWI) for molecular grading with that for histological grading of adult-type diffuse glioma, and to evaluate the correlation between these ADC maps and molecular and histological biomarkers. METHODS This study retrospectively enrolled forty adult-type diffuse glioma patients, diagnosed using the 2021 WHO classification criteria. Preoperative imaging data, including multiple b-value DWI and conventional magnetic resonance imaging, were collected. Tumors were graded using both histological and molecular criteria. Histogram analysis was conducted to generate 14 parameters for each tumor. Receiver operating characteristic curves and the area under the curve (AUC) were used to evaluate tumor grading and molecular status differentiation. Analysis of histological biomarkers was performed by calculating the Pearson and Spearman correlation coefficients of continuous and hierarchical variables, respectively. RESULTS The intensity-related parameters for molecular grading were found to be superior to those for histological grading for the identification of WHO grade 4 (WHO4) adult-type diffuse glioma. The AUC of both grading systems increased with increasing b-values, with ADC8000-based histogram parameters showing the best results (molecular grading, square root: AUC = 0.897; histological grading, median: AUC = 0.737). The intensity-related parameters could also differentiate molecular WHO4 gliomas from histologically lower-grade gliomas (ADC8000-based square root: AUC = 0.919), and different ADC8000-based kurtosis was observed between molecular and histological WHO4 gliomas (AUC = 0.833). Significant correlations between the Ki-67 index and molecular status prediction for IDH, CDKN2A, and EGFR were also demonstrated. CONCLUSION The histogram parameters derived from high b-value ADC maps were found to be more effective for differentiating molecular grades of WHO4 adult-type diffuse glioma than for differentiating histological grades.
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Affiliation(s)
- Jiahe Guo
- Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China
| | - Xiuwei Fu
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China
| | - Yiming Li
- Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China
| | - Haolang Ming
- Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China
| | - Yu Lin
- Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China
| | - Shengping Yu
- Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China
| | - Huijie Wei
- Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China
| | - Cuiyun Sun
- Department of Neuropathology, Tianjin Medical University General Hospital, Tianjin, China
| | - Kai Zhang
- Department of Neurosurgery, Beijing Tsinghua Changgung Hospital, Tsinghua University, Beijing, China; Institute for Intelligent Healthcare, Tsinghua University, Beijing, China
| | - Xuejun Yang
- Department of Neurosurgery, Beijing Tsinghua Changgung Hospital, Tsinghua University, Beijing, China; Institute for Intelligent Healthcare, Tsinghua University, Beijing, China.
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14
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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 2-Summary of Imaging Findings on Pediatric-Type Diffuse High-Grade Gliomas, Pediatric-Type Diffuse Low-Grade Gliomas, and Circumscribed Astrocytic Gliomas. J Magn Reson Imaging 2023; 58:690-708. [PMID: 37069764 DOI: 10.1002/jmri.28740] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 03/26/2023] [Accepted: 03/27/2023] [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. This Part 2 review focuses on the molecular diagnostics and imaging findings of pediatric-type diffuse high-grade gliomas, pediatric-type diffuse low-grade gliomas, and circumscribed astrocytic gliomas. Each tumor type in pediatric-type diffuse high-grade glioma mostly harbors a distinct molecular marker. On the other hand, in pediatric-type diffuse low-grade gliomas and circumscribed astrocytic gliomas, molecular diagnostics may be extremely complicated at a glance in the 2021 WHO classification. It is crucial for radiologists to understand the molecular diagnostics and imaging findings and leverage the knowledge in clinical practice. 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, South 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, South Korea
| | - Jong Hee Chang
- Department of Neurosurgery, Yonsei University College of Medicine, Seoul, South Korea
| | - Se Hoon Kim
- Department of Pathology, Yonsei University College of Medicine, Seoul, South Korea
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15
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Anzai Y, Ertl-Wagner B. Neuroradiology 2040: A Glimpse into the Future. Radiology 2023; 308:e231267. [PMID: 37750766 DOI: 10.1148/radiol.231267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/27/2023]
Affiliation(s)
- Yoshimi Anzai
- From the Department of Radiology and Imaging Sciences, University of Utah Health, Salth Lake City, Utah (Y.A.); Department of Diagnostic and Interventional Radiology, The Hospital for Sick Children, 555 University Ave, Toronto, ON, Canada M5G 1X8 (B.E.W.); and Department of Medical Imaging, University of Toronto, Toronto, Ontario, Canada (B.E.W.)
| | - Birgit Ertl-Wagner
- From the Department of Radiology and Imaging Sciences, University of Utah Health, Salth Lake City, Utah (Y.A.); Department of Diagnostic and Interventional Radiology, The Hospital for Sick Children, 555 University Ave, Toronto, ON, Canada M5G 1X8 (B.E.W.); and Department of Medical Imaging, University of Toronto, Toronto, Ontario, Canada (B.E.W.)
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16
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Griessmair M, Delbridge C, Ziegenfeuter J, Bernhardt D, Gempt J, Schmidt-Graf F, Kertels O, Thomas M, Meyer HS, Zimmer C, Meyer B, Combs SE, Yakushev I, Wiestler B, Metz MC. Imaging the WHO 2021 Brain Tumor Classification: Fully Automated Analysis of Imaging Features of Newly Diagnosed Gliomas. Cancers (Basel) 2023; 15:2355. [PMID: 37190283 PMCID: PMC10136825 DOI: 10.3390/cancers15082355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2023] [Revised: 03/13/2023] [Accepted: 04/14/2023] [Indexed: 05/17/2023] Open
Abstract
BACKGROUND The fifth version of the World Health Organization (WHO) classification of tumors of the central nervous system (CNS) in 2021 brought substantial changes. Driven by the enhanced implementation of molecular characterization, some diagnoses were adapted while others were newly introduced. How these changes are reflected in imaging features remains scarcely investigated. MATERIALS AND METHODS We retrospectively analyzed 226 treatment-naive primary brain tumor patients from our institution who received extensive molecular characterization by epigenome-wide methylation microarray and were diagnosed according to the 2021 WHO brain tumor classification. From multimodal preoperative 3T MRI scans, we extracted imaging metrics via a fully automated, AI-based image segmentation and processing pipeline. Subsequently, we examined differences in imaging features between the three main glioma entities (glioblastoma, astrocytoma, and oligodendroglioma) and particularly investigated new entities such as astrocytoma, WHO grade 4. RESULTS Our results confirm prior studies that found significantly higher median CBV (p = 0.00003, ANOVA) and lower median ADC in contrast-enhancing areas of glioblastomas, compared to astrocytomas and oligodendrogliomas (p = 0.41333, ANOVA). Interestingly, molecularly defined glioblastoma, which usually does not contain contrast-enhancing areas, also shows significantly higher CBV values in the non-enhancing tumor than common glioblastoma and astrocytoma grade 4 (p = 0.01309, ANOVA). CONCLUSIONS This work provides extensive insights into the imaging features of gliomas in light of the new 2021 WHO CNS tumor classification. Advanced imaging shows promise in visualizing tumor biology and improving the diagnosis of brain tumor patients.
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Affiliation(s)
- Michael Griessmair
- Department of Neuroradiology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
| | - Claire Delbridge
- Department of Pathology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
| | - Julian Ziegenfeuter
- Department of Neuroradiology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
| | - Denise Bernhardt
- Department of Radiation Oncology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
| | - Jens Gempt
- Department of Neurosurgery, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany
| | | | - Olivia Kertels
- Department of Neuroradiology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
| | - Marie Thomas
- Department of Neuroradiology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
| | - Hanno S. Meyer
- Department of Neurosurgery, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany
| | - Claus Zimmer
- Department of Neuroradiology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
| | - Bernhard Meyer
- Department of Neurosurgery, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
| | - Stephanie E. Combs
- Department of Radiation Oncology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
| | - Igor Yakushev
- Department of Nuclear Medicine, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
| | - Benedikt Wiestler
- Department of Neuroradiology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
- TranslaTUM, TU Munich, 81675 Munich, Germany
| | - Marie-Christin Metz
- Department of Neuroradiology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany
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