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Hwa JC, Wong AMC, Jung SM, Wu CT. Pediatric-type diffuse low-grade glioma with T2-FLAIR mismatch sign: a case report and literature review. Childs Nerv Syst 2024; 40:2271-2278. [PMID: 38884778 DOI: 10.1007/s00381-024-06487-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/25/2023] [Accepted: 06/01/2024] [Indexed: 06/18/2024]
Abstract
INTRODUCTION Pediatric-type diffuse low-grade gliomas are a new entity that was introduced in the fifth edition of the World Health Organization Classification of Tumors of the Central Nervous System, which was published in 2021. Notably, the information regarding the radiophenotypes of this new entity is limited. OBJECTIVE T2-FLAIR mismatch sign has been mostly studied in adult-type diffuse gliomas so far. We aimed to present more pediatric cases for future research about T2-FLAIR mismatch signs in pediatric-type diffuse low-grade gliomas. CASE PRESENTATION The current study presents a case of a 2-year-old boy who has a subcortical tumor at the right precentral frontal region. This tumor exhibited a T2-fluid-attenuated inversion recovery (FLAIR) mismatch sign that was identified as specific for isocitrate dehydrogenase (IDH)-mutant 1p/19q non-co-deleted astrocytomas. The tumor was pathologically identified as pediatric-type diffuse low-grade gliomas, and it tested negative for IDH-1 immunohistochemistry. The whole-exome sequencing of tumor tissue revealed negative results for IDH mutation, 1p/19q co-deletion, MYB rearrangement, and all other potential pathogenic mutations. CONCLUSION The T2-FLAIR mismatch sign may not be 100% specific for IDH-mutant gliomas, especially in children, and researchers must further investigate the pathophysiology of the T2-FLAIR mismatch sign in brain tumors and the radiophenotypes of entities of pediatric brain tumors.
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Affiliation(s)
- Jia-Ching Hwa
- Department of Medical Imaging, National Taiwan University Hospital, Taipei, Taiwan
| | - Alex Mun-Ching Wong
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Keelung and Linkou, Chang Gung University College of Medicine, Keelung and Linkou, Taiwan
| | - Shih-Ming Jung
- Department of Pathology, Chang Gung Memorial Hospital, Taoyuan, Linkou, Taiwan
| | - Chieh-Tsai Wu
- Department of Neurosurgery, Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Taoyuan, Linkou, Taiwan.
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Lu Y, Du N, Fang X, Shu W, Liu W, Xu X, Ye Y, Xiao L, Mao R, Li K, Lin G, Li S. Identification of T2W hypointense ring as a novel noninvasive indicator for glioma grade and IDH genotype. Cancer Imaging 2024; 24:80. [PMID: 38943156 PMCID: PMC11212435 DOI: 10.1186/s40644-024-00726-3] [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: 06/21/2023] [Accepted: 06/20/2024] [Indexed: 07/01/2024] Open
Abstract
BACKGROUND This study aimed to evaluate the T2W hypointense ring and T2-FLAIR mismatch signs in gliomas and use these signs to construct prediction models for glioma grading and isocitrate dehydrogenase (IDH) mutation status. METHODS Two independent radiologists retrospectively evaluated 207 glioma patients to assess the presence of T2W hypointense ring and T2-FLAIR mismatch signs. The inter-rater reliability was calculated using the Cohen's kappa statistic. Two logistic regression models were constructed to differentiate glioma grade and predict IDH genotype noninvasively, respectively. Receiver operating characteristic (ROC) analysis was used to evaluate the developed models. RESULTS Of the 207 patients enrolled (119 males and 88 females, mean age 51.6 ± 14.8 years), 45 cases were low-grade gliomas (LGGs), 162 were high-grade gliomas (HGGs), 55 patients had IDH mutations, and 116 were IDH wild-type. The number of T2W hypointense ring signs was higher in HGGs compared to LGGs (p < 0.001) and higher in the IDH wild-type group than in the IDH mutant group (p < 0.001). There were also significant differences in T2-FLAIR mismatch signs between HGGs and LGGs, as well as between IDH mutant and wild-type groups (p < 0.001). Two predictive models incorporating T2W hypointense ring, absence of T2-FLAIR mismatch, and age were constructed. The area under the ROC curve (AUROC) was 0.940 for predicting HGGs (95% CI = 0.907-0.972) and 0.830 for differentiating IDH wild-type (95% CI = 0.757-0.904). CONCLUSIONS The combination of T2W hypointense ring, absence of T2-FLAIR mismatch, and age demonstrate good predictive capability for HGGs and IDH wild-type. These findings suggest that MRI can be used noninvasively to predict glioma grading and IDH mutation status, which may have important implications for patient management and treatment planning.
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Affiliation(s)
- Yawen Lu
- Department of Radiology, Huadong Hospital, Fudan University, No.220 West YanAn Road, Shanghai, 200040, China
| | - Ningfang Du
- Department of Radiology, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Xuhao Fang
- Department of Neurosurgery, Huadong Hospital, Fudan University, Shanghai, China
| | - Weiquan Shu
- Department of Neurosurgery, Huadong Hospital, Fudan University, Shanghai, China
| | - Wei Liu
- Department of Radiology, Huadong Hospital, Fudan University, No.220 West YanAn Road, Shanghai, 200040, China
| | - Xinxin Xu
- Clinical Research Center for Gerontology, Huadong Hospital, Fudan University, Shanghai, China
| | - Yao Ye
- Department of Pathology, Huadong Hospital, Fudan University, Shanghai, China
| | - Li Xiao
- Department of Pathology, Huadong Hospital, Fudan University, Shanghai, China
| | - Renling Mao
- Department of Neurosurgery, Huadong Hospital, Fudan University, Shanghai, China
| | - Kefeng Li
- Center for AI-driven Drug Discovery, Faculty of Applied Sciences, Macao Polytechnic University, Macao, SAR, China.
| | - Guangwu Lin
- Department of Radiology, Huadong Hospital, Fudan University, No.220 West YanAn Road, Shanghai, 200040, China.
| | - Shihong Li
- Department of Radiology, Huadong Hospital, Fudan University, No.220 West YanAn Road, Shanghai, 200040, China.
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Ma A, Yan X, Qu Y, Wen H, Zou X, Liu X, Lu M, Mo J, Wen Z. Amide proton transfer weighted and diffusion weighted imaging based radiomics classification algorithm for predicting 1p/19q co-deletion status in low grade gliomas. BMC Med Imaging 2024; 24:85. [PMID: 38600452 PMCID: PMC11005152 DOI: 10.1186/s12880-024-01262-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 03/27/2024] [Indexed: 04/12/2024] Open
Abstract
BACKGROUND 1p/19q co-deletion in low-grade gliomas (LGG, World Health Organization grade II and III) is of great significance in clinical decision making. We aim to use radiomics analysis to predict 1p/19q co-deletion in LGG based on amide proton transfer weighted (APTw), diffusion weighted imaging (DWI), and conventional MRI. METHODS This retrospective study included 90 patients histopathologically diagnosed with LGG. We performed a radiomics analysis by extracting 8454 MRI-based features form APTw, DWI and conventional MR images and applied a least absolute shrinkage and selection operator (LASSO) algorithm to select radiomics signature. A radiomics score (Rad-score) was generated using a linear combination of the values of the selected features weighted for each of the patients. Three neuroradiologists, including one experienced neuroradiologist and two resident physicians, independently evaluated the MR features of LGG and provided predictions on whether the tumor had 1p/19q co-deletion or 1p/19q intact status. A clinical model was then constructed based on the significant variables identified in this analysis. A combined model incorporating both the Rad-score and clinical factors was also constructed. The predictive performance was validated by receiver operating characteristic curve analysis, DeLong analysis and decision curve analysis. P < 0.05 was statistically significant. RESULTS The radiomics model and the combined model both exhibited excellent performance on both the training and test sets, achieving areas under the curve (AUCs) of 0.948 and 0.966, as well as 0.909 and 0.896, respectively. These results surpassed the performance of the clinical model, which achieved AUCs of 0.760 and 0.766 on the training and test sets, respectively. After performing Delong analysis, the clinical model did not significantly differ in predictive performance from three neuroradiologists. In the training set, both the radiomic and combined models performed better than all neuroradiologists. In the test set, the models exhibited higher AUCs than the neuroradiologists, with the radiomics model significantly outperforming resident physicians B and C, but not differing significantly from experienced neuroradiologist. CONCLUSIONS Our results suggest that our algorithm can noninvasively predict the 1p/19q co-deletion status of LGG. The predictive performance of radiomics model was comparable to that of experienced neuroradiologist, significantly outperforming the diagnostic accuracy of resident physicians, thereby offering the potential to facilitate non-invasive 1p/19q co-deletion prediction of LGG.
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Affiliation(s)
- Andong Ma
- Department of Radiology, Zhujiang Hospital, Southern Medical University, Haizhu District, 253 Gongye Middle Avenue, Guangzhou, Guangdong, 510282, China
| | - Xinran Yan
- Department of Radiology, Zhujiang Hospital, Southern Medical University, Haizhu District, 253 Gongye Middle Avenue, Guangzhou, Guangdong, 510282, China
| | - Yaoming Qu
- Department of Radiology, Zhujiang Hospital, Southern Medical University, Haizhu District, 253 Gongye Middle Avenue, Guangzhou, Guangdong, 510282, China
| | - Haitao Wen
- Department of Radiology, Zhujiang Hospital, Southern Medical University, Haizhu District, 253 Gongye Middle Avenue, Guangzhou, Guangdong, 510282, China
| | - Xia Zou
- Department of Radiology, Zhujiang Hospital, Southern Medical University, Haizhu District, 253 Gongye Middle Avenue, Guangzhou, Guangdong, 510282, China
| | - Xinzi Liu
- Department of Radiology, Zhujiang Hospital, Southern Medical University, Haizhu District, 253 Gongye Middle Avenue, Guangzhou, Guangdong, 510282, China
| | - Mingjun Lu
- Department of Radiology, Zhujiang Hospital, Southern Medical University, Haizhu District, 253 Gongye Middle Avenue, Guangzhou, Guangdong, 510282, China
| | - Jianhua Mo
- Department of Radiology, Zhujiang Hospital, Southern Medical University, Haizhu District, 253 Gongye Middle Avenue, Guangzhou, Guangdong, 510282, China
| | - Zhibo Wen
- Department of Radiology, Zhujiang Hospital, Southern Medical University, Haizhu District, 253 Gongye Middle Avenue, Guangzhou, Guangdong, 510282, China.
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Park YW, Kim S, Han K, Ahn SS, Moon JH, Kim EH, Kim J, Kang SG, Kim SH, Lee SK, Chang JH. Rethinking extent of resection of contrast-enhancing and non-enhancing tumor: different survival impacts on adult-type diffuse gliomas in 2021 World Health Organization classification. Eur Radiol 2024; 34:1376-1387. [PMID: 37608093 DOI: 10.1007/s00330-023-10125-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Revised: 06/22/2023] [Accepted: 07/01/2023] [Indexed: 08/24/2023]
Abstract
OBJECTIVES Extent of resection (EOR) of contrast-enhancing (CE) and non-enhancing (NE) tumors may have different impacts on survival according to types of adult-type diffuse gliomas in the molecular era. This study aimed to evaluate the impact of EOR of CE and NE tumors in glioma according to the 2021 World Health Organization classification. METHODS This retrospective study included 1193 adult-type diffuse glioma patients diagnosed between 2001 and 2021 (183 oligodendroglioma, 211 isocitrate dehydrogenase [IDH]-mutant astrocytoma, and 799 IDH-wildtype glioblastoma patients) from a single institution. Patients had complete information on IDH mutation, 1p/19q codeletion, and O6-methylguanine-methyltransferase (MGMT) status. Cox survival analyses were performed within each glioma type to assess predictors of overall survival, including clinical, imaging data, histological grade, MGMT status, adjuvant treatment, and EOR of CE and NE tumors. Subgroup analyses were performed in patients with CE tumor. RESULTS Among 1193 patients, 935 (78.4%) patients had CE tumors. In entire oligodendrogliomas, gross total resection (GTR) of NE tumor was not associated with survival (HR = 0.56, p = 0.223). In 86 (47.0%) oligodendroglioma patients with CE tumor, GTR of CE tumor was the only independent predictor of survival (HR = 0.16, p = 0.004) in multivariable analysis. GTR of CE and NE tumors was independently associated with better survival in IDH-mutant astrocytoma and IDH-wildtype glioblastoma (all ps < 0.05). CONCLUSIONS GTR of both CE and NE tumors may significantly improve survival within IDH-mutant astrocytomas and IDH-wildtype glioblastomas. In oligodendrogliomas, the EOR of CE tumor may be crucial in survival; aggressive GTR of NE tumor may be unnecessary, whereas GTR of the CE tumor is recommended. CLINICAL RELEVANCE STATEMENT Surgical strategies on contrast-enhancing (CE) and non-enhancing (NE) tumors should be reassessed considering the different survival outcomes after gross total resection depending on CE and NE tumors in the 2021 World Health Organization classification of adult-type diffuse gliomas. KEY POINTS The survival impact of extent of resection of contrast-enhancing (CE) and non-enhancing (NE) tumors was evaluated in adult-type diffuse gliomas. Gross total resection of both CE and NE tumors may improve survival in isocitrate dehydrogenase (IDH)-mutant astrocytomas and IDH-wildtype glioblastomas, while only gross total resection of the CE tumor improves survival in oligodendrogliomas. Surgical strategies should be reconsidered according to types in adult-type diffuse gliomas.
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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, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Korea
| | - Sooyon Kim
- Department of Statistics and Data Science, Yonsei University, Seoul, Korea
| | - Kyunghwa Han
- Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Korea
| | - Sung Soo Ahn
- Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Korea.
| | - Ju Hyung Moon
- Department of Neurosurgery, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Korea
| | - Eui Hyun Kim
- Department of Neurosurgery, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Korea
| | - Jinna Kim
- Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Korea
| | - Seok-Gu Kang
- Department of Neurosurgery, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Korea
| | - Se Hoon Kim
- Department of Pathology, Yonsei University College of Medicine, Seoul, Korea
| | - Seung-Koo Lee
- Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Korea
| | - Jong Hee Chang
- Department of Neurosurgery, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Korea.
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Godoy LFDS, Paes VR, Ayres AS, Bandeira GA, Moreno RA, Hirata FDCC, Silva FAB, Nascimento F, Campos Neto GDC, Gentil AF, Lucato LT, Amaro Junior E, Young RJ, Malheiros SMF. Advances in diffuse glial tumors diagnosis. ARQUIVOS DE NEURO-PSIQUIATRIA 2023; 81:1134-1145. [PMID: 38157879 PMCID: PMC10756793 DOI: 10.1055/s-0043-1777729] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Accepted: 10/27/2023] [Indexed: 01/03/2024]
Abstract
In recent decades, there have been significant advances in the diagnosis of diffuse gliomas, driven by the integration of novel technologies. These advancements have deepened our understanding of tumor oncogenesis, enabling a more refined stratification of the biological behavior of these neoplasms. This progress culminated in the fifth edition of the WHO classification of central nervous system (CNS) tumors in 2021. This comprehensive review article aims to elucidate these advances within a multidisciplinary framework, contextualized within the backdrop of the new classification. This article will explore morphologic pathology and molecular/genetics techniques (immunohistochemistry, genetic sequencing, and methylation profiling), which are pivotal in diagnosis, besides the correlation of structural neuroimaging radiophenotypes to pathology and genetics. It briefly reviews the usefulness of tractography and functional neuroimaging in surgical planning. Additionally, the article addresses the value of other functional imaging techniques such as perfusion MRI, spectroscopy, and nuclear medicine in distinguishing tumor progression from treatment-related changes. Furthermore, it discusses the advantages of evolving diagnostic techniques in classifying these tumors, as well as their limitations in terms of availability and utilization. Moreover, the expanding domains of data processing, artificial intelligence, radiomics, and radiogenomics hold great promise and may soon exert a substantial influence on glioma diagnosis. These innovative technologies have the potential to revolutionize our approach to these tumors. Ultimately, this review underscores the fundamental importance of multidisciplinary collaboration in employing recent diagnostic advancements, thereby hoping to translate them into improved quality of life and extended survival for glioma patients.
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Affiliation(s)
- Luis Filipe de Souza Godoy
- Hospital Israelita Albert Einstein, Departamento de Radiologia, Seção de Neuroradiologia, São Paulo SP, Brazil.
- Universidade de São Paulo, Faculdade de Medicina, Hospital das Clínicas, Seção de Neuroradiologia, São Paulo SP, Brazil.
| | - Vitor Ribeiro Paes
- Hospital Israelita Albert Einstein, Laboratório de Patologia Cirúrgica, São Paulo SP, Brazil.
- Universidade de São Paulo, Faculdade de Medicina, Departamento de Patologia, São Paulo SP, Brazil.
| | - Aline Sgnolf Ayres
- Universidade de São Paulo, Faculdade de Medicina, Hospital das Clínicas, Seção de Neuroradiologia, São Paulo SP, Brazil.
| | - Gabriela Alencar Bandeira
- Instituto do Câncer do Estado de São Paulo, Departamento de Radiologia, Seção de Neuroradiologia, São Paulo SP, Brazil.
| | - Raquel Andrade Moreno
- Instituto do Câncer do Estado de São Paulo, Departamento de Radiologia, Seção de Neuroradiologia, São Paulo SP, Brazil.
- Rede D'Or São Luiz, Departamento de Radiologia, Seção de Neuroradiologia, São Paulo SP, Brazil.
| | | | | | - Felipe Nascimento
- Hospital Israelita Albert Einstein, Departamento de Radiologia, Seção de Neuroradiologia, São Paulo SP, Brazil.
| | | | - Andre Felix Gentil
- Hospital Israelita Albert Einstein, Departamento de Neurocirurgia, São Paulo SP, Brazil.
| | - Leandro Tavares Lucato
- Universidade de São Paulo, Faculdade de Medicina, Hospital das Clínicas, Seção de Neuroradiologia, São Paulo SP, Brazil.
- Grupo Fleury, São Paulo SP, Brazil.
| | - Edson Amaro Junior
- Hospital Israelita Albert Einstein, Departamento de Radiologia, Seção de Neuroradiologia, São Paulo SP, Brazil.
| | - Robert J. Young
- Memorial Sloan-Kettering Cancer Center, Neuroradiology Service, New York, New York, United States.
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Picca A, Bruno F, Nichelli L, Sanson M, Rudà R. Advances in molecular and imaging biomarkers in lower-grade gliomas. Expert Rev Neurother 2023; 23:1217-1231. [PMID: 37982735 DOI: 10.1080/14737175.2023.2285472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Accepted: 11/15/2023] [Indexed: 11/21/2023]
Abstract
INTRODUCTION Lower-grade (grade 2-3) gliomas (LGGs) constitutes a group of primary brain tumors with variable clinical behaviors and treatment responses. Recent advancements in molecular biology have redefined their classification, and novel imaging modalities emerged for the noninvasive diagnosis and follow-up. AREAS COVERED This review comprehensively analyses the current knowledge on molecular and imaging biomarkers in LGGs. Key molecular alterations, such as IDH mutations and 1p/19q codeletion, are discussed for their prognostic and predictive implications in guiding treatment decisions. Moreover, the authors explore theranostic biomarkers for the potential of tailored therapies. Additionally, they also describe the utility of advanced imaging modalities, including widely available techniques, as dynamic susceptibility contrast perfusion-weighted imaging and less validated, emerging approaches, for the noninvasive LGGs characterization and follow-up. EXPERT OPINION The integration of molecular markers enhanced the stratification of LGGs, leading to the new concept of integrated histomolecular classification. While the IDH mutation is an established key prognostic and predictive marker, recent results from IDH inhibitors trials showed its potential value as a theranostic marker. In this setting, advanced MRI techniques such as 2-D-hydroxyglutarate spectroscopy are very promising for the noninvasive diagnosis and monitoring of LGGs. This progress offers exciting prospects for personalized medicine and improved treatment outcomes in LGGs.
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Affiliation(s)
- Alberto Picca
- Service de Neurologie 2 Mazarin, Hôpital Universitaire Pitié-Salpêtrière, AP-HP, Paris, France
- Sorbonne Université, Inserm, CNRS, UMRS1127, Institut du Cerveau-Paris Brain Institute-ICM, AP-HP, Paris, France
| | - Francesco Bruno
- Division of Neuro-Oncology, Department of Neuroscience "Rita Levi Montalcini", University and City of Health and Science University Hospital, Turin, Italy
| | - Lucia Nichelli
- Service de Neuroradiologie, Hôpital Universitaire Pitié-Salpêtrière, AP-HP, Paris, France
| | - Marc Sanson
- Service de Neurologie 2 Mazarin, Hôpital Universitaire Pitié-Salpêtrière, AP-HP, Paris, France
- Sorbonne Université, Inserm, CNRS, UMRS1127, Institut du Cerveau-Paris Brain Institute-ICM, AP-HP, Paris, France
| | - Roberta Rudà
- Division of Neuro-Oncology, Department of Neuroscience "Rita Levi Montalcini", University and City of Health and Science University Hospital, Turin, Italy
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Li M, Wang J, Chen X, Dong G, Zhang W, Shen S, Jiang H, Yang C, Zhang X, Zhao X, Zhu Q, Li M, Cui Y, Ren X, Lin S. The sinuous, wave-like intratumoral-wall sign is a sensitive and specific radiological biomarker for oligodendrogliomas. Eur Radiol 2022; 33:4440-4452. [PMID: 36520179 DOI: 10.1007/s00330-022-09314-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2022] [Revised: 10/10/2022] [Accepted: 11/21/2022] [Indexed: 12/23/2022]
Abstract
OBJECTIVES The purpose of this study was to investigate the clinical utility of the sinuous, wave-like intratumoral-wall (SWITW) sign on T2WI in diagnosing isocitrate dehydrogenase (IDH) mutant and 1p/19q codeleted (IDHmut-Codel) oligodendrogliomas, for which a relatively conservative resection strategy might be sufficient due to a better response to chemoradiotherapy and favorable prognosis. METHODS Imaging data from consecutive adult patients with diffuse lower-grade gliomas (LGGs, histological grades 2-3) in Beijing Tiantan Hospital (December 1, 2013, to October 31, 2021, BTH set, n = 711) and the Cancer Imaging Archive (TCIA) LGGs set (n = 117) were used to develop and validate our findings. Two independent observers assessed the SWITW sign and some well-reported discriminative radiological features to establish a practical diagnostic strategy. RESULTS The SWITW sign showed satisfying sensitivity (0.684 and 0.722 for BTH and TCIA sets) and specificity (0.938 and 0.914 for BTH and TCIA sets) in defining IDHmut-Codels, and the interobserver agreement was substantial (κ 0.718 and 0.756 for BTH and TCIA sets). Compared to calcification, the SWITW sign improved the sensitivity by 0.28 (0.404 to 0.684) in the BTH set, and 81.0% (277/342) of IDHmut-Codel cases demonstrated SWITW and/ or calcification positivity. Combining the SWITW sign, calcification, low ADC values, and other discriminative features, we established a concise and reliable diagnostic protocol for IDHmut-Codels. CONCLUSIONS The SWITW sign was a sensitive and specific imaging biomarker for IDHmut-Codels. The integrated protocol provided an explicable, efficient, and reproducible method for precise preoperative diagnosis, which was essential to guide individualized surgical plan-making. KEY POINTS • The SWITW sign was a sensitive and specific imaging biomarker for IDHmut-Codel oligodendrogliomas. • The SWITW sign was more sensitive than calcification and an integrated strategy could improve diagnostic sensitivity for IDHmut-Codel oligodendrogliomas. • Combining SWITW, calcification, low ADC values, and other discriminative features could make a precise preoperative diagnosis for IDHmut-Codel oligodendrogliomas.
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Affiliation(s)
- Mingxiao Li
- Department of Neurosurgical Oncology, Beijing Tiantan Hospital, Capital Medical University, China National Clinical Research Center for Neurological Diseases, Beijing Neurosurgical Institute, Beijing, 100070, China
- Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Jincheng Wang
- Department of Radiology, Peking University Cancer Hospital, Beijing, China
| | - Xuzhu Chen
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Gehong Dong
- Department of Pathology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Weiwei Zhang
- Department of Pathology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Shaoping Shen
- Department of Neurosurgical Oncology, Beijing Tiantan Hospital, Capital Medical University, China National Clinical Research Center for Neurological Diseases, Beijing Neurosurgical Institute, Beijing, 100070, China
- Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Haihui Jiang
- Department of Neurosurgery, Peking University Third Hospital, Peking University, Beijing, China
| | - Chuanwei Yang
- Department of Neurosurgical Oncology, Beijing Tiantan Hospital, Capital Medical University, China National Clinical Research Center for Neurological Diseases, Beijing Neurosurgical Institute, Beijing, 100070, China
- Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Xiaokang Zhang
- Department of Neurosurgical Oncology, Beijing Tiantan Hospital, Capital Medical University, China National Clinical Research Center for Neurological Diseases, Beijing Neurosurgical Institute, Beijing, 100070, China
- Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Xuzhe Zhao
- Department of Neurosurgical Oncology, Beijing Tiantan Hospital, Capital Medical University, China National Clinical Research Center for Neurological Diseases, Beijing Neurosurgical Institute, Beijing, 100070, China
- Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Qinghui Zhu
- Department of Neurosurgical Oncology, Beijing Tiantan Hospital, Capital Medical University, China National Clinical Research Center for Neurological Diseases, Beijing Neurosurgical Institute, Beijing, 100070, China
- Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Ming Li
- Department of Neurosurgical Oncology, Beijing Tiantan Hospital, Capital Medical University, China National Clinical Research Center for Neurological Diseases, Beijing Neurosurgical Institute, Beijing, 100070, China
- Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Yong Cui
- Department of Neurosurgical Oncology, Beijing Tiantan Hospital, Capital Medical University, China National Clinical Research Center for Neurological Diseases, Beijing Neurosurgical Institute, Beijing, 100070, China
- Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Xiaohui Ren
- Department of Neurosurgical Oncology, Beijing Tiantan Hospital, Capital Medical University, China National Clinical Research Center for Neurological Diseases, Beijing Neurosurgical Institute, Beijing, 100070, China.
- Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
| | - Song Lin
- Department of Neurosurgical Oncology, Beijing Tiantan Hospital, Capital Medical University, China National Clinical Research Center for Neurological Diseases, Beijing Neurosurgical Institute, Beijing, 100070, China.
- Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
- Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Center of Brain Tumor, Institute for Brain Disorders and Beijing Key Laboratory of Brain Tumor, Beijing, China.
- Department of Neurosurgical Oncology, Beijing Tiantan Hospital, Center of Brain Tumor, Beijing Institute for Brain Disorders, Beijing Key Laboratory of Brain Tumor, Capital Medical University, China National Clinical Research Center for Neurological Diseases, Beijing Neurosurgical Institute, Beijing, 100070, China.
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Jang EB, Kim HS, Park JE, Park SY, Nam YK, Nam SJ, Kim YH, Kim JH. Diffuse glioma, not otherwise specified: imaging-based risk stratification achieves histomolecular-level prognostication. Eur Radiol 2022; 32:7780-7788. [PMID: 35587830 DOI: 10.1007/s00330-022-08850-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Revised: 04/20/2022] [Accepted: 04/27/2022] [Indexed: 01/03/2023]
Abstract
OBJECTIVES To determine whether imaging-based risk stratification enables prognostication in diffuse glioma, NOS (not otherwise specified). METHODS Data from 220 patients classified as diffuse glioma, NOS, between January 2011 and December 2020 were retrospectively included. Two neuroradiologists analyzed pre-surgical CT and MRI to assign gliomas to the three imaging-based risk types considering well-known imaging phenotypes (e.g., T2/FLAIR mismatch). According to the 2021 World Health Organization classification, the three risk types included (1) low-risk, expecting oligodendroglioma, isocitrate dehydrogenase (IDH)-mutant, and 1p/19q-codeleted; (2) intermediate-risk, expecting astrocytoma, IDH-mutant; and (3) high-risk, expecting glioblastoma, IDH-wildtype. Progression-free survival (PFS) and overall survival (OS) were estimated for each risk type. Time-dependent receiver operating characteristic analysis using 10-fold cross-validation with 100-fold bootstrapping was used to compare the performance of an imaging-based survival model with that of a historical molecular-based survival model published in 2015, created using The Cancer Genome Archive data. RESULTS Prognostication according to the three imaging-based risk types was achieved for both PFS and OS (log-rank test, p < 0.001). The imaging-based survival model showed high prognostic value, with areas under the curves (AUCs) of 0.772 and 0.650 for 1-year PFS and OS, respectively, similar to the historical molecular-based survival model (AUC = 0.74 for PFS and 0.87 for OS). The imaging-based survival model achieved high long-term performance in both 3-year PFS (AUC = 0.806) and 5-year OS (AUC = 0.812). CONCLUSION Imaging-based risk stratification achieved histomolecular-level prognostication in diffuse glioma, NOS, and could aid in guiding patient referral for insufficient or unsuccessful molecular diagnosis. KEY POINTS • Three imaging-based risk types enable distinct prognostication in diffuse glioma, NOS (not otherwise specified). • The imaging-based survival model achieved similar prognostic performance as a historical molecular-based survival model. • For long-term prognostication of 3 and 5 years, the imaging-based survival model showed high performance.
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Affiliation(s)
- Eun Bee Jang
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, Republic of Korea
| | - Ho Sung Kim
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, Republic of Korea.
| | - Ji Eun Park
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, Republic of Korea
| | - Seo Young Park
- Department of Statistics and Data Science, Korea National Open University, Seoul, Republic of Korea
| | - Yeo Kyung Nam
- Department of Radiology, Shinchon Yonsei Hospital, Seoul, Republic of Korea
| | - Soo Jung Nam
- Department of Pathology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Young-Hoon Kim
- Department of Neurosurgery, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Jeong Hoon Kim
- Department of Neurosurgery, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
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9
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Deacu M, Popescu S, Docu Axelerad A, Topliceanu TS, Aschie M, Bosoteanu M, Cozaru GC, Cretu AM, Voda RI, Orasanu CI. Prognostic Factors of Low-Grade Gliomas in Adults. Curr Oncol 2022; 29:7327-7342. [PMID: 36290853 PMCID: PMC9600247 DOI: 10.3390/curroncol29100576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Revised: 09/22/2022] [Accepted: 09/29/2022] [Indexed: 11/22/2022] Open
Abstract
Adult low-grade gliomas are a rare and aggressive pathology of the central nervous system. Some of their characteristics contribute to the patient's life expectancy and to their management. This study aimed to characterize and identify the main prognostic factors of low-grade gliomas. The six-year retrospective study statistically analyzed the demographic, imaging, and morphogenetic characteristics of the patient group through appropriate parameters. Immunohistochemical tests were performed: IDH1, Ki-67, p53, and Nestin, as well as FISH tests on the CDKN2A gene and 1p/19q codeletion. The pathology was prevalent in females, with patients having an average age of 56.31 years. The average tumor volume was 41.61 cm3, producing a midline shift with an average of 7.5 mm. Its displacement had a negative impact on survival. The presence of a residual tumor resulted in decreased survival and is an independent risk factor for mortality. Positivity for p53 identified a low survival rate. CDKN2A mutations were an independent risk factor for mortality. We identified that a negative prognosis is influenced by the association of epilepsy with headache, tumor volume, and immunoreactivity to IDH1 and p53. Independent factors associated with mortality were midline shift, presence of tumor residue, and CDKN2A gene deletions and amplifications.
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Affiliation(s)
- Mariana Deacu
- Clinical Service of Pathology, Departments of Pathology, Sfantul Apostol Andrei Emergency County Hospital, 900591 Constanta, Romania
- Faculty of Medicine, “Ovidius” University of Constanta, 900470 Constanta, Romania
| | - Steliana Popescu
- Faculty of Medicine, “Ovidius” University of Constanta, 900470 Constanta, Romania
- Department of Radiology, Sfantul Apostol Andrei Emergency County Hospital, 900591 Constanta, Romania
| | - Any Docu Axelerad
- Faculty of Medicine, “Ovidius” University of Constanta, 900470 Constanta, Romania
- Department of Neurology, Sfantul Apostol Andrei Emergency County Hospital, 900591 Constanta, Romania
| | - Theodor Sebastian Topliceanu
- Center for Research and Development of the Morphological and Genetic Studyies of Malignant Pathology (CEDMOG), Ovidius University of Constanta, 900591 Constanta, Romania
| | - Mariana Aschie
- Clinical Service of Pathology, Departments of Pathology, Sfantul Apostol Andrei Emergency County Hospital, 900591 Constanta, Romania
- Faculty of Medicine, “Ovidius” University of Constanta, 900470 Constanta, Romania
- Academy of Medical Sciences of Romania, 030167 Bucharest, Romania
| | - Madalina Bosoteanu
- Clinical Service of Pathology, Departments of Pathology, Sfantul Apostol Andrei Emergency County Hospital, 900591 Constanta, Romania
- Faculty of Medicine, “Ovidius” University of Constanta, 900470 Constanta, Romania
| | - Georgeta Camelia Cozaru
- Center for Research and Development of the Morphological and Genetic Studyies of Malignant Pathology (CEDMOG), Ovidius University of Constanta, 900591 Constanta, Romania
- Clinical Service of Pathology, Departments of Genetics, Sfantul Apostol Andrei Emergency County Hospital, 900591 Constanta, Romania
| | - Ana Maria Cretu
- Clinical Service of Pathology, Departments of Pathology, Sfantul Apostol Andrei Emergency County Hospital, 900591 Constanta, Romania
- Center for Research and Development of the Morphological and Genetic Studyies of Malignant Pathology (CEDMOG), Ovidius University of Constanta, 900591 Constanta, Romania
| | - Raluca Ioana Voda
- Clinical Service of Pathology, Departments of Pathology, Sfantul Apostol Andrei Emergency County Hospital, 900591 Constanta, Romania
- Center for Research and Development of the Morphological and Genetic Studyies of Malignant Pathology (CEDMOG), Ovidius University of Constanta, 900591 Constanta, Romania
| | - Cristian Ionut Orasanu
- Clinical Service of Pathology, Departments of Pathology, Sfantul Apostol Andrei Emergency County Hospital, 900591 Constanta, Romania
- Center for Research and Development of the Morphological and Genetic Studyies of Malignant Pathology (CEDMOG), Ovidius University of Constanta, 900591 Constanta, Romania
- Correspondence: ; Tel.: +40-72-281-4037
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10
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Valentino WL, Okada D, Bhanu S. A curious case of T2-FLAIR mismatch in H3K27M mutant glioma. Radiol Case Rep 2022; 17:2930-2935. [PMID: 35755103 PMCID: PMC9218295 DOI: 10.1016/j.radcr.2022.05.017] [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: 04/10/2022] [Revised: 05/04/2022] [Accepted: 05/11/2022] [Indexed: 11/19/2022] Open
Abstract
Diffuse midline gliomas are a rare relatively new classification of primary central nervous system tumors which include astrocytomas, oligodendrogliomas, and glioblastomas. The T2-FLAIR mismatch sign is regarded as a highly specific imaging feature of IDH-mutant, 1p/19q non-codeleted astrocytomas. The case presented herein demonstrates this sign, however, in a non-IDH mutated diffuse midline glioma with a H3K27M mutation, a World Health Organization Grade IV neoplasm. Although preoperative diagnosis can provide important treatment and prognostic information, it is often quite difficult particularly in primary central nervous system tumors.
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Affiliation(s)
- William L. Valentino
- Riverside Community Hospital, 4445 Magnolia Avenue, Riverside, CA, 92501 USA
- HCA Healthcare, Nashville, TN, USA
- Corresponding author.
| | - Darren Okada
- Riverside Community Hospital, 4445 Magnolia Avenue, Riverside, CA, 92501 USA
- HCA Healthcare, Nashville, TN, USA
| | - Shiv Bhanu
- Riverside Community Hospital, 4445 Magnolia Avenue, Riverside, CA, 92501 USA
- HCA Healthcare, Nashville, TN, USA
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11
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Osborn AG, Louis DN, Poussaint TY, Linscott LL, Salzman KL. The 2021 World Health Organization Classification of Tumors of the Central Nervous System: What Neuroradiologists Need to Know. AJNR Am J Neuroradiol 2022; 43:928-937. [PMID: 35710121 DOI: 10.3174/ajnr.a7462] [Citation(s) in RCA: 79] [Impact Index Per Article: 39.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Accepted: 11/08/2021] [Indexed: 12/12/2022]
Abstract
Neuroradiologists play a key role in brain tumor diagnosis and management. Staying current with the latest classification systems and diagnostic markers is important to provide optimal patient care. Publication of the 2016 World Health Organization Classification of Tumors of the Central Nervous System introduced a paradigm shift in the diagnosis of CNS neoplasms. For the first time, both histologic features and genetic alterations were incorporated into the diagnostic framework, classifying and grading brain tumors. The newly published 2021 World Health Organization Classification of Tumors of the Central Nervous System, May 2021, 5th edition, has added even more molecular features and updated pathologic diagnoses. We present, summarize, and illustrate the most salient aspects of the new 5th edition. We have selected the key "must know" topics for practicing neuroradiologists.
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Affiliation(s)
- A G Osborn
- From the Department of Radiology and Imaging Sciences (A.G.O., K.L.S.), University of Utah School of Medicine, Salt Lake City, Utah
| | - D N Louis
- Department of Pathology (D.N.L.), Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - T Y Poussaint
- Department of Radiology (T.Y.P.), Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts
| | - L L Linscott
- Intermountain Pediatric Imaging (L.L.L.), Primary Children's Hospital, University of Utah School of Medicine, Salt Lake City, Utah
| | - K L Salzman
- From the Department of Radiology and Imaging Sciences (A.G.O., K.L.S.), University of Utah School of Medicine, Salt Lake City, Utah
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12
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Lasocki A, Buckland ME, Drummond KJ, Wei H, Xie J, Christie M, Neal A, Gaillard F. Conventional MRI features can predict the molecular subtype of adult grade 2-3 intracranial diffuse gliomas. Neuroradiology 2022; 64:2295-2305. [PMID: 35606654 PMCID: PMC9643259 DOI: 10.1007/s00234-022-02975-0] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Accepted: 05/04/2022] [Indexed: 12/02/2022]
Abstract
Purpose Molecular biomarkers are important for classifying intracranial gliomas, prompting research into correlating imaging with genotype (“radiogenomics”). A limitation of the existing radiogenomics literature is the paucity of studies specifically characterizing grade 2–3 gliomas into the three key molecular subtypes. Our study investigated the accuracy of multiple different conventional MRI features for genotype prediction. Methods Grade 2–3 gliomas diagnosed between 2007 and 2013 were identified. Two neuroradiologists independently assessed nine conventional MRI features. Features with better inter-observer agreement (κ ≥ 0.6) proceeded to consensus assessment. MRI features were correlated with genotype, classified as IDH-mutant and 1p/19q-codeleted (IDHmut/1p19qcodel), IDH-mutant and 1p/19q-intact (IDHmut/1p19qint), or IDH-wildtype (IDHwt). For IDHwt tumors, additional molecular markers of glioblastoma were noted. Results One hundred nineteen patients were included. T2-FLAIR mismatch (stratified as > 50%, 25–50%, or < 25%) was the most predictive feature across genotypes (p < 0.001). All 30 tumors with > 50% mismatch were IDHmut/1p19qint, and all seven with 25–50% mismatch. Well-defined margins correlated with IDHmut/1p19qint status on univariate analysis (p < 0.001), but this related to correlation with T2-FLAIR mismatch; there was no longer an association when considering only tumors with < 25% mismatch (p = 0.386). Enhancement (p = 0.001), necrosis (p = 0.002), and hemorrhage (p = 0.027) correlated with IDHwt status (especially “molecular glioblastoma”). Calcification correlated with IDHmut/1p19qcodel status (p = 0.003). A simple, step-wise algorithm incorporating these features, when present, correctly predicted genotype with a positive predictive value 91.8%. Conclusion T2-FLAIR mismatch strongly predicts IDHmut/1p19qint even with a lower threshold of ≥ 25% mismatch and outweighs other features. Secondary features include enhancement, necrosis and hemorrhage (predicting IDHwt, especially “molecular glioblastoma”), and calcification (predicting IDHmut/1p19qcodel).
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Affiliation(s)
- Arian Lasocki
- Department of Cancer Imaging, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia.,Sir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, VIC, Australia
| | - Michael E Buckland
- Department of Neuropathology, Royal Prince Alfred Hospital, Camperdown, NSW, Australia.,School of Medical Sciences, University of Sydney, Camperdown, NSW, Australia
| | - Katharine J Drummond
- Department of Neurosurgery, The Royal Melbourne Hospital, Parkville, VIC, Australia.,Department of Surgery, The University of Melbourne, Parkville, VIC, Australia
| | - Heng Wei
- Department of Neuropathology, Royal Prince Alfred Hospital, Camperdown, NSW, Australia
| | - Jing Xie
- Centre for Biostatistics and Clinical Trials, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
| | - Michael Christie
- Department of Anatomical Pathology, The Royal Melbourne Hospital, Parkville, VIC, Australia
| | - Andrew Neal
- Department of Neurology, The Royal Melbourne Hospital, Parkville, VIC, Australia.,Department of Neuroscience, Central Clinical School, Monash University, Clayton, VIC, Australia
| | - Frank Gaillard
- Department of Radiology, The Royal Melbourne Hospital, Parkville, VIC, Australia.,Department of Radiology, The University of Melbourne, Parkville, VIC, Australia
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13
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Radiogenomic association between the T2-FLAIR mismatch sign and IDH mutation status in adult patients with lower-grade gliomas: an updated systematic review and meta-analysis. Eur Radiol 2022; 32:5339-5352. [PMID: 35169897 DOI: 10.1007/s00330-022-08607-8] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Revised: 12/24/2021] [Accepted: 01/22/2022] [Indexed: 11/04/2022]
Abstract
OBJECTIVES To reveal a radiogenomic correlation between the presence of the T2-fluid-attenuated inversion recovery resection (T2-FLAIR) mismatch sign on MR images and isocitrate dehydrogenase (IDH) mutation status in adult patients with lower-grade gliomas (LGGs). METHODS A web-based systemic search for eligible literature up to April 13, 2021, was conducted on PubMed, Embase, and the Cochrane Library databases by two independent reviewers. This study was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. We included studies evaluating the accuracy of the T2-FLAIR mismatch sign in diagnosing the IDH mutation in adult patients with LGGs. The T2-FLAIR mismatch sign was defined as a T2-hyperintense lesion that is hypointense on FLAIR except for a hyperintense rim. RESULTS Fourteen studies (n = 1986) were finally identified. The mean age of patients in the included studies ranged from 38.5 to 56 years. The pooled area under the curve (AUC), sensitivity, and specificity were obtained for each molecular profile: IDHmut-Codel: 0.46 (95% confidence interval [CI]: 0.42-0.50), 1% (95%CI: 0-7%), and 69% (95%CI: 62-75%), respectively; IDHmut-Noncodel: 0.75 (95%CI: 0.71-0.79), 42% (95%CI: 34-50%), and 99% (95%CI: 96-100%), respectively; IDH-Mutation regardless of 1p/19q codeletion status: 0.77 (95%CI: 0.73-0.80), 29% (95%CI: 21-40%), and 99% (95%CI: 92-100%), respectively. CONCLUSIONS The T2-FLAIR mismatch sign was an insensitive but highly specific marker for IDHmut-Noncodel and IDH-Mutation LGGs, whereas it was not a useful marker for IDHmut-Codel LGGs. The findings might identify the T2-FLAIR mismatch sign as a non-invasive imaging biomarker for the selection of patients with IDH-mutant LGGs. KEY POINTS • The T2-FLAIR mismatch sign was not a sensitive sign for IDH mutation in LGGs. • The T2-FLAIR mismatch sign was related to IDHmut-Noncodel with a specificity of 99%. • The pooled specificity (69%) of the T2-FLAIR mismatch sign for IDHmut-Codel was low.
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14
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Mohammed S, Ravikumar V, Warner E, Patel S, Bakas S, Rao A, Jain R. Quantifying T2-FLAIR Mismatch Using Geographically Weighted Regression and Predicting Molecular Status in Lower-Grade Gliomas. AJNR Am J Neuroradiol 2022; 43:33-39. [PMID: 34764084 PMCID: PMC8757555 DOI: 10.3174/ajnr.a7341] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Accepted: 09/03/2021] [Indexed: 01/03/2023]
Abstract
BACKGROUND AND PURPOSE The T2-FLAIR mismatch sign is a validated imaging sign of isocitrate dehydrogenase-mutant 1p/19q noncodeleted gliomas. It is identified by radiologists through visual inspection of preoperative MR imaging scans and has been shown to identify isocitrate dehydrogenase-mutant 1p/19q noncodeleted gliomas with a high positive predictive value. We have developed an approach to quantify the T2-FLAIR mismatch signature and use it to predict the molecular status of lower-grade gliomas. MATERIALS AND METHODS We used multiparametric MR imaging scans and segmentation labels of 108 preoperative lower-grade glioma tumors from The Cancer Imaging Archive. Clinical information and T2-FLAIR mismatch sign labels were obtained from supplementary material of relevant publications. We adopted an objective analytic approach to estimate this sign through a geographically weighted regression and used the residuals for each case to construct a probability density function (serving as a residual signature). These functions were then analyzed using an appropriate statistical framework. RESULTS We observed statistically significant (P value = .05) differences between the averages of residual signatures for an isocitrate dehydrogenase-mutant 1p/19q noncodeleted class of tumors versus other categories. Our classifier predicts these cases with area under the curve of 0.98 and high specificity and sensitivity. It also predicts the T2-FLAIR mismatch sign within these cases with an under the curve of 0.93. CONCLUSIONS On the basis of this retrospective study, we show that geographically weighted regression-based residual signatures are highly informative of the T2-FLAIR mismatch sign and can identify isocitrate dehydrogenase-mutation and 1p/19q codeletion status with high predictive power. The utility of the proposed quantification of the T2-FLAIR mismatch sign can be potentially validated through a prospective multi-institutional study.
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Affiliation(s)
- S. Mohammed
- From the Departments of Biostatistics (S.M., A.R.),Computational Medicine & Bioinformatics (S.M., V.R., E.W., A.R.)
| | - V. Ravikumar
- Computational Medicine & Bioinformatics (S.M., V.R., E.W., A.R.)
| | - E. Warner
- Computational Medicine & Bioinformatics (S.M., V.R., E.W., A.R.)
| | - S.H. Patel
- Department of Radiology & Medical Imaging (S.H.P.), University of Virginia School of Medicine, Charlottesville, Virginia
| | - S. Bakas
- Departments of Radiology (S.B.),Pathology & Laboratory Medicine (S.B.), University of Pennsylvania, Philadelphia, Pennsylvania
| | - A. Rao
- From the Departments of Biostatistics (S.M., A.R.),Computational Medicine & Bioinformatics (S.M., V.R., E.W., A.R.),Radiation Oncology (A.R.),Michigan Institute for Data Sciences (A.R.),Department of Biomedical Engineering (A.R.), University of Michigan, Ann Arbor, Michigan
| | - R. Jain
- Departments of Radiology (R.J.),Neurosurgery (R.J.), New York University Grossman School of Medicine, New York, New York
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15
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Kha QH, Le VH, Hung TNK, Le NQK. Development and Validation of an Efficient MRI Radiomics Signature for Improving the Predictive Performance of 1p/19q Co-Deletion in Lower-Grade Gliomas. Cancers (Basel) 2021; 13:cancers13215398. [PMID: 34771562 PMCID: PMC8582370 DOI: 10.3390/cancers13215398] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Revised: 10/19/2021] [Accepted: 10/26/2021] [Indexed: 12/30/2022] Open
Abstract
Simple Summary Low-grade gliomas (LGG) with the 1p/19q co-deletion mutation have been proven to have a better survival prognosis and response to treatment than individuals without the mutation. Identifying this mutation has a vital role in managing LGG patients; however, the current diagnostic gold standard, including the brain-tissue biopsy or the surgical resection of the tumor, remains highly invasive and time-consuming. We proposed a model based on the eXtreme Gradient Boosting (XGBoost) classifier to detect 1p/19q co-deletion mutation using non-invasive medical images. The performance of our model achieved 87% and 82.8% accuracy on the training and external test set, respectively. Significantly, the prediction was based on only seven optimal wavelet radiomics features extracted from brain Magnetic Resonance (MR) images. We believe that this model can address clinicians in the rapid diagnosis of clinical 1p/19q co-deletion mutation, thereby improving the treatment prognosis of LGG patients. Abstract The prognosis and treatment plans for patients diagnosed with low-grade gliomas (LGGs) may significantly be improved if there is evidence of chromosome 1p/19q co-deletion mutation. Many studies proved that the codeletion status of 1p/19q enhances the sensitivity of the tumor to different types of therapeutics. However, the current clinical gold standard of detecting this chromosomal mutation remains invasive and poses implicit risks to patients. Radiomics features derived from medical images have been used as a new approach for non-invasive diagnosis and clinical decisions. This study proposed an eXtreme Gradient Boosting (XGBoost)-based model to predict the 1p/19q codeletion status in a binary classification task. We trained our model on the public database extracted from The Cancer Imaging Archive (TCIA), including 159 LGG patients with 1p/19q co-deletion mutation status. The XGBoost was the baseline algorithm, and we combined the SHapley Additive exPlanations (SHAP) analysis to select the seven most optimal radiomics features to build the final predictive model. Our final model achieved an accuracy of 87% and 82.8% on the training set and external test set, respectively. With seven wavelet radiomics features, our XGBoost-based model can identify the 1p/19q codeletion status in LGG-diagnosed patients for better management and address the drawbacks of invasive gold-standard tests in clinical practice.
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Affiliation(s)
- Quang-Hien Kha
- International Master/Ph.D. Program in Medicine, College of Medicine, Taipei Medical University, Taipei 110, Taiwan; (Q.-H.K.); (V.-H.L.); (T.N.K.H.)
| | - Viet-Huan Le
- International Master/Ph.D. Program in Medicine, College of Medicine, Taipei Medical University, Taipei 110, Taiwan; (Q.-H.K.); (V.-H.L.); (T.N.K.H.)
- Department of Thoracic Surgery, Khanh Hoa General Hospital, Nha Trang City 65000, Vietnam
| | - Truong Nguyen Khanh Hung
- International Master/Ph.D. Program in Medicine, College of Medicine, Taipei Medical University, Taipei 110, Taiwan; (Q.-H.K.); (V.-H.L.); (T.N.K.H.)
- Department of Orthopedic and Trauma, Cho Ray Hospital, Ho Chi Minh City 70000, Vietnam
| | - Nguyen Quoc Khanh Le
- International Master/Ph.D. Program in Medicine, College of Medicine, Taipei Medical University, Taipei 110, Taiwan; (Q.-H.K.); (V.-H.L.); (T.N.K.H.)
- Professional Master Program in Artificial Intelligence in Medicine, College of Medicine, Taipei Medical University, Taipei 106, Taiwan
- Research Center for Artificial Intelligence in Medicine, Taipei Medical University, Taipei 106, Taiwan
- Translational Imaging Research Center, Taipei Medical University Hospital, Taipei 110, Taiwan
- Correspondence: ; Tel.: +886-02-663-82736-1992
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16
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Adamou A, Beltsios ET, Papanagiotou P. The T2-FLAIR Mismatch Sign as an Imaging Indicator of IDH-Mutant, 1p/19q Non-Codeleted Lower Grade Gliomas: A Systematic Review and Diagnostic Accuracy Meta-Analysis. Diagnostics (Basel) 2021; 11:diagnostics11091620. [PMID: 34573962 PMCID: PMC8471804 DOI: 10.3390/diagnostics11091620] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 08/27/2021] [Accepted: 08/31/2021] [Indexed: 02/01/2023] Open
Abstract
The study's objective was the evaluation of the diagnostic accuracy of the T2-FLAIR mismatch sign in terms of diagnosing IDH-mutant non-codeleted (IDHmut-Noncodel) lower grade gliomas (LGG) of the brain. We searched the MEDLINE, Scopus and Cochrane Central databases. The last database search was performed on 12 April 2021. Studies that met the following were included: MRI scan assessing the presence of T2-FLAIR mismatch sign, and available IDH mutation and 1p/19q codeletion status. The quality of studies was assessed using the QUADAS-2 tool. Twelve studies involving 14 cohorts were included in the quantitative analysis. The diagnostic odds ratio [DOR (95% confidence interval; CI)] was estimated at 34.42 (20.95, 56.56), Pz < 0.01. Pooled sensitivity and specificity (95% CI) were estimated at 40% (31-50%; Pz = 0.05) and 97% (93-99%; Pz < 0.01), respectively. The likelihood ratio (LR; 95% CI) for a positive test was 11.39 (6.10, 21.29; Pz < 0.01) and the LR (95% CI) for a negative test was 0.40 (0.24, 0.65; Pz < 0.01).The T2-FLAIR mismatch sign is a highly specific biomarker for the diagnosis of IDHmut-Noncodel LGGs. However, the test was found positive in some other tumors and had a high number of false negative results. The diagnostic accuracy of the mismatch sign might be improved when combined with further imaging parameters.
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Affiliation(s)
- Antonis Adamou
- Department of Radiology and Medical Imaging, University of Thessaly, 41110 Larissa, Greece;
| | - Eleftherios T. Beltsios
- Faculty of Medicine, School of Health Sciences, University of Thessaly, 41110 Larissa, Greece;
| | - Panagiotis Papanagiotou
- Department of Diagnostic and Interventional Neuroradiology, Hospital Bremen-Mitte/Bremen-Ost, 28205 Bremen, Germany
- First Department of Radiology, School of Medicine, National & Kapodistrian University of Athens, Areteion Hospital, 11528 Athens, Greece
- Correspondence:
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Banan R, Akbarian A, Samii M, Samii A, Bertalanffy H, Lehmann U, Hartmann C, Brüning R. Diffuse midline gliomas, H3 K27M-mutant are associated with less peritumoral edema and contrast enhancement in comparison to glioblastomas, H3 K27M-wildtype of midline structures. PLoS One 2021; 16:e0249647. [PMID: 34347774 PMCID: PMC8336828 DOI: 10.1371/journal.pone.0249647] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Accepted: 03/23/2021] [Indexed: 12/19/2022] Open
Abstract
Purpose The entity ‘diffuse midline glioma, H3 K27M-mutant (DMG)’ was introduced in the revised 4th edition of the 2016 WHO classification of brain tumors. However, there are only a few reports on magnetic resonance imaging (MRI) of these tumors. Thus, we conducted a retrospective survey focused on MRI features of DMG compared to midline glioblastomas H3 K27M-wildtype (mGBM-H3wt). Methods We identified 24 DMG cases and 19 mGBM-H3wt patients as controls. After being retrospectively evaluated for microscopic evidence of microvascular proliferations (MVP) and tumor necrosis by two experienced neuropathologists to identify the defining histological criteria of mGBM-H3wt, the samples were further analyzed by two experienced readers regarding imaging features such as shape, peritumoral edema and contrast enhancement. Results The DMG were found in the thalamus in 37.5% of cases (controls 63%), in the brainstem in 50% (vs. 32%) and spinal cord in 12.5% (vs. 5%). In MRI and considering MVP, DMG were found to be by far less likely to develop peritumoral edema (OR: 0.13; 95%-CL: 0.02–0.62) (p = 0.010). They, similarly, were associated with a significantly lower probability of developing strong contrast enhancement compared to mGBM-H3wt (OR: 0.10; 95%-CL: 0.02–0.47) (P = 0.003). Conclusion Despite having highly variable imaging features, DMG exhibited markedly less edema and lower contrast enhancement in MRI compared to mGBM-H3wt. Of these features, the enhancement level was associated with evidence of MVP.
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Affiliation(s)
- Rouzbeh Banan
- Department of Neuropathology, University of Heidelberg, Heidelberg, Germany
- Department of Neuropathology, Institute of Pathology, Hannover Medical School, Hannover, Germany
| | - Arash Akbarian
- Department of Neuroradiology, INI-Hannover, Hannover, Germany
| | - Majid Samii
- Department of Neurosurgery, INI-Hannover, Hannover, Germany
| | - Amir Samii
- Department of Neurosurgery, INI-Hannover, Hannover, Germany
| | | | - Ulrich Lehmann
- Institute of Pathology, Hannover Medical School, Hannover, Germany
| | - Christian Hartmann
- Department of Neuropathology, Institute of Pathology, Hannover Medical School, Hannover, Germany
| | - Roland Brüning
- Radiology and Neuroradiology, Asklepios Klinik Barmbek, Hamburg, Germany
- * E-mail:
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18
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van Kempen EJ, Post M, Mannil M, Kusters B, ter Laan M, Meijer FJA, Henssen DJHA. Accuracy of Machine Learning Algorithms for the Classification of Molecular Features of Gliomas on MRI: A Systematic Literature Review and Meta-Analysis. Cancers (Basel) 2021; 13:cancers13112606. [PMID: 34073309 PMCID: PMC8198025 DOI: 10.3390/cancers13112606] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Revised: 05/17/2021] [Accepted: 05/18/2021] [Indexed: 12/12/2022] Open
Abstract
Simple Summary Glioma prognosis and treatment are based on histopathological characteristics and molecular profile. Following the World Health Organization (WHO) guidelines (2016), the most important molecular diagnostic markers include IDH1/2-genotype and 1p/19q codeletion status, although more recent publications also include ARTX genotype and TERT- and MGMT promoter methylation. Machine learning algorithms (MLAs), however, were described to successfully determine these molecular characteristics non-invasively by using magnetic resonance imaging (MRI) data. The aim of this review and meta-analysis was to define the diagnostic accuracy of MLAs with regard to these different molecular markers. We found high accuracies of MLAs to predict each individual molecular marker, with IDH1/2-genotype being the most investigated and the most accurate. Radiogenomics could therefore be a promising tool for discriminating genetically determined gliomas in a non-invasive fashion. Although encouraging results are presented here, large-scale, prospective trials with external validation groups are warranted. Abstract Treatment planning and prognosis in glioma treatment are based on the classification into low- and high-grade oligodendroglioma or astrocytoma, which is mainly based on molecular characteristics (IDH1/2- and 1p/19q codeletion status). It would be of great value if this classification could be made reliably before surgery, without biopsy. Machine learning algorithms (MLAs) could play a role in achieving this by enabling glioma characterization on magnetic resonance imaging (MRI) data without invasive tissue sampling. The aim of this study is to provide a performance evaluation and meta-analysis of various MLAs for glioma characterization. Systematic literature search and meta-analysis were performed on the aggregated data, after which subgroup analyses for several target conditions were conducted. This study is registered with PROSPERO, CRD42020191033. We identified 724 studies; 60 and 17 studies were eligible to be included in the systematic review and meta-analysis, respectively. Meta-analysis showed excellent accuracy for all subgroups, with the classification of 1p/19q codeletion status scoring significantly poorer than other subgroups (AUC: 0.748, p = 0.132). There was considerable heterogeneity among some of the included studies. Although promising results were found with regard to the ability of MLA-tools to be used for the non-invasive classification of gliomas, large-scale, prospective trials with external validation are warranted in the future.
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Affiliation(s)
- Evi J. van Kempen
- Department of Medical Imaging, Radboud University Medical Center, Radboud University, 6500HB Nijmegen, The Netherlands; (E.J.v.K.); (M.P.); (F.J.A.M.)
| | - Max Post
- Department of Medical Imaging, Radboud University Medical Center, Radboud University, 6500HB Nijmegen, The Netherlands; (E.J.v.K.); (M.P.); (F.J.A.M.)
| | - Manoj Mannil
- Clinic of Radiology, University Hospital Münster, WWU University of Münster, 48149 Münster, Germany;
| | - Benno Kusters
- Department of Pathology, Radboud University Medical Center, Radboud University, 6500HB Nijmegen, The Netherlands;
| | - Mark ter Laan
- Department of Neurosurgery, Radboud University Medical Center, Radboud University, 6500HB Nijmegen, The Netherlands;
| | - Frederick J. A. Meijer
- Department of Medical Imaging, Radboud University Medical Center, Radboud University, 6500HB Nijmegen, The Netherlands; (E.J.v.K.); (M.P.); (F.J.A.M.)
| | - Dylan J. H. A. Henssen
- Department of Medical Imaging, Radboud University Medical Center, Radboud University, 6500HB Nijmegen, The Netherlands; (E.J.v.K.); (M.P.); (F.J.A.M.)
- Correspondence:
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19
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Jain R, Johnson DR, Patel SH, Castillo M, Smits M, van den Bent MJ, Chi AS, Cahill DP. "Real world" use of a highly reliable imaging sign: "T2-FLAIR mismatch" for identification of IDH mutant astrocytomas. Neuro Oncol 2021; 22:936-943. [PMID: 32064507 DOI: 10.1093/neuonc/noaa041] [Citation(s) in RCA: 80] [Impact Index Per Article: 26.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
AbstractThe T2-FLAIR (fluid attenuated inversion recovery) mismatch sign is an easily detectable imaging sign on routine clinical MRI studies that suggests diagnosis of isocitrate dehydrogenase (IDH)-mutant 1p/19q non-codeleted gliomas. Multiple independent studies show that the T2-FLAIR mismatch sign has near-perfect specificity, but low sensitivity for diagnosing IDH-mutant astrocytomas. Thus, the T2-FLAIR mismatch sign represents a non-invasive radiogenomic diagnostic finding with potential clinical impact. Recently, false positive cases have been reported, many related to variable application of the sign's imaging criteria and differences in image acquisition, as well as to differences in the included patient populations. Here we summarize the imaging criteria for the T2-FLAIR mismatch sign, review similarities and differences between the multiple validation studies, outline strategies to optimize its clinical use, and discuss potential opportunities to refine imaging criteria in order to maximize its impact in glioma diagnostics.
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Affiliation(s)
- Rajan Jain
- Departments of Radiology and Neurosurgery, New York University Langone Health, New York, New York, USA
| | - Derek R Johnson
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - Sohil H Patel
- Department of Radiology, University of Virginia Health, Charlottesville, Virginia, USA
| | - Mauricio Castillo
- Department of Radiology, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Marion Smits
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, Netherlands
| | | | | | - Daniel P Cahill
- Department of Neurosurgery, Massachusetts General Hospital, Boston, Massachusetts, USA
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20
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Patel SH, Batchala PP, Muttikkal TJE, Ferrante SS, Patrie JT, Fadul CE, Schiff D, Lopes MB, Jain R. Fluid attenuation in non-contrast-enhancing tumor (nCET): an MRI Marker for Isocitrate Dehydrogenase (IDH) mutation in Glioblastoma. J Neurooncol 2021; 152:523-531. [PMID: 33661425 DOI: 10.1007/s11060-021-03720-y] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Revised: 02/12/2021] [Accepted: 02/15/2021] [Indexed: 11/29/2022]
Abstract
PURPOSE The WHO 2016 update classifies glioblastomas (WHO grade IV) according to isocitrate dehydrogenase (IDH) gene mutation status. We aimed to determine MRI-based metrics for predicting IDH mutation in glioblastoma. METHODS This retrospective study included glioblastoma cases (n = 199) with known IDH mutation status and pre-operative MRI (T1WI, T2WI, FLAIR, contrast-enhanced T1W1 at minimum). Two neuroradiologists determined the following MRI metrics: (1) primary lobe of involvement (frontal or non-frontal); (2) presence/absence of contrast-enhancement; (3) presence/absence of necrosis; (4) presence/absence of fluid attenuation in the non-contrast-enhancing tumor (nCET); (5) maximum width of peritumoral edema (cm); (6) presence/absence of multifocal disease. Inter-reader agreement was determined. After resolving discordant measurements, multivariate association between consensus MRI metrics/patient age and IDH mutation status was determined. RESULTS Among 199 glioblastomas, 16 were IDH-mutant. Inter-reader agreement was calculated for contrast-enhancement (ĸ = 0.49 [- 0.11-1.00]), necrosis (ĸ = 0.55 [0.34-0.76]), fluid attenuation in nCET (ĸ = 0.83 [0.68-0.99]), multifocal disease (ĸ = 0.55 [0.39-0.70]), and primary lobe (ĸ = 0.85 [0.80-0.91]). Mean difference for peritumoral edema width between readers was 0.3 cm [0.2-0.5], p < 0.001. Multivariate analysis uncovered significant associations between IDH-mutation and fluid attenuation in nCET (OR 82.9 [19.22, ∞], p < 0.001), younger age (OR 0.93 [0.86, 0.98], p = 0.009), frontal lobe location (OR 11.08 [1.14, 352.97], p = 0.037), and less peritumoral edema (OR 0.15 [0, 0.65], p = 0.044). CONCLUSIONS Conventional MRI metrics and patient age predict IDH-mutation status in glioblastoma. Among MRI markers, fluid attenuation in nCET represents a novel marker with high inter-reader agreement that is strongly associated with Glioblastoma, IDH-mutant.
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Affiliation(s)
- Sohil H Patel
- Department of Radiology and Medical Imaging, University of Virginia Health System, PO Box 800170, Charlottesville, VA, 22908, USA.
| | - Prem P Batchala
- Department of Radiology and Medical Imaging, University of Virginia Health System, PO Box 800170, Charlottesville, VA, 22908, USA
| | - Thomas J Eluvathingal Muttikkal
- Department of Radiology and Medical Imaging, University of Virginia Health System, PO Box 800170, Charlottesville, VA, 22908, USA
| | - Sergio S Ferrante
- Department of Radiology and Medical Imaging, University of Virginia Health System, PO Box 800170, Charlottesville, VA, 22908, USA
| | - James T Patrie
- Department of Public Health Sciences, University of Virginia Health System, Charlottesville, VA, USA
| | - Camilo E Fadul
- Division of Neuro-Oncology, Department of Neurology, University of Virginia Health System, Charlottesville, VA, USA
| | - David Schiff
- Division of Neuro-Oncology, Department of Neurology, University of Virginia Health System, Charlottesville, VA, USA
| | - M Beatriz Lopes
- Department of Pathology, Divisions of Neuropathology and Molecular Diagnostics, University of Virginia Health System, Charlottesville, VA, USA
| | - Rajan Jain
- Department of Radiology, New York University School of Medicine, 550 1st Avenue, New York, NY, 10016, USA.,Department of Neurosurgery, New York University School of Medicine, 550 1st Avenue, New York, NY, 10016, USA
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21
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Dono A, Ballester LY, Primdahl D, Esquenazi Y, Bhatia A. IDH-Mutant Low-grade Glioma: Advances in Molecular Diagnosis, Management, and Future Directions. Curr Oncol Rep 2021; 23:20. [PMID: 33492489 DOI: 10.1007/s11912-020-01006-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/17/2020] [Indexed: 12/19/2022]
Abstract
PURPOSE OF REVIEW IDH-mutant low-grade gliomas (LGG) have emerged as a distinct clinical and molecular entity with unique treatment considerations. Here, we review updates in IDH-mutant LGG diagnosis and classification, imaging biomarkers, therapies, and neurocognitive and patient-reported outcomes. RECENT FINDINGS CDKN2A/B homozygous deletion in IDH-mutant astrocytoma is associated with shorter survival, similar to WHO grade 4. The T2-FLAIR mismatch, a highly specific but insensitive sign, is diagnostic of IDH-mutant astrocytoma. Maximal safe resection is currently indicated in all LGG cases. Radiotherapy with subsequent PCV (procarbazine, lomustine, vincristine) provides longer overall survival compared to radiotherapy alone. Temozolomide in place of PCV is reasonable, but high-level evidence is still lacking. LGG adjuvant treatment has important quality of life and neurocognitive side effects that should be considered. Although incurable, IDH-mutant LGG have a favorable survival compared to IDH-WT glioma. Recent advances in molecular-based classification, imaging, and targeted therapies will hopefully improve survival and quality of life.
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Affiliation(s)
- Antonio Dono
- Vivian L. Smith Department of Neurosurgery, The University of Texas Health Science Center, 6431 Fannin Street, MSB 3.000, Houston, TX, 77030, USA.,Department of Pathology and Laboratory Medicine, The University of Texas Health Science Center, 6431 Fannin St., MSB 2.136, Houston, TX, 77030, USA
| | - Leomar Y Ballester
- Vivian L. Smith Department of Neurosurgery, The University of Texas Health Science Center, 6431 Fannin Street, MSB 3.000, Houston, TX, 77030, USA.,Department of Pathology and Laboratory Medicine, The University of Texas Health Science Center, 6431 Fannin St., MSB 2.136, Houston, TX, 77030, USA.,Memorial Hermann Health System, Houston, TX, USA
| | - Ditte Primdahl
- Department of Neurology, University of Wisconsin School of Medicine and Public Health, 600 Highland Ave, Madison, WI, 53792, USA
| | - Yoshua Esquenazi
- Vivian L. Smith Department of Neurosurgery, The University of Texas Health Science Center, 6431 Fannin Street, MSB 3.000, Houston, TX, 77030, USA.,Memorial Hermann Health System, Houston, TX, USA.,Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center, 6400 Fannin Street, Suite # 2800, Houston, TX, 77030, USA
| | - Ankush Bhatia
- Memorial Hermann Health System, Houston, TX, USA. .,Department of Neurology, The University of Texas Health Science Center at Houston - McGovern Medical School, 6410 Fannin Street, Suite # 1014, Houston, TX, 77030, USA.
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22
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Kinoshita M, Arita H, Takahashi M, Uda T, Fukai J, Ishibashi K, Kijima N, Hirayama R, Sakai M, Arisawa A, Takahashi H, Nakanishi K, Kagawa N, Ichimura K, Kanemura Y, Narita Y, Kishima H. Impact of Inversion Time for FLAIR Acquisition on the T2-FLAIR Mismatch Detectability for IDH-Mutant, Non-CODEL Astrocytomas. Front Oncol 2021; 10:596448. [PMID: 33520709 PMCID: PMC7841010 DOI: 10.3389/fonc.2020.596448] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2020] [Accepted: 11/30/2020] [Indexed: 11/29/2022] Open
Abstract
The current research tested the hypothesis that inversion time (TI) shorter than 2,400 ms under 3T for FLAIR can improve the diagnostic accuracy of the T2-FLAIR mismatch sign for identifying IDHmt, non-CODEL astrocytomas. We prepared three different cohorts; 94 MRI from 76 IDHmt, non-CODEL Lower-grade gliomas (LrGGs), 33 MRI from 31 LrGG under the restriction of FLAIR being acquired with TI < 2,400 ms for 3T or 2,016 ms for 1.5T, and 112 MRI from 112 patients from the TCIA/TCGA dataset for LrGG. The presence or absence of the “T2-FLAIR mismatch sign” was evaluated, and we compared diagnostic accuracies according to TI used for FLAIR acquisition. The T2-FLAIR mismatch sign was more frequently positive when TI was shorter than 2,400 ms under 3T for FLAIR acquisition (p = 0.0009, Fisher’s exact test). The T2-FLAIR mismatch sign was positive only for IDHmt, non-CODEL astrocytomas even if we confined the cohort with FLAIR acquired with shorter TI (p = 0.0001, Fisher’s exact test). TCIA/TCGA dataset validated that the sensitivity, specificity, PPV, and NPV of the T2-FLAIR mismatch sign to identify IDHmt, non-CODEL astrocytomas improved from 31, 90, 79, and 51% to 67, 94, 92, and 74%, respectively and the area under the curve of ROC improved from 0.63 to 0.87 when FLAIR was acquired with shorter TI. We revealed that TI for FLAIR impacts the T2-FLAIR mismatch sign’s diagnostic accuracy and that FLAIR scanned with TI < 2,400 ms in 3T is necessary for LrGG imaging.
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Affiliation(s)
- Manabu Kinoshita
- Department of Neurosurgery, Osaka University Graduate School of Medicine, Suita, Japan
| | - Hideyuki Arita
- Department of Neurosurgery, Osaka University Graduate School of Medicine, Suita, Japan.,Department of Neurosurgery, Takatsuki General Hospital, Takatsuki, Japan
| | - Masamichi Takahashi
- Department of Neurosurgery and Neuro-Oncology, National Cancer Center Hospital, Tokyo, Japan
| | - Takehiro Uda
- Department of Neurosurgery, Osaka City University Graduate School of Medicine, Osaka, Japan
| | - Junya Fukai
- Department of Neurological Surgery, Wakayama Medical University, Wakayama, Japan
| | - Kenichi Ishibashi
- Department of Neurosurgery, Osaka City General Hospital, Osaka, Japan
| | - Noriyuki Kijima
- Department of Neurosurgery, Osaka University Graduate School of Medicine, Suita, Japan
| | - Ryuichi Hirayama
- Department of Neurosurgery, Osaka University Graduate School of Medicine, Suita, Japan
| | - Mio Sakai
- Department of Diagnostic Radiology, Osaka International Cancer Institute, Osaka, Japan
| | - Atsuko Arisawa
- Department of Radiology, Osaka University Graduate School of Medicine, Suita, Japan
| | - Hiroto Takahashi
- Department of Radiology, Osaka University Graduate School of Medicine, Suita, Japan
| | - Katsuyuki Nakanishi
- Department of Diagnostic Radiology, Osaka International Cancer Institute, Osaka, Japan
| | - Naoki Kagawa
- Department of Neurosurgery, Osaka University Graduate School of Medicine, Suita, Japan
| | - Kouichi Ichimura
- Division of Brain Tumor Translational Research, National Cancer Center Research Institute, Tokyo, Japan
| | - Yonehiro Kanemura
- Department of Biomedical Research and Innovation, Institute for Clinical Research, National Hospital Organization Osaka National Hospital, Osaka, Japan
| | - Yoshitaka Narita
- Department of Neurosurgery and Neuro-Oncology, National Cancer Center Hospital, Tokyo, Japan
| | - Haruhiko Kishima
- Department of Neurosurgery, Osaka University Graduate School of Medicine, Suita, Japan
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23
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Park SI, Suh CH, Guenette JP, Huang RY, Kim HS. The T2-FLAIR mismatch sign as a predictor of IDH-mutant, 1p/19q-noncodeleted lower-grade gliomas: a systematic review and diagnostic meta-analysis. Eur Radiol 2021; 31:5289-5299. [PMID: 33409784 DOI: 10.1007/s00330-020-07467-4] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2020] [Revised: 09/30/2020] [Accepted: 11/04/2020] [Indexed: 10/22/2022]
Abstract
OBJECTIVES To evaluate the diagnostic performance of the T2-FLAIR mismatch sign for prediction of isocitrate dehydrogenase (IDH)-mutant, 1p/19q-noncodeleted lower-grade gliomas (LGGs) and review studies with false positive results. METHODS The MEDLINE and EMBASE databases were searched up to March 13, 2020, to identify articles reporting the diagnostic performance of the T2-FLAIR mismatch sign for prediction of IDH-mutant, 1p/19q-noncodeleted LGGs (IDHmut-Noncodel) using the search terms (T2 FLAIR mismatch). Pooled sensitivity, specificity, and correlation coefficient for interobserver agreement were calculated. RESULTS Twelve studies including a total of 1053 patients were included. The median age was 43 (median; range, 14-56). The pooled sensitivity and specificity were 42% (95% CI, 28-58%) and 100% (95% CI, 88-100%), respectively. According to the HSROC curve, the area under the curve was 0.77 (95% CI, 0.73-0.80). Considerable heterogeneity was possible among the studies in terms of both sensitivity and specificity. A threshold effect was suggested and was considered to explain most of the heterogeneity. Four studies reported false positive results for the T2-FLAIR mismatch sign, including dysembryoplastic neuroepithelial tumor, pediatric-type gliomas, and non-neoplastic lesions. The 2 original articles with false positive results showed the highest sensitivities among the 10 studies included in the quantitative analysis, supporting the probability of the threshold effect. The pooled correlation coefficient was 0.87 (95% CI, 0.73-0.94). CONCLUSIONS The T2-FLAIR mismatch sign had a high specificity and interobserver agreement for the prediction of IDHmut-Noncodel. However, the sign demonstrated low sensitivity, and a few studies with false positive cases were also reported. KEY POINTS • The pooled sensitivity and specificity of the T2-FLAIR mismatch sign for prediction of IDH-mutant, 1p/19q-noncodeleted lower-grade gliomas were 42% and 100%, respectively. • Four studies reported false positive results. • The pooled correlation coefficient was 0.87, suggesting almost perfect interobserver agreement.
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Affiliation(s)
- Sang Ik Park
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Olympic-ro 33, Seoul, 05505, Republic of Korea
| | - Chong Hyun Suh
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Olympic-ro 33, Seoul, 05505, Republic of Korea.
| | - Jeffrey P Guenette
- Division of Neuroradiology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, 75 Francis Street, Boston, MA, 02115, USA
| | - Raymond Y Huang
- Division of Neuroradiology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, 75 Francis Street, Boston, MA, 02115, USA
| | - Ho Sung Kim
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Olympic-ro 33, Seoul, 05505, Republic of Korea
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24
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Yamasaki F, Nishibuchi I, Karakawa S, Kaichi Y, Kolakshyapati M, Takano M, Yonezawa U, Imano N, Taguchi A, Shimomura M, Taniguchi M, Onishi S, Okada S, Awai K, Sugiyama K, Nagata Y. T2-FLAIR Mismatch Sign and Response to Radiotherapy in Diffuse Intrinsic Pontine Glioma. Pediatr Neurosurg 2021; 56:1-9. [PMID: 33535215 DOI: 10.1159/000513360] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/02/2020] [Accepted: 11/23/2020] [Indexed: 11/19/2022]
Abstract
PURPOSE The T2-fluid-attenuated inversion recovery (FLAIR) mismatch sign was previously reported as a diagnostic indicator of diffuse astrocytoma, isocitrate dehydrogenase-mutant, and 1p/19q noncodeletion. Subsequently, it was reported that the same findings were observed in diffuse intrinsic pontine glioma (DIPG). We investigated the clinical significance of T2-FLAIR mismatch sign in DIPG. METHODS Twenty-one patients with DIPG (Male: Female = 12:9) were treated at our institute between 2004 and 2019. All patients were treated with local radiotherapy of 54 Gy/30 fractions. The positive T2-FLAIR mismatch sign was defined if it fulfilled the following criteria: (1) T2-FLAIR mismatch volume was >50% of T2 high volume at nonenhanced area, (2) the FLAIR low lesion is not associated with gadolinium enhancement (inside of enhancement or just outside of enhancement defined as edema), and (3) signal-intensity of FLAIR lowest lesion at tumor is lower than the normal cerebellar cortex. RESULTS In our patient series, T2-FLAIR mismatch sign was found in 5 out of 21 patients. Objective response rate of radiotherapy was 100% in patients positive for T2-FLAIR mismatch, while it was 25.0% in patients negative for T2-FLAIR mismatch, and this difference was statistically significant (p < 0.01, Fisher's exact test). In patients under the age of 18-years, T2-FLAIR mismatch positive had a slightly better prognosis (p < 0.05, Wilcoxon test). CONCLUSION T2-FLAIR mismatch sign in DIPG may be an indicator for better response to radiotherapy and a better prognostic factor.
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Affiliation(s)
- Fumiyuki Yamasaki
- Department of Neurosurgery, Hiroshima University Hospital, Hiroshima, Japan,
| | - Ikuno Nishibuchi
- Department of Radiation Oncology, Hiroshima University Hospital, Hiroshima, Japan
| | - Shuhei Karakawa
- Department of Pediatrics, Hiroshima University Hospital, Hiroshima, Japan
| | - Yoko Kaichi
- Department of Diagnostic Radiology, Hiroshima University Hospital, Hiroshima, Japan
| | | | - Motoki Takano
- Department of Neurosurgery, Hiroshima University Hospital, Hiroshima, Japan
| | - Ushio Yonezawa
- Department of Neurosurgery, Hiroshima University Hospital, Hiroshima, Japan
| | - Nobuki Imano
- Department of Radiation Oncology, Hiroshima University Hospital, Hiroshima, Japan
| | - Akira Taguchi
- Department of Neurosurgery, Hiroshima University Hospital, Hiroshima, Japan
| | - Maiko Shimomura
- Department of Pediatrics, Hiroshima University Hospital, Hiroshima, Japan
| | - Maki Taniguchi
- Department of Pediatrics, Hiroshima University Hospital, Hiroshima, Japan
| | - Shumpei Onishi
- Department of Neurosurgery, Hiroshima University Hospital, Hiroshima, Japan
| | - Satoshi Okada
- Department of Pediatrics, Hiroshima University Hospital, Hiroshima, Japan
| | - Kazuo Awai
- Department of Diagnostic Radiology, Hiroshima University Hospital, Hiroshima, Japan
| | - Kazuhiko Sugiyama
- Department of Clinical Oncology and Neuro-Oncology Program, Hiroshima University Hospital, Hiroshima, Japan
| | - Yasushi Nagata
- Department of Radiation Oncology, Hiroshima University Hospital, Hiroshima, Japan
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25
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Radiological evaluation of ex novo high grade glioma: velocity of diametric expansion and acceleration time study. Radiol Oncol 2020; 55:26-34. [PMID: 33885243 PMCID: PMC7877266 DOI: 10.2478/raon-2020-0071] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Accepted: 10/16/2020] [Indexed: 12/03/2022] Open
Abstract
Background One of the greatest neuro-oncological concern remains the lack of knowledge about the etiopathogenesis and physiopathology of gliomas. Several studies reported a strict correlation between radiological features and biological behaviour of gliomas; in this way the velocity of diametric expansion (VDE) correlate with lower grade glioma aggressiveness. However, there are no the same strong evidences for high grade gliomas (HGG) because of the lack of several preoperative MRI. Patients and methods We describe a series of 4 patients affected by HGG followed from 2014 to January 2019. Two patients are male and two female; two had a pathological diagnosis of glioblastoma (GBM), one of anaplastic astrocytoma (AA) and one had a neuroradiological diagnosis of GBM. The VDE and the acceleration time (AT) was calculated for fluid attenuated inversion recovery (FLAIR) volume and for the enhancing nodule (EN). Every patients underwent sequential MRI study along a mean period of 413 days. Results Mean VDE evaluated on FLAIR volume was 39.91 mm/year. Mean percentage ratio between peak values and mean value of acceleration was 282.7%. Median appearance time of EN after first MRI scan was 432 days. Mean VDE was 45.02 mm/year. Mean percentage ratio between peak values and mean value of acceleration was 257.52%. Conclusions To our knowledge, this is the first report on VDE and acceleration growth in HGG confirming their strong aggressiveness. In a case in which we need to repeat an MRI, time between consecutive scans should be reduced to a maximum of 15–20 days and surgery should be executed as soon as possible.
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The Role of the T2-FLAIR Mismatch Sign as an Imaging Marker of IDH Status in a Mixed Population of Low- and High-Grade Gliomas. Brain Sci 2020; 10:brainsci10110874. [PMID: 33228171 PMCID: PMC7699466 DOI: 10.3390/brainsci10110874] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Revised: 11/09/2020] [Accepted: 11/14/2020] [Indexed: 11/16/2022] Open
Abstract
Our study evaluated the role of the T2-fluid-attenuated inversion recovery (FLAIR) mismatch sign in detecting isocitrate dehydrogenase (IDH) mutations based on a mixed sample of 24 patients with low- and high- grade gliomas. The association between the two was realized using univariate and multivariate logistic regression analysis. There was a substantial agreement between the two raters for the detection of the T2-FLAIR mismatch sign (Cohen's kappa coefficient was 0.647). The T2-FLAIR mismatch sign when co-registered with the degree of tumor homogeneity were significant predictors of the IDH status (OR 29.642; 95% CI 1.73-509.15, p = 0.019). The probability of being IDH mutant in the presence of T2-FLAIR mismatch sign was as high as 92.9% (95% CI 63-99%). The sensitivity and specificity of T2-FLAIR mismatch sign in the detection of the IDH mutation was 88.9% and 86.7%, respectively. The T2-FLAIR mismatch sign may be an easy to use and helpful tool in recognizing IDH mutant patients, particularly if formal IDH testing is not available. We suggest that the adoption of a protocol based on imaging and histological data for optimal glioma characterization could be very helpful.
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Lasocki A, Rosenthal MA, Roberts-Thomson SJ, Neal A, Drummond KJ. Neuro-Oncology and Radiogenomics: Time to Integrate? AJNR Am J Neuroradiol 2020; 41:1982-1988. [PMID: 32912874 DOI: 10.3174/ajnr.a6769] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Accepted: 06/27/2020] [Indexed: 12/17/2022]
Abstract
Radiogenomics aims to predict genetic markers based on imaging features. The critical importance of molecular markers in the diagnosis and management of intracranial gliomas has led to a rapid growth in radiogenomics research, with progressively increasing complexity. Despite the advances in the techniques being examined, there has been little translation into the clinical domain. This has resulted in a growing disconnect between cutting-edge research and assimilation into clinical practice, though the fundamental goal is for these techniques to improve patient care. The goal of this review, therefore, is to discuss possible clinical scenarios in which the addition of radiogenomics may aid patient management. This includes facilitating patient counseling, determining optimal patient management when complete molecular characterization is not possible, reclassifying tumors, and overcoming some of the limitations of histologic assessment. The review also discusses considerations for selecting relevant radiogenomic features based on the clinical setting.
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Affiliation(s)
- A Lasocki
- From the Department of Cancer Imaging (A.L.)
- Sir Peter MacCallum Department of Oncology (A.L.)
| | - M A Rosenthal
- Medical Oncology (M.A.R.), Peter MacCallum Cancer Centre, Melbourne, Australia
| | | | - A Neal
- Neurology (A.N.)
- Department of Neuroscience, Faculty of Medicine (A.N.), Nursing and Health Sciences, Central Clinical School, Monash University, Melbourne, Australia
| | - K J Drummond
- Department of Surgery (K.J.D.), The University of Melbourne, Parkville, Australia
- Neurosurgery (K.J.D.), The Royal Melbourne Hospital, Parkville, Australia
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28
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Le NQK, Do DT, Chiu FY, Yapp EKY, Yeh HY, Chen CY. XGBoost Improves Classification of MGMT Promoter Methylation Status in IDH1 Wildtype Glioblastoma. J Pers Med 2020; 10:jpm10030128. [PMID: 32942564 PMCID: PMC7563334 DOI: 10.3390/jpm10030128] [Citation(s) in RCA: 57] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2020] [Revised: 09/03/2020] [Accepted: 09/09/2020] [Indexed: 02/07/2023] Open
Abstract
Approximately 96% of patients with glioblastomas (GBM) have IDH1 wildtype GBMs, characterized by extremely poor prognosis, partly due to resistance to standard temozolomide treatment. O6-Methylguanine-DNA methyltransferase (MGMT) promoter methylation status is a crucial prognostic biomarker for alkylating chemotherapy resistance in patients with GBM. However, MGMT methylation status identification methods, where the tumor tissue is often undersampled, are time consuming and expensive. Currently, presurgical noninvasive imaging methods are used to identify biomarkers to predict MGMT methylation status. We evaluated a novel radiomics-based eXtreme Gradient Boosting (XGBoost) model to identify MGMT promoter methylation status in patients with IDH1 wildtype GBM. This retrospective study enrolled 53 patients with pathologically proven GBM and tested MGMT methylation and IDH1 status. Radiomics features were extracted from multimodality MRI and tested by F-score analysis to identify important features to improve our model. We identified nine radiomics features that reached an area under the curve of 0.896, which outperformed other classifiers reported previously. These features could be important biomarkers for identifying MGMT methylation status in IDH1 wildtype GBM. The combination of radiomics feature extraction and F-core feature selection significantly improved the performance of the XGBoost model, which may have implications for patient stratification and therapeutic strategy in GBM.
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Affiliation(s)
- Nguyen Quoc Khanh Le
- Professional Master Program in Artificial Intelligence in Medicine, College of Medicine, Taipei Medical University, Taipei City 106, Taiwan
- Research Center for Artificial Intelligence in Medicine, Taipei Medical University, Taipei City 106, Taiwan;
- Correspondence: (N.Q.K.L.); (C.-Y.C.); Tel.: +886-266-382-736 (ext. 1992) (N.Q.K.L.); Fax: +886-2-2732-1956 (N.Q.K.L.)
| | - Duyen Thi Do
- Faculty of Applied Sciences, Ton Duc Thang University, Ho Chi Minh City 70000, Vietnam;
| | - Fang-Ying Chiu
- Research Center for Artificial Intelligence in Medicine, Taipei Medical University, Taipei City 106, Taiwan;
| | - Edward Kien Yee Yapp
- Singapore Institute of Manufacturing Technology, 2 Fusionopolis Way, #08-04, Innovis, Singapore 138634, Singapore;
| | - Hui-Yuan Yeh
- Medical Humanities Research Cluster, School of Humanities, Nanyang Technological University, 48 Nanyang Ave, Singapore 639798, Singapore;
| | - Cheng-Yu Chen
- Professional Master Program in Artificial Intelligence in Medicine, College of Medicine, Taipei Medical University, Taipei City 106, Taiwan
- Research Center for Artificial Intelligence in Medicine, Taipei Medical University, Taipei City 106, Taiwan;
- Department of Radiology, School of Medicine, College of Medicine, Taipei Medical University, Taipei 11031, Taiwan
- Department of Medical Imaging, Taipei Medical University Hospital, Taipei 11031, Taiwan
- Correspondence: (N.Q.K.L.); (C.-Y.C.); Tel.: +886-266-382-736 (ext. 1992) (N.Q.K.L.); Fax: +886-2-2732-1956 (N.Q.K.L.)
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Hong EK, Choi SH, Shin DJ, Jo SW, Yoo RE, Kang KM, Yun TJ, Kim JH, Sohn CH, Park SH, Won JK, Kim TM, Park CK, Kim IH, Lee ST. Comparison of Genetic Profiles and Prognosis of High-Grade Gliomas Using Quantitative and Qualitative MRI Features: A Focus on G3 Gliomas. Korean J Radiol 2020; 22:233-242. [PMID: 32932560 PMCID: PMC7817637 DOI: 10.3348/kjr.2020.0011] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2019] [Revised: 05/12/2020] [Accepted: 06/04/2020] [Indexed: 02/06/2023] Open
Abstract
Objective To evaluate the association of MRI features with the major genomic profiles and prognosis of World Health Organization grade III (G3) gliomas compared with those of glioblastomas (GBMs). Materials and Methods We enrolled 76 G3 glioma and 155 GBM patients with pathologically confirmed disease who had pretreatment brain MRI and major genetic information of tumors. Qualitative and quantitative imaging features, including volumetrics and histogram parameters, such as normalized cerebral blood volume (nCBV), cerebral blood flow (nCBF), and apparent diffusion coefficient (nADC) were evaluated. The G3 gliomas were divided into three groups for the analysis: with this isocitrate dehydrogenase (IDH)-mutation, IDH mutation and a chromosome arm1p/19q-codeleted (IDHmut1p/19qdel), IDH mutation, 1p/19q-nondeleted (IDHmut1p/19qnondel), and IDH wildtype (IDHwt). A prediction model for the genetic profiles of G3 gliomas was developed and validated on a separate cohort. Both the quantitative and qualitative imaging parameters and progression-free survival (PFS) of G3 gliomas were compared and survival analysis was performed. Moreover, the imaging parameters and PFS between IDHwt G3 gliomas and GBMs were compared. Results IDHmut G3 gliomas showed a larger volume (p = 0.017), lower nCBF (p = 0.048), and higher nADC (p = 0.007) than IDHwt. Between the IDHmut tumors, IDHmut1p/19qdel G3 gliomas had higher nCBV (p = 0.024) and lower nADC (p = 0.002) than IDHmut1p/19qnondel G3 gliomas. Moreover, IDHmut1p/19qdel tumors had the best prognosis and IDHwt tumors had the worst prognosis among G3 gliomas (p < 0.001). PFS was significantly associated with the 95th percentile values of nCBV and nCBF in G3 gliomas. There was no significant difference in neither PFS nor imaging features between IDHwt G3 gliomas and IDHwt GBMs. Conclusion We found significant differences in MRI features, including volumetrics, CBV, and ADC, in G3 gliomas, according to IDH mutation and 1p/19q codeletion status, which can be utilized for the prediction of genomic profiles and the prognosis of G3 glioma patients. The MRI signatures and prognosis of IDHwt G3 gliomas tend to follow those of IDHwt GBMs.
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Affiliation(s)
- Eun Kyoung Hong
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
| | - Seung Hong Choi
- Department of Radiology, Seoul National University Hospital, Seoul, Korea.,Department of Radiology, Seoul National University College of Medicine, Seoul, Korea.
| | - Dong Jae Shin
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
| | - Sang Won Jo
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
| | - Roh Eul Yoo
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
| | - Koung Mi Kang
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
| | - Tae Jin Yun
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
| | - Ji Hoon Kim
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
| | - Chul Ho Sohn
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
| | - Sung Hye Park
- Department of Pathology, Seoul National University Hospital, Seoul, Korea
| | - Jae Kyoung Won
- Department of Pathology, Seoul National University Hospital, Seoul, Korea
| | - Tae Min Kim
- Department of Internal Medicine, Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea
| | - Chul Kee Park
- Department of Neurosurgery, Biomedical Research Institute, Seoul National University College of Medicine, Seoul, Korea
| | - Il Han Kim
- Department of Radiation Oncology, Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea
| | - Soon Tae Lee
- Department of Neurology, Seoul National University College of Medicine, Seoul, Korea
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30
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Conventional MRI features of adult diffuse glioma molecular subtypes: a systematic review. Neuroradiology 2020; 63:353-362. [PMID: 32840682 DOI: 10.1007/s00234-020-02532-7] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Accepted: 08/17/2020] [Indexed: 12/21/2022]
Abstract
PURPOSE Molecular parameters have become integral to glioma diagnosis. Much of radiogenomics research has focused on the use of advanced MRI techniques, but conventional MRI sequences remain the mainstay of clinical assessments. The aim of this research was to synthesize the current published data on the accuracy of standard clinical MRI for diffuse glioma genotyping, specifically targeting IDH and 1p19q status. METHODS A systematic search was performed in September 2019 using PubMed and the Cochrane Library, identifying studies on the diagnostic value of T1 pre-/post-contrast, T2, FLAIR, T2*/SWI and/or 3-directional diffusion-weighted imaging sequences for the prediction of IDH and/or 1p19q status in WHO grade II-IV diffuse astrocytic and oligodendroglial tumours as defined in the WHO 2016 Classification of CNS Tumours. RESULTS Forty-four studies including a total of 5286 patients fulfilled the inclusion criteria. Correlations between key glioma molecular markers, namely IDH and 1p19q, and distinctive MRI findings have been established, including tumour location, signal composition (including the T2-FLAIR mismatch sign) and apparent diffusion coefficient values. CONCLUSION Consistent trends have emerged indicating that conventional MRI is valuable for glioma genotyping, particularly in presumed lower grade glioma. However, due to limited interobserver testing, the reproducibility of qualitatively assessed visual features remains an area of uncertainty.
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Throckmorton P, Graber JJ. T2-FLAIR mismatch in isocitrate dehydrogenase mutant astrocytomas: Variability and evolution. Neurology 2020; 95:e1582-e1589. [PMID: 32690782 DOI: 10.1212/wnl.0000000000010324] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2019] [Accepted: 03/30/2020] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To assess the predictive value of T2 appearance as a defining criterion of T2-fluid-attenuated inversion recovery (FLAIR) mismatch sign (T2FM), further characterize tumors that display the marker, and describe its radiographic evolution. METHODS Records from 64 patients with astrocytomas were assessed for age at diagnosis, sex, tumor characteristics on pretreatment CT, MRI, and pathology, documentation of T2FM, treatment course, and temporal changes in tumor appearance. Cases were divided into those meeting classic criteria (homogenous T2, hyperintense FLAIR rim), those considered geographic (heterogeneous T2, hyperintense FLAIR rim), and those that were negative (no FLAIR rim). Groups were compared using χ2, estimate of effect, and qualitative analyses. RESULTS Including geographic tumors increased T2FM sensitivity 30% among astrocytomas without decreased specificity for IDH mutation. Tumors with T2FM characteristics were more cystic, less enhancing, and affected younger patients. T2FM persisted in residual tumors following subtotal resection and disappeared with radiotherapy, persisted in 5/8 recurrent tumors that were originally T2FM-positive, and was identified in tumors with high-grade characteristics. T2FM was able to predict IDH mutation status on sequencing when antibody testing was negative. CONCLUSIONS The presence of a hyperintense FLAIR rim, regardless of T2 appearance, is a reliable indicator of IDH mutation among astrocytomas. Tumors with a FLAIR rim are more cystic and this may lend to their characteristic appearance on MRI. T2FM demonstrates distinctive temporal radiographic changes, may be seen in high-grade gliomas, and may be used in combination with other variables to strengthen prediction of IDH status.
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Affiliation(s)
- Patrick Throckmorton
- From the School of Medicine (P.T.) and Departments of Neurology and Neurosurgery at the Alvord Brain Tumor Center (J.J.G.), the University of Washington; and Seattle Cancer Care Alliance (J.J.G.), WA
| | - Jerome J Graber
- From the School of Medicine (P.T.) and Departments of Neurology and Neurosurgery at the Alvord Brain Tumor Center (J.J.G.), the University of Washington; and Seattle Cancer Care Alliance (J.J.G.), WA.
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Corell A, Ferreyra Vega S, Hoefling N, Carstam L, Smits A, Olsson Bontell T, Björkman-Burtscher IM, Carén H, Jakola AS. The clinical significance of the T2-FLAIR mismatch sign in grade II and III gliomas: a population-based study. BMC Cancer 2020; 20:450. [PMID: 32434559 PMCID: PMC7238512 DOI: 10.1186/s12885-020-06951-w] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2019] [Accepted: 05/11/2020] [Indexed: 11/18/2022] Open
Abstract
Background The T2-FLAIR mismatch sign is an imaging finding highly suggestive of isocitrate dehydrogenase mutated (IDH-mut) 1p19q non-codeleted (non-codel) gliomas (astrocytomas). In previous studies, it has shown excellent specificity but limited sensitivity for IDH-mut astrocytomas. Whether the mismatch sign is a marker of a clinically relevant subtype of IDH-mut astrocytomas is unknown. Methods We included histopathologically verified supratentorial lower-grade gliomas (LGG) WHO grade II-III retrospectively during the period 2010–2016. In the period 2017–2018, patients with suspected LGG radiologically were prospectively included, and in this cohort other diagnoses than glioma could occur. Clinical, radiological and molecular data were collected. For clinical evaluation we included all patients with IDH-mut astrocytomas. In the 2010–2016 cohort DNA methylation analysis with Infinium MethylationEPIC BeadChip (Illumina) was performed for patients with an IDH-mut astrocytoma with available tissue. We aimed to examine the association of the T2-FLAIR mismatch sign with clinical factors and outcomes. Additionally, we evaluated the diagnostic reliability of the mismatch sign and its relation to methylation profiles. Results Out of 215 patients with LGG, 135 had known IDH-mutation and 1p19q codeletion status. Fifty patients had an IDH-mut astrocytoma and 12 of these (24.0%) showed a mismatch sign. The sensitivity and specificity of the mismatch sign for IDH-mut detection were 26.4 and 97.6%, respectively. There were no differences between patients with an IDH-mut astrocytoma with or without mismatch sign when grouped according to T2-FLAIR mismatch sign with respect to baseline characteristics, clinical outcomes and methylation profiles. The overall interrater agreement between neuroradiologist and clinical neurosurgeons for the T2-FLAIR mismatch sign was significant when all 215 MRI examination assessed (κ = 0.77, p < 0.001, N = 215). Conclusion The T2-FLAIR mismatch sign in patients with an IDH-mut astrocytoma is not associated with clinical presentation or outcome. It seems unlikely that the IDH-mut astrocytomas with mismatch sign represent a specific subentity. Finally, we have validated that the T2-FLAIR mismatch sign is a reliable and specific marker of IDH-mut astrocytomas.
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Affiliation(s)
- Alba Corell
- Department of Neurosurgery, Sahlgrenska University Hospital, Gothenburg, Sweden. .,Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, University of Gothenburg, Sahlgrenska Academy, Gothenburg, Sweden.
| | - Sandra Ferreyra Vega
- Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, University of Gothenburg, Sahlgrenska Academy, Gothenburg, Sweden
| | - Nickoleta Hoefling
- Department of Radiology, Sahlgrenska University Hospital, Gothenburg, Sweden.,Department of Radiology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Louise Carstam
- Department of Neurosurgery, Sahlgrenska University Hospital, Gothenburg, Sweden.,Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, University of Gothenburg, Sahlgrenska Academy, Gothenburg, Sweden
| | - Anja Smits
- Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, University of Gothenburg, Sahlgrenska Academy, Gothenburg, Sweden.,Department of Neuroscience, Neurology, Uppsala University, Uppsala, Sweden
| | - Thomas Olsson Bontell
- Department of Clinical Pathology and Cytology, Sahlgrenska University Hospital, Gothenburg, Sweden.,Department of Physiology, Institute of Neuroscience and Physiology, University of Gothenburg, Sahlgrenska Academy, Gothenburg, Sweden
| | - Isabella M Björkman-Burtscher
- Department of Radiology, Sahlgrenska University Hospital, Gothenburg, Sweden.,Department of Radiology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Helena Carén
- Sahlgrenska Cancer Center, Department of Laboratory Medicine, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Asgeir Store Jakola
- Department of Neurosurgery, Sahlgrenska University Hospital, Gothenburg, Sweden.,Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, University of Gothenburg, Sahlgrenska Academy, Gothenburg, Sweden.,Department of Neuromedicine and Movement Science, NTNU, Trondheim, Norway
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Darvishi P, Batchala PP, Patrie JT, Poisson LM, Lopes MB, Jain R, Fadul CE, Schiff D, Patel SH. Prognostic Value of Preoperative MRI Metrics for Diffuse Lower-Grade Glioma Molecular Subtypes. AJNR Am J Neuroradiol 2020; 41:815-821. [PMID: 32327434 DOI: 10.3174/ajnr.a6511] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2019] [Accepted: 02/29/2020] [Indexed: 02/01/2023]
Abstract
BACKGROUND AND PURPOSE Despite the improved prognostic relevance of the 2016 WHO molecular-based classification of lower-grade gliomas, variability in clinical outcome persists within existing molecular subtypes. Our aim was to determine prognostically significant metrics on preoperative MR imaging for lower-grade gliomas within currently defined molecular categories. MATERIALS AND METHODS We undertook a retrospective analysis of 306 patients with lower-grade gliomas accrued from an institutional data base and The Cancer Genome Atlas. Two neuroradiologists in consensus analyzed preoperative MRIs of each lower-grade glioma to determine the following: tumor size, tumor location, number of involved lobes, corpus callosum involvement, hydrocephalus, midline shift, eloquent cortex involvement, ependymal extension, margins, contrast enhancement, and necrosis. Adjusted hazard ratios determined the association between MR imaging metrics and overall survival per molecular subtype, after adjustment for patient age, patient sex, World Health Organization grade, and surgical resection status. RESULTS For isocitrate dehydrogenase (IDH) wild-type lower-grade gliomas, tumor size (hazard ratio, 3.82; 95% CI, 1.94-7.75; P < .001), number of involved lobes (hazard ratio, 1.70; 95% CI, 1.28-2.27; P < .001), hydrocephalus (hazard ratio, 4.43; 95% CI, 1.12-17.54; P = .034), midline shift (hazard ratio, 1.16; 95% CI, 1.03-1.30; P = .013), margins (P = .031), and contrast enhancement (hazard ratio, 0.34; 95% CI, 0.13-0.90; P = .030) were associated with overall survival. For IDH-mutant 1p/19q-codeleted lower-grade gliomas, tumor size (hazard ratio, 2.85; 95% CI, 1.06-7.70; P = .039) and ependymal extension (hazard ratio, 6.34; 95% CI, 1.07-37.59; P = .042) were associated with overall survival. CONCLUSIONS MR imaging metrics offers prognostic information for patients with lower-grade gliomas within molecularly defined classes, with the greatest prognostic value for IDH wild-type lower-grade gliomas.
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Affiliation(s)
- P Darvishi
- From the Departments of Radiology and Medical Imaging (P.D., P.P.B., S.H.P.)
| | - P P Batchala
- From the Departments of Radiology and Medical Imaging (P.D., P.P.B., S.H.P.)
| | | | - L M Poisson
- Department of Public Health (L.M.P.), Henry Ford Health System, Detroit, Michigan
| | - M-B Lopes
- Pathology, Divisions of Neuropathology and Molecular Diagnostics (M.-B.L.)
| | - R Jain
- Departments of Radiology (R.J.) and Neurosurgery (R.J.), New York University School of Medicine, New York, New York
| | - C E Fadul
- Division of Neuro-Oncology (C.E.F., D.S.), University of Virginia Health System, Charlottesville, Virginia
| | - D Schiff
- Division of Neuro-Oncology (C.E.F., D.S.), University of Virginia Health System, Charlottesville, Virginia
| | - S H Patel
- From the Departments of Radiology and Medical Imaging (P.D., P.P.B., S.H.P.)
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Kinoshita M, Uchikoshi M, Sakai M, Kanemura Y, Kishima H, Nakanishi K. T 2-FLAIR Mismatch Sign Is Caused by Long T 1 and T 2 of IDH-mutant, 1p19q Non-codeleted Astrocytoma. Magn Reson Med Sci 2020; 20:119-123. [PMID: 32101817 PMCID: PMC7952199 DOI: 10.2463/mrms.bc.2019-0196] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
T2-fluid-attenuated inversion recovery images (FLAIR) mismatch sign is now known to be a specific yet insensitive image feature for IDH-mutant, 1p19q non-codeleted astrocytoma. The current study revealed that lesion presenting T2-FLAIR mismatch exhibited extremely long T1- and T2-relaxation time while T2-FLAIR matched lesions showed low to moderate values. On the other hand, IDH-wildtype tumors presented noticeably short T1- and T2-relaxation time. These different relaxation time characteristics seemed to render T2-FLAIR mismatch sign of becoming such a unique and specific image feature for IDH-mutant, 1p19q non-codeleted astrocytoma.
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Affiliation(s)
- Manabu Kinoshita
- Department of Neurosurgery, Osaka International Cancer Institute
| | - Masato Uchikoshi
- Department of Neurosurgery, Osaka International Cancer Institute.,Canon Medical Systems Corporation
| | - Mio Sakai
- Department of Diagnostic and Interventional Radiology, Osaka International Cancer Institute
| | - Yonehiro Kanemura
- Department of Biomedical Research and Innovation, Institute for Clinical Research, National Hospital Organization Osaka National Hospital
| | - Haruhiko Kishima
- Department of Neurosurgery, Osaka University Graduate School of Medicine
| | - Katsuyuki Nakanishi
- Department of Diagnostic and Interventional Radiology, Osaka International Cancer Institute
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35
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Kern M, Auer TA, Fehrenbach U, Tanyildizi Y, Picht T, Misch M, Wiener E. Multivariable non-invasive association of isocitrate dehydrogenase mutational status in World Health Organization grade II and III gliomas with advanced magnetic resonance imaging T2 mapping techniques. Neuroradiol J 2020; 33:160-168. [PMID: 31957551 DOI: 10.1177/1971400919890099] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
AIM To investigate multivariable analyses for noninvasive association of the isocitrate dehydrogenase (IDH) mutational status in grade II and III gliomas including evaluation of T2 mapping-sequences. METHODS Magnetic resonance imaging (MRI) examinations with histopathologically proven World Health Organization grade II and III gliomas were retrospectively enrolled. Multivariate receiver operating characteristics (ROC) analyses to associate IDH mutational status were performed containing quantitative T2 mapping analyses and qualitative characteristics (sex, age, localization, heterogeneity, oedema, necrosis and diameter). Relaxation times were calculated pixelwise by means of standardized ROI analyses. Interobserver variability also was tested. RESULTS Out of 32 patients (mean age: 50.7 years; range: 32-83), nine had grade II gliomas and 24 grade III, while 59.5% showed a positive IDH mutated state (IDHm) and 40.5% were wildtype (IDHw). Multivariable ROC analyses were calculated for relaxation time and range, localization and age with a cumulative 0.955 area under the curve (AUC) (p < 0.001), while central T2-relaxation time had by far the highest single variable sensitivity (AUC: 0.873; range: 0.762; age: 0.809; localization: 0.713). Age (cut off: 49 years; p = 0.031) and localization (p = 0.014) were the only qualitative parameters found to be significant as IDHw gliomas were older and IDHm gliomas were preferentially located fronto-temporal. CONCLUSIONS This is the first study evaluating quantitative T2 mapping sequences for association of the IDH mutational status in grade II and III gliomas demonstrating an association between relaxation time and mutational status. Analyses of T2 mapping relaxation times may even be suitable for predicting the correct IDH mutational state. Prognostic accuracy increases significantly in predicting the correct mutational state when combing T2 relaxation time characteristics and the qualitative MRI features age and localization.
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Affiliation(s)
- Maike Kern
- Department of Neuroradiology, Charite University Hospital Berlin, Germany.,Department of Radiology, Charite University Hospital Berlin, Germany
| | - Timo A Auer
- Department of Radiology, Charite University Hospital Berlin, Germany
| | - Uli Fehrenbach
- Department of Radiology, Charite University Hospital Berlin, Germany
| | | | - Thomas Picht
- Department of Neurosurgery, Charite University Hospital Berlin, Germany *These authors contributed equally to this work
| | - Martin Misch
- Department of Neurosurgery, Charite University Hospital Berlin, Germany *These authors contributed equally to this work
| | - Edzard Wiener
- Department of Neuroradiology, Charite University Hospital Berlin, Germany
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Foltyn M, Nieto Taborda KN, Neuberger U, Brugnara G, Reinhardt A, Stichel D, Heiland S, Herold-Mende C, Unterberg A, Debus J, von Deimling A, Wick W, Bendszus M, Kickingereder P. T2/FLAIR-mismatch sign for noninvasive detection of IDH-mutant 1p/19q non-codeleted gliomas: validity and pathophysiology. Neurooncol Adv 2020; 2:vdaa004. [PMID: 32642675 PMCID: PMC7212872 DOI: 10.1093/noajnl/vdaa004] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Background This study aimed to assess the validity and pathophysiology of the T2/FLAIR-mismatch sign for noninvasive identification of isocitrate dehydrogenase (IDH)-mutant 1p/19q non-codeleted glioma. Methods Magnetic resonance imaging scans from 408 consecutive patients with newly diagnosed glioma (113 lower-grade gliomas and 295 glioblastomas) were evaluated for the presence of T2/FLAIR-mismatch sign by 2 independent reviewers. Sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) were calculated to assess the performance of the T2/FLAIR-mismatch sign for identifying IDH-mutant 1p/19q non-codeleted tumors. An exploratory analysis of differences in contrast-enhancing tumor volumes, apparent diffusion coefficient (ADC) values, and relative cerebral blood volume (rCBV) values in IDH-mutant gliomas with versus without the presence of a T2/FLAIR-mismatch sign (as well as analysis of spatial differences within tumors with the presence of a T2/FLAIR-mismatch sign) was performed. Results The T2/FLAIR-mismatch sign was present in 12 cases with lower-grade glioma (10.6%), all of them being IDH-mutant 1p/19q non-codeleted tumors (sensitivity = 10.9%, specificity = 100%, PPV = 100%, NPV = 3.0%, accuracy = 13.3%). There was a substantial interrater agreement to identify the T2/FLAIR-mismatch sign (Cohen's kappa = 0.75 [95% CI, 0.57-0.93]). The T2/FLAIR-mismatch sign was not identified in any other molecular subgroup, including IDH-mutant glioblastoma cases (n = 5). IDH-mutant gliomas with a T2/FLAIR-mismatch sign showed significantly higher ADC (P < .0001) and lower rCBV values (P = .0123) as compared to IDH-mutant gliomas without a T2/FLAIR-mismatch sign. Moreover, in IDH-mutant gliomas with T2/FLAIR-mismatch sign the ADC values were significantly lower in the FLAIR-hyperintense rim as compared to the FLAIR-hypointense core of the tumor (P = .0005). Conclusions This study confirms the high specificity of the T2/FLAIR-mismatch sign for noninvasive identification of IDH-mutant 1p/19q non-codeleted gliomas; however, sensitivity is low and applicability is limited to lower-grade gliomas. Whether the higher ADC and lower rCBV values in IDH-mutant gliomas with a T2/FLAIR-mismatch sign (as compared to those without) translate into a measurable prognostic effect requires investigation in future studies. Moreover, spatial differences in ADC values between the core and rim of tumors with a T2/FLAIR-mismatch sign potentially reflect specific distinctions in tumor cellularity and microenvironment.
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Affiliation(s)
- Martha Foltyn
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany
| | | | - Ulf Neuberger
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany
| | - Gianluca Brugnara
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany
| | - Annekathrin Reinhardt
- Department of Neuropathology, University of Heidelberg Medical Center, Heidelberg, Germany
| | - Damian Stichel
- Department of Neuropathology, University of Heidelberg Medical Center, Heidelberg, Germany
| | - Sabine Heiland
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany
| | - Christel Herold-Mende
- Department of Neurosurgery, University of Heidelberg Medical Center, Heidelberg, Germany
| | - Andreas Unterberg
- Department of Neurosurgery, University of Heidelberg Medical Center, Heidelberg, Germany
| | - Jürgen Debus
- Department of Radiation Oncology, University of Heidelberg Medical Center, Heidelberg Institute of Radiation Oncology and National Center for Radiation Research in Oncology, Heidelberg, Germany.,Division of Molecular and Translational Radiation Oncology, National Center for Tumor Diseases, Heidelberg University Hospital and DKFZ, Heidelberg, Germany
| | - Andreas von Deimling
- Department of Neuropathology, University of Heidelberg Medical Center, Heidelberg, Germany.,Clinical Cooperation Unit Neuropathology, German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Wolfgang Wick
- Neurology Clinic, University of Heidelberg Medical Center, Heidelberg, Germany.,Clinical Cooperation Unit Neuro-oncology, DKTK, DKFZ, Heidelberg, Germany
| | - Martin Bendszus
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany
| | - Philipp Kickingereder
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany
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Bonm AV, Ritterbusch R, Throckmorton P, Graber JJ. Clinical Imaging for Diagnostic Challenges in the Management of Gliomas: A Review. J Neuroimaging 2020; 30:139-145. [PMID: 31925884 DOI: 10.1111/jon.12687] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2019] [Revised: 01/03/2020] [Accepted: 01/03/2020] [Indexed: 02/06/2023] Open
Abstract
Neuroimaging plays a critical role in the management of patients with gliomas. While conventional magnetic resonance imaging (MRI) remains the standard imaging modality, it is frequently insufficient to inform clinical decision-making. There is a need for noninvasive strategies for reliably distinguishing low-grade from high-grade gliomas, identifying important molecular features of glioma, choosing an appropriate target for biopsy, delineating target area for surgery or radiosurgery, and distinguishing tumor progression (TP) from pseudoprogression (PsP). One recent advance is the identification of the T2/fluid-attenuated inversion recovery mismatch sign on standard MRI to identify isocitrate dehydrogenase mutant astrocytomas. However, to meet other challenges, neuro-oncologists are increasingly turning to advanced imaging modalities. Diffusion-weighted imaging modalities including diffusion tensor imaging and diffusion kurtosis imaging can be helpful in delineating tumor margins and better visualization of tissue architecture. Perfusion imaging including dynamic contrast-enhanced MRI using gadolinium or ferumoxytol contrast agents can be helpful for grading as well as distinguishing TP from PsP. Positron emission tomography is useful for measuring tumor metabolism, which correlates with grade and can distinguish TP/PsP in the right setting. Magnetic resonance spectroscopy can identify tissue by its chemical composition, can distinguish TP/PsP, and can identify molecular features like 2-hydroxyglutarate. Finally, amide proton transfer imaging measures intracellular protein content, which can be used to identify tumor grade/progression and distinguish TP/PsP.
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Affiliation(s)
- Alipi V Bonm
- Department of Neurology, University of Washington, Seattle, WA
| | | | | | - Jerome J Graber
- Department of Neurology, University of Washington, Seattle, WA.,Departments of Neurology and Neurosurgery, Alvord Brain Tumor Center, University of Washington, Seattle, WA
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Magnetic resonance imaging texture analyses in lower-grade gliomas with a commercially available software: correlation of apparent diffusion coefficient and T2 skewness with 1p/19q codeletion. Neurosurg Rev 2019; 43:1211-1219. [PMID: 31402410 DOI: 10.1007/s10143-019-01157-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2019] [Revised: 07/01/2019] [Accepted: 08/05/2019] [Indexed: 10/26/2022]
Abstract
Preoperative prediction of molecular information of lower-grade gliomas (LrGGs) helps to determine the overall treatment strategy as well as the initial surgical strategy. This study aimed to detect magnetic resonance imaging (MRI) texture parameters to predict the molecular signature of LrGGs using a commercially available software and routine MR images. Forty-three patients treated at Keio University Hospital who had World Health Organization grade II or III gliomas were included. All patients having preoperative T1- and T2-weighted, fluid-attenuated inversion recovery (FLAIR) and diffusion-weighted (DW) images were also included. Texture analyses of T2, FLAIR, and apparent diffusion coefficient (ADC) histograms were performed using a commercially available software. Texture parameters including kurtosis, skewness, and entropy were investigated to determine any correlation with the presence or absence of isocitrate dehydrogenase (IDH) mutations, 1p/19q codeletion, and O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation. ADC skewness and T2 skewness were significantly associated with 1p/19q codeletion status. ADC skewness of ≥ 0.25 predicted 1p/19q codeletion with a sensitivity and specificity of 80% and 65.2%, respectively (AUC = 0.728). T2 skewness of ≥ - 0.11 predicted 1p/19q codeletion with a sensitivity and specificity of 80% and 91.3%, respectively, (AUC = 0.866). None of the texture parameters were associated with IDH mutation and MGMT promoter methylation. MRI texture analysis using a commercially available software demonstrated that T2 skewness could predict 1p/19q codeletion with high sensitivity and specificity, suggesting a clinical utility.
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