Arian Lasocki1,2, Mustafa Anjari3, Suna Ӧrs Kokurcan3,4, Stefanie C Thust3,5. 1. Department of Cancer Imaging, Peter MacCallum Cancer Centre, Grattan St, Melbourne, Victoria, 3000, Australia. arian.lasocki@petermac.org. 2. Sir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, Australia. arian.lasocki@petermac.org. 3. Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, London, UK. 4. Department of Diagnostic Neuroradiology, Health Science University, Bakirkoy Dr Sadi Konuk Training and Research Hospital, Istanbul, Turkey. 5. Department of Brain Repair and Rehabilitation, Neuroradiological Academic Unit, UCL Institute of Neurology, London, UK.
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.
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.
Entities:
Keywords:
Glioblastoma; Glioma; Imaging genomics; Magnetic resonance imaging; Radiogenomics
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