Sohil H Patel1, Prem P Batchala2, Thomas J Eluvathingal Muttikkal2, Sergio S Ferrante2, James T Patrie3, Camilo E Fadul4, David Schiff4, M Beatriz Lopes5, Rajan Jain6,7. 1. Department of Radiology and Medical Imaging, University of Virginia Health System, PO Box 800170, Charlottesville, VA, 22908, USA. shp4k@virginia.edu. 2. Department of Radiology and Medical Imaging, University of Virginia Health System, PO Box 800170, Charlottesville, VA, 22908, USA. 3. Department of Public Health Sciences, University of Virginia Health System, Charlottesville, VA, USA. 4. Division of Neuro-Oncology, Department of Neurology, University of Virginia Health System, Charlottesville, VA, USA. 5. Department of Pathology, Divisions of Neuropathology and Molecular Diagnostics, University of Virginia Health System, Charlottesville, VA, USA. 6. Department of Radiology, New York University School of Medicine, 550 1st Avenue, New York, NY, 10016, USA. 7. Department of Neurosurgery, New York University School of Medicine, 550 1st Avenue, New York, NY, 10016, USA.
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.
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.
Authors: D Williams Parsons; Siân Jones; Xiaosong Zhang; Jimmy Cheng-Ho Lin; Rebecca J Leary; Philipp Angenendt; Parminder Mankoo; Hannah Carter; I-Mei Siu; Gary L Gallia; Alessandro Olivi; Roger McLendon; B Ahmed Rasheed; Stephen Keir; Tatiana Nikolskaya; Yuri Nikolsky; Dana A Busam; Hanna Tekleab; Luis A Diaz; James Hartigan; Doug R Smith; Robert L Strausberg; Suely Kazue Nagahashi Marie; Sueli Mieko Oba Shinjo; Hai Yan; Gregory J Riggins; Darell D Bigner; Rachel Karchin; Nick Papadopoulos; Giovanni Parmigiani; Bert Vogelstein; Victor E Velculescu; Kenneth W Kinzler Journal: Science Date: 2008-09-04 Impact factor: 47.728
Authors: Jason Beiko; Dima Suki; Kenneth R Hess; Benjamin D Fox; Vincent Cheung; Matthew Cabral; Nicole Shonka; Mark R Gilbert; Raymond Sawaya; Sujit S Prabhu; Jeffrey Weinberg; Frederick F Lang; Kenneth D Aldape; Erik P Sulman; Ganesh Rao; Ian E McCutcheon; Daniel P Cahill Journal: Neuro Oncol Date: 2013-12-04 Impact factor: 12.300
Authors: Jeanette E Eckel-Passow; Daniel H Lachance; Annette M Molinaro; Kyle M Walsh; Paul A Decker; Hugues Sicotte; Melike Pekmezci; Terri Rice; Matt L Kosel; Ivan V Smirnov; Gobinda Sarkar; Alissa A Caron; Thomas M Kollmeyer; Corinne E Praska; Anisha R Chada; Chandralekha Halder; Helen M Hansen; Lucie S McCoy; Paige M Bracci; Roxanne Marshall; Shichun Zheng; Gerald F Reis; Alexander R Pico; Brian P O'Neill; Jan C Buckner; Caterina Giannini; Jason T Huse; Arie Perry; Tarik Tihan; Mitchell S Berger; Susan M Chang; Michael D Prados; Joseph Wiemels; John K Wiencke; Margaret R Wrensch; Robert B Jenkins Journal: N Engl J Med Date: 2015-06-10 Impact factor: 176.079
Authors: Hai Yan; D Williams Parsons; Genglin Jin; Roger McLendon; B Ahmed Rasheed; Weishi Yuan; Ivan Kos; Ines Batinic-Haberle; Siân Jones; Gregory J Riggins; Henry Friedman; Allan Friedman; David Reardon; James Herndon; Kenneth W Kinzler; Victor E Velculescu; Bert Vogelstein; Darell D Bigner Journal: N Engl J Med Date: 2009-02-19 Impact factor: 176.079
Authors: Christian Hartmann; Bettina Hentschel; Matthias Simon; Manfred Westphal; Gabriele Schackert; Jörg C Tonn; Markus Loeffler; Guido Reifenberger; Torsten Pietsch; Andreas von Deimling; Michael Weller Journal: Clin Cancer Res Date: 2013-08-05 Impact factor: 13.801
Authors: Arian Lasocki; Michael E Buckland; Katharine J Drummond; Heng Wei; Jing Xie; Michael Christie; Andrew Neal; Frank Gaillard Journal: Neuroradiology Date: 2022-05-24 Impact factor: 2.804
Authors: David A Joyner; John Garrett; Prem P Batchala; Bharath Rama; Joshua R Ravicz; James T Patrie; Maria-B Lopes; Camilo E Fadul; David Schiff; Rajan Jain; Sohil H Patel Journal: Neuroradiology Date: 2022-08-12 Impact factor: 2.995