Journal
RADIOLOGY
Volume 296, Issue 1, Pages 111-121Publisher
RADIOLOGICAL SOC NORTH AMERICA
DOI: 10.1148/radiol.2020191832
Keywords
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Funding
- University College London Hospitals
- National Institute of Health Research Biomedical Research Centre
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Background: A readily implemented MRI biomarker for glioma genotyping is currently lacking. Purpose: To evaluate clinically available MRI parameters for predicting isocitrate dehydrogenase (IDH) status in patients with glioma. Materials and Methods: In this retrospective study of patients studied from July 2008 to February 2019, untreated World Health Organization (WHO) grade II/III gliomas were analyzed by three neuroradiologists blinded to tissue results. Apparent diffusion coefficient (ADC) minimum (ADC(min)) and mean (ADC(mean)) regions of interest were defined in tumor and normal appearing white matter (ADC(NAWM)). A visual rating of anatomic features (T1 weighted, T1 weighted with contrast enhancement, T2 weighted, and fluid-attenuated inversion recovery) was performed. Inter observer comparison (intraclass correlation coefficient and Cohen kappa) was followed by nonparametric (Kruskal-Wallis analysis of variance) testing of associations between ADC metrics and glioma genotypes,including Bonferroni correction for multiple testing. Descriptors with sufficient concordance (intraclass correlation coefficient >0.8; kappa > 0.6) underwent univariable analysis. Predictive variables (P <.05) were entered into a multivariable logistic regression and tested in an additional test sample of patients with glioma. Results: The study included 290 patients (median age, 40 years; interquartile range, 33-52 years; 169 male patients) with 82 IDH wild-type, 107 IDH mutant/1p19q intact, and 101 IDH mutant/1p19q codeleted gliomas. Two predictive models incorporating ADC(mean)-to-ADC(NAWM) ratio, age, and morphologic characteristics, with model A mandating calcification result and model B recording cyst formation, classified tumor type with areas under the receiver operating characteristic curve of 0.94 (95% confidence interval [CI]:0.91, 0.97) and 0.96 (95% CI: 0.93, 0.98), respectively. In the test sample of 49 gliomas (nine IDH wild type, 21 IDH mutant/1p19q intact, and 19 IDH mutant/1p19q codeleted), the classification accuracy was 40 of 49 gliomas (82%; 95% CI: 71%, 92%) for model A and 42 of 49 gliomas (86%; 95% CI: 76%, 96%) for model B. Conclusion: Two algorithms that incorporated apparent diffusion coefficient values, age, and tumor morphologic characteristics predicted isocitrate dehydrogenase status in World Health Organization grade II/III gliomas on the basis of standard clinical MRI sequences alone. (C) RSNA, 2020
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