NI-12 The ratio of T1-Weighted to T2-Weighted Signal Intensity and IDH mutation in glioma. (6th December 2021)

• Record Type: Journal Article
• Authors: Sanada, Takahiro; Yamamoto, Shota; Sato, Hirotaka; Sakai, Mio; Saito, Masato; Mitsui, Nobuyuki; Hiroshima, Satoru; Anei, Ryogo; Kanemura, Yonehiro; Nakanishi, Katsuyuki; Kishima, Haruhiko; Kinoshita, Manabu
• Is Part Of: Neuro-oncology advances. Volume 3(2021)Supplement 6
• Page Start: vi20
• Page End: vi20
• Publication Date: 2021-12-06
• Subjects: glioma -- IDH mutation -- MRI; 616.99481
• DOI: 10.1093/noajnl/vdab159.074
• Languages: English
• ISSNs: 2632-2498

Abstract

Abstract: Introduction: Prediction of IDH mutation status for Lower-grade glioma (LrGG) is clinically significant. The purpose of this study is to test the hypothesis that the T1-weighted image/T2-weighted image ratio (rT1/T2), an imaging surrogate developed for myelin integrity, is a useful MRI biomarker for predicting the IDH mutation status of LrGG. Methods: Twenty-five LrGG patients (IDHwt: 8, IDHmt: 17) at Asahikawa Medical University Hospital (AMUH) were used as an exploratory cohort. Twenty-nine LrGG patients (IDHwt: 13, IDHmt: 16) from Osaka International Cancer Institute (OICI) and 103 patients from the Cancer Imaging Archive (TCIA) / Cancer Genome Atlas (TCGA) dataset (IDHwt: 19, IDHmt: 84) were used as validation cohorts. rT1/T2 images were calculated from T1- and T2-weighted images using a recommended signal correction. The region-of-interest was defined on T2-weighted images, and the relationship between the mean rT1/T2 (mrT1/T2) and the IDH mutation status was investigated. Results: The mrT1/T2 was able to significantly predict the IDH mutation status for the AMUH exploratory cohort (AUC = 0.75, p = 0.048). The ideal cut-off for detecting mutant IDH was mrT1/T2 < 0.666 ~ 0.677, with a sensitivity of 58.8% and a specificity of 87.5%. This result was further validated by the OICI validation cohort (AUC = 0.75, p = 0.023) with a sensitivity of 56.3% and a specificity of 69.2%. On the other hand, the sensitivity was 42.9% and the specificity was 68.4 % for the TCIA validation cohort (AUC = 0.63, p = 0.068). Conclusion: Our results supported the hypothesis that mrT1/T2 could be a useful image surrogate to predict the IDH mutation status of LrGG using two domestic cohorts. The decline of the accuracy for the TCIA cohort should be further investigated.