Radiomics for predicting grades, isocitrate dehydrogenase mutation, and oxygen 6-methylguanine-DNA methyltransferase promoter methylation of adult diffuse gliomas: combination of structural MRI, apparent diffusion coefficient, and susceptibility-weighted imaging

作者：Zhengyang Zhu, Jingfei Shen, Xue Liang, Jianan Zhou, Jiawei Liang, Ling Ni, Han Wang, Meiping Ye, Sixuan Chen, Huiquan Yang, Qian Chen, Xin Li, Wen Zhang, Jiaming Lu, Danni Ge, Linqing Fu, Yajing Zhu, Xin Zhang, Yuying Sun, Bing Zhang · 发表于：Quantitative Imaging in Medicine and Surgery · 年份：2024 · DOI：10.21037/qims-24-1110 · 被引用次数：7 · 研究领域：Glioma Diagnosis and Treatment、Radiomics and Machine Learning in Medical Imaging、MRI in cancer diagnosis

Background: ) mutation, and oxygen 6-methylguanine-DNA methyltransferase (MGMT) promoter methylation in patients with diffuse gliomas. Methods: test were used for assessing the statistical differences in patients' clinical characteristics. Delong test was performed to compare the areas under the curve (AUCs) of different radiomics models. Results: For WHO Grade task, the combined model of structural MRI, ADC, and SWI achieved the highest AUC of 0.951 [95% confidence interval (CI): 0.886-1.000] on the external test cohort. For IDH mutation task, the structural MRI model achieved the highest AUC of 0.917 (95% CI: 0.801-1.000) on the external test cohort. For MGMT task, the combined model of structural MRI and ADC achieved the highest AUC of 0.650 (95% CI: 0.485-0.814) on the internal validation cohort. Conclusions: mutation.