Abstract #2331

Prediction of IDH status of Glioma using Diffusion Tensor Imaging and Clinical features

Yuxia Liang¹, Yuhan Ren², Yu Shang³, Xiang Liu³, Maode Wang³, Ming Zhang³, and Chen Niu⁴

¹The first affiliated hospital of Xi'an Jiaotong University, Xi'An, China, ²Hospital of Stomatology Xi'an Jiaotong University, Xi'an, China, ³The first affiliated hospital of Xi'an Jiaotong University, Xi'an, China, ⁴The first affiliated hospital of Xi'an Jiaotong University, XI'an, China

Synopsis

Keywords: Tumors, Diffusion Tensor Imaging, gliomaIsocitrate dehydrogenase (IDH) is critical to prognosis of glioma. While, reliable techniques for preoperative assessment of IDH status remain scarce. In this study, we investigated mean diffusivity (MD) and anisotropy fraction (FA) using Diffusion Tensor Imaging (DTI) combined with the clinical features to predict IDH status. Our results found significant differences in FA_mean/FA_nawm, MD_min, NLR, and age between IDH mutant and IDH wild groups. The model incorporating FA_mean/FA_nawm, MD_min, NLR, and age predicted IDH status with area under ROC curve of 0.85, 95% CI: 74.3%~95.7%. Our findings suggested that DTI combined with clinical features can non-invasively prediction of IDH status.

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