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Publication

Radiomics Features of Hippocampal Regions in Conventional and Diffusion Tensor Imagings can Differentiate Temporal Lobe Epilepsy Patients from Healthy Controls
Journal
Scientific Reports
Vol
10
Page
19567
Author
Yae Won Park, Yun Seo Choi, Song E Kim, Dongmin Choi, Kyunghwa Han, Hwiyoung Kim, Sung Soo Ahn, Sol-Ah Kim, Hyeon Jin Kim, Soo Mee Lim, Hyang Woon Lee
Year
AI-powered Diagnosis
Date
Nov, 2020
File
s41598-020-76283-z.pdf (2.0M) 2회 다운로드 DATE : 2021-03-15 16:25:50
To investigative whether radiomics features in bilateral hippocampi from MRI can identify temporal lobe epilepsy (TLE). A total of 131 subjects with MRI (66 TLE patients [35 right and 31 left TLE] and 65 healthy controls [HC]) were allocated to training (n = 90) and test (n = 41) sets. Radiomics features (n = 186) from the bilateral hippocampi were extracted from T1-weighted images. After feature selection, machine learning models were trained. The performance of the classifier was validated in the test set to differentiate TLE from HC and ipsilateral TLE from HC. Identical processes were performed to differentiate right TLE from HC (training set, n = 69; test set; n = 31) and left TLE from HC (training set, n = 66; test set, n = 30). The best-performing model for identifying TLE showed an AUC, accuracy, sensitivity, and specificity of 0.848, 84.8%, 76.2%, and 75.0% in the test set, respectively. The best-performing radiomics models for identifying right TLE and left TLE subgroups showed AUCs of 0.845 and 0.840 in the test set, respectively. In addition, multiple radiomics features significantly correlated with neuropsychological test scores (false discovery rate-corrected p-values < 0.05). The radiomics model from hippocampus can be a potential biomarker for identifying TLE.