[Differentiation of temporal lobe epilepsy and temporal plus epilepsy using radiomics nomogram based on MPRAGE images].

A total of 82 patients with temporal lobe epilepsy (TLE) and temporal plus epilepsy (TPE)admitted in Xuanwu Hospital from January 1, 2019, to January 1, 2021 were restrospectively analyzed, including 41 males and 41 females, aged 2 to 52 (24±10) years. The patients were randomly divided into the training set (58 cases) and test set (24 cases) by Python. FreeSurfer software was used to segment the cortex of the affected hemisphere, defining 33 regions of interest (ROIs), and radiomics features were extracted by Python. After selecting features using the filter-based feature selection method, a radiomics model was constructed with a logistic regression classifier, and radiomics scores were calculated. Combining clinical characteristics with radiomics scores, a nomogram model was constructed using R software, the predictive accuracy of the model was assessed with the concordance index (C-index), and the model's goodness-of-fit was tested with the Hosmer-Lemeshow method. The results showed statistically significant differences between TLE and TPE patients in disease duration, intracranial electrode implantation, and hippocampal sclerosis (both P<0.05). The accuracy of the radiomics model in the training set and the test set was 91.4% and 87.5%, respectively. The nomogram model uses C-index to predict accuracy. Hosmer-Lemeshow method was used to test the goodness of fit, with AUCs of 0.95 (95%CI: 0.853-0.991) in the training set and 0.84 (95%CI: 0.676-0.999) in the test set. The study indicates that the radiomics nomogram model based on MPRAGE sequences can effectively differentiate TLE from TPE, providing reference for the development of personalized treatment plans in clinical practice.