ML of Striatum rs-fMRI Features Predicts TLE Diagnosis
Abstract Objective: To determine whether patients with temporal lobe epilepsy (TLE) exhibit aberrant resting-state functional magnetic resonance imaging (rs-fMRI)-functional connectivity and build an individualized TLE prediction model using ML (ML). Methods: Sixty TLE patients and fifty-one controls underwent rs-fMRI scanning. The striatum was divided into 12 striatal seeds. rs-FC was compared between groups to enable TLE classification based on striatal FC using the SPM12, SVM and PRONTO softwares. Bilateral striatal FC values were extracted and significance values were obtained using leave-one-out (LOO) SVM analysis and permutation testing (2,000) for cross-validation.Results: Patients with TLE exhibited a significantly decreased rs-FC between the left inferior ventral striatum and the right posterior central gyrus, left superior frontal gyrus;and between the left dorsal rostral putamen and right superior parietal lobule, right middle frontal gyrus. And between right dorsal caudate And left prefrontal lobe, and right middle temporal gyrus. rs-fMRI analysis a revealed significantly increased FC between the left inferior ventral striatum seed and right anterior cingulate in TLE patients (p<0.05). Right dorsal caudate FC may distinguish individuals with TLE from controls with 79.08% Accuracy, including a 72.77% Sensitivity and 76.44% Specificity, resulting in an AUC of 0.71 (p <0 .01). The areas informing classification included left prefrontal lobe, right middle temporal gyrus, and left superior parietal lobule.Conclusion: Our findings demonstrate aberrant FC in certain brain regions, such as the right dorsal caudate, may play an important role as potential biomarkers of TLE and highlight the utility of ML-based models for clinical decision making.