BackgroundTraumatic brain injury (TBI) causes early seizures and is the leading cause of post-traumatic epilepsy. We prospectively assessed structural imaging biomarkers differentiating patients who develop seizures secondary to TBI from patients who do not.DesignMulticentre prospective cohort study starting in 2018. Imaging data are acquired around day 14 post-injury, detection of seizure events occurred early (within 1 week) and late (up to 90 days post-TBI).ResultsFrom a sample of 96 patients surviving moderate-to-severe TBI, we performed shape analysis of local volume deficits in subcortical areas (analysable sample: 57 patients; 35 no seizure, 14 early, 8 late) and cortical ribbon thinning (analysable sample: 46 patients; 29 no seizure, 10 early, 7 late). Right hippocampal volume deficit and inferior temporal cortex thinning demonstrated a significant effect across groups. Additionally, the degree of left frontal and temporal pole thinning, and clinical score at the time of the MRI, could differentiate patients experiencing early seizures from patients not experiencing them with 89% accuracy.Conclusions and relevanceAlthough this is an initial report, these data show that specific areas of localised volume deficit, as visible on routine imaging data, are associated with the emergence of seizures after TBI.

Traumatic brain injury (TBI) can cause severe disorders, including post-traumatic epilepsy (PTE). Lesion segmentation is an MRI-based analysis to identify brain structures that correlate with PTE development post-TBI. Unfortunately, manual segmentation, considered the gold standard, is highly tedious and noisy. Thus, we propose the first automated machine-learning based lesion segmentation method for MRI of TBI patients enrolled in the Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx). Experimental validation demonstrates considerable visual overlap of lesion predictions and ground-truths with 61% precision. Early and automated lesion segmentation via our approach can aid experts in MRI analysis and successful PTE identification following TBI.