Neuroimage: Reports (Sep 2024)
Early alterations of thalami- and hippocampi-cortical functional connectivity as biomarkers of seizures after traumatic brain injury
Abstract
The Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx, project 3) is a prospective multicenter clinical observational study to identify early biomarkers of epileptogenesis after moderate-to-severe traumatic brain injury (TBI). We used a seed-based approach applied to acute (i.e., ≤14 days) fMRI imaging data, directly testing the hypothesis that the presence of seizures up to two years following brain trauma is associated with functional changes within hippocampi and thalami-cortical networks. Additionally, we hypothesized that the network connectivity involving thalami and hippocampi circuits underlying early and late-onset seizures would differ. Approximately 30% of the initial dataset was deemed unusable due to MRI issues. Approximately 50% of the enrolled sample was lost to a 2-year follow-up. After preprocessing the fMRI data, approximately 40% of the follow-up sample had to be excluded from the analysis due to excessive in-scanner movements, as assessed by state-of-the-art quality control protocols. Only 37 patients provided data that was suitable for the seed-based analysis. Despite these challenges, the remaining, high-quality data returned noteworthy findings. We identified specific hippocampi and thalami biomarkers associated with both early and late seizures following TBI (p < .05, FWE-corrected at the cluster level). The predictive capability for the development of late seizures after TBI, when adding fMRI data to demographic and clinical data, provided 88% accuracy — an additional 8% improvement compared to using demographic and clinical data alone. Our findings highlight the potential of fMRI for uncovering, in hippocampal and thalamic cortical networks, biomarkers of early and late seizures following TBI. However, they also highlight the important challenges that need to be overcome in order for fMRI to become an effective biomarker and prognostic tool in the intensive care context.
