Keywords: Neonatal, Diagnosis/Prediction, biomarkers; multimodal; remote seizure; neonatal arterial ischemic stroke; diffusion MRI; arterial spin labeling MRI
Motivation: Neonatal arterial ischemic stroke (NAIS) could lead to childhood epilepsy. It is critical to accurately predict remote seizures after NAIS diagnosis by adding understudied brain perfusion measures.
Goal(s): To leverage multimodal MRI biomarkers to accurately predict remote seizures after investigating diffusion and perfusion MRI patterns in NAIS patients.
Approach: Baseline diffusion and perfusion MRI scans acquired at initial presentation were analyzed to build an ensemble model for remote seizure prediction.
Results: Unlike hypoperfusion pattern in adult brain stroke, predominant cases of hyperperfusion were identified in the NAIS population. Integrated optimized multimodal MRI-derived biomarkers effectively predict remote seizures.
Impact: This study enhances understanding of NAIS by revealing unique perfusion characteristics and developing a predictive model for remote seizure after NAIS. It supports personalized interventions, potentially improving long-term outcomes and guiding future research on NAIS management and outcomes.
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