Brain Inform. 2025 Dec 28. doi: 10.1186/s40708-025-00284-9. Online ahead of print.
ABSTRACT
BACKGROUND/OBJECTIVE: Predicting neurological outcomes in comatose cardiac arrest survivors remains challenging. Diffusion tensor imaging (DTI) offers potential as an objective biomarker of white matter injury, but its prognostic value needs further validation. We aimed to investigate the predictive value of DTI-derived metrics for six-month neurological outcomes in comatose cardiac arrest patients.
METHODS: This prospective study enrolled 28 comatose cardiac arrest patients (mean age 54.36 ± 3.01 years; 71% male) and 28 age-/sex-matched healthy controls (HCs). All participants underwent 3T brain MRI (median 4 days post-arrest). DTI parameters (fractional anisotropy [FA], mean diffusivity [MD], axial diffusivity [AD], radial diffusivity [RD]) were analyzed using Tract-based spatial statistics (TBSS) and ROI approaches based on white matter atlas. Neurological outcome was assessed at six months using the modified Rankin Scale (good outcome: mRS 0-2; poor outcome: mRS 3-5). Statistical analyses included voxel-wise comparisons and ROC curve analysis for predictive performance.
RESULTS: Compared to HCs, patients showed widespread reductions in FA, MD, AD, and RD (TFCE-corrected p < 0.05). Patients with poor outcomes (n = 18) exhibited significantly lower DTI metrics than those with good outcomes (n = 10) across most white matter tracts. The combination of whole-brain FA and RD demonstrated exceptional prognostic accuracy for good outcome (AUC = 0.984; 95% CI 0.925-1.000; sensitivity 92%, specificity 97.7%), significantly outperforming clinical variables and individual DTI parameters. ROI analysis identified specific tracts (e.g., right cingulum hippocampus, right uncinate fasciculus) with high predictive values. Ventricular fibrillation as initial rhythm was more frequent in the group with good outcomes.
CONCLUSIONS: DTI metrics, particularly the combination of FA and RD, provided outstanding early prediction of good six-month neurological outcomes after cardiac arrest, surpassing traditional biomarkers. These findings supported integrating DTI into multimodal prognostic models to guide clinical decisions and prevent premature withdrawal of life-sustaining therapy.
PMID:41457125 | DOI:10.1186/s40708-025-00284-9
