Quantitative and radiological assessment of post-cardiac arrest comatose patients with diffusion-weighted magnetic resonance imaging

Abstract

AbstractBackgroundAlthough MR imaging, particularly diffusion weighted imaging, has increasingly been utilized as part of a multimodal approach to prognostication in patients comatose after cardiac arrest, the performance of quantitative analysis of apparent diffusion coefficient (ADC) maps, as compared to standard radiologist impression, has not been well characterized. This retrospective study evaluated quantitative ADC analysis to the identification of anoxic brain injury by diffusion abnormalities on standard clinical MRI reports.MethodsThe cohort included 204 previously described comatose patient post-cardiac arrest. Clinical outcome was assessed by 1) 3-6 month cerebral performance category (CPC); 2) Coma recovery to following commands. Radiological evaluation was obtained from clinical reports and characterized as diffuse, cortex only, deep gray matter structures only, or no injury. Quantitative analysis of ADC maps were obtained in specific regions of interest (ROI), whole cortex, and whole brain. A subgroup analysis of 172 was performed after eliminating images with artifacts and pre-existing lesions.ResultsRadiological assessment outperformed quantitative assessment over all evaluated regions (AUC 0.80 for radiological interpretation, 0.70 for occipital region, the best-performing ROI, p=0.11); agreement was substantial for all regions. Radiological assessment still outperformed quantitative analysis in the subgroup analysis, though by smaller margins, and with substantial to near-perfect agreement. When assessing for coma recovery only, the difference was no longer significant (AUC 0.83 vs 0.81, p=0.70).DiscussionAlthough quantitative analysis eliminates interrater differences in the interpretation of abnormal diffusion imaging and avoids bias from other prediction modalities, clinical radiologist interpretation has a higher predictive value for outcome. This difference appears to be driven by poor scan quality, foreign body artifacts, and pre-existing stroke and white matter disease. Quantitative analysis is comparable to clinical interpretation after eliminating such scans. Further research is required into improving quantitative imaging techniques to account for such variability.