COMPUTATIONAL IMAGE-BASED STROKE ASSESSMENT FOR EVALUATION OF CEREBROPROTECTANTS WITH LONGITUDINAL AND MULTI-SITE PRECLINICAL MRI

While ischemic stroke is a leading cause of death worldwide, there has been little success translating putative cerebroprotectants from rodent preclinical trials to human patients. We investigated computational image-based assessment tools for practical improvement of the quality, scalability, and outlook for large scale preclinical screening for potential therapeutic interventions in rodent models. We developed, evaluated, and deployed a pipeline for imagebased stroke outcome quantification for the Stroke Preclinical Assessment Network (SPAN), a multi-site, multi-arm, multistage study evaluating a suite of cerebroprotectant interventions. Our fully automated pipeline combines state-of-the-art algorithmic and data analytic approaches to assess stroke outcomes from multi-parameter MRI data collected longitudinally from a rodent model of middle cerebral artery occlusion (MCAO), including measures of infarct volume, brain atrophy, midline shift, and data quality. We applied our approach to 1,368 scans and report population level results of lesion extent and longitudinal changes from injury. We validated our system by comparison with both manual annotations of coronal MRI slices and tissue sections from the same brain, using crowdsourcing from blinded stroke experts from the network. Our results demonstrate the efficacy and robustness of our image-based stroke assessments. The pipeline may provide a promising resource for ongoing rodent preclinical studies conducted by SPAN and other networks in the future.

Automated summary

This study developed a pipeline for image-based stroke outcome quantification to improve the assessment quality and scalability of potential therapeutic interventions in rodent models. By analyzing multi-parameter MRI data, including measures of lesion extent and longitudinal changes, the study revealed the overall effects and long-term variations of stroke injury. The validated method may serve as a promising resource for future preclinical studies.