Automated quantitative assessment of cerebral edema after ischemic stroke using CSF volumetrics.

Reduction in CSF volume from baseline to follow-up CT at or beyond 24 -hs can serve as a quantitative biomarker of cerebral edema after stroke. We have demonstrated that assessment of CSF displacement reflects edema metrics such as lesion volume, midline shift, and neurologic deterioration. We have also developed a neural network-based image segmentation algorithm that can automatically measure CSF volume on serial CT scans from stroke patients. We have integrated this algorithm into an image processing pipeline that can extract this edema biomarker from large cohorts of stroke patients. Finally, we have created a stroke repository that can archive and process images from thousands of stroke patients in order to measure CSF volumetrics. We plan on applying this metric as a quantitative endophenotype of cerebral edema to facilitate early prediction of clinical deterioration as well as large-scale genetic studies.