A segmentation-based volumetric approach to localize and quantify cerebral vasospasm based on tomographic imaging data.

Quantification of cerebral vasospasm after subarachnoid hemorrhage (SAH) is crucial in animal studies as well as clinical routine. We have developed a method for computer-based volumetric assessment of intracranial blood vessels from cross-sectional imaging data. Here we demonstrate the quantification of vasospasm from micro computed tomography (micro-CT) data in a rodent SAH model and the transferability of the volumetric approach to clinical data.We obtained rodent data by performing an ex vivo micro-CT of murine brains after sham surgery or SAH by endovascular filament perforation on day 3 post hemorrhage. Clinical CT angiography (CTA) was performed for diagnostic reasons unrelated to this study. We digitally reconstructed and segmented intracranial vascular trees, followed by calculating volumes of defined vessel segments by standardized protocols using Amira® software.SAH animals demonstrated significantly smaller vessel diameters compared with sham (MCA: 134.4±26.9μm vs.165.0±18.7μm, p