Automatic segmentation of intracranial arteries and veins in four-dimensional cerebral CT perfusion scans

A. Mendrik, E. Vonken, B. van Ginneken, E. Smit, A. Waaijer, G. Bertolini, M. Viergever and M. Prokop

Medical Physics 2010;37(6):2956-2966.

DOI PMID Cited by ~32

PURPOSE: CT angiography (CTA) scans are the current standard for vascular analysis of patients with cerebrovascular diseases, such as acute stroke and subarachnoid hemorrhage. An additional CT perfusion (CTP) scan is acquired of these patients to assess the perfusion of the cerebral tissue. The aim of this study is to extend the diagnostic yield of the CTP scans to also include vascular information. METHODS: CTP scans are acquired by injecting contrast material and repeatedly scanning the head over time. Therefore, time-intensity profiles are available for each voxel in the scanned volume, resulting in a 4D dataset. These profiles can be utilized to differentiate not only between vessels and background but also between arteries and veins. In this article, a fully automatic method is proposed for the segmentation of the intracranial arteries and veins from 4D cerebral CTP scans. Furthermore, a vessel enhanced volume is presented, in which the vasculature is highlighted and background structures are suppressed. Combining this volume with the artery/vein segmentation results in an arteriogram and a venogram, which could serve as additional means for vascular analysis in patients with cerebrovascular diseases. The artery/vein segmentation is quantitatively evaluated by comparing the results to manual segmentations by two expert observers. RESULTS: Results (paired two-tailed t-test) show that the accuracies of the proposed artery/vein labeling are not significantly different from the accuracies of the expert observer manual labeling (ground truth). Moreover, sensitivity and specificity of the proposed artery/vein labeling, relative to both expert observer ground truths, were similar to the sensitivity and specificity of the expert observer labeling compared to each other. CONCLUSIONS: The proposed method for artery/vein segmentation is shown to be very accurate for arteries and veins with normal perfusion. Combining the artery/vein segmentation with the vessel enhanced volume produces an arteriogram and a venogram, which have the potential to extend the diagnostic yield of CTP scans and replace the additional CTA scan, but could also be helpful to radiologists in addition to the CTA scan.