Automatic cerebral computed tomography venographic imaging based on the prior knowledge of cerebral blood circulation

Abstract

Background and purposeCurrent clinical computed tomography venographic (cCTV) images present limited cerebral venous profiles. Therefore, this study aimed to develop an automatic cerebral CTV imaging technique using computed tomographic perfusion (CTP) images in a cohort of patients with stroke. Materials and MethodsWe retrospectively evaluated 10 (intracerebral hemorrhage) and 2 (acute ischemic stroke) patients who underwent institutional CTP imaging. CTV images were processed with the proposed CTV (pCTV) technique, and pCTV and cCTV images were then independently evaluated by two experienced neuroradiologists blinded to all clinical information using a novel scoring method that considered overall image quality, venous visibility, and arterial mis-segmentation. Venous visibility was separately evaluated for the dural sinus, superficial vein, and deep vein. Then, statistical analysis was performed to determine whether the pCTV technique was superior to the cCTV technique. ResultsIn total, 14 sets of pCTV images were generated and compared with cCTV images. The overall image quality and venous visibility scores of pCTV images were significantly higher than those of cCTV images (all values of p<0.05), especially for the dural sinus (median [25th, 75th percentiles], 14.00 [13.63, 15.50] vs. 7.50 [7.00, 10.88]), and superficial vein (9.00 [8.88, 10.00] vs. 3.25 [1.63, 8.25]), while the difference in arterial mis-segmentation was not statistically significant (p= 0.164). ConclusionsThis study proposed an automatic cerebral CTV imaging technique to eliminate residual bone and soft tissues, minimize the impact of the cerebral arterial system, and present a relatively comprehensive cerebral venous system, which would help physicians assess cerebral venous outflow profiles after stroke and seek imaging markers associated with clinical outcomes.