The Cerebral Imaging using Vessel-Around Method in the Perfusion CT of the Human Brain

摘要

Perfusion CT has been successfully used as a functional imaging technique for diagnosis of patients with hyperacute stroke. However, the commonly used methods based on curve-fitting are time consuming. Numerous researchers have investigated to what extent Perfusion CT can be used for the quantitative assessment of cerebral ischemia and to rapidly obtain comprehensive information regarding the extent of ischemic damage in acute stroke patients. The aim of this study is to propose an alternative approach to rapidly obtain the brain perfusion mapping and to show the proposed cerebral flow imaging of the vessel and tissue in human brain be reliable and useful. Our main design concern was algorithmic speed, robustness and automation in order to allow its potential use in the emergency situation of acute stroke. To obtain a more effective mapping, we analyzed the signal characteristics of Perfusion CT and defined the vessel-around model which includes the vessel and tissue. We proposed a nonparametric vessel-around approach which automatically discriminates the vessel and tissue around vessel from non-interested brain matter stratifying the level of maximum enhancement of pixel-based TAC. The stratification of pixel-based TAC was executed using the mean and standard deviation of the signal intensity of each pixel and mapped to the cerebral flow imaging. The defined vesselaround model was used to show the cerebral flow imaging and to specify the area of markedly reduced perfusion with loss of function of still viable neurons.