Features extraction of cerebral vascular perfusion based on DSA dynamic imaging

Objective: To extract the cerebral perfusion characteristics from the DSA images. Methods: A retrospective analysis was made on the 11 cases of stoke with the cerebral vascular interventional surgery. The middle cerebral artery and carotid artery DSA data were obtained, and the time-gray scale curve of the ROI was extracted by using the software platform. And then the curve was analyzed to obtain characteristic parameters, including time-to-peak (TTP), before-peak-curvilinear integral (PCI), curve-fitting-slope (CFS) and the ratio of the minimum and maximum (MIN/MAX). These characteristic parameters were analyzed statistically. Results: In the carotid artery, the postoperative PCI, CFS and MIN/MAX were significantly lower than those of the pre-operation (all P<0.05), while the postoperative TTP was higher than that of the pre-operation, but there was no statistical difference. In the middle cerebral artery, the postoperative PCI, CFS and MIN/MAX were significantly lower than those of the pre-operation (all P<0.05), while the postoperative TTP was significantly higher than that of the pre-operation (P<0.05). Conclusion: The TTP and CFS extracted from DSA dynamic imaging can represent the blood flow velocity of the cerebral vascular; the MIN/MAX may predict the vibration level; the PCI can be used to predict the hyperperfusion syndrome. The four parameters can be used to evaluate the cerebral perfusion status.