Study of Vertebral Artery Dissection by Ultrasound Superb Microvascular Imaging Based on Deep Neural Network Model

To assess the diagnostic value of ultrasound Superb Microvascular Imaging (SMI) and versus Doppler ultrasound (TCD) for microvascular structure and aerodynamic changes in vertebral artery dissection (VAD). In this paper, we firstly simulate the process of clinician recognition of vertebral artery dissection and propose a combination of a priori shape information of vertebral artery dissection and deep folly convolutional networks (DFCNs) for IVUS. In this paper, 15 patients with vertebral artery dissection confirmed by SMI, digital subtraction angiography (DSA), or computed tomography angiography (CTA) from 2020 to 2021 were selected, and the true and false lumen diameters, peak systolic flow velocity (PSV), end-diastolic flow velocity (EDV) and PSV, EDV, and plasticity index (PI) of the intracranial vertebral artery were measured. Among the 15 patients with VAD, 4 (27%, 4/15) had trauma-induced secondary vertebral artery entrapment and 11 (73%, 11/15) had spontaneous entrapment without a clear cause. According to the structural characteristics of the vessels, there were 11 cases (73%, 11/15) of double-lumen, intramural hematoma, and vertebral artery dissection aneurysm, and 11 cases (73%, 11/15) of V1 segment. SMI not only provides an objective assessment of the vascular morphology and aerodynamic changes in VAD but also, in combination with TCD, can further determine the opening of the traffic branches in the posterior circulation, providing reliable information for the early diagnosis and treatment of microvascular dissection of the vertebral artery.