Medical Scientist Training Program, University of California, San Diego, La Jolla, California.
Department of Medicine, University of California, San Diego, La Jolla, California.
Magn Reson Med. 2018 Aug;80(2):748-755. doi: 10.1002/mrm.27159. Epub 2018 Mar 7.
To develop a rapid segmentation-free method to visualize and compute wall shear stress (WSS) throughout the aorta using 4D Flow MRI data. WSS is the drag force-per-area the vessel endothelium exerts on luminal blood; abnormal levels of WSS are associated with cardiovascular pathologies. Previous methods for computing WSS are bottlenecked by labor-intensive manual segmentation of vessel boundaries. A rapid automated segmentation-free method for computing WSS is presented.
Shear stress is the dot-product of the viscous stress tensor and the inward normal vector. The inward normal vectors are approximated as the gradient of fluid speed at every voxel. Subsequently, a 4D map of shear stress is computed as the partial derivatives of velocity with respect to the inward normal vectors. We highlight the shear stress near the wall by fusing visualization with edge-emphasized anatomical data.
As a proof-of-concept, four cases with aortic pathologies are presented. Visualization allows for rapid localization of pathologic WSS. Subsequent analysis of these pathological regions enables quantification of WSS. Average WSS during peak systole measures approximately 50-60 cPa in nonpathological regions of the aorta and is elevated in regions of stenosis, coarctation, and dissection. WSS is reduced in regions of aneurysm.
A volumetric technique for calculation and visualization of WSS from 4D Flow MRI data is presented. Traditional labor-intensive methods for WSS rely on explicit manual segmentation of vessel boundaries before visualization. This automated volumetric strategy for visualization and quantification of WSS may facilitate its clinical translation.
开发一种快速、无需分割的方法，利用 4D Flow MRI 数据可视化并计算整个主动脉的壁面切应力（WSS）。WSS 是血管内皮对管腔血流施加的单位面积曳力；异常的 WSS 水平与心血管病理有关。之前计算 WSS 的方法受到血管边界手动分割的限制。提出了一种快速、自动的无需分割的计算 WSS 的方法。
剪切应力是粘性应力张量与向内法向量的点积。向内法向量近似为每个体素处的流体速度梯度。随后，作为速度相对于向内法向量的偏导数，计算剪切应力的 4D 图。通过融合可视化与边缘增强的解剖数据，突出显示靠近壁面的剪切应力。
作为概念验证，展示了四个主动脉病变的病例。可视化允许快速定位病理性 WSS。对这些病变区域的后续分析可量化 WSS。在主动脉的非病变区域，峰值收缩期的平均 WSS 约为 50-60 cPa，在狭窄、缩窄和夹层区域升高，在动脉瘤区域降低。
提出了一种从 4D Flow MRI 数据计算和可视化 WSS 的容积技术。传统的 WSS 费力方法依赖于在可视化之前对血管边界进行明确的手动分割。这种用于可视化和量化 WSS 的自动容积策略可能有助于其临床转化。
