Does WSSNet improve the accuracy of aortic wall shear stress estimation from 4D Flow MRI compared to existing parabolic fitting methods?
WSSNet provides a more accurate, deep learning-based method for estimating spatiotemporal aortic wall shear stress from 4D Flow MRI compared to traditional parabolic fitting.
4D Flow MRI cases, effectively estimating WSS from standard clinical images. Compared with the existing parabolic fitting method, WSSNet estimates showed 2-3 × higher values, closer to CFD, and a Pearson correlation of 0.68 ± 0.12. This approach, considering both geometric and velocity information from the image, is capable of estimating spatiotemporal WSS with varying image resolution, and is more accurate than existing methods while still preserving the correct WSS pattern distribution.
Ferdian et al. (Mon,) studied this question.