Abstract
The research objective is to develop and validate a noninvasive method to quantify trans-stenotic pressure gradient in aortorenal system through image-based computational hemodynamics (ICH) for supporting clinical decision of stenting therapy. Renal artery stenosis (RAS) causes renovascular hypertension but the true severity of RAS is hard to be determined thus effective stenting therapy cannot be well planned. We hypothesize that the trans-stenotic pressure gradient truly reflects the severity of RAS. Recently, ICH has merged as a unique tool, using clinical CT and Doppler images as well as the 3-element WindKessel model. As schematized in Fig. 1(a), ICH noninvasively quantify the live hemodynamics, e.g. pressure in Fig. 1(b), in human vessels. One challenge in ICH is to introduce the appropriate values of proximal resistance (r), distal resistance (R), and compliance (C). We have developed a comprehensive algorithm to determine these values by comparing the computational flow-rates at the exits of aortic artery (AA), left renal (LR), and right renal (RR) arteries with the corresponding flow-rates from Doppler images. The image data of the study case consist of CT data, Doppler images at the juxtarenal AA, LR and RR arteries, and invasive pressure measurement at the corresponding arteries from pressure wire transducers. The r, R, and C values determined through the Doppler images are shown in Fig. 19(c). The three non-invasively computed pressure waves are in good agreements with the invasively measured pressure waves (Fig. 1(d)). The validated ICH is a practical tool to noninvasively measure pressure gradients so that physicians can make better decision at treatment of RAS.
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