A new noninvasive and patient‐specific hemodynamic index for the severity of renal stenosis and outcome of interventional treatment. (18th May 2022)

• Record Type: Journal Article
• Authors: Yu, Huidan; Khan, Monsurul; Wu, Hao; Du, Xiaoping; Chen, Rou; Rollins, Dave M.; Fang, Xin; Long, Jianyun; Xu, Chenke; Sawchuk, Alan P.
• Is Part Of: International journal for numerical methods in biomedical engineering. Volume 38:Number 7(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-05-18
• Subjects: image‐based computational hemodynamics -- noninvasive and patient‐specific assessment -- renal arterial stenosis -- uncertainty quantification -- volumetric lattice Boltzmann method; Biomedical engineering -- Periodicals; Imaging systems in medicine -- Periodicals; Numerical analysis -- Periodicals; Engineering mathematics -- Periodicals; 610.28
• DOI: 10.1002/cnm.3611
• Languages: English
• ISSNs: 2040-7939

Abstract

Abstract: Renal arterial stenosis (RAS) often causes renovascular hypertension, which may result in kidney failure and life‐threatening consequences. Direct assessment of the hemodynamic severity of RAS has yet to be addressed. In this work, we present a computational concept to derive a new, noninvasive, and patient‐specific index to assess the hemodynamic severity of RAS and predict the potential benefit to the patient from a stenting therapy. The hemodynamic index is derived from a functional relation between the translesional pressure indicator (TPI) and lumen volume reduction (S) through a parametric deterioration of the RAS. Our in‐house computational platform, InVascular, for image‐based computational hemodynamics is used to compute the TPI at given S . InVascular integrates unified computational modeling for both image processing and computational hemodynamics with graphic processing unit parallel computing technology. The TPI–S curve reveals a pair of thresholds of S indicating mild or severe RAS. The TPI at S = 0 represents the pressure improvement following a successful stenting therapy. Six patient cases with a total of 6 aortic and 12 renal arteries are studied. The computed blood pressure waveforms have good agreements with the in vivo measured ones and the systolic pressure is statistical equivalence to the in‐vivo measurements with p < .001. Uncertainty quantification provides the reliability of the computed pressure through the corresponding 95% confidence interval. The severity assessments of RAS in four cases are consistent with the medical practice. The preliminary results inspire a more sophisticated investigation for real medical insights of the new index. This computational concept can be applied to other arterial stenoses such as iliac stenosis. Such a noninvasive and patient‐specific hemodynamic index has the potential to aid in the clinical decision‐making of interventional treatment with reduced medical cost and patient risks. Abstract : This work presents a computational concept to derive a new, noninvasive, and patient‐specific hemodynamic index to assess the hemodynamic severity of renal arterial stenosis from medical imaging data. The computed blood pressure waveforms have good agreements with the in vivo measured ones and uncertainty quantification provides its reliability through the corresponding 95% confidence interval. The severity assessments of renal stenosis in four cases are consistent with the medical practice. This computational concept can be applied to other arterial stenoses such as iliac stenosis.