Contrast-enhanced ultrasound evaluation of renal perfusion before angioplasty and its predictive value for hypertension

Author:

Ran Xu11,Niu Guo-Chen21,Shao Yu-Hong1,Fan Fang-Fang3,Yang Min2,Lin Le-Tao4,Chen Lu-Zeng1,Zou Ying-Hua2

Affiliation:

1. Department of Ultrasound Medicine, Peking University First Hospital, Beijing, China

2. Department of Interventional Radiology and Vascular Surgery, Peking University First Hospital, Beijing, China

3. Department of Cardiology, Peking University First Hospital, Beijing, China

4. Minimally Invasive Interventional Division, Department of Medical Imaging and Interventional Radiology, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China

Abstract

BACKGROUND: Atherosclerotic renal artery stenosis (ARAS) is a common disease in the elderly population. OBJECTIVE: The aim was to develop a contrast-enhanced ultrasound (CEUS)-based model for predicting post-angioplasty improvement in hypertension in patients with severe ARAS. METHODS: Thirty-five patients with severe ARAS (⩾ 70%) were included in this study, and 42 renal arteries received percutaneous transluminal renal arterial stenting. An optimal integral formula was developed from pre-interventional color-coded duplex sonography (CCDS) and CEUS parameters using least absolute shrinkage and selection operator (LASSO) regression and receiver operating characteristic (ROC) curve analysis. A model for predicting short-term hypertension improvement was established using the integral formula and clinical risk factors. Bootstrapping was used for internal validation. RESULTS: Two integral formulas, LASSO.CCDS and LASSO.CEUS, were established. ROC curves of the two integral formulas showed that LASSO.CEUS was the better formula for predicting hypertension improvement (AUC 0.816, specificity 78.6%). Univariate and multivariate regression analyses showed that duration of hypertension (OR 0.841, P= 0.027), diabetes (OR = 0.019, P= 0.010), and LASSO.CEUS (OR 7.641, P= 0.052) were predictors of short-term hypertension improvement after interventional therapy. Using LASSO.CEUS combined with clinical risk factors, the following prediction model was established: logit (short-term improvement in hypertension) = 1.879–0.173 × hypertension duration – 3.961 × diabetes + 2.034 × LASSO.CEUS (AUC 0.939). CONCLUSIONS: The model established using CEUS parameters and clinical risk factors could predict hypertension improvement after interventional therapy, but further research and verification are needed.

Publisher

IOS Press

Subject

Health Informatics,Biomedical Engineering,Information Systems,Biomaterials,Bioengineering,Biophysics

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