Renal Microvessel Imaging for Characterization of Chronic Kidney Disease

PROJECT SUMMARY Chronic kidney disease (CKD) is estimated to affect 30 million Americans and incur healthcare cost of $30.9 billion every year. There is an urgent need of a safe and noninvasive clinical tool for accurate staging of CKD, which is essential for its management. The importance of renal parenchyma perfusion and vasculature morphology for CKD characterization has been documented by many studies, but is not used clinically due to lack of translatable imaging solutions. In this project, we will use a novel super-resolution ultrasound imaging (SRUI) technology, which can resolve 50-micron renal cortex microvessels and measure their blood flow speed in human, to quantify cortex microvessel morphology and perfusion for accurate CKD characterization. Aim 1: Technical development. New acquisition and processing methods will be developed to enhance performance of SRUI through phantom and patient experiments. Novel quantitative parameters of SRUI for renal cortex will be developed, which includes vessel density, diameter, and tortuosity, as well as mean blood flow velocity, micro- Resistive Index of arterioles and venules, and perfusion index. Aim 2: Animal validations. We will study 7 normal pigs and 14 CKD pigs with renal artery stenosis (RAS) to validate SRUI measurements using independent measurements obtained through contrast enhanced CT, micro-CT, and histology. Aim 3: Clinical study. We will study 50 healthy volunteers to establish the normal range of SRUI parameters and study 116 CKD patients with clinically indicated renal biopsy to investigate the efficacy of SRUI for CKD staging, using biopsy histology as the reference standard. Statistical difference between CKD patients and healthy controls and differences across CKD stages defined by histology will be evaluated. The association of each ultrasound parameter with histology CKD score will be assessed. Univariate and multivariate logistic regression and ROC analyses (receiver operating characteristic) analyses will be performed to assess the performance of SRUI, conventional ultrasound (renal length, cortex thickness, Doppler renal resistive index, and shear wave elastography), and clinical parameters (eGFR and proteinuria) for distinguishing histology CKD stages. A subset (N=45) of patients will be scanned by two sonographers randomly selected from a pool of five sonographers. Intraclass correlation coefficients will be used to evaluate the inter-sonographer agreement. The inter-sonographer variance will be calculated to estimate the minimum detectable difference for longitudinal follow-ups. Successful completion of this project will result in a safe, noninvasive, cost-effective, and accessible ultrasound technology for accurate characterization of chronic kidney disease to guide treatment decision making.