Following renal transplantation, about 30-40% of patients suffer at least one episode of acute graft dysfunction. Treatment is radically different depending on the cause of renal dysfunction, which may include acute tubular necrosis (ATN), acute and chronic rejection (AR/CR) and drug toxicity. The definitive diagnosis of renal transplant dysfunction is based on percutaneous biopsy, which is invasive and difficult to repeat. Magnetic resonance imaging (MRI) provides an accurate assessment of allograft anatomy, as well as of vascular or obstructive disorders. In addition, functional MRI can provide insight into renal function using dynamic contrast-enhanced MRI (DCE-MRI, using low dose gadolinium contrast agent, which estimates renal perfusion and flow), intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI, which provides information on flow and diffusion), arterial spin labeling (ASL, which quantifies renal flow without a contrast agent), and blood oxygen level dependent imaging (BOLD, which reflects oxygen bioavailability). Although functional MRI is non-invasive, it has not yet emerged as a ?virtual biopsy? because of the small number of validation studies, each generally focusing on a single MRI technique. Multiparametric MRI has the unique potential to identify intrinsic causes of renal transplant dysfunction.
Specific Aim 1 : Develop a quality control (QC) framework to evaluate a quantitative multiparametric MRI protocol including IVIM diffusion, DCE-MRI perfusion, ASL, and BOLD in renal transplant patients. Hypothesis: a QC framework will improve data quality and reproducibility of MRI metrics measured in renal allografts. We will build a QC and image optimization algorithm for renal functional MRI, and we will test it in 16 patients with renal transplant.
Specific Aim 2 : Quantify MRI parameters in renal transplant patients with normal and abnormal renal function, and assess the value of MRI parameters alone and in combination for characterizing renal dysfunction using clinical parameters and/or pathology as the reference. Hypothesis: Renal graft dysfunction can be diagnosed and characterized by a combination of biomarkers measurable by functional MRI. Renal diffusion and perfusion, as measured by IVIM parameters, renal plasma flow (RPF) measured by DCE and ASL, medullar and medullar-to-cortical ratio of the transverse relaxation time R2* (as measured by BOLD techniques) will decrease, while mean transit time (MTT) of the contrast agent through the renal tubules as measured by DCE-MRI, will increase in dysfunctional allografts compared to normally functional allografts. Furthermore, dysfunctional allografts with ATN can be distinguished from those without ATN by longer mean transit time in the renal tubules, as computed by the three-compartment model from DCE-MRI data, and by a higher ratio of medullar to cortical R2*. We will test this hypothesis in 97 renal transplant recipients with functional and dysfunctional allografts, as clinically indicated by laboratory tests and biopsy.

Public Health Relevance

Differential diagnosis of the causes of renal allograft dysfunction, including acute tubular necrosis, acute and chronic rejection, or drug toxicity, requires percutaneous biopsy, which is invasive and difficult to repeat. Our project seeks to develop and validate a non-invasive, multiparametric magnetic resonance imaging (MRI) protocol for differential diagnosis of the etiologies of renal allograft dysfunction.

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Postdoctoral Individual National Research Service Award (F32)
Project #
5F32DK109591-02
Application #
9414913
Study Section
Special Emphasis Panel (ZDK1)
Program Officer
Rankin, Tracy L
Project Start
2016-12-01
Project End
2018-11-30
Budget Start
2017-12-01
Budget End
2018-11-30
Support Year
2
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Icahn School of Medicine at Mount Sinai
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
078861598
City
New York
State
NY
Country
United States
Zip Code
10029