Polycystic kidney disease (PKD) is a common inherited disorder that causes fluid-filled cysts to form in the kidneys, which increases kidney size and can lead to end-stage renal failure requiring dialysis or kidney transplant. An increase in kidney size is a strong predictor of risk for rapid progression of PKD, but other measures are needed for earlier PKD detection and better risk prediction.
Feng Wang, PhD, and colleagues compared multiple MRI parameters for assessing and predicting the severity of PKD over time. They used a 7T MRI system to image a mouse model of PKD at 5, 9 and 26 weeks of age and control mice without PKD. They also collected kidney tissues for histological examination.
The study, reported in Magnetic Resonance in Medicine, identified optimal MRI parameters for estimating the severity of PKD. While imaging parameters for human studies still need to be identified, there is clear potential for translating multiparametric MRI to clinical use for PKD, the authors note.
Co-authors of the study included Seo Yeon Lee, Fatemeh Adelnia, PhD, Keiko Takahashi, Kevin Harkins, PhD, Lilly He, Zhongliang Zu, PhD, Philipp Ellinger, PhD, Manuel Grundmann, PhD, Raymond Harris, MD, Takamune Takahashi, MD, PhD, and John Gore, PhD.
The research was supported by Bayer and Vanderbilt Collaboration and by the National Institutes of Health (grants DK114809, EB024525, OD019993).
