Background: Autosomal-dominant polycystic kidney disease (ADPKD) is an inherited disorder characterized by renal cyst growth, early development of hypertension, and late occurrence of renal insufficiency. Despite evidence for the importance of nephroangiosclerosis in the progression of renal insufficiency in ADPKD, evaluation of renal blood flow (RBF) as a surrogate marker of disease severity has received little attention.
Methods: Flow phantoms and repeat RBF measurements assessed accuracy and reproducibility. One hundred twenty-seven ADPKD subjects with creatinine clearances >70 mL/min underwent measurements of RBF, total, and cyst renal volumes, and % cyst volumes by magnetic resonance (MR) and of glomerular filtration rate (GFR). Renal vascular resistance (RVR) was calculated. MR blood flow sequences utilized a two-dimensional cine phase-contrast breath-hold pulse sequence perpendicular to the renal arteries. Flow rates were calculated utilizing FLOW software. Volumetric analysis was performed using stereology and region-based thresholding.
Results: Excellent accuracy and intraobserver and interobserver reproducibility were demonstrated. Anatomic (total kidney volume, total cyst volume, and % cyst volume), hemodynamic (RBF and RVR), and functional (GFR) parameters were strongly correlated. Left polycystic kidneys were larger and had more severe disease. Regression analysis showed that age, diagnosis of hypertension, anatomic parameters and hemodynamic parameters were significant predictors of GFR. Multiple linear regression analysis identified age and hemodynamic parameters only as separate predictors of GFR. Anatomic, hemodynamic, and functional parameters discriminated between normotensive and hypertensive subjects despite antihypertensive treatments.
Conclusion: Renal hemodynamic parameters measured by MR correlate with anatomic and functional indices of disease severity, are the strongest predictors of renal function, and deserve further consideration as an outcome measure in clinical trials to guide therapy in ADPKD.