Objective To evaluate the performance of a semi-automated method for the segmentation of individual renal cysts from magnetic resonance (MR) images in patients with autosomal dominant polycystic kidney disease (ADPKD). Design, setting, participants, & measurements This semi-automated method was based on a morphologic watershed techniquewith shape-detection level set for segmentation of renal cysts fromMR images. T2-weighted MR image sets of 40 kidneys were selected from 20 patients with mild to moderate renal cyst burden (kidney volume, 1500 ml) in the Consortiumfor Radiologic Imaging Studies of Polycystic Kidney Disease (CRISP). The performance of the semi-automated method was assessed in terms of two reference metrics in each kidney: the total number of cysts measured by manual counting and the total volume of cysts measured with a region-based thresholding method. The proposed and reference measurements were compared using intraclass correlation coefficient (ICC) and Bland-Altman analysis. Results Individual renal cysts were successfully segmented with the semi-automated method in all 20 cases. The total number of cysts in each kidney measuredwith the two methods correlatedwell (ICC, 0.99),with a very small relative bias (0.3% increase with the semi-automated method; limits of agreement, 15.2% reduction to 17.2% increase). The total volume of cysts measured using both methods also correlated well (ICC, 1.00), with a small relative bias of,10%(9.0%decrease in the semi-automatedmethod; limits of agreement, 17.1%increase to 43.3% decrease). Conclusion This semi-automated method to segment individual renal cysts in ADPKD kidneys provides a quantitative indicator of severity in early and moderate stages of the disease.
|Original language||English (US)|
|Number of pages||9|
|Journal||Clinical Journal of the American Society of Nephrology|
|State||Published - Jul 2013|
ASJC Scopus subject areas
- Critical Care and Intensive Care Medicine