Segmentation of individual renal cysts from MR images in patients with autosomal dominant polycystic kidney disease

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).This semi-automated method was based on a morphologic watershed technique with shape-detection level set for segmentation of renal cysts from MR images. T2-weighted MR image sets of 40 kidneys were selected from 20 patients with mild to moderate renal cyst burden (kidney volume1500 ml) in the Consortium for 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.Individual renal cysts were successfully segmented with the semi-automated method in all 20 cases. The total number of cysts in each kidney measured with the two methods correlated well (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 of10% (9.0% decrease in the semi-automated method; limits of agreement, 17.1% increase to 43.3% decrease).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.