A semi-automated “blanket” method for renal segmentation from non-contrast T1-weighted MR images

Objective: To investigate the precision and accuracy of a new semi-automated method for kidney segmentation from single-breath-hold non-contrast MRI. Materials and methods: The user draws approximate kidney contours on every tenth slice, focusing on separating adjacent organs from the kidney. The program then performs a sequence of fully automatic steps: contour filling, interpolation, non-uniformity correction, sampling of representative parenchyma signal, and 3D binary morphology. Three independent observers applied the method to images of 40 kidneys ranging in volume from 94.6 to 254.5 cm³. Manually constructed reference masks were used to assess accuracy. Results: The volume errors for the three readers were: 4.4 % ± 3.0 %, 2.9 % ± 2.3 %, and 3.1 % ± 2.7 %. The relative discrepancy across readers was 2.5 % ± 2.1 %. The interactive processing time on average was 1.5 min per kidney. Conclusions: Pending further validation, the semi-automated method could be applied for monitoring of renal status using non-contrast MRI.