Intra- and inter-observer reproducibility of volume measurement of knee cartilage segmented from the OAI MR image set using a novel semi-automated segmentation method

Objective: We developed a semi-automated method based on a graph-cuts algorithm for segmentation and volumetric measurements of the cartilage from high-resolution knee magnetic resonance (MR) images from the Osteoarthritis Initiative (OAI) database and assessed the intra- and inter-observer reproducibility of measurements obtained via this method. Design: MR image sets from 20 subjects of varying Kellgren-Lawrence (KL) grades (from 0 to IV) on fixed flexion knee radiographs were selected from the baseline double-echo and steady-state (DESS) knee MR images in the OAI database (0.B.1 Imaging Data set). Two trained radiologists independently performed the segmentation of knee cartilage twice using the semi-automated method. The volumes of segmented cartilage were computed and compared. The intra- and inter-observer reproducibility were determined by means of the coefficient of variation (CV%) of repeated cartilage segmented volume measurements. The subjects were also divided into the low- (0, I or II) and high-KL (III or IV) groups. The differences in cartilage volume measurements and CV% within and between the observers were tested with t tests. Results: The mean (±SD) intra-observer CV% for the 20 cases was 1.29 (±1.05)% for observer 1 and 1.67 (±1.14)% for observer 2, while the mean (±SD) inter-observer CV% was 1.31 (±1.26)% for session 1 and 1.79 (±1.72)% for session 2. There was no significant difference between the two intra-observer CV%'s (P = 0.272) and between the two inter-observer CV%'s (P = 0.353). The mean intra-observer CV% of the low-KL group was significantly smaller than that for the high-KL group for observer 1 (0.83 vs 1.86%: P = 0.025). The segmentation processing times used by the two observers were significantly different (observer 1 vs 2): (mean 49 ± 12 vs 33 ± 6 min) for session 1 and (49 ± 8 vs 32 ± 8 min) for session 2. Conclusion: The semi-automated graph-cuts method allowed us to segment and measure cartilage from high-resolution 3 T MR images of the knee with high intra- and inter-observer reproducibility in subjects with varying severity of OA.