Abstract
Purpose: Understanding of calcified cartilage morphology could provide new cues on osteoarthritis development. However, since calcified cartilage and subchondral bone share similar X-ray attenuation properties their separation from micro-computed tomography (micro-CT) images remains challenging. This study aimed at developing and validating a novel method for the segmentation and thickness analysis of calcified cartilage (CC) using micro-CT. Methods: To facilitate high-resolution micro-CT imaging, eight healthy knees from skeletally mature rabbits (N = 8) were dissected to six smaller osteochondral samples, i.e. lateral and medial femoral condyles, femoral groove, lateral and medial tibial plateau as well as patella (in total n = 48 samples). The samples were imaged with micro-CT device (isotropic voxel size: 3.2 μm). After imaging, the samples were decalcified and embedded in paraffin. Three histology sections (∼5 μm thickness) were stained with Goldner’s trichrome from each sample. Preprocessing for CC segmentation: The micro-CT data were reconstructed into two image stacks with: 1) standard and 2) mineral windows, respectively. The standard window (SW) image stack contained information from a wide attenuation coefficient range, while the mineral window (MW) image stack contained information from a narrow attenuation coefficient range providing a high contrast between CC and bone. Both stacks were co-registered. Trabecular bone volume-of-interest (VOItrab) was obtained from the SW stack with manual segmentation. VOItrab was subtracted from the SW stack. The output stack was inverted and refined with a shrink-wrap operation. This generated a subchondral plate VOI (VOIplate) including both subchondral bone and CC. CC segmentation: The region defined by VOIplate was selected from the MW stack and a narrow, high threshold window was applied to select only subchondral bone. Subsequently, the selected subchondral bone was subtracted from the VOIplate region to produce the CC segmentation. Finally, morphological opening operations were used for eliminating the edge artifact for more realistic estimation of CC thickness (CC.Th). CC thickness analysis: First, 2D analysis both from micro-CT and histology was conducted to validate the micro-CT-based CC.Th analysis. The CC.Th obtained from micro-CT (as an average of five slices) was compared with the CC.Th from histology sections using ImageJ (BoneJ plugin). Then, CC.Th was analyzed in 3D using a sphere-based method utilizing a distance transformation. Statistics: Normality of the CC.Th data were first ensured (Shapiro-Wilk test). The agreement between the 2D micro-CT and histology analysis was evaluated with a Bland-Altman plot. One-way ANOVA test (post-hoc test: Newman-Keuls) was used for comparing the CC.Th between different locations. The level of significance was set to 0.05. Results: CC.Th in 2D had a good agreement between histology and micro-CT (Figure 1A to 1C, bias: -8.6 μm, levels of agreement: [-71.3, 54.1] μm). In the 2D histology analysis (Figure 1D), the patella had the thickest CC, while the thinnest locations were found for the tibial plateau and medial femoral condyle. Interestingly, in all 2D and 3D analyses (Figure 1E and 1F) CC was always thicker in the patella compared to the femoral groove and tibial plateau. Furthermore, CC in the lateral femoral condyle was always thicker than in the medial tibial plateau. Conclusions: In this study, we presented and validated a novel method for the thickness analysis of CC from micro-CT images. In addition, we observed different CC.Th. between anatomical locations with both histology and micro-CT. The different CC.Th. between anatomical locations is most likely related with local loading conditions.In the future, this method can be used for assessing the potential changes of CC.Th. for different joint pathologies, such as osteoarthritis.
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