Abstract
Objectives:
Osteoarthritis (OA) is a heterogeneous disease characterized by progressive cartilage loss, subchondral bone remodeling, osteophyte formation, and synovial inflammation which can lead to joint pain and disability and affects an estimated 250 million people worldwide. Osteoarthritic degeneration of the joint following an acute injury, such as an articular fracture, chondral injury, or ligament or meniscal tear is termed post-traumatic OA (PTOA). Despite treatment, between 23-50% of individuals who suffer a knee joint trauma eventually develop PTOA and the factors which may indicate PTOA progression are not well understood. Previous studies have explored shape changes in the tibiofemoral joint following ACL reconstruction (ACLR), which may serve as an indicator of PTOA progression; however, there is relatively little reporting of similar data for the patellofemoral joint. The purpose of this study was to investigate patella bone shape as an early indicator for PTOA using longitudinal changes and associations with injury, sex, KOOS, and cartilage T1rho values.
Methods:
Bilateral knee MRIs from 86 patients (48 males, age: 29.5 ± 9.8 years, BMI: 24.6 ± 2.3 kg/m2, 38 females, age: 26.1 ± 10.4 years, BMI: 23.6 ± 3.2 kg/m2) who suffered a single complete ACL injury and 15 controls (9 males, age: 30.2 ± 4 years, BMI: 24.8 ± 2 kg/m2, 6 females, age: 33.4 ± 5.6 years, BMI: 22.6 ± 2.3 kg/m2) were collected as part of an IRB-approved multisite study using 3-T fat saturated CUBE sequences. Patient MRIs were acquired prior to ACLR (baseline) and 6 months and 12 months following ACLR while control MRIs were collected twice, 12 months apart. In addition, KOOS and patella cartilage T1rho relaxation times were obtained for all subjects. A two-stage deep learning process (global and local 2D U-Net models) was used to automatically segment the patellae of each subject at each time point (Figure 1a). The automated segmentations of all 576 patellae were manually inspected and corrected as needed and then used to generate smoothed 3D surface reconstructions (Figure 1b). Next, a minimum deformation template was deformably registered to each patella surface and the subchondral region of the bone was isolated by finding the area of overlap between the template and its patella cartilage segmentation (Figure 1c). The subchondral regions of the patellae were separated to account for substantial morphological alterations to the anterior and inferior surfaces caused by ACLR, particularly for bone-patella tendon-bone grafts. Finally, a generalized Procrustes analysis produced size invariant point distributions from the registered surfaces and a statistical shape model of the subchondral region was created using a principal components analysis (PCA). The first 16 shape modes, which explained approximately 95% of the variance in the data, were retained for further analysis and their PC scores were calculated. One control subject was missing baseline height data and two were missing baseline weight, so these data were imputed by linear regression. Mixed effects models were used to investigate differences across ipsilateral, contralateral, and control patella shapes, sex differences, longitudinal shape changes, and associations with changes in KOOS and ipsilateral T1rho values from baseline to 12 months following ACLR. An overall significance cutoff of p ≤ 0.0011 was determined using false discovery rate control set at 5%.
Results:
At baseline, significant (p ≤ 0.0011) differences between ipsilateral, contralateral and control patella shapes were found for mode 1 (Figure 2a), while significant (p ≤ 0.0011) sexual dimorphisms were observed for ipsilateral and contralateral modes 1 (Figure 2b) and 5 (Figure 2 c). No significant longitudinal changes were found for ipsilateral, contralateral, or control patella shapes. Changes in KOOS pain were found to be significantly (p ≤ 0.0011) associated with baseline, ipsilateral shape mode 10 scores (Figure 3); however, no significant associations with T1rho were observed.
Conclusions:
Shape mode 1, which accounted for approximately 24% of the total patella shape variation, was found to be predictive of knee injury status (ipsilateral/contralateral vs. control) and sex. Figures 2a-b and 4a-c show that taller, narrower patellae are correlated with ACL injury and are more indicative of females in ACL-injured subjects. Shape mode 5 represented 7.5% of the patella shape variability and showed that ACL-injured females have more prominent vertical ridges than their male counterparts (Figure 2c, Figure 4d-f). Shape mode 10 corresponded to 2.6% of the patella shape variation and described changes to the geometry of the medial facet and lateral margin (Figure 4g-i). These changes were found to be negatively associated with differences in KOOS pain scores between baseline and 1-year follow-ups, suggesting a potential link between patella shape and patient-reported outcomes following ACLR.
Overall, these results suggest that patella shape may influence ACL injury and patient-reported outcomes after ACLR. While no significant longitudinal changes that would directly indicate PTOA development were found, several time-related trends in patella shape were observed that may prove significant with a longer follow-up time. Further studies will be needed to confirm these results and to determine the biomechanical connection between patella shape, ACL injury, and PTOA.
