Abstract
Objectives: Osteochondral allograft transplantation (OCA) for cartilage defects provides excellent long-term clinical outcomes. Articular step-off between the donor and recipient has been shown to significantly alter contact pressures, potentially contributing to worse long-term survival. The trochlea in particular is at risk for graft mismatch due to the complexity and variability of trochlear anatomy. Currently, commercial allograft donor selection is primarily based on simple anatomical parameters such as trochlear length, trochlear width, and tibial width. However, there is limited guidance in literature on factors which best predict an adequate match, as defined by ≤1.0 mm articular step-off. We hypothesize that more complex anatomic parameters which better describe trochlear morphology, including sulcus angle, sagittal angle, and radius of curvature, may help optimize donor selection to reduce articular step off for trochlear osteochondral allograft transplantation. Methods: Ten deidentified, cadaveric trochlear specimens were utilized for this study (JRF Ortho, Denver, CO). Computed tomography (CT) images of the specimens were obtained, and three-dimensional (3D) point cloud models of the trochleae were then created and exported using a medical segmentation software program (Mimics, Materialise Inc., Leuven, Belgium). Circular defect models were created virtually in each point-cloud model of the recipient trochlea at both supero-lateral (18 mm and 22.5 mm) and central (18 mm, 22.5 mm, 30 mm) locations (Figure 1A). Circular graft models were created on all possible locations on the articular cartilage surface models of the donor trochleae. The graft models were virtually placed on the defect models, and a mean value of the minimum distances between the graft and recipient surfaces was calculated for each position of the graft model. This was repeated for all points in the articular surface model of the donor patella and the best possible match was identified. Step-off was calculated as the least mean square difference between the defect and graft along the periphery. Ideal match was defined as ≤0.5 mm articular step-off, and an acceptable match was defined as ≤1.0 mm articular step-off. Demographic and anatomic factors measured include age, sex, laterality, lateral facet width, medial facet width, lateral condyle radius of curvature, trochlear groove radius of curvature, trochlear length, and trochlear width. Sulcus angle and sagittal angle at the center of the defect and grafts for the central trochlear location were calculated by a custom-designed program (Figure 1B). Tibial width for each specimen was provided by the tissue bank. Differences between the donor and recipient trochleae were calculated for each factor and the absolute value of the difference was utilized for analysis. Pearson correlation ( r) or Spearman rank correlation (ρ) were calculated for continuous or categorical variables, respectively. Linear regression multivariate analysis for was performed with significant univariate predictors. Statistical analysis was performed in STATAv16.1 (Statacorp, Houston TX) and RStudio (software version 4.1.0, R Foundation for Statistical Computing, Vienna, Austria). Results: Ideal graft matches were identified in all superolateral trochlear defects, while central defects had a decreasing frequency of ideal matches with increasing defect size (18 mm: 53.4%, 22.5 mm: 35.21%, 30 mm: 14.8%) (Table 1). Univariate predictors of articular step-off are presented in Table 2. On multivariate analysis, sulcus angle difference (β=0.019, p=0.002), sagittal angle difference (β=0.018, p=0.001), and lateral condyle radius of curvature (β=0.015, p=0.003) remained significant predictors of articular step-off for 18 mm central defects (R2=0.45). For 22.5 mm central defects, sulcus angle difference (β=0.029, p<0.001), sagittal angle difference (β=0.025, p<.001), medial facet width (β=0.026, p=0.021), and lateral radius of curvature (β=0.013, p=0.025) were significant. Similarly, for 30 mm central defects, sulcus angle difference (β=0.03, p=0.001), lateral radius of curvature (β=.032, p=0.004), and trochlear length (β=0.041, p<0.001), were significant predictors of articular step-off (Figure 2). For 18 mm superolateral defects, medial facet width was the only factor with univariate significance. However, on multivariate analysis considering all factors, no significant predictors were identified. For 22.5 mm superolateral trochlear defects, medial facet width (β=.006, p<0.001) was a significant multivariate predictor of articular step-off. For 22.5 mm superolateral defects, trochlear length (β=.002, p=0.003) was also a significant multivariate predictor. Conclusions: Central trochlear defects of increasing size become more difficult to find ideal and acceptable graft matches for based on articular step-off. Tibial width did not correlate with articular step-off in the setting of a computer-simulated model of osteochondral allograft for central or superolateral trochlear defects. Minimizing mismatch in anatomic factors such as sulcus angle, sagittal angle, lateral condyle radius of curvature, and medial facet width may contribute to a more optimal graft. Limitations of this computer-simulated study include the inability to account for surgeon technique in ultimate graft matching outcome. [Figure: see text][Table: see text][Table: see text][Figure: see text]
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