A three-dimensional statistical shape model to describe clinical shape variation of the proximal femur in patients with legg-calvé-perthes disease deformity

Legg-Calvé-Perthes Disease (LCPD) is a pediatric hip condition that affects approximately 1 in 10,000 children. In LCPD the femoral head is deformed by osteonecrosis, often resulting in a permanent residual hip deformity. Residual LCPD is associated with at least a 20 times greater risk of early-onset OA in affected hips, even in patients with only mild radiographic deformity. Current routine assessment using 2D radiographic imaging does not adequately describe the complex 3D pathomorphology of LCPD. Statistical shape modeling (SSM) provides an objective and compact description of 3D shape variability, which may be used to better describe patient specific LCPD deformity and identify which features lead to early OA. 1) Construct and evaluate a compact and accurate shape model of LCPDs pathomorphology using open-source SSM software. 2) Examine the relationship between 3D LCPD pathomorphology and corresponding clinical radiographic measurements. MR images (N=13 hips, 11 patients, 3 F/8 M) of affected hips were obtained in a previous study from patients with LCPD (age range: 6-12 years, stage II-IV). Imaging was performed using a GE 1.5T HDxt scanner (Waukesha, WI) with a coronal 3D FSPGR sequence: TR=8.9 ms, TE 2.8ms, flip angle 10°, 1.0mm slice thickness, 288 × 288 matrix. For this study, MR volumes were resampled isotropically to the smallest voxel dimension (.47 - .63 mm), and two raters manually segmented the proximal femurs. The ShapeWorks SSM software (SCI Institute, University of Utah, Salt Lake City, UT) was used to produce an SSM with 512 particles using an incremental optimization routine. Shapes were aligned and scaled with generalized Procrustes analysis. Modes of shape variation were quantified using principal component analysis. The SSM's generalizability to unfamiliar shapes was evaluated with a leave-one-out cross-validation analysis. The relationship between neck-shaft angle, articulo-trochanteric distance and femoral head asphericity with principal component scores was examined with Spearman's rank correlation coefficient (ρ). The first four shape modes, describing 87.5% of the population variability, were selected to form a compact shape model. With these modes, the generalizability (point-to-point reconstruction error) was <1 mm. Notable associations were observed between mode IV and femoral head asphericity (ρ = 0.79), modes II and IV with neck-shaft angle (ρ = -0.43, 0.63 respectively), and modes I and II with articulo-trochanteric distance (ρ = 0.58, -0.63 respectively). This SSM provides a compact and accurate representation of 3D shape variation in LCPD. Limitations to this model include a small sample size, but nonetheless it generalizes well to unfamiliar LCPD examples. The robust and repeatable methodology will allow the model to be supplemented with additional shapes in future. With this SSM, we aim to evaluate how well clinical metrics based on 2D projections of anatomy can represent the anatomical changes that may lead to OA, and to determine why some patients with little to no radiographic deformity still develop early-onset OA. Canadian Institutes of Health Research, Funding reference #165956 L.G. Johnson is supported by Arthritis Society Canada. CORRESPONDENCE ADDRESS: [email protected]