Department: Bioengineering
Faculty Advisor(s): Robert Sah
Award(s): Honorable Mention

Primary Student
Name: Elaine F Chan
Email: efchan@ucsd.edu
Phone: 858-822-4788
Grad Year: 2012

Introduction: The shape of the proximal femur is afflicted by a number of developmental disorders, including slipped capital femoral epiphysis (SCFE) and Legg-Calvé-Perthes (LCPD). While radiographs and metrics provide indices for disease diagnosis, alterations in 3-D geometry are complex and challenging to characterize and quantify. The hypothesis of this study was that the variation in proximal femoral shape with SCFE and LCPD can be distinguished from asymptomatic normal hips by 3-D statistical shape modeling (SSM), and that statistical shape parameters are correlated with conventional parameters of proximal femoral shape. Methods: With IRB approval, pelvic CT scans of 32 patients (age 13.0±2.6 years, range 7.0 to 18.2 years) with a range of hip symptoms and diagnoses were obtained. Left and right hips were classified, based on clinical parameters and CT assessment by a pediatric orthopaedic surgeon, as asymptomatic (n=27), LCPD cam impingement (3) or cam+pincer impingement (3), SCFE mild (10), moderate (7), or severe (4) slip, with others not analyzed further (10). Cortical bone surfaces of the proximal femurs were segmented from CT scans and exported as point clouds. The SSM was constructed using 29 initial training shapes, with principal component analysis to identify the mean shape and the modes of variation that cumulatively accounted for >90% of the variance in femur shape. Results: The SSM modes delineated key variations in 3D proximal femoral shape that can occur during skeletal development, and distinguished between LCPD and SCFE at characteristic sites. Displacement and strain maps illustrated major differences compared to asymptomatic hips in LCPD at the superior head and neck regions, and in SCFE at the superolateral neck, posterior head, and greater trochanter regions. Significance: Quantification of 3-D joint shape facilitates evaluation, provides insight into etiology and pathogenesis, and will be useful in management and prognosis of skeletal diseases.

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