Combined Shape Model of the Lower Limb in a Pediatric Population Provides Accurate Bone Shape Estimation

This study aimed to address the limitations of using adult-based musculoskeletal models for children by developing a population-based atlas of lower limb bone shapes in a typically developed pediatric population. The researchers obtained post-mortem CT scans of 324 children aged 4 to 18 years and segmented the pelvis, femura, and tibiae/fibulae. Non-rigid registration and template fitting techniques were used to establish nodal correspondence and alignment with a selected neutral pose. A shape model was then created using principal component analysis. The results revealed that the first three principal components captured the majority of variation in the dataset, describing both size and shape variation as well as the aspect ratio of the long bones. The predictive power of the shape model was assessed using a leave one out analysis, and it demonstrated an average root mean square error of 4.9 ± 1.4 mm. This novel dataset provides valuable insights into the morphological variation of lower limb bones in a pediatric population. It enables the prediction of new bone shapes with lower errors compared to conventional scaling methods, offering potential applications in clinical settings and musculoskeletal modeling. This study contributes to the development of more accurate and precise musculoskeletal models for children, addressing the need for pediatric-specific considerations in clinical practice and research.