Pediatric hand bone shapes show sex differences and growth patterns
Sexual dimorphism and sex-specific features of pediatric hand bone shapes via statistical shape modeling
Computer Vision and Pattern Recognition
Summary
Understanding how children's hand bones change shape as they grow and differ between boys and girls is tricky. The authors used computer models to study many X-ray images of hand bones from children of different ages and sexes. They found clear differences in bone shape between boys and girls and how these shapes change during growth. Their method could help create detailed models to track bone development and differences in populations over time.
What this means in practice
- •For medical imaging teams: Improve bone segmentation and analysis for pediatric hand X-rays by providing accurate population-based shape models.
- •For medical device designers: Design better pediatric orthopedic implants or tools by incorporating sex-specific and growth-related bone shape variations.
Authors
Edwin Tay, Amir A. Zadpoor, Nazli Tümer
Abstract
Understanding the envelope of shape variation encompassing both sexual dimorphism and growth-related changes in living tissue is a non-trivial task. In this work, we use statistical shape models (SSMs) and analyze demographic-stratified shape parameters to quantify sexual dimorphism and sex-specific shape changes. To this end, we developed a two-stage detection-segmentation framework that accurately segmented $n = 27664$ unique bone masks from a radiographic dataset of $n = 1456$ subjects with diverse ages and sexes (HD95 = $1.512 \pm 0.005$, ASSD $0.449 \pm 001$, Dice = $0.987 \pm 0.00004$, IoU = $0.975 \pm 0.0001$). Following SSM fitting, our follow-up analyses of stratified shape parameters highlighted the morphology of sexual dimorphisms for each bone and demonstrated sex-specific differences in shape development. Our results were consistent with existing literature and provided an unambiguous, data-driven methodology for characterizing tissue shape and its population-scale variation. This approach provides a potential methodological foundation for developing population-based models of anatomical variation and could be extended to investigate tissue growth and shape changes over time. Future work should evaluate the applicability of this methodology on alternative anatomical structures and imaging modalities, with the goal of validating these growth trajectories on longitudinal data.