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Development of predictive statistical shape models for paediatric lower limb bones.

Beichen Shi1, Martina Barzan1, Azadeh Nasseri1

  • 1Griffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Griffith University, Australia; School of Health Sciences and Social Work, Griffith University, Gold Coast Campus, Parklands Dr Southport, Gold Coast, QLD, Australia.

Computer Methods and Programs in Biomedicine
|July 26, 2022
PubMed
Summary
This summary is machine-generated.

Statistical shape models (SSM) for pediatric lower limb bones were developed, showing accurate reconstruction capabilities. These models are more effective for pediatric bones than adult-based models.

Keywords:
BiomechanicsBone shapeMedical imagingSubject-specific modelling

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Area of Science:

  • Biomedical Engineering
  • Orthopedics
  • Medical Imaging

Background:

  • Accurate bone shape representation is crucial for subject-specific musculoskeletal models.
  • Existing statistical shape models (SSM) for lower limb bones are validated for adults but not applicable to pediatric populations.
  • Developing pediatric-specific SSM can reduce the time and cost associated with medical imaging for bone reconstruction.

Purpose of the Study:

  • To develop statistical shape models (SSM) for pediatric lower limb bones (femur, pelvis, tibia, fibula, patella).
  • To evaluate the reconstruction accuracy of these pediatric SSM using sparse anatomical landmarks.
  • To compare the performance of pediatric SSM against adult-based models for pediatric bone reconstruction.

Main Methods:

  • Generated 3D models of 56 femurs, 29 pelves, 56 tibias, 56 fibulas, and 56 patellae from MRI scans of 29 children.
  • Created SSM for individual bones and combined structures (haunch, shank).
  • Utilized a leave-one-out cross-validation method to reconstruct bones using full and sparse (anatomical landmarks) inputs, comparing against original segmentations via RMSE, Jaccard index, DSC, and Hausdorff distance.

Main Results:

  • SSM with full-input achieved RMSE between 0.89 ± 0.10 mm (patella) and 1.98 ± 0.38 mm (pelvis).
  • SSM with sparse-input showed RMSE ranging from 1.33 ± 0.61 mm (patella) to 3.60 ± 1.05 mm (pelvis).
  • Reconstruction metrics (Jaccard, DSC, Hausdorff distance) indicated good accuracy for both input types, with sparse-input generally showing slightly lower performance compared to full-input.

Conclusions:

  • The developed SSM for pediatric lower limb bones demonstrate reconstruction accuracy comparable to existing models.
  • These pediatric-specific SSM outperform adult-based SSM when reconstructing pediatric bones.
  • The findings support the use of SSM with sparse anatomical landmarks for efficient and accurate pediatric bone shape estimation.