Robust workflow for diaphyseal cortical bone thickness calculation.

Area of Science:

• Biomechanics
• Medical Imaging
• Orthopedics

Background:

• Cortical bone is crucial for skeletal mechanical strength and fracture risk assessment.
• Existing automated CT scan analysis methods for cortical thickness struggle with diverse bone morphologies.
• Accurate, large-scale analysis of cortical bone is needed for better understanding of skeletal health.

Purpose of the Study:

• To adapt and improve an automated technique for measuring cortical bone thickness from clinical CT scans.
• To enhance the robustness of cortical thickness measurement across various long bone shapes.
• To facilitate large-scale analysis of skeletal mechanical properties and osteogenic phenomena.

Main Methods:

• Adapted an existing automated technique for cortical thickness measurement from CT scans.
• Evaluated the adapted method on 240 long bones across six types (humerus, femur, radius, ulna, tibia, fibula).
• Compared failure rates and accuracy against the original 2012 method.

Main Results:

• The original method failed across all tested bone types with mean failure rates up to 24.8%.
• The adapted method eliminated failures in most bones, with a significantly reduced mean failure rate of 1.9% in the fibula.
• The new method demonstrated improved robustness in handling morphological variations in long bones.

Conclusions:

• The adapted technique significantly improves the reliability of automated cortical bone thickness measurement from CT scans.
• This enhanced method is more suitable for large-scale studies and analyzing population-level skeletal variability.
• The workflow is a valuable resource for improving understanding of bone health and disease in clinical contexts.