Distribution and variability study of the femur cortical thickness from computer tomography

Abstract

In the context of patient-specific 3D bone reconstruction, enhancing the surface with cortical thickness (COT) opens a large field of applications for research and medicine. This functionality calls for database analysis for better knowledge of COT. Our study provides a new approach to reconstruct 3D internal and external cortical surfaces from computer tomography (CT) scans and analyses COT distribution and variability on a set of asymptomatic femurs. The reconstruction method relies on a short (∼5 min) initialisation phase based on 3D reconstruction from biplanar CT-based virtual X-rays and an automatic optimisation phase based on intensity-based cortical structure detection in the CT volume, the COT being the distance between internal and external cortical surfaces. Surfaces and COT show root mean square reconstruction errors below 1 and 1.3 mm. Descriptions of the COT distributions by anatomical regions are provided and principal component analysis has been applied. The first mode, 16–50% of the variance, corresponds to the variation of the mean COT around its averaged shape; the second mode, 9–28%, corresponds to a fine variation of its shape. A femur COT model can, therefore, be described as the averaged COT distribution in which the first parameter adjusts its mean value and a second parameter adjusts its shape.

Keywords::

• bone cortical thickness
• human femur
• 3D reconstruction
• biomedical imaging
• CT
• bone modelling

Acknowledgements

This work is part of the SterEOS+project funded by the Ile-de-France region though the Medicen competitive cluster. The authors would like to thank the donors, the ‘Service du don des corps’ of the University Paris Descartes, for providing the PMHS, the Radiology Service of Cochin University Hospital for the CT-Scan, the CEESAR and the LAB (GIE PSA Renault) for the technical support. The study benefited also of useful discussions with Benjamin Aubert and manual segmentations completed by Hussam Hanna. Finally, we would like to thank two anonymous reviewers who helped us to improve the paper.