A computational approach to determine key anatomic landmarks on pelvis and its application to acetabular orientation assessment and hip computational biomechanics.

Anatomic landmarks Cartilage biomechanics Multiscale computational modelling Native acetabular orientation Natural hip

Journal

Medical engineering & physics
ISSN: 1873-4030
Titre abrégé: Med Eng Phys
Pays: England
ID NLM: 9422753

Informations de publication

Date de publication:
07 2022
Historique:
received: 04 11 2021
revised: 07 04 2022
accepted: 25 05 2022
entrez: 5 7 2022
pubmed: 6 7 2022
medline: 8 7 2022
Statut: ppublish

Résumé

The determination of anatomic landmarks on the pelvis is an important procedure in orthopaedics, computational biomechanics and morphometrics. This study aimed to develop a robust method for determining the anatomic landmarks on the pelvis and demonstrate the application of the method in assessing the native acetabular orientation and developing multiscale computational modelling for hip biomechanics. Two Matlab algorithms, named "Pelvisor" and "Acetabulor", were developed to determine four anatomic landmarks on the pelvis and assess the acetabular orientation in the natural hip. The algorithms were then applied to: (1) assess the native acetabular orientations for a cohort of subjects; (2) develop a multiscale computational modelling to investigate the biomechanical behaviour of the biphasic cartilage in the natural hip joint. Results showed that the present method can accurately determine the key anatomic landmarks on the pelvis and assess the acetabular orientation in the natural hip joint. Significant differences in acetabular inclination and anteversion between males and females were identified, with larger orientations in females. The interstitial fluid pressure in the cartilage supported over 90% of loading during gait, and the stresses and strains within the solid matrix of the cartilage were as low as 1.8 MPa and 0.12, respectively.

Identifiants

pubmed: 35781388
pii: S1350-4533(22)00073-X
doi: 10.1016/j.medengphy.2022.103824
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

103824

Informations de copyright

Copyright © 2022 IPEM. Published by Elsevier Ltd. All rights reserved.

Auteurs

Xijin Hua (X)

Institute for Manufacturing, Department of Engineering, University of Cambridge, Cambridge, CB2 1PZ United Kingdom. Electronic address: xijinhua@outlook.com.

Junyan Li (J)

Tribology Research Institute, School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, 610031, China. Electronic address: jyli@swjtu.edu.cn.

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Classifications MeSH