Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Automatic Generation of Personalised Skeletal Models of the Lower Limb from Three-Dimensional Bone Geometries

View ORCID ProfileLuca Modenese, Jean-Baptiste Renault
doi: https://doi.org/10.1101/2020.06.23.162727
Luca Modenese
1Department of Civil and Environmental Engineering, Imperial College London, UK
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Luca Modenese
  • For correspondence: l.modenese@imperial.ac.uk
Jean-Baptiste Renault
2Aix-Marseille University, CNRS, ISM UMR 7287, 13009 Marseille, France
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Data/Code
  • Preview PDF
Loading

Abstract

The generation of personalised and patient-specific musculoskeletal models is currently a cumbersome and time-consuming task that normally requires several processing hours and trained operators. We believe that this aspect discourages the use of computational models even when appropriate data are available and personalised biomechanical analysis would be beneficial. In this paper we present a computational tool that enables the fully automatic generation of skeletal models of the lower limb from three-dimensional bone geometries, normally obtained by segmentation of medical images. This tool was evaluated against four manually created lower limb models finding remarkable agreement in the computed joint parameters, well within human operator repeatability. The coordinate systems origins were identified with maximum differences between 0.5 mm (hip joint) and 5.9 mm (subtalar joint), while the joint axes presented discrepancies between 1° (knee joint) to 11° (subtalar joint). To prove the robustness of the methodology, the models were built from four datasets including both genders, anatomies ranging from juvenile to elderly and bone geometries reconstructed from high-quality computed tomography as well as lower-quality magnetic resonance imaging scans. The entire workflow, implemented in MATLAB scripting language, executed in seconds and required no operator intervention, creating lower extremity models ready to use for kinematic and kinetic analysis or as baselines for more advanced musculoskeletal modelling approaches, of which we provide some practical examples. We auspicate that this technical advancement, together with upcoming progress in medical image segmentation techniques, will promote the use of personalised models in larger-scale studies than those hitherto undertaken.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • Revised manuscript to address comments of reviewers of Journal of Biomechanics. Includes: * explanation of why manual reference systems, rather than morphological registration, are considered gold standard (Introduction) * quantification and discussion of skeletal modelling and segmentation time (Results, Discussion) * comparison of walking simulation results using automatic and manual models (Results, Discussion) * improved quality of all figures * details of automatic joint models (Methods)

  • https://simtk.org/projects/auto-sk-models

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
Back to top
PreviousNext
Posted October 29, 2020.
Download PDF

Supplementary Material

Data/Code
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Automatic Generation of Personalised Skeletal Models of the Lower Limb from Three-Dimensional Bone Geometries
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Automatic Generation of Personalised Skeletal Models of the Lower Limb from Three-Dimensional Bone Geometries
Luca Modenese, Jean-Baptiste Renault
bioRxiv 2020.06.23.162727; doi: https://doi.org/10.1101/2020.06.23.162727
Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
Citation Tools
Automatic Generation of Personalised Skeletal Models of the Lower Limb from Three-Dimensional Bone Geometries
Luca Modenese, Jean-Baptiste Renault
bioRxiv 2020.06.23.162727; doi: https://doi.org/10.1101/2020.06.23.162727

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Bioengineering
Subject Areas
All Articles
  • Animal Behavior and Cognition (2430)
  • Biochemistry (4787)
  • Bioengineering (3330)
  • Bioinformatics (14671)
  • Biophysics (6634)
  • Cancer Biology (5167)
  • Cell Biology (7423)
  • Clinical Trials (138)
  • Developmental Biology (4362)
  • Ecology (6873)
  • Epidemiology (2057)
  • Evolutionary Biology (9913)
  • Genetics (7344)
  • Genomics (9522)
  • Immunology (4550)
  • Microbiology (12673)
  • Molecular Biology (4942)
  • Neuroscience (28313)
  • Paleontology (199)
  • Pathology (808)
  • Pharmacology and Toxicology (1391)
  • Physiology (2024)
  • Plant Biology (4494)
  • Scientific Communication and Education (977)
  • Synthetic Biology (1299)
  • Systems Biology (3912)
  • Zoology (725)