Image-based biomechanical models of the musculoskeletal system

Fabio Galbusera, Andrea Cina, Matteo Panico, Domenico Albano, Carmelo Messina

Research output: Contribution to journalReview articlepeer-review

Abstract

Finite element modeling is a precious tool for the investigation of the biomechanics of the musculoskeletal system. A key element for the development of anatomically accurate, state-of-the art finite element models is medical imaging. Indeed, the workflow for the generation of a finite element model includes steps which require the availability of medical images of the subject of interest: segmentation, which is the assignment of each voxel of the images to a specific material such as bone and cartilage, allowing for a three-dimensional reconstruction of the anatomy; meshing, which is the creation of the computational mesh necessary for the approximation of the equations describing the physics of the problem; assignment of the material properties to the various parts of the model, which can be estimated for example from quantitative computed tomography for the bone tissue and with other techniques (elastography, T1rho, and T2 mapping from magnetic resonance imaging) for soft tissues. This paper presents a brief overview of the techniques used for image segmentation, meshing, and assessing the mechanical properties of biological tissues, with focus on finite element models of the musculoskeletal system. Both consolidated methods and recent advances such as those based on artificial intelligence are described.

Original languageEnglish
Article number49
JournalEuropean radiology experimental
Volume4
Issue number1
DOIs
Publication statusPublished - Dec 1 2020

Keywords

  • Artificial intelligence
  • Finite element analysis
  • Musculoskeletal System
  • Tomography
  • Tomography (x-ray computed), Magnetic resonance imaging

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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