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Quantitative assessment of muscle morphology from MR image analysis
The deterioration of trunk muscles can have serious biomechanical consequences. The goal of this project is an analysis of magnetic resonance imaging (MRI) datasets to determine muscle morphological properties for inclusion in a musculoskeletal model.
Sarcopenia is an age-related loss of muscle mass and function, leading to a number of serious clinical consequences. In particular, trunk muscles affected by sarcopenia lose their ability to stabilize and energize the vertebral column, resulting in altered biomechanics of the spine, loss of posture and back pain. We aim to investigate the effects of sarcopenia on spinal loading and related risk of vertebral fractures using a numerical musculoskeletal model. However, realistic quantitative data regarding muscle morphology is missing in the model.
Therefore, the morphological properties of trunk muscles will be evaluated analysing datasets of MR images taken from clinical scans of young and elderly subjects. Since muscle deterioration is reflected in a progressive decrease of muscle cross-sectional area, and the replacement of lean muscle tissue with fat, both the geometry and composition of muscles need to be analysed. The analysis will be performed by means of semi-automatic segmentation of MR images with the aid of an application developed for this purpose (collaboration with the University of Bern).
Sarcopenia is an age-related loss of muscle mass and function, leading to a number of serious clinical consequences. In particular, trunk muscles affected by sarcopenia lose their ability to stabilize and energize the vertebral column, resulting in altered biomechanics of the spine, loss of posture and back pain. We aim to investigate the effects of sarcopenia on spinal loading and related risk of vertebral fractures using a numerical musculoskeletal model. However, realistic quantitative data regarding muscle morphology is missing in the model.
Therefore, the morphological properties of trunk muscles will be evaluated analysing datasets of MR images taken from clinical scans of young and elderly subjects. Since muscle deterioration is reflected in a progressive decrease of muscle cross-sectional area, and the replacement of lean muscle tissue with fat, both the geometry and composition of muscles need to be analysed. The analysis will be performed by means of semi-automatic segmentation of MR images with the aid of an application developed for this purpose (collaboration with the University of Bern).
The aim of this student project is to analyse a dataset of MR images and extract parameters describing morphological properties of trunk muscles to be included in a musculoskeletal model. The analysis will involve image segmentation and evaluation of muscle geometry and composition.
Tasks:
10% literature review, 80% image analysis and
10% preparation of report and presentation.
The aim of this student project is to analyse a dataset of MR images and extract parameters describing morphological properties of trunk muscles to be included in a musculoskeletal model. The analysis will involve image segmentation and evaluation of muscle geometry and composition.
Tasks: 10% literature review, 80% image analysis and 10% preparation of report and presentation.
Dominika Ignasiak, dignasiak@ethz.ch / Institute for Biomechanics, HPP O 13, ETH Zürich / Professorship Stephen Ferguson
Dominika Ignasiak, dignasiak@ethz.ch / Institute for Biomechanics, HPP O 13, ETH Zürich / Professorship Stephen Ferguson
