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Subject-Specific Alignment and Mass Distribution in Musculoskeletal Models of the Lumbar Spine

Musculoskeletal modeling is a well-established method in spine biomechanics and generally employed for investigations concerning both the healthy and the pathological spine. It commonly involves inverse kinematics and optimization of muscle activity and provides detailed insight into joint loading....

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Autores principales: Fasser , Marie-Rosa, Jokeit , Moritz, Kalthoff , Mirjam, Gomez Romero , David A., Trache, Tudor, Snedeker, Jess G., Farshad, Mazda, Widmer , Jonas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8438119/
https://www.ncbi.nlm.nih.gov/pubmed/34532314
http://dx.doi.org/10.3389/fbioe.2021.721042
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author Fasser , Marie-Rosa
Jokeit , Moritz
Kalthoff , Mirjam
Gomez Romero , David A.
Trache, Tudor
Snedeker, Jess G.
Farshad, Mazda
Widmer , Jonas
author_facet Fasser , Marie-Rosa
Jokeit , Moritz
Kalthoff , Mirjam
Gomez Romero , David A.
Trache, Tudor
Snedeker, Jess G.
Farshad, Mazda
Widmer , Jonas
author_sort Fasser , Marie-Rosa
collection PubMed
description Musculoskeletal modeling is a well-established method in spine biomechanics and generally employed for investigations concerning both the healthy and the pathological spine. It commonly involves inverse kinematics and optimization of muscle activity and provides detailed insight into joint loading. The aim of the present work was to develop and validate a procedure for the automatized generation of semi-subject-specific multi-rigid body models with an articulated lumbar spine. Individualization of the models was achieved with a novel approach incorporating information from annotated EOS images. The size and alignment of bony structures, as well as specific body weight distribution along the spine segments, were accurately reproduced in the 3D models. To ensure the pipeline’s robustness, models based on 145 EOS images of subjects with various weight distributions and spinopelvic parameters were generated. For validation, we performed kinematics-dependent and segment-dependent comparisons of the average joint loads obtained for our cohort with the outcome of various published in vivo and in situ studies. Overall, our results agreed well with literature data. The here described method is a promising tool for studying a variety of clinical questions, ranging from the evaluation of the effects of alignment variation on joint loading to the assessment of possible pathomechanisms involved in adjacent segment disease.
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spelling pubmed-84381192021-09-15 Subject-Specific Alignment and Mass Distribution in Musculoskeletal Models of the Lumbar Spine Fasser , Marie-Rosa Jokeit , Moritz Kalthoff , Mirjam Gomez Romero , David A. Trache, Tudor Snedeker, Jess G. Farshad, Mazda Widmer , Jonas Front Bioeng Biotechnol Bioengineering and Biotechnology Musculoskeletal modeling is a well-established method in spine biomechanics and generally employed for investigations concerning both the healthy and the pathological spine. It commonly involves inverse kinematics and optimization of muscle activity and provides detailed insight into joint loading. The aim of the present work was to develop and validate a procedure for the automatized generation of semi-subject-specific multi-rigid body models with an articulated lumbar spine. Individualization of the models was achieved with a novel approach incorporating information from annotated EOS images. The size and alignment of bony structures, as well as specific body weight distribution along the spine segments, were accurately reproduced in the 3D models. To ensure the pipeline’s robustness, models based on 145 EOS images of subjects with various weight distributions and spinopelvic parameters were generated. For validation, we performed kinematics-dependent and segment-dependent comparisons of the average joint loads obtained for our cohort with the outcome of various published in vivo and in situ studies. Overall, our results agreed well with literature data. The here described method is a promising tool for studying a variety of clinical questions, ranging from the evaluation of the effects of alignment variation on joint loading to the assessment of possible pathomechanisms involved in adjacent segment disease. Frontiers Media S.A. 2021-08-31 /pmc/articles/PMC8438119/ /pubmed/34532314 http://dx.doi.org/10.3389/fbioe.2021.721042 Text en Copyright © 2021 Fasser , Jokeit , Kalthoff , Gomez Romero , Trache, Snedeker, Farshad and Widmer . https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Bioengineering and Biotechnology
Fasser , Marie-Rosa
Jokeit , Moritz
Kalthoff , Mirjam
Gomez Romero , David A.
Trache, Tudor
Snedeker, Jess G.
Farshad, Mazda
Widmer , Jonas
Subject-Specific Alignment and Mass Distribution in Musculoskeletal Models of the Lumbar Spine
title Subject-Specific Alignment and Mass Distribution in Musculoskeletal Models of the Lumbar Spine
title_full Subject-Specific Alignment and Mass Distribution in Musculoskeletal Models of the Lumbar Spine
title_fullStr Subject-Specific Alignment and Mass Distribution in Musculoskeletal Models of the Lumbar Spine
title_full_unstemmed Subject-Specific Alignment and Mass Distribution in Musculoskeletal Models of the Lumbar Spine
title_short Subject-Specific Alignment and Mass Distribution in Musculoskeletal Models of the Lumbar Spine
title_sort subject-specific alignment and mass distribution in musculoskeletal models of the lumbar spine
topic Bioengineering and Biotechnology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8438119/
https://www.ncbi.nlm.nih.gov/pubmed/34532314
http://dx.doi.org/10.3389/fbioe.2021.721042
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