1
|
Fernandez J, Shim V, Schneider M, Choisne J, Handsfield G, Yeung T, Zhang J, Hunter P, Besier T. A Narrative Review of Personalized Musculoskeletal Modeling Using the Physiome and Musculoskeletal Atlas Projects. J Appl Biomech 2023; 39:304-317. [PMID: 37607721 DOI: 10.1123/jab.2023-0079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 07/02/2023] [Accepted: 07/24/2023] [Indexed: 08/24/2023]
Abstract
In this narrative review, we explore developments in the field of computational musculoskeletal model personalization using the Physiome and Musculoskeletal Atlas Projects. Model geometry personalization; statistical shape modeling; and its impact on segmentation, classification, and model creation are explored. Examples include the trapeziometacarpal and tibiofemoral joints, Achilles tendon, gastrocnemius muscle, and pediatric lower limb bones. Finally, a more general approach to model personalization is discussed based on the idea of multiscale personalization called scaffolds.
Collapse
Affiliation(s)
- Justin Fernandez
- Auckland Bioengineering Institute, University of Auckland, Auckland,New Zealand
- Department of Engineering Science and Biomedical Engineering, University of Auckland, Auckland,New Zealand
| | - Vickie Shim
- Auckland Bioengineering Institute, University of Auckland, Auckland,New Zealand
| | - Marco Schneider
- Auckland Bioengineering Institute, University of Auckland, Auckland,New Zealand
| | - Julie Choisne
- Auckland Bioengineering Institute, University of Auckland, Auckland,New Zealand
| | - Geoff Handsfield
- Auckland Bioengineering Institute, University of Auckland, Auckland,New Zealand
| | - Ted Yeung
- Auckland Bioengineering Institute, University of Auckland, Auckland,New Zealand
| | - Ju Zhang
- Auckland Bioengineering Institute, University of Auckland, Auckland,New Zealand
| | - Peter Hunter
- Auckland Bioengineering Institute, University of Auckland, Auckland,New Zealand
| | - Thor Besier
- Auckland Bioengineering Institute, University of Auckland, Auckland,New Zealand
- Department of Engineering Science and Biomedical Engineering, University of Auckland, Auckland,New Zealand
| |
Collapse
|
2
|
Sensale M, Vendeuvre T, Germaneau A, Grivot C, Rochette M, Dall'Ara E. Prediction of the 3D shape of the L1 vertebral body from adjacent vertebrae. Med Image Anal 2023; 87:102827. [PMID: 37099970 DOI: 10.1016/j.media.2023.102827] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Revised: 04/14/2023] [Accepted: 04/18/2023] [Indexed: 04/28/2023]
Abstract
The aim of treatments of vertebral fractures is the anatomical reduction to restore the physiological biomechanics of the spine and the stabilization of the fracture to allow bone healing. However, the three-dimensional shape of the fractured vertebral body before the fracture is unknown in the clinical setting. Information about the pre-fracture vertebral body shape could help surgeons to select the optimal treatment. The goal of this study was to develop and validate a method based on Singular Value Decomposition (SVD) to predict the shape of the vertebral body of L1 from the shapes of T12 and L2. The geometry of the vertebral bodies of T12, L1 and L2 vertebrae of 40 patients were extracted from CT scans available from the VerSe2020 open-access dataset. Surface triangular meshes of each vertebra were morphed onto a template mesh. The set of vectors with the node coordinates of the morphed T12, L1 and L2 were compressed with SVD and used to build a system of linear equations. This system was used to solve a minimization problem and to reconstruct the shape of L1. A leave-one-out cross-validation was performed. Moreover, the approach was tested against an independent dataset with large osteophytes. The results of the study show a good prediction of the shape of the vertebral body of L1 from the shapes of the two adjacent vertebrae (mean error equal to 0.51 ± 0.11 mm on average, Hausdorff distance equal to 2.11 ± 0.56 mm on average), compared to current CT resolution typically used in the operating room. The error was slightly higher for patients presenting large osteophytes or severe bone degeneration (mean error equal to 0.65 ± 0.10 mm, Hausdorff distance equal to 3.54 ± 1.03 mm). The accuracy of the prediction was significantly better than approximating the shape of the vertebral body of L1 by the shape of T12 or L2. This approach could be used in the future to improve the pre-planning of spine surgeries to treat vertebral fractures.
Collapse
Affiliation(s)
- M Sensale
- Ansys France, Lyon, France; Department of Oncology and Metabolism, INSIGNEO Institute for in silico Medicine, University of Sheffield, United Kingdom
| | - T Vendeuvre
- Spine & Neuromodulation Functional Unit, University Hospital of Poitiers, Poitiers, France; Insitut Pprime UPR 3346 CNRS - Université de Poitiers - ISAE-ENSMA, Poitiers, France
| | - A Germaneau
- Insitut Pprime UPR 3346 CNRS - Université de Poitiers - ISAE-ENSMA, Poitiers, France
| | | | | | - E Dall'Ara
- Department of Oncology and Metabolism, INSIGNEO Institute for in silico Medicine, University of Sheffield, United Kingdom.
| |
Collapse
|
3
|
Mei Q, Kim HK, Xiang L, Shim V, Wang A, Baker JS, Gu Y, Fernandez J. Toward improved understanding of foot shape, foot posture, and foot biomechanics during running: A narrative review. Front Physiol 2022; 13:1062598. [PMID: 36569759 PMCID: PMC9773215 DOI: 10.3389/fphys.2022.1062598] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Accepted: 11/28/2022] [Indexed: 12/14/2022] Open
Abstract
The current narrative review has explored known associations between foot shape, foot posture, and foot conditions during running. The artificial intelligence was found to be a useful metric of foot posture but was less useful in developing and obese individuals. Care should be taken when using the foot posture index to associate pronation with injury risk, and the Achilles tendon and longitudinal arch angles are required to elucidate the risk. The statistical shape modeling (SSM) may derive learnt information from population-based inference and fill in missing data from personalized information. Bone shapes and tissue morphology have been associated with pathology, gender, age, and height and may develop rapid population-specific foot classifiers. Based on this review, future studies are suggested for 1) tracking the internal multi-segmental foot motion and mapping the biplanar 2D motion to 3D shape motion using the SSM; 2) implementing multivariate machine learning or convolutional neural network to address nonlinear correlations in foot mechanics with shape or posture; 3) standardizing wearable data for rapid prediction of instant mechanics, load accumulation, injury risks and adaptation in foot tissue and bones, and correlation with shapes; 4) analyzing dynamic shape and posture via marker-less and real-time techniques under real-life scenarios for precise evaluation of clinical foot conditions and performance-fit footwear development.
Collapse
Affiliation(s)
- Qichang Mei
- Faculty of Sports Science, Ningbo University, Ningbo, China,Research Academy of Grand Health, Ningbo University, Ningbo, China,Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand,*Correspondence: Qichang Mei, , ; Yaodong Gu, ,
| | - Hyun Kyung Kim
- School of Kinesiology, Louisiana State University, Baton Rouge, LA, United States
| | - Liangliang Xiang
- Faculty of Sports Science, Ningbo University, Ningbo, China,Research Academy of Grand Health, Ningbo University, Ningbo, China,Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
| | - Vickie Shim
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
| | - Alan Wang
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
| | - Julien S. Baker
- Centre for Health and Exercise Science Research, Hong Kong Baptist University, Kowloon, Hong Kong SAR, China
| | - Yaodong Gu
- Faculty of Sports Science, Ningbo University, Ningbo, China,Research Academy of Grand Health, Ningbo University, Ningbo, China,Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand,*Correspondence: Qichang Mei, , ; Yaodong Gu, ,
| | - Justin Fernandez
- Faculty of Sports Science, Ningbo University, Ningbo, China,Research Academy of Grand Health, Ningbo University, Ningbo, China,Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand,Department of Engineering Science, The University of Auckland, Auckland, New Zealand
| |
Collapse
|
4
|
Lung and fissure shape is associated with age in healthy never-smoking adults aged 20-90 years. Sci Rep 2020; 10:16135. [PMID: 32999328 PMCID: PMC7528089 DOI: 10.1038/s41598-020-73117-w] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Accepted: 09/10/2020] [Indexed: 11/08/2022] Open
Abstract
Lung shape could hold prognostic information for age-related diseases that affect lung tissue mechanics. We sought to quantify mean lung shape, its modes of variation, and shape associations with lung size, age, sex, and Body Mass Index (BMI) in healthy subjects across a seven-decade age span. Volumetric computed tomography from 83 subjects (49 M/34 F, BMI [Formula: see text]) was used to derive two statistical shape models using a principal component analysis. One model included, and the other controlled for, lung volume. Volume made the strongest contribution to shape when it was included. Shape had a strong relationship with age but not sex when volume was controlled for, and BMI had only a small but significant association with shape. The first principal shape mode was associated with decrease in the antero-posterior dimension from base to apex. In older subjects this was rapid and obvious, whereas younger subjects had relatively more constant dimension. A shift of the fissures of both lungs in the basal direction was apparent for the older subjects, consistent with a change in tissue elasticity with age. This study suggests a quantifiable structure-function relationship for the healthy adult lung that can potentially be exploited as a normative description against which abnormal can be compared.
Collapse
|