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Robinson A, Zheng B, von Kleeck BW, Tan J, Gayzik FS. Holistic shape variation of the rib cage in an adult population. Front Bioeng Biotechnol 2024; 12:1432911. [PMID: 39359263 PMCID: PMC11445027 DOI: 10.3389/fbioe.2024.1432911] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2024] [Accepted: 09/06/2024] [Indexed: 10/04/2024] Open
Abstract
Traumatic injuries to the thorax are a common occurrence, and given the disparity in outcomes, injury risk is non-uniformly distributed within the population. Rib cage geometry, in conjunction with well-established biomechanical characteristics, is thought to influence injury tolerance, but quantifiable descriptions of adult rib cage shape as a whole are lacking. Here, we develop an automated pipeline to extract whole rib cage measurements from a large population and produce distributions of these measurements to assess variability in rib cage shape. Ten measurements of whole rib cage shape were collected from 1,719 individuals aged 25-45 years old including angular, linear, areal, and volumetric measures. The resulting pipeline produced measurements with a mean percent difference to manually collected measurements of 1.7% ± 1.6%, and the whole process takes 30 s per scan. Each measurement followed a normal distribution with a maximum absolute skew value of 0.43 and a maximum absolute excess kurtosis value of 0.6. Significant differences were found between the sexes (p < 0.001) in all except angular measures. Multivariate regression revealed that demographic predictors explain 29%-68% of the variance in the data. The angular measurements had the three lowest R2 values and were also the only three to have little correlation with subject stature. Unlike other measures, rib cage height had a negative correlation with BMI. Stature was the dominant demographic factor in predicting rib cage height, coronal area, sagittal area, and volume. Subject weight was the dominant demographic factor for rib cage width, depth, axial area, and angular measurements. Age was minimally important in this cohort of adults from a narrow age range. Individuals of similar height and weight had average rib cage measurements near the regression predictions, but the range of values across all subjects encompassed a large portion of their respective distributions. Our findings characterize the variability in adult rib cage geometry, including the variation within narrow demographic criteria. In future work, these can be integrated into computer aided engineering workflows to assess the influence of whole rib cage shape on the biomechanics of the adult human thorax.
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Affiliation(s)
- Andrea Robinson
- Department of Biomedical Engineering, Wake Forest University School of Medicine, Winston-Salem, NC, United States
- Virginia Tech-Wake Forest Center for Injury Biomechanics, Wake Forest University School of Medicine, Winston-Salem, NC, United States
| | - Bowen Zheng
- Department of Biomedical Engineering, Columbia University, New York, NY, United States
| | - B Wade von Kleeck
- Department of Biomedical Engineering, Wake Forest University School of Medicine, Winston-Salem, NC, United States
- Virginia Tech-Wake Forest Center for Injury Biomechanics, Wake Forest University School of Medicine, Winston-Salem, NC, United States
| | - Josh Tan
- Department of Radiology - Imaging Informatics, Wake Forest University School of Medicine, Winston-Salem, NC, United States
| | - F Scott Gayzik
- Department of Biomedical Engineering, Wake Forest University School of Medicine, Winston-Salem, NC, United States
- Virginia Tech-Wake Forest Center for Injury Biomechanics, Wake Forest University School of Medicine, Winston-Salem, NC, United States
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Li X, Yuan Q, Lindgren N, Huang Q, Fahlstedt M, Östh J, Pipkorn B, Jakobsson L, Kleiven S. Personalization of human body models and beyond via image registration. Front Bioeng Biotechnol 2023; 11:1169365. [PMID: 37274163 PMCID: PMC10236199 DOI: 10.3389/fbioe.2023.1169365] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2023] [Accepted: 04/28/2023] [Indexed: 06/06/2023] Open
Abstract
Finite element human body models (HBMs) are becoming increasingly important numerical tools for traffic safety. Developing a validated and reliable HBM from the start requires integrated efforts and continues to be a challenging task. Mesh morphing is an efficient technique to generate personalized HBMs accounting for individual anatomy once a baseline model has been developed. This study presents a new image registration-based mesh morphing method to generate personalized HBMs. The method is demonstrated by morphing four baseline HBMs (SAFER, THUMS, and VIVA+ in both seated and standing postures) into ten subjects with varying heights, body mass indices (BMIs), and sex. The resulting personalized HBMs show comparable element quality to the baseline models. This method enables the comparison of HBMs by morphing them into the same subject, eliminating geometric differences. The method also shows superior geometry correction capabilities, which facilitates converting a seated HBM to a standing one, combined with additional positioning tools. Furthermore, this method can be extended to personalize other models, and the feasibility of morphing vehicle models has been illustrated. In conclusion, this new image registration-based mesh morphing method allows rapid and robust personalization of HBMs, facilitating personalized simulations.
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Affiliation(s)
- Xiaogai Li
- Division of Neuronic Engineering, Department of Biomedical Engineering and Health Systems, KTH Royal Institute of Technology, Huddinge, Sweden
| | - Qiantailang Yuan
- Division of Neuronic Engineering, Department of Biomedical Engineering and Health Systems, KTH Royal Institute of Technology, Huddinge, Sweden
| | - Natalia Lindgren
- Division of Neuronic Engineering, Department of Biomedical Engineering and Health Systems, KTH Royal Institute of Technology, Huddinge, Sweden
| | - Qi Huang
- Division of Neuronic Engineering, Department of Biomedical Engineering and Health Systems, KTH Royal Institute of Technology, Huddinge, Sweden
| | | | - Jonas Östh
- Volvo Cars Safety Centre, Gothenburg, Sweden
- Division of Vehicle Safety, Department of Mechanics and Maritime Sciences, Chalmers University of Technology, Gothenburg, Sweden
| | - Bengt Pipkorn
- Division of Vehicle Safety, Department of Mechanics and Maritime Sciences, Chalmers University of Technology, Gothenburg, Sweden
- Autoliv Research, Vargarda, Sweden
| | - Lotta Jakobsson
- Volvo Cars Safety Centre, Gothenburg, Sweden
- Division of Vehicle Safety, Department of Mechanics and Maritime Sciences, Chalmers University of Technology, Gothenburg, Sweden
| | - Svein Kleiven
- Division of Neuronic Engineering, Department of Biomedical Engineering and Health Systems, KTH Royal Institute of Technology, Huddinge, Sweden
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Incorporating Nutrition, Vests, Education, and Strength Training (INVEST) in Bone Health: Trial Design and Methods. Contemp Clin Trials 2021; 104:106326. [PMID: 33631359 DOI: 10.1016/j.cct.2021.106326] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Revised: 02/16/2021] [Accepted: 02/17/2021] [Indexed: 12/16/2022]
Abstract
BACKGROUND Achievement of 5-10% weight loss (WL) among older adults living with obesity considerably improves prognosis of health-related outcomes; however, concomitant declines in bone mineral density (BMD) limit overall benefit by increasing fracture risk. Declines in mechanical loading contribute to WL-associated BMD loss, with pilot data signaling the addition of external weight replacement (via weighted vest use) during intentional WL mitigates bone loss at weight bearing sites to a similar degree as resistance exercise training (RT). Definitive data in support of weighted vest use as a potential strategy to mitigate WL-associated bone loss in this population are needed. METHODS In the Incorporating Nutrition, Vests, Education, and Strength Training (INVEST) in Bone Health trial (NCT04076618), 192 older adults (60-85 years) who are overweight (BMI ≥ 27 kg/m2) with at least one obesity-related risk factor or obese (BMI = 30-40 kg/m2) will be randomly assigned to participate in one of three 12-month intervention groups: WL alone, WL + weighted vest use (WL + VEST), or WL + RT. The primary aim is to determine the effects of WL + VEST compared to WL alone and WL + RT on indicators of bone health and subsequent fracture risk. DISCUSSION Determining effective, translatable strategies that minimize bone loss during intentional WL among older adults holds public health potential. The INVEST in Bone Health trial offers an innovative approach for increasing mechanical stress during intentional WL in the absence of RT. If successful, findings from this study will provide evidence in support of a scalable solution to minimize bone loss during intentional WL among older adults with obesity.
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Yates KM, Agnew AM, Albert DL, Kemper AR, Untaroiu CD. Subject-specific rib finite element models with material data derived from coupon tests under bending loading. J Mech Behav Biomed Mater 2021; 116:104358. [PMID: 33610029 DOI: 10.1016/j.jmbbm.2021.104358] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Revised: 12/19/2020] [Accepted: 01/22/2021] [Indexed: 11/30/2022]
Abstract
Rib fractures are common thoracic injuries in motor vehicle crashes. Several human finite element (FE) human models have been created to numerically assess thoracic injury risks. However, the accurate prediction of rib biomechanical response has shown to be challenging due to human variation and modeling approaches. The main objective of this study was to better understand the role of modeling approaches on the biomechanical response of human ribs in anterior-posterior bending. Since the development of subject specific rib models is a time-consuming process, the second objective of this study was to develop an accurate morphing approach to quickly generate high quality subject specific rib meshes. The exterior geometries and cortical-trabecular boundaries of five human 6th-level ribs were extracted from CT-images. One rib mesh was developed in a parametric fashion and the other four ribs were developed with an in-house morphing algorithm. The morphing algorithm automatically defined landmarks on both the periosteal and endosteal boundaries of the cortical layer, which were used to morph the template nodes to target geometries. Three different cortical bone material models were defined based on the stress-strain data obtained from subject-specific tensile coupon tests for each rib. Full rib anterior-posterior bending tests were simulated based on data recorded in testing. The results showed similar trends to test data with some sensitivity relative to the material modeling approach. Additionally, the FE models were substantially more resistant to failure, highlighting the need for better techniques to model rib fracture. Overall, the results of this work can be used to improve the biofidelity of human rib finite element models.
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Yates KM, Untaroiu CD. Finite element modeling of the human kidney for probabilistic occupant models: Statistical shape analysis and mesh morphing. J Biomech 2018; 74:50-56. [DOI: 10.1016/j.jbiomech.2018.04.016] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2017] [Revised: 04/05/2018] [Accepted: 04/07/2018] [Indexed: 10/17/2022]
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Davis ML, Koya B, Schap JM, Gayzik FS. Development and Full Body Validation of a 5th Percentile Female Finite Element Model. STAPP CAR CRASH JOURNAL 2016; 60:509-544. [PMID: 27871105 DOI: 10.4271/2016-22-0015] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
To mitigate the societal impact of vehicle crash, researchers are using a variety of tools, including finite element models (FEMs). As part of the Global Human Body Models Consortium (GHBMC) project, comprehensive medical image and anthropometrical data of the 5th percentile female (F05) were acquired for the explicit purpose of FEM development. The F05-O (occupant) FEM model consists of 981 parts, 2.6 million elements, 1.4 million nodes, and has a mass of 51.1 kg. The model was compared to experimental data in 10 validation cases ranging from localized rigid hub impacts to full body sled cases. In order to make direct comparisons to experimental data, which represent the mass of an average male, the model was compared to experimental corridors using two methods: 1) post-hoc scaling the outputs from the baseline F05-O model and 2) geometrically morphing the model to the body habitus of the average male to allow direct comparisons. This second step required running the morphed full body model in all 10 simulations for a total of 20 full body simulations presented. Overall, geometrically morphing the model was found to more closely match the target data with an average ISO score for the rigid impacts of 0.76 compared to 0.67 for the scaled responses. Based on these data, the morphed model was then used for model validation in the vehicle sled cases. Overall, the morphed model attained an average weighted score of 0.69 for the two sled impacts. Hard tissue injuries were also assessed and the baseline F05-O model was found to predict a greater occurrence of pelvic fractures compared to the GHBMC average male model, but predicted fewer rib fractures.
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Affiliation(s)
- Matthew L Davis
- Wake Forest School of Medicine
- Virginia Tech-Wake Forest University Center for Injury Biomechanics
| | - Bharath Koya
- Wake Forest School of Medicine
- Virginia Tech-Wake Forest University Center for Injury Biomechanics
| | - Jeremy M Schap
- Wake Forest School of Medicine
- Virginia Tech-Wake Forest University Center for Injury Biomechanics
| | - F Scott Gayzik
- Wake Forest School of Medicine
- Virginia Tech-Wake Forest University Center for Injury Biomechanics
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