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Image-based finite-element modeling of the human femur
Computer Methods in Biomechanics and Biomedical Engineering ( IF 1.6 ) Pub Date : 2020-07-12 , DOI: 10.1080/10255842.2020.1789863
Cristina Falcinelli 1 , Cari Whyne 1
Affiliation  

Abstract Fracture is considered a critical clinical endpoint in skeletal pathologies including osteoporosis and bone metastases. However, current clinical guidelines are limited with respect to identifying cases at high risk of fracture, as they do not account for many mechanical determinants that contribute to bone fracture. Improving fracture risk assessment is an important area of research with clear clinical relevance. Patient-specific numerical musculoskeletal models generated from diagnostic images are widely used in biomechanics research and may provide the foundation for clinical tools used to quantify fracture risk. However, prior to clinical translation, in vitro validation of predictions generated from such numerical models is necessary. Despite adopting radically different models, in vitro validation of image-based finite element (FE) models of the proximal femur (predicting strains and failure loads) have shown very similar, encouraging levels of accuracy. The accuracy of such in vitro models has motivated their application to clinical studies of osteoporotic and metastatic fractures. Such models have demonstrated promising but heterogeneous results, which may be explained by the lack of a uniform strategy with respect to FE modeling of the human femur. This review aims to critically discuss the state of the art of image-based femoral FE modeling strategies, highlighting principal features and differences among current approaches. Quantitative results are also reported with respect to the level of accuracy achieved from in vitro evaluations and clinical applications and are used to motivate the adoption of a standardized approach/workflow for image-based FE modeling of the femur.

中文翻译:

基于图像的人类股骨有限元建模

摘要 骨折被认为是包括骨质疏松症和骨转移在内的骨骼病理学的关键临床终点。然而,目前的临床指南在识别骨折高风险病例方面是有限的,因为它们没有考虑许多导致骨折的机械决定因素。改进骨折风险评估是一个重要的研究领域,具有明确的临床相关性。从诊断图像生成的特定于患者的数值肌肉骨骼模型广泛用于生物力学研究,并可能为用于量化骨折风险的临床工具提供基础。然而,在临床转化之前,必须对这些数值模型产生的预测进行体外验证。尽管采用了截然不同的模型,股骨近端基于图像的有限元 (FE) 模型(预测应变和失效载荷)的体外验证显示出非常相似、令人鼓舞的准确度水平。这种体外模型的准确性推动了它们在骨质疏松性和转移性骨折的临床研究中的应用。这些模型已经证明了有希望但异质的结果,这可能是由于缺乏关于人类股骨的有限元建模的统一策略。本综述旨在批判性地讨论基于图像的股骨 FE 建模策略的最新技术,突出当前方法之间的主要特征和差异。
更新日期:2020-07-12
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