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REVIEW article
Front. Endocrinol.
Sec. Bone Research
Volume 16 - 2025 |
doi: 10.3389/fendo.2025.1538460
This article is part of the Research Topic Imaging-Based Methods for Fracture Risk Assessment View all 4 articles
Biomechanical Perspectives on Image-Based Hip Fracture Risk Assessment: Advances and Challenges
Provisionally accepted- University of Manitoba, Winnipeg, Canada
Hip fractures pose a significant health challenge, particularly in aging populations, leading to substantial morbidity and economic burden. Most hip fractures result from a combination of osteoporosis and falls. Accurate assessment of hip fracture risk is essential for identifying high-risk individuals and implementing effective preventive strategies. Current clinical tools, such as the Fracture Risk Assessment Tool (FRAX), primarily rely on statistical models of clinical risk factors derived from large population studies. However, these tools often lack specificity in capturing the individual biomechanical factors that directly influence fracture susceptibility. Consequently, imagebased biomechanical approaches, primarily leveraging dual-energy X-ray absorptiometry (DXA) and quantitative computed tomography (QCT), have garnered attention for their potential to provide a more precise evaluation of bone strength and the impact forces involved in falls, thereby enhancing risk prediction accuracy. Biomechanical approaches rely on two fundamental components: assessing bone strength and predicting fall-induced impact forces. While significant advancements have been made in image-based finite element (FE) modeling for bone strength analysis and dynamic simulations of fallinduced impact forces, substantial challenges remain. In this review, we examine recent progress in these areas and highlight the key challenges that must be addressed to advance the field and improve fracture risk prediction.
Keywords: Hip fracture, Risk Assessment, DXA, QCT, bone strength, fall-induced impact force
Received: 02 Dec 2024; Accepted: 27 Jan 2025.
Copyright: © 2025 Luo. 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) or licensor 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.
* Correspondence:
Yunhua Luo, University of Manitoba, Winnipeg, Canada
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