# Biomechanical perspectives on image-based hip fracture risk assessment: advances and challenges

## TL;DR

This paper reviews how biomechanical methods using imaging can better predict hip fracture risk compared to traditional tools.

## Contribution

The paper highlights recent advances and challenges in image-based biomechanical approaches for hip fracture risk assessment.

## Key findings

- Image-based biomechanical methods offer more precise evaluation of bone strength and fall impact forces.
- Finite element modeling and dynamic simulations have advanced but still face significant challenges.
- Current clinical tools lack specificity in capturing individual biomechanical factors.

## Abstract

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, image-based 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 fall-induced 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.