Bone fracture

Introduction

Bone fractures, especially fragility fractures, present a significant healthcare challenge with profound socioeconomic implications. As the global population ages, the prevalence of conditions like osteoporosis, which contribute to increased fracture risk, continues to surge. The ability to accurately assess an individual’s fracture risk non-invasively and efficiently remains an elusive goal in the field of orthopedics. However, in a groundbreaking study published in “Scientific Reports,” a team of interdisciplinary researchers from the Department of Orthopedics at University Medicine Rostock, Germany, and associated institutions have introduced a computational workflow that might just change the playing field.

In their study titled “Neuro-musculoskeletal flexible multibody simulation yields a framework for efficient bone failure risk assessment” (DOI: 10.1038/s41598-019-43028-6), the team, led by Dr. Andreas Geier, unveiled a neuro-musculoskeletal flexible multibody simulation (NfMBS) integrated with quantitative CT-based finite-element models (FEMs). This novel approach provides an effective tool for early bone fracture risk assessment, filling a crucial gap in patient-specific evaluations of bone strength and breakage susceptibility under various strain scenarios.

The proposed workflow expressly quantifies bone strength via osteogenic stresses and strains. These measures are generated due to physiological-like loading of the bone under patient-specific neuro-musculoskeletal dynamics, making the analysis highly personalized and relevant for clinical use. The most noteworthy aspect of this approach is its computational efficiency. The researchers successfully simulated an entire squat in just 38 seconds of CPU time, highlighting its potential for real-world application where quick decision-making is often critical.

Experimental validation using a fresh human femur, side-by-side with consistency in femur strength computations in line with existing literature, provides a convincing argument for the method’s accuracy. The results revealed that a loss of bone mineral density (BMD), 16% in cortical and 33% in trabecular bone, caused a 31.4% increase in the strain measure tied with bone fracture. In practical terms, this equates to a higher risk of femoral hip fracture.

The authors underscore the urgency of addressing fragility fractures and point to key statistics expressing the magnitude of the issue. Hernlund et al. (2013) estimate that osteoporosis affects 22 million women and 5.5 million men within the European Union alone, with a projection of the number increasing by 23% by 2025 (Arch Osteoporos, DOI: 10.1007/s11657-013-0136-1). The Surgeon General’s report on Bone Health and Osteoporosis echoes these concerns, forecasting significant public health burdens if these trends persist (Rockville [MD], 2004).

The study’s workflow combines the advantages of various existing methodologies. Finite element analysis (FEA), as evaluated by Imai (2015) for fracture risk and treatment assessment, can robustly predict bone strength and fracture risk when supplemented with CT data (World J Exp Med, DOI: 10.5493/wjem.v5.i3.182). Robling, Castillo, and Turner (2006) detail the biomechanical and molecular regulation of bone remodeling, whichensures that bones maintain a healthy composition and structure under normal physiological conditions (Ann Rev Biomed Eng, DOI: 10.1146/annurev.bioeng.8.061505.095721).

The integration of NfMBS adds a layer of dynamism to these assessments, permitting simulated loading scenarios that reflect the complex interactions of muscles, tendons, and bones during movement. By adjusting for nuances in patient gait, muscular strength, and bone density, this approach can predict how slight alterations in everyday movements could either mitigate or exacerbate fracture risk. Such a detailed, dynamic analysis was previously unachievable due to computational limitations.

The practical implications of this research are immense. Optimized bone fracture risk assessment tools could enable clinicians to make informed decisions about interventions, whether they be changes in physical activities or surgical options. Rehabilitation strategies could also be tailored to individual biomechanical profiles, potentially improving outcomes for patients at high risk of fractures.

Conclusion

With more exhaustive validation and integration into clinical workflows, the neuro-musculoskeletal flexible multibody simulation framework could revolutionize the process of fracture risk assessment. This innovation holds the potential to reduce fragility fractures significantly, improving quality of life for countless individuals and easing the associated economic burdens on healthcare systems.

References

1. Geier et al. Neuro-musculoskeletal flexible multibody simulation yields a framework for efficient bone failure risk assessment. Sci Rep, DOI: 10.1038/s41598-019-43028-6.
2. Robling et al. Biomechanical and molecular regulation of bone remodeling. Ann Rev Biomed Eng, DOI: 10.1146/annurev.bioeng.8.061505.095721.
3. Hernlund et al. Osteoporosis in the European Union. Arch Osteoporos, DOI: 10.1007/s11657-013-0136-1.
4. Imai et al. Computed tomography-based finite element analysis to assess fracture risk and osteoporosis treatment. World J Exp Med, DOI: 10.5493/wjem.v5.i3.182.
5. Bone Health and Osteoporosis. A Report of the Surgeon General. (Rockville [MD], 2004).

Keywords

1. Bone Fracture Risk Assessment
2. Neuro-musculoskeletal Simulation
3. Personalized Bone Strength Analysis
4. Quantitative CT-based FEM
5. Efficient Bone Health Evaluation