Computational Frameworks for Subject-specific Prediction of Vertebral Fracture Risk




Prado, Maria

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Aging leads to a significant decrease in bone mineral density (BMD), loss of muscle mass and strength, high risk for falls, and fractures. These musculoskeletal (MSK) changes significantly and negatively affect quality of life. Osteoporosis is a systemic skeletal disease in adults characterized by natural bone loss. Currently, about 20 million Americans over the age of 50 have osteoporosis while the prevalence increased from ∼10 million to >14 million people in 2020. Osteoporosis-related fractures affect nearly 2 million Americans annually and 9 million worldwide. Vertebral fractures, the hallmark of osteoporosis, cause substantial back pain and disability. Dual-energy X-ray absorptiometry (DXA) is the clinical gold-standard imaging technique for the estimation of 2D areal BMD (aBMD) as a surrogate for fracture risk. Quantitative computed tomography (QCT) provides a 3D measure of BMD and can more accurately describe bone heterogeneity and structure, addressing some of the disadvantages of DXA. When QCT is combined with finite element analysis (FEA) it can successfully be used to assess fracture properties of bones such as stiffness and failure loads. Besides bone properties, other can also affect the risk for fracture, including but not limited to spine curvatures and spinal loads. Skeletal muscle mass decline in older individuals can eventually result in altered spine curvature. Evaluation of spine loads can explain how loading on the various spine regions varies with physiological activities and over time, potentially leading to vertebral fractures. To address in vivo measurement challenges, MSK models can be developed to predict the loading of the intersegmental vertebral bodies during daily living activities.


The full text of this item is not available at this time because the author has placed this item under an embargo until December 20, 2024.


Finite element analysis, Fracture risk, Osteoporosis, Quantitative computed tomography, Spine



Biomedical Engineering