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Delivery of Ovarian Hormones for Bone Health
Published in Emmanuel Opara, Controlled Drug Delivery Systems, 2020
Indeed, osteoporosis is the leading cause of bone fracture with direct costs alone expected to reach $25 billion by 2025.5 BMD is widely used to determine whether a patient has osteoporosis and is prone to fracture risk. BMD is typically reported as a T-score, which normalizes BMD to the average BMD of a healthy, young adult. Per the World Health Organization, a T-score within ± standard deviation of 0 is considered normal. T-scores of −1 to −2.5 standard deviations below 0 indicate low bone mass, which is often considered osteopenia. T-scores of more than −2.5 standard deviations from 0 indicate osteoporosis and thus has an increased risk of fracture.3 While BMD has been a traditional measure for osteoporosis, it is not particularly accurate in predicting risks of bone fracture.31,91 The use of BMD in conjunction with analysis of other risk factors, such as age, smoking history, family history of hip fracture, glucocorticoid use, and arthritis, has led to a more accurate prediction of fracture risk known as the Fracture Risk Assessment Tool (FRAX) method.154 Blood testing for bone turnover markers such as the C-telopeptide of collagen may allow further predictive capacity of osteoporosis and the likelihood of fracture.137,161 Unfortunately, bone fracture remains the most likely clinical presentation of osteoporosis.154
Musculoskeletal system
Published in A Stewart Whitley, Jan Dodgeon, Angela Meadows, Jane Cullingworth, Ken Holmes, Marcus Jackson, Graham Hoadley, Randeep Kumar Kulshrestha, Clark’s Procedures in Diagnostic Imaging: A System-Based Approach, 2020
A Stewart Whitley, Jan Dodgeon, Angela Meadows, Jane Cullingworth, Ken Holmes, Marcus Jackson, Graham Hoadley, Randeep Kumar Kulshrestha
The FRAX assessment tool has been developed by WHO [91] to evaluate fracture risk assessment of patients. It is based on individual patient models that integrate the clinical risk factors as well as BMD at the femoral neck (Fig. 3.68a). The FRAX models have been developed by studying population-based cohorts from Europe, North America, Asia and Australia. The FRAX algorithms give the 10-year probability of fracture. The output is a 10-year probability of hip fracture and the 10-year probability of a major osteoporotic fracture (spine, hip, shoulder or wrist). These measurements are confined to post-menopausal Caucasian women and patients aged 40–90 years of age (Fig. 3.68b).
Predicting population level hip fracture risk: a novel hierarchical model incorporating probabilistic approaches and factor of risk principles
Published in Computer Methods in Biomechanics and Biomedical Engineering, 2020
Daniel R. Martel, Martin Lysy, Andrew C. Laing
Existing clinical tools to assess fracture risk typically use epidemiological, rather than mechanistic, approaches to risk assessment, e.g. FRAX, CAROC, QFracture, Garvan, trabecular bone score (Kanis et al. 2008; Leslie and Lix 2010; Leslie et al. 2014; Aspray 2015; Briot et al. 2018; White et al. 2018). While these tools can identify individuals at higher risk of hip fracture, most applications require subject-specific medical histories and/or assessments to determine the presence of relevant risk factors. In conjunction with individual-level assessment tools, models that generate population-level estimates of hip fracture risk could be a valuable tool for policy and organizational-level decision makers. Models of this type could simulate the effects of intervention approaches a priori, and if appropriately used, inform the development and incentivization of prevention methods to reduce hip fracture rates. However, the inherent variability within populations is a challenge to incorporate into deterministic modelling approaches. In contrast, probabilistic modelling methods can embrace this variability and provide frameworks to support population-level estimates of health outcomes (e.g. Rao and Mccabe 2016; Pérez-Rodríguez et al. 2019). While probabilistic modelling isn’t new to the field of biomechanics (e.g. Chopp-Hurley et al. 2016; Coombs et al. 2017), such approaches have never been coupled with injury mechanics to provide population-level risk estimates for hip fractures.
Prediction of proximal femur fracture risk from DXA images based on novel fracture indexes
Published in Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 2021
Said Zellagui, Audrey Hivet, Marouane El Mouss, Ridha Hambli
Considering (i) the clinical applicability of DXA to diagnose osteoporosis, (ii) the simplicity with which hip models can be generated from DXA, (iii) the short time required to perform a DXA scan and to process the images and (iv) the availability of large databases (cohorts) of patients obtained during follow-up studies composed of DXA images, the present study used the DXA imaging modality. In addition, besides its diagnostic use, DXA is the only procedure that can be used with the Fracture Risk Assessment Tool, or FRAX, which is particularly useful in identifying patients who are at a higher risk for fracture (1994. World Health Organization 2009).
Texture analysis based on Gabor filters improves the estimate of bone fracture risk from DXA images
Published in Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 2018
Rui-Sheng Lu, Elaine Dennison, Hayley Denison, Cyrus Cooper, Mark Taylor, Murk J. Bottema
Textural analysis of bone in the assessment of fracture risk is a topical area; trabecular bone score is a recently developed tool that performs grey-level texture analysis on lumbar spine DXA images providing information relating to trabecular micro-architecture. Trabecular bone score has been shown to relate to fracture risk independent of clinical risk factors and aBMD, and has a predictive value for fracture independent of fracture probabilities using FRAX (Harvey et al. 2015). The methodology discussed in this study provides information at the other site assessed by DXA, the femoral hip.