Single-component imaging and ultrasound-based tools for the assessment of fracture risk.
Authors
Affiliations (26)
Affiliations (26)
- WHO Collaborating Centre for Epidemiology of Musculoskeletal Health and Aging, Liège, Belgium.
- Lifecourse Epidemiology Centre, University of Southampton, Southampton, UK.
- Department of Biochemistry, College of Science, King Saud University, Riyadh, Saudi Arabia.
- Division of Public Health, Epidemiology and Health Economics, University of Liège, Liège, Belgium.
- Saint Camillus International University of Health Sciences, Faculty of Medicine, Rome, Italy.
- Unità Locale Socio-Sanitaria 3 "Serenissima", Primary Care Department, Venice, Italy.
- Chair for Biomarkers of Chronic Diseases, Biochemistry Department, College of Science, King Saud University, Riyadh, Saudi Arabia.
- Protein Research Chair, Biochemistry Department, College of Science, King Saud University, Riyadh, Saudi Arabia.
- UQAM, Faculty of Sciences, Department of Exercise Sciences, GRAPA, Montreal, Quebec, Canada.
- Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal (CRIUGM), Montreal, Quebec, Canada.
- Department of Internal Medicine, Division of Geriatrics, Istanbul Medical Faculty, Istanbul University, Istanbul, Türkiye.
- Namur Research Institute for Life Sciences (NARILIS), University of Namur, Namur, Belgium.
- Research Unit in Public Health, Epidemiology and Health Economics, University of Liège, Liège, Belgium.
- The European Society for Clinical and Economic Aspects of Osteoporosis, Osteoarthritis and Musculoskeletal Diseases (ESCEO), Liege, Belgium.
- Department of Clinical Chemistry, University of Liege, CIRM, CHU de Liège, Liège, Belgium.
- Osteoporosis and Bone Metabolism Unit, Department of Endocrinology, Singapore General Hospital, Singapore, Singapore.
- Department of Medicine, School of Clinical Sciences, Monash University, Clayton, Victoria, Australia.
- Nutrition, Exercise Physiology and Sarcopenia Laboratory, Jean Mayer USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA, USA.
- Department of Health Services Research, CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, the Netherlands.
- Department of Endocrinology, Ghent University Hospital, Ghent, Belgium.
- Research Unit of Health Sciences and Technology, University of Oulu, Oulu, Finland.
- Department of Physical Therapy, Marquette University, Milwaukee, WI, USA.
- Paris Cité University, Faculty of Health, School/Unit of Medicine, Paris, France.
- Geriatrics Department, Brugmann University Hospital, Université Libre de Bruxelles, Brussels, Belgium.
- Science, Innovation & Monitoring, Department of Sexual, Reproductive, Maternal, Newborn, Child, Adolescent Health and Ageing (LHR), World Health Organization, Geneva, Switzerland. [email protected].
- Geneva University Hospitals and Faculty of Medicine, Geneva, Switzerland.
Abstract
Emerging imaging and computational technologies are reshaping how osteoporosis and low bone mass are assessed. Dual-energy X-ray absorptiometry (DXA) is key for the operational definition of osteoporosis, but advances in single-component tools such as finite element analysis, trabecular bone score, DXA-based 3D shape modelling, quantitative ultrasound, radiofrequency echographic multi-spectrometry and artificial-intelligence-driven interpretation of routine radiology offer complementary insights into bone strength, microarchitecture and fracture risk. Some of these approaches provide additional fracture-risk measures beyond areal bone mineral density, whereas others enable opportunistic identification of people with low bone density in populations who would otherwise be missed. Strong pre-clinical and encouraging observational data support the use of these technologies and, although their current use in clinical practice varies with the age of the technology, they all have a potential role in the assessment of fracture risk at a variety of points in the patient journey (from screening to monitoring response to therapy). As their use becomes more widespread, monitoring performance, assessing the equitability of implementation and evaluating the health-service benefits of these tools in clinical practice will be key.