Assessment of Cortical Bone Mechanics Technology (CBMT) Fracture Discrimination Capability
- Conditions
- Osteopenia or OsteoporosisOsteoporosis, PostmenopausalBone FractureOsteoporosisOsteoporotic FracturesOsteoporosis RiskFragility Fracture
- Interventions
- Diagnostic Test: Cortical Bone Mechanics Technology
- Registration Number
- NCT05721898
- Lead Sponsor
- Ohio University
- Brief Summary
Osteoporosis is a disease characterized by low bone mass and structural deterioration of bone tissue leading to bone fragility (i.e., weakness) and an increased risk for fracture. Bone strength is a critical factor in a bone's ability to resist fracture and is clearly an important outcome in studies of osteoporosis. The current standard for assessing bone health and diagnosing osteoporosis is to use dual-energy x-ray absorptiometry (DXA) to quantify the areal bone mineral density (BMD), typically at the hip and spine. However, DXA-derived BMD has limited discriminatory accuracy for distinguishing individuals that experience fragility fracture from those who do not. One well known limitation of DXA-derived BMD is that it does not adequately assay bone strength. There is a critical unmet need to identify persons more accurately with diminished bone strength who are at high risk of experiencing a fragility fracture in order to determine an appropriate therapy. A potential new diagnostic approach to assess skeletal health and improve osteoporosis diagnosis is the use of Cortical Bone Mechanics Technology (CBMT). CBMT leverages multifrequency vibration analysis to conduct a noninvasive, dynamic 3-point bending test that makes direct, mechanical measurements of ulnar cortical bone. Data indicates that CBMT-derived ulnar flexural rigidity accurately estimates ulnar whole bone strength and provides information about cortical bone that is unique and independent of DXA-derived BMD. However, the clinical utility of CBMT-derived flexural rigidity has not yet been demonstrated. The investigators have designed a clinical study to assess the accuracy of CBMT-derived ulnar flexural rigidity in discriminating post-menopausal women who have suffered a fragility fracture from those who have not. These data will be compared to DXA-derived peripheral and central measures of BMD obtained from the same subjects.
- Detailed Description
Osteoporosis is a disease characterized by low bone mass and structural deterioration of bone tissue, leading to bone fragility (i.e., weakness), and an increased risk for fracture. The incidence of osteoporosis related fragility fractures (i.e., low energy fractures resulting from a fall from standing height or less) increases with age and is highest in post-menopausal women. In the United States, there were approximately 2.3 million fragility fractures in 2020. The total annual expense of providing direct and indirect care for osteoporotic fractures among Medicare beneficiaries was estimated at $57 billion in 2018, with an expected increase to over $95 billion by 2040.
Bone strength is a critical factor in a bone's ability to resist fracture and is clearly an important outcome in studies of osteoporosis. The current standard for assessing bone health and diagnosing osteoporosis is to use dual-energy x-ray absorptiometry (DXA) to quantify the areal bone mineral density (BMD), typically at the hip and spine. However, DXA-derived BMD has relatively poor discriminatory accuracy to distinguish individuals who will fracture from those who will not.
One well known limitation of BMD is that it does not adequately assay bone strength. As with any complex structure, bone strength depends on the interplay between a variety of factors, including the amount or mass of bone present and the structural organization and quality of the material. BMD primarily indicates bone mass but does not adequately assess the contributions of bone structure or quality to bone strength.
Reflecting the limitations of DXA, BMD explains less than half of the variation in whole bone strength, and when bone strength is improved and fracture risk reduced via bisphosphonate drug therapy, less than 18% of the observed reductions in vertebral fracture risk can be attributed to increases in BMD. These findings clearly suggest that the current standard care is insufficient for identifying those who might benefit most from early intervention to improve bone health, as well as for assessing the effect of new therapies targeted at increasing bone strength. A potential new diagnostic approach to address this critical unmet need and improve osteoporosis diagnosis is the use of Cortical Bone Mechanics Technology (CBMT).
CBMT leverages multifrequency vibration analysis to conduct a noninvasive, dynamic 3-point bending test that makes direct, functional mechanical measurements of ulnar cortical bone (e.g., flexural rigidity). Because CBMT is a whole bone test, its measurements reflect the combined influences of bone quantity, structure, and quality at all hierarchical levels. Its validity in accurate measurements of ulna flexural rigidity and estimations of quasistatic ulna bending strength have been demonstrated. CBMT-derived flexural rigidity yielded a near perfect estimate of cadaveric bone strength (R2=0.99). Additionally, flexural rigidity has been reported to decrease 21% following potassium hydroxide-induced collagen degradation whereas BMD was not altered. Thus, current data indicates that CBMT-derived ulnar flexural rigidity accurately estimates ulnar whole bone strength and provides information about cortical bone that is unique and independent of BMD. Assessing cortical bone, in particular, is important because after \~65 years most bone loss is cortical, and the cortical bone loss is associated with increased incidence of fragility fractures. However, the clinical utility of CBMT-derived flexural rigidity has not yet been demonstrated.
The investigators have designed a clinical study to assess the accuracy of CBMT-derived ulnar flexural rigidity in discriminating post-menopausal women who have suffered a fragility fracture from those who have not. These data will be compared to DXA-derived peripheral and central measures of BMD obtained from the same subjects.
Recruitment & Eligibility
- Status
- COMPLETED
- Sex
- Female
- Target Recruitment
- 394
Not provided
Not provided
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Arm && Interventions
Group Intervention Description Non-Fracture Controls Cortical Bone Mechanics Technology Controls: Post-menopausal females between 50-80 years who have not experienced a fracture at any site after the age of 40 years (does not include fractures of the digits, toes or face). Does not self-report losing more than 1.5 inches in stature (height) in the previous 15 years. Body mass index between 18.5 and 35 kg/m2. Fracture Cases Cortical Bone Mechanics Technology Fragility Fracture Cases: Post-menopausal females between 50-80 years who have experienced a fragility fracture of the arms (including wrist fractures) or legs (including hip, pelvis, or ankle fractures) after the age of 50 years. Fractures of the spine, digits, toes or face will not be considered. A fragility fracture is operationally define based on self-report of an arm or leg fracture caused by falls from a height \<6 inches. A fragility fracture will not count if it is associated with 1) running, bicycling or other similar fast-moving activity such as sports subjects, 2) being struck by a falling or otherwise quickly moving heavy object, or 3) a motor vehicle accident. Insufficiency/stress fractures will not be included. Body mass index between 18.5 and 35 kg/m2.
- Primary Outcome Measures
Name Time Method Discriminatory Accuracy of CBMT vs. BMD 1 Day Discriminatory accuracy of ulnar flexural rigidity in comparison to the bone mineral density.
CBMT's Added Value 1 Day Binomial logistic regression's Walt coefficient to quantify how ulnar flexural rigidity and areal BMD predicts group membership (cases and controls).
- Secondary Outcome Measures
Name Time Method
Trial Locations
- Locations (4)
Indiana Center for Musculoskeletal Health
🇺🇸Indianapolis, Indiana, United States
University of South Florida
🇺🇸Tampa, Florida, United States
Ohio Musculoskeletal and Neurological Institute at Ohio University
🇺🇸Athens, Ohio, United States
University of Florida
🇺🇸Jacksonville, Florida, United States