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Introduction: While preoperative bone health optimization is typical in the fragile population, objective assessment is limited. Among the aged, localized discordance in bone loss is prevalent and may not be assessed properly with traditional diagnostic measures. Etiology for bone loss discordance is unknown, but may be attributed to aging, disease state, habitus, or activity. This study investigated the association between body composition measures and common fragility fractures. Hypothesis: We hypothesized that each different fracture outcome would associate differently with measures of body composition. Methods: The Fragility Fracture Clinic at the University of Michigan provides comprehensive care to promote bone health, accelerate healing, and reduce fracture risk in those with and at-risk for fractures. Participants (N=344) included those who enrolled at the clinic between 2013 and 2020 and received an abdomen and/or pelvis computed tomography (CT) scan up to 120 days prior to initial enrollment date. Fracture categorizations included acute vs. non-acute, intensity (high vs. low energy), and location (thoracic vs. lumbar vertebral). Retrospective CT-scans were obtained from the University of Michigan Picture Archive and Communication System. Analytic Morphomics was used to obtain granular vertebral-indexed measurements of vertebral bone density, fascia, adipose tissue, muscle, vasculature, and interior body dimensions. Relevant measures include bone mineral density (BMD) [vertebral body trabecular bone density in Hounsfield Units (HU)], lower muscle group density in HU (DMG) (cross sectional area of DMG in HU range of 31-100), cortical bone density [anterior cortical half-maximum (in HU)], and fascial width (in mm). Measurements were divided by their standard deviation to ease interpretation of odds ratios. Multivariable logistic regression was used to evaluate the relationship between body measures and fracture type. Coefficients are reported as odds ratio (OR) and 95% confidence interval (CI). An alpha level of 0.05 determine statistical significance. Results: Associations were observed between acute fracture and BMD at L3 [OR 0.58, 95% CI 0.36-0.85]; high energy fracture and DMG at L3 [OR 2.08, 1.05-4.64]; low energy fracture and BMD at T8 [OR 0.39, 0.17-0.81]; thoracic vertebral fractures and BMD at T11 [OR 0.39, 0.17-0.81], cortical bone density at T11 [OR 0.64, 0.40-0.95], and fascial width at L4 [OR 0.67, 0.43-0.98]; lumbar vertebral fracture and BMD at L3 [OR 0.44, 95% CI 0.20-0.88]. Conclusion: Body composition measures uniquely associated with fracture outcomes. Lower vertebral trabecular bone density was associated with acute, high energy, thoracic vertebral, and lumbar vertebral fractures; lower lean muscle with high energy fractures; cortical bone density and facial (i.e. visceral cavity) width with thoracic vertebral fractures.

Introduction: Aortic calcification can be utilized to assess cardiovascular risk. While contrast is useful for vascular enhancement in diagnostic imaging, enhancement creates heterogeneity between post and non-contrast scans and limits their direct comparability. Hypothesis: We hypothesized that post and non-contrast aortic calcification measures will correlate, and a correction score can be developed for statistical comparability. Methods: Retrospective CT-scans were obtained from the University of Michigan. Participants (N=330) received abdominal scans with and without contrast enhancement within 120 calendar days. Analytic Morphomics was used to obtain vertebral-indexed measurements of aortic calcium area, and aortic wall obfuscation percentage. Calcification was specifically identified as regions with a given morphology and pixel value five standard deviations above the defined central lumen zone. Pearson correlation and multiple linear regression were used to explain the relationship between aortic measurements with and without contrast. Regressions include calcification percent (Model 1), and area (Model 2). Independent variables were non-contrast measurements and dependent variables were contrast measurements, age, and sex. Results: Correlations of calcification percent ranged from 0.86 at T11 and 0.94 and L2. Correlations of calcification area ranged from 0.66 at T12 to 0.84 at L3. In Model 1, for every percent increase in post-contrast calcification, non-contrast calcification percent increased by 11% (β=1.11, p Conclusion: In conclusion, this research proposes a correction score for comparisons of abdominal aortic calcification measurements in post-contrast and non-contrast scans.