Pamela Rufus-Membere

Introduction: Impact microindentation (IMI) measures bone material strength index (BMSi) in vivo. However, its ability to predict fractures is still uncertain. This study aimed to determine the association between BMSi and 10 year fracture probability, as calculated by the FRAX algorithm. Materials and methods: BMSi was measured using the OsteoProbe in 388 men (ages 40–90 yr) from the Geelong Osteoporosis Study. The probabilities for a major osteoporotic fracture (MOF) and hip fracture (HF) were calculated using the Australian FRAX tool. Hip (HF) and major osteoporotic (MOF) fracture probabilities were computed with and without the inclusion of femoral neck bone mineral density (BMD). For each participant, four 10 year probability scores were therefore generated: (i) HF-FRAXnoBMD; (ii) HF-FRAXBMD; (iii) MOF-FRAXnoBMD; (iv) MOF-FRAXBMD. Results: BMSi was negatively correlated with age (r = − 0.114, p = 0.025), no associations were detected between BMSi and femoral neck BMD (r = + 0.035, p = 0.507). BMSi was negatively correlated with HF-FRAXnoBMD (r = − 0.135, p = 0.008) and MOF-FRAXnoBMD (r = − 0.153, p = 0.003). These trends held true for HF-FRAXBMD (r = − 0.087, p = 0.094) and MOF-FRAXBMD (r = − 0.111, p = 0.034), but only the latter reached significance. Conclusion: BMSi captures the cumulative effect of clinical risk factors in the FRAX algorithm, suggesting that it could provide additional information that may be useful in predicting risk of fractures. Further studies are warranted to establish its efficacy in predicting fracture risk.

Components of the renin–angiotensin–aldosterone system (RAAS) are present on bone cells. One measure of RAAS activity, the aldosterone-renin-ratio (ARR), is used to screen for primary aldosteronism. Associations between ARR and bone mineral density are conflicting. This study investigated associations between ARR and peripheral quantitative computed tomography (pQCT) and impact microindentation (IMI). Male participants (n = 431) were from the Geelong Osteoporosis Study. “Likely” primary aldosteronism was defined as ARR ≥ 70 pmol/mIU. Another group, “possible” primary aldosteronism, was defined as either ARR ≥ 70 pmol/mIU or taking a medication that affects the RAAS, but not a beta blocker, and renin < 15 mU/L. Using pQCT, images at 4% and 66% of radial (n = 365) and tibial (n = 356) length were obtained. Using IMI measurements, bone material strength index (BMSi; n = 332) was determined. Associations between ARR or likely/possible primary aldosteronism and IMI or pQCT-derived bone parameters were tested using median regression. ARR and aldosterone values were not associated with any of the pQCT-derived bone variables in either unadjusted or adjusted analyses. Men with likely primary aldosteronism (n = 16), had lower adjusted total bone area (radial 66% site, − 12.5%). No associations were observed for men with possible primary aldosteronism (unadjusted or adjusted). No associations with BMSi were observed (p > 0.05). There were no associations between ARR or aldosterone and pQCT-derived bone parameters. Men with likely primary aldosteronism had lower bone area, suggesting clinically high levels of ARR may have a negative impact on bone health.

Bone material strength index (BMSi) values are obtained using impact microindentation, which assesses the ability of bone to resist indentation. Differences in BMSi between men and women are unclear, and to date, BMSi sex differences have not been compared for individuals from the same population. Therefore, we compared BMSi values for men and women drawn from the same geographical location in Australia. Participants (n = 220) were from the Geelong Osteoporosis Study. BMSi was measured, following international published guidelines, using an OsteoProbe for participants at recent follow-up phases (women 2022–2023 and men 2016–2022). Women (n = 55) were age matched to men (n = 165) in a 1:3 ratio. A two-sample t test was used to determine the intergroup difference in mean BMSi. Linear regression was also performed, adjusting for weight and height. Median (IQR) ages for men and women were 67.0 (61.7–71.5) and 67.4 (62.0–71.2) years (p = 0.998). Men were heavier (81.0 ± 10.9 vs 71.0 ± 13.9 kg, p < 0.001) and taller (173.9 ± 6.4 vs 161.5 ± 7.5 cm, p < 0.001) than women. Mean (± SD) BMSi for women (75.7 ± 7.4) was lower than for men (82.8 ± 6.8) (p < 0.001). The difference persisted after adjustment for weight and height (mean ± SE: 76.5 ± 1.1 vs 82.5 ± 0.6, p < 0.001). Given the higher fracture risk observed for women, the higher mean BMSi values in men are consistent with cross sectional data suggesting this measure may be useful in fracture prediction.

Impact microindentation (IMI) is a novel technique for assessing bone material strength index (BMSi) in vivo, by measuring the depth of a micron-sized, spherical tip into cortical bone that is then indexed to the depth of the tip into a reference material. The aim of this study was to define the reference intervals for men and women by evaluating healthy adults from the United States of America, Europe and Australia. Participants included community-based volunteers and participants drawn from clinical and population-based studies. BMSi was measured on the tibial diaphysis using an OsteoProbe in 479 healthy adults (197 male and 282 female, ages 25 to 98 years) across seven research centres, between 2011 and 2018. Associations between BMSi, age, sex and areal bone mineral density (BMD) were examined following an a posteriori method. Unitless BMSi values ranged from 48 to 101. The mean (± standard deviation) BMSi for men was 84.4 ± 6.9 and for women, 79.0 ± 9.1. Healthy reference intervals for BMSi were identified as 71.0 to 97.9 for men and 59.8 to 95.2 for women. This study provides healthy reference data that can be used to calculate T- and Z-scores for BMSi and assist in determining the utility of BMSi in fracture prediction. These data will be useful for positioning individuals within the population and for identifying those with BMSi at the extremes of the population.

Impact microindentation (IMI) measures bone material strength index (BMSi) in vivo. However, its ability to predict fractures is still uncertain. This study aimed to determine the association between BMSi and 10-year fracture probability, as calculated by the FRAX algorithm. BMSi was measured using the OsteoProbe in 390 men (ages 40-90yr) from the Geelong Osteoporosis Study. The probabilities for a major osteoporotic fracture (MOF) and hip fracture (HF) were calculated using the Australian FRAX tool. Fracture probabilities were computed with and without the inclusion of femoral neck bone mineral density (BMD). For each participant, four 10-year probability scores were therefore generated: (i)HF-FRAXnoBMD; (ii)HF-FRAXBMD; (iii)MOF-FRAXnoBMD; (iv)MOF-FRAXBMD. BMSi was negatively correlated with age (r = -0.114, p = 0.025), no associations were detected between BMSi and femoral neck BMD (r = +0.035, p=0.507). BMSi was negatively correlated with HF-FRAXnoBMD (r = -0.135, p=0.008) and MOF-FRAXnoBMD (r = -0.153, p=0.003). This relationship tended to be weaker with the inclusion of femoral neck BMD; HF-FRAXBMD (r =-0.087, p=0.094); MOF-FRAXBMD (r = -0.111, p=0.034). BMSi captures the cumulative effect of clinical risk factors in the FRAX algorithm, suggesting that it could provide additional information that may be useful in predicting risk of fractures.

Accumulation of fat in the liver and skeletal muscle is associated with obesity and poor health outcomes. Liver steatosis is a characteristic of non-alcoholic fatty liver disease (NAFLD) and myosteatosis, of poor muscle quality in sarcopenia. In this study of 403 men (33–96 years), we investigated associations between the fatty liver index (FLI) and muscle density, as markers of fat accumulation in these organs. We also investigated associations between the FLI and parameters of sarcopenia, including DXA-derived appendicular lean mass (ALM) and handgrip strength by dynamometry. Muscle density was measured using pQCT at the radius and tibia. FLI was calculated from BMI, waist circumference, and levels of triglycerides and gamma-glutamyltransferase. There was a pattern of decreasing muscle density across increasing quartiles of FLI. After adjusting for age and lifestyle, mean radial muscle density in Q4 was 2.1% lower than Q1 (p < 0.001) and mean tibial muscle density was 1.8% lower in Q3 and 3.0% lower in Q4, compared to Q1 (p = 0.022 and < 0.001, respectively). After adjusting for age and sedentary lifestyle, participants in the highest FLI quartile were sixfold more likely to have sarcopenia. In conclusion, our results suggest that fat accumulation in the liver co-exists with fat infiltration into skeletal muscle.