Weight loss in older age can cause bone loss. In older adults with overweight/obesity in a weight loss trial, 6-month hip bone strength increased with higher protein intake versus controls consuming the Recommended Dietary Allowance. However, greater weight loss was associated with greater 18-month hip bone mineral density loss. PURPOSE:Weight loss (WL) to treat obesity in older age can exacerbate bone loss. METHODS:This trial assessed the effects of higher protein intake on hip bone outcomes in 187 older adults with overweight/obesity participating in 6 months of active WL (caloric restriction + aerobic exercise) followed by a 12-month maintenance phase. Participants were randomized to either the Recommended Dietary Allowance for protein intake of 0.8 g protein/kg body weight/day (RecProt) or higher protein intake of 1.2 g protein/kg/day for the 6-month WL period only (6-mo HiProt) or the full 18-month period (18-mo HiProt). CT scans at baseline, 6 months, and 18 months were analyzed for hip volumetric bone mineral density (vBMD) and cortical thickness; bone strength was assessed via finite element modeling of a sideways fall. Areal (a)BMD was measured with hip dual-energy X-ray absorptiometry. Analyses examined 6-month and 18-month bone changes using analysis of covariance, and Spearman's correlations of WL vs. bone changes. RESULTS:Greater WL was associated with greater gains in hip bone strength (p = 0.007) at 6 months, but greater trabecular vBMD loss at 18 months (p = 0.011) and aBMD loss at 6 and 18 months (p < 0.001). Hip bone strength increased 3.8 ± 1.7% over 6 months in the 18-mo HiProt group vs. 0.5 ± 1.6% in the RecProt group (p = 0.02) despite similar 6-month WL across groups (-8.0 ± 5.0%); however, there were no differences between the other groups. Eighteen-month group differences were non-significant. CONCLUSION:Higher protein intake had a beneficial effect on hip bone strength in older adults with overweight/obesity undergoing a WL intervention over the short-term.

Femur segmentation is a precursor to image analysis pipelines that evaluate hip bone measures with subject-specific finite element models, but historically required time-intensive efforts of operators. Implementing deep learning techniques offers a promising pathway for rapid, automated, and accurate segmentation. This study evaluates the feasibility of using a convolutional neural network (CNN) developed and validated for femur segmentation of Icelandic older adults to segment femurs in a sample of 166 CT scans of older adults with obesity in the United States. The performance of the segmentation model was quantitatively evaluated against manually segmented ground truth data using the Dice similarity coefficient (DSC) and the 95% Hausdorff distance (HD95), and qualitatively evaluated using manual image review. The mean DSC was 0.974 ± 0.009 and mean HD95 for the foreground was 1.078 ± 0.41 mm, indicating excellent segmentation quality. The CNN segmentation model averaged 32 ± 3 s for each mask prediction. Visual inspection revealed segmentations with minor errors in delineating boundaries at the femoral head and detecting osteophytes, requiring refinement during post-processing. The present CNN, when evaluated on this dataset of older adults with obesity, produced femur segmentations with improved quality and speed compared to manual segmentation. Additional model training with a more diverse training dataset could help further minimize manual intervention that is currently required during pre- and postprocessing. This study demonstrates the potential for femur segmentation CNN models to be applicable to diverse clinical datasets.

Background Muscle fat fraction (MFF) obtained through magnetic resonance imaging (MRI) is the gold standard for assessing muscle quality, but it is expensive and time consuming. Portable methods to examine muscles such as tensiomyography (TMG) are emerging and could enable broader screening. This study aims to examine associations between TMG-derived muscle contractile parameters and MFF in older adults with and without sarcopenia. Methods A sample of 51 Slovenian older adults (53% females) were scanned with Dixon MRIs to evaluate muscle MFF and contractile parameters were assessed with TMG estimating delay time (Td), maximal displacement (Dm) and radial contraction velocity (Vc). Right leg vastus lateralis (VL) and biceps femoris (BF) were analyzed. Sarcopenia was defined using both European Working Group on Sarcopenia in Older People (EWGSOP2) and Sarcopenia Definition and Outcomes Consortium (SDOC) criteria. Regression models adjusted for age and sex were used to assess associations between TMG-derived contractile parameters and MFF. Results Age- and sex-adjusted models revealed associations between increased MFF and reduced Dm (R-2 = 0.29, p = .003) and Vc (R-2 = 0.32, p = .002) for the VL. SDOC-classified sarcopenic individuals showed increased VL MFF (27.2% vs. 22.5%, p = .019),while EWGSOP2 classified sarcopenia displayed no differences. Discussion The study reveals that increased MFF is associated with reduced muscle contractility in VL. MFF differs between sarcopenic and non-sarcopenic groups using only SDOC criteria. Since the TMG Dm increase is regularly found in atrophic muscles after bed rest, in sarcopenic muscle MFF explains lowering of the Dm, highlighting the TMG potential for early detection of changes in aging muscle.

BACKGROUND:Skeletal muscle health is a key determinant of aging, independence, and disease outcomes. Traditional computed tomography (CT)-derived measures of muscle cross-sectional area (CSA) and density reflect muscle quantity and quality but may not capture structural heterogeneity relevant to functional decline. Radiomics, a CT image analysis approach, enables extraction of high-dimensional texture features, offering additional insight into muscle quality. While muscle radiomics have been associated with strength and mobility in older adults, longitudinal applications remain understudied. We examined whether 5-year changes in thigh muscle radiomic features were associated with changes in muscle strength and performance in the Health, Aging, and Body Composition Study. METHODS:Thigh CT scans from 1321 older adults were analyzed using automated muscle segmentation to quantify CSA, density, and extract radiomic features. Strength measures included grip strength and maximal isokinetic knee extension; performance measures included 20-m walking speed, 5-time chair stands, and a modified performance score. Factor analysis reduced radiomic features to seven latent factors. Nested linear mixed-effects models tested associations of muscle CSA and density with outcomes, with and without radiomic factors. RESULTS:Factors 2 and 5 were consistently associated with 5-year changes across muscle outcomes. Factor 2 (high pixel gray-level intensity and uniformity) was positively associated, whereas Factor 5 (pixel clustering asymmetry and heterogeneity) was inversely associated. Adding radiomic factors modestly improved model fit (p < .05), explaining 1%-2% additional variation in performance. CONCLUSION:Longitudinal changes in thigh muscle radiomics capture subtle compositional characteristics beyond muscle CSA or density, enhancing understanding of functional decline with aging.

BACKGROUND:The INVEST in Bone Health Trial examined the effects of weight loss (WL), WL plus resistance training (WL + RT), or WL plus weighted vest use (WL + VEST) on musculoskeletal health. This secondary analysis evaluated changes in muscle area and density using computed tomography (CT) and lean and fat mass using dual-energy x-ray absorptiometry (DXA). METHODS:One hundred fifty participants (50/group) were randomized to 12-months of WL, WL + RT, or WL + VEST, undergoing CT and DXA scans at baseline, six- and 12-months. DXA measured lean and fat mass, while CT assessed muscle and intermuscular adipose tissue (IMAT) cross-sectional area (CSA) and density. Mixed linear models evaluated changes and treatment effects, and partial Pearson's correlations examined relationships between weight change and CT/DXA outcomes. RESULTS:Participants (66.4 ± 4.6 years, 75% female, 69% white) were living with overweight (14.7%) or obesity (85.3%). All groups achieved similar and significant weight loss (∼10%). At 12-months, WL + RT increased mid-thigh muscle CSA (0.5%, p < .05), improved muscle density (3.7%-5.9%, p < .03), and reduced IMAT (20%-22%, p < .05) and fat masses (22%-26.8%, all p < .061). At the trunk, WL + VEST showed a trend toward muscle preservation and improved density (4.2%, p = .08) compared to WL, but had minimal impact on other measures. Differences between WL + VEST and WL were insignificant (all p > .05), but group comparisons showed improvements for WL + RT. Weight loss correlated with increased muscle density (r < 0, p < .001) but reduced muscle CSA and IMAT (r > 0, p < .001), indicating improved quality but reduced quantity. CONCLUSION:Our findings underscore the significance of weight loss-associated muscle loss, highlighting progressive RT as a minimally effective preservation strategy.

Assessments of 3D geometry, bone density distribution and bone strength improve hip fracture risk prediction but currently require the use of computed tomography (CT). 2D-to-3D statistical shape and appearance model (SSAM) reconstructions from dual-energy X-ray absorptiometry (DXA) projections have been proposed as surrogates for CT-based models. Several studies have used 3D-DXAs reconstructed by 3D-Shaper’s software method, but no study has independently cross-validated 3D-DXAs on in vivo clinical images. The first aim of this study was to evaluate the extent 3D-DXA is applicable across a diverse population. 120 paired DXA and CT images from three ethnicities (age: 20–85; aBMD:0.611–1.214 g/cm2) were analysed for differences in bone volume (BV), bone mineral content, vertex-to-surface distance, volumetric bone mineral density (vBMD) distribution and predicted bone strength. No subject or parameter groups showed outlier behaviour, as correlations for all results were above R2 > 0.76. However, differences were observed for volumetric measurements (BV: slope = 0.89, bias = 9.73 cm3; vBMD: slope = 0.88, bias = 6.27 g/cm3) and bone strength. To improve the performance, we introduced an image-processing pipeline (named as 3D-DXA*) that calibrated the linear-regression slopes and intercepts for BV, total vBMD and the minimum fall strength (N = 96). Validation results (N = 24) in 11 fall orientations showed successful correction of proportional bias to unitary slope and zero intercept (before: slopes = 0.62–0.79, bias = 0.44–0.86 kN; after: slopes = 0.88–1.03, bias = 0.12–0.70 kN). However, Pearson correlations degraded by 0.01–0.02 for 2 cases and prediction scatter (RMSE) expanded by 3–29% for 10 fall orientations. Sub-analysis showed 3D-DXA* reduced differences in vBMD distribution with the CT models, but cohort-specific differences remained. This is the first study to independently evaluate 3D-DXAs on multi-ethnic data across a wide age, including previously unstudied cohorts, and more than doubling the number of subjects used in prior validation works. These results provide detailed insights into the accuracy and limitations of DXA-based 3D reconstruction methods.

Introduction:The INVEST in Bone Health randomized controlled trial examined whether 1 year of weight loss paired with resistance training (WL+RT) or weighted vest use (WL+VEST) sustained bone mineral density (BMD) at the hip better than weight loss alone (WL). All groups lost similar amounts of body weight, but neither those wearing the vest nor those engaging in structured resistance training retained greater bone density relative to those in the weight loss-only condition. One possible reason for the absence of a group difference may be that the bone-sparing benefits of the weighted vest may relate to the amount of time one spends standing and therefore exposed to additional loading Purpose: The purpose of this secondary analysis was to determine whether the time an individual spent upright moderated the effect of the intervention on BMD at the hip. Methods:Older adults (mean age 66.9 ± 4.8 years) were eligible if they were living with obesity or who were both overweight with an indication for weight loss. Participants were randomized to one of the three WL interventions. Participants completed quantitative computed tomography (CT) and dual energy x-ray absorptiometry (DXA) assessments of hip BMD and wore an ActivPAL accelerometer to measure upright time for 1 week at baseline, 6, and 12 months. Results:In total 131 participants had sufficient DXA data and 132 and sufficient CT data for inclusion in linear mixed effects models. The model for DXA-derived hip areal BMD (aBMD) revealed a significant interaction between upright time and group assignment (p = 0.023) such that upright time was positively associated with baseline-adjusted change in aBMD in WL+VEST, but the opposite was true for WL (p = 0.009). The relationship between upright time and change in aBMD likewise differed significantly between WL+RT and WL (p = 0.043), as WL+RT demonstrated a less negative relationship than did WL. There were no significant interactions between group assignment and upright time for CT-derived measures of BMD. Conclusion:These results suggest a need for research investigating the efficacy of a weighted vest intervention paired with a focus on improving daily upright time for sustaining bone health among older adults as they lose weight.

Musculoskeletal pain and mobility disability are common in older adults, but relationships among pain parameters and physical performance are poorly understood. We quantified the impact of different pain measures—recalled and movement-evoked pain—on walk and stair climb time in older adults from the Study of Muscle, Mobility and Aging (SOMMA). In SOMMA (N = 879, age = 76.3 ± 5.0 years, 59

This study investigated how vehicle front-end geometry, impact speed, and vehicle category influence injury risk to a midsize male pedestrian. Eighty-one generic vehicle (GV) models representing sedans, sport utility vehicles (SUVs), pickup trucks, and minivans sold in the United States were developed by morphing three base models using an automated pipeline. Front-end parameters that were varied included ground clearance (GC), bumper height (BH), hood leading-edge (HLE) height, hood length (HL), bumper lead angle (BLA), hood angle (HA), and windshield angle (WSA). Each vehicle impacted the Global Human Body Models Consortium 50th percentile male simplified pedestrian (GHBMC M50-PS) model at 30, 40, and 50 kph, totaling 243 simulations. Boundary conditions followed the European New Car Assessment Program (Euro NCAP) pedestrian test protocol. Thirty-five injury metrics were extracted across the head, neck, thorax, abdomen, pelvis, and lower extremities. Linear mixed-effects regression models assessed relationships between vehicle front-end geometry, impact speed, and injury outcomes, with predictor selection guided by principal component analysis (PCA) and collinearity diagnostics. Impact speed was the strongest predictor of injury severity across all body regions. GC and HLE height were also dominant predictors. Wrap-type trajectories were common at lower speeds and in SUVs, trucks, and minivans, while sedans and minivans showed roof vaulting at higher speeds. Head injury severity increased with speed and was influenced by HA and BLA. Minivans showed elevated brain injury criterion (BrIC) and cumulative strain damage measure (CSDM25) values, indicating increased diffuse brain injury risk. Trucks produced the highest thoracoabdominal injury metrics, which correlated with HL, HA, femur forces than SUVs and minivans, and lowest tibia moments. Trucks had greater tibia bending moments, while SUVs and minivans had higher left femur moments compared to sedans. GC and impact speed exacerbated lower extremity injuries, varying by vehicle category. These effects are driven by geometry: Higher GC increases the unsupported span below the knee, promoting tibial bending, while lower HLE heights shift impact forces above the knee, elevating femur injury risk.

BACKGROUND:Machine learning applied to computed tomography (CT) images captures variations in skeletal muscle texture and structure not detectable by conventional measures. These novel 'radiomic' features may offer added value in predicting muscle function and physical performance beyond traditional CT-derived muscle area and density. We aimed to identify radiomic features of skeletal muscle associated with grip strength, leg power and walking speed in older men. METHODS:In the Osteoporotic Fractures in Men study (n = 3404; 73.8 ± 5.9 years), participants underwent baseline CT scans (trunk L1, L3; right and left thigh) and assessments of grip strength, 6 m walk and leg power (Nottingham Power Rig). Muscle area and density were derived from automatically segmented CT images. Radiomic features were extracted using PyRadiomics. Elastic net regression and factor analysis identified key radiomic features; associations with muscle function/performance were assessed using regression models. RESULTS:Factor analysis identified nine factors for Trunk-L1 and eight for the other regions. Trunk-based factors significantly improved model fit for leg power, grip strength and walking speed (P < .05). Factor 1, representing body size and muscle texture complexity, was the most consistent predictor across outcomes. The Gray-Level Co-occurrence Matrix feature 'cluster prominence' was inversely associated with walking speed (β = -0.06 at L1; -0.05 at L3) and leg power (β = -0.05 at L1), independent of age, height, weight, muscle CSA, muscle density and technical group. CONCLUSION:CT-derived radiomic features in the trunk region may reflect skeletal muscle structural characteristics that independently relate to strength, power and mobility in older men.

Pectus excavatum (PE) is the most common congenital chest wall deformity, characterized by a depression of the anterior chest wall which may compromise cardiac function and cause symptoms like exercise intolerance, chest pain, and shortness of breath. While diagnosis is often based on appearance, imaging-based metrics provide objective severity assessment. This study evaluated associations between PE severity indices and cardiac rotation angle in 37 adolescents generated two sex-specific anatomical models of severe cases for future diagnostic and treatment planning. Chest computed tomography (CT) scans of 30 male and seven female PE patients aged 12-16 years were analyzed to measure the Haller index, Correction index, and cardiac rotation angle. Severity by Haller index was classified as mild (2.0-3.2 cm,n= 15), moderate (3.2-3.5 cm,n= 7), or severe (>3.5 cm,n= 15). Cardiac rotation angle increased with severity (p= 0.001): mild (37.6 ± 13.1°), moderate (44.8 ± 13.6°), and severe (51 ± 13.2°). Cardiac rotation angle was positively associated with the Haller index (R2= 0.24,p= 0.002), but not the Correction index (R2= 0.01,p= 0.55). CT scans of a representative male and female were segmented to generate 3D models of thoracic and abdominal structures. These measurements and models may inform diagnostic criteria, treatment planning, and personalized device development for adolescents with PE.

As HR-pQCT increases in popularity for studying bone dynamics, it becomes increasingly important to quantify the factors that impact rigor and reproducibility in research, particularly for longitudinal studies. Previously reported data for HR-pQCT precision primarily use first-generation HR-pQCT, and focus on single operators, with narrow study populations that reflect the population of a larger research question. This study at a single academic imaging center with standardized, single-analyst post-processing was designed to investigate how operator characteristics in scan acquisition and participant demographics influence measurement precision. In total, 45 adults (58% female; 22-82 yr; BMI 18.4-44.8 kg/m2) underwent same-day repeat HR-pQCT scanning of the distal tibia and radius, with 3 imaging technologists each acquiring 15 participant scan pairs, and registration was applied in post-processing to accurately depict the standard workflow at the center. The root-mean-square coefficient of variation was ≤1.3% for BMD measures and <2% for area measures in both the radius and tibia. Trabecular microarchitecture ranged from 1.22% to 2.24% in the radius and from 1.14% to 2.82% in the tibia, while cortical thickness precision was calculated as 1.99% in the radius and 1.57% in the tibia. Cortical porosity was much higher, at 24.66% in the radius and 20.90% in the tibia. Significant differences were not found when analyzed by technologists, or in statistical modeling of participant demographics as potential covariates. While final image quality scores varied among technologists, it did not influence precision outcomes. These results offer reference values for the least significant change and demonstrate that standardized technologist training can yield consistent scan-rescan precision across operators.

Low BMD and impaired bone strength are established risk factors for fractures in older adults. Decreased muscle size also contributes to fracture risk; however, the relationship between muscle size and bone density, microarchitecture, and strength using state-of-the-art assessment methods is not clear. In The Study of Muscle, Mobility and Aging, muscle size was assessed using whole-body muscle mass (kg, deuterated creatine [D3Cr] dilution method) and thigh muscle volume (L, by MRI). We investigated cross-sectional associations between baseline D3Cr muscle mass and MRI thigh muscle volume with bone volumetric density, microarchitecture, and strength from HR-pQCT at the distal tibia (DT) and radius (DR), and hip areal BMD from DXA at the first annual follow-up visit (year 1). Muscle and bone parameters were standardized within sex and analyses were stratified by sex. Linear regression models were adjusted for age, race, weight, ≥1 alcoholic drink/wk, ever cigarette smoker, total activity from wrist-worn accelerometry, multimorbidity count (0-11), arthritis, and tibia or ulna length. In 181 women (age 76.2 ± 4.7 yr, 86% White) and 118 men (age 76.1 ± 4.3 yr, 93% White), higher thigh muscle volume (per SD: 1.1 L women; 1.5 L men) was associated with higher DT and DR failure load (p < .05). Greater thigh muscle volume was associated with higher DXA total hip BMD in men but not in women. Greater D3Cr muscle mass (per SD: 4.4 kg women; 5.5 kg men) was associated with higher DT and DR failure load (p < .05) in women only. Associations of muscle size with microarchitecture were variable and differed by sex. Given that failure load is a strong predictor of fracture risk, future studies should investigate whether interventions that target muscle size may impact fracture risk in older adults.

OBJECTIVE:Bone mineral density (BMD) and muscle health influence an occupant's tolerance to motor vehicle crash (MVC), and these musculoskeletal factors can be used to design more effective countermeasures. CT imaging routinely acquired during trauma evaluation can be leveraged to obtain volumetric (v)BMD and muscle metrics, yet extracting measurements manually from CT is time-consuming and inconsistent, typically limiting it to single anatomical regions. In this retrospective observational study, we applied an existing AI-based CT segmentation tool to characterize the musculoskeletal status of MVC occupants. METHODS:An external cohort of 55 adults with CT scans including a bone calibration phantom was used to validate the automated segmentation of trunk muscle cross-sectional area (CSA) and an automated tissue-calibrated method for vBMD. Agreement with manual CSA and phantom-calibrated vBMD was assessed via correlation and Bland-Altman analyses. The validated automated pipeline was then applied to 851 CT scans from Crash Injury Research and Engineering Network (CIREN) cases collected between 2005-2023. The Data Analysis and Facilitation Suite (v3.11.3, Voronoi Health Analytics) software was used to measure lumbar spine (L1-L4), pelvis, femur head, femur neck and femur trochanter + shaft vBMD, as well as trunk muscle CSA and density. Sarcopenia was defined as a trunk muscle CSA divided by height squared <38.5 cm2/m2 for females and <52.4 cm2/m2 for males. Osteopenia was defined as lumbar spine vBMD <145 mg/cm3. These characteristics were examined in association to regional fracture count with abbreviated injury scale (AIS) severity and injury severity score (ISS) using negative binominal regression, including crash variables (delta-V, belt status, driver status, airbag deployment, principal direction of force, model year, curb weight) and occupant characteristics (age, sex, height, weight). RESULTS:In the validation cohort (64% female; ages 66 ± 4), automated and manual trunk muscle CSA measurements agreed (r = 0.996; p < 0.0001), with small average differences (-4.9 cm2). Automated tissue-calibrated lumbar vBMD closely matched phantom-calibrated values (r = 0.938, mean difference -0.21 mg/cm³), and femur regions showed similar agreement (correlation = 0.865-0.927; all p < 0.0001).In CIREN occupants (56% female; ages 47 ± 20), 31% had sarcopenia, 28% had osteopenia, and 14% osteosarcopenia according to the CT-based definitions. vBMD declined with age across all regions (all p < 0.0001). Lower vBMD was associated with higher ISS in the pelvis (p = 0.003), femur head (p < 0.0001), femur neck (p < 0.0001), and trochanter + shaft (p = 0.00087). Additionally, a 10 mg/cm³ higher femur head vBMD was associated with 1.6% fewer AIS 2 fractures (p-value = 0.005). CONCLUSIONS:Application of an AI-based segmentation platform to MVC CT scans demonstrated that compromised musculoskeletal tissue quality is common and associated with fractures and injury severity beyond traditional occupant and crash characteristics. This suggests that musculoskeletal profiling can inform MVC injury prevention, occupant protection design, and post-crash care strategies.

Age-related changes to BMD, morphometry, and microarchitecture do not occur uniformly across the population and the common skeletal phenotypes beyond BMD are not well defined. Additionally, the associations between bone and muscle are critical to understanding fall and fracture risk. We hypothesized that unsupervised clustering of High Resolution-peripheral Quantitative Computed Tomography (HR-pQCT) measures at the distal tibia (DT) and radius (DR), separately, would reveal unique skeletal phenotypes; and certain phenotypes would be associated with worse muscle function. In the Study of Muscle, Mobility and Aging (SOMMA; first annual follow-up visit), a cohort of community-dwelling older women and men (61% women; 87% White), HR-pQCT parameters acquired at the DT (N = 321; 76.3 ± 4.6 yr) and DR (N = 295; 76.1 ± 4.5 yr) were standardized within-sex then combined to form clusters. This resulted in 3 phenotypic clusters, (C1) high total BMD (Tt.BMD) and cortical area (Ct.Ar); (C2) medium Tt.BMD, Ct.Ar and low trabecular BMD (Tb.BMD); and (C3) low Tt.BMD, and Ct.Ar. DT C2 and C3 exhibited lower micro finite element analysis failure loads, with the cortical load fraction higher in C2 and lower in C3. C2 and C3 both had a similar proportion of osteoporotic and osteopenic/low bone density individuals, highlighting the novel granularity of HR-pQCT clusters vs. aBMD clinical cutoffs. In linear regression models for women, DT C3 was associated with lower leg power (p < .05). For men, DT C3 was associated with lower stair climb and leg power (p < .05). No significant difference was found in grip strength between DT clusters. For DR, no significant difference or association was found between muscle function and clusters for women and men. These findings suggest the concept of bone phenotypic-specific associations with lower but not upper extremity muscle function and have possible implications for the interaction between skeletal phenotypes and muscle function as potential contributory factors to fracture risk.

Importance:Weight loss (WL) in older adults is associated with bone loss, increasing the risk of fracture. Because skeletal tissue is responsive to mechanical stress, replacing lost weight externally may be an innovative way to minimize WL-associated bone loss in this population. Objective:To examine the effect of 12 months of weighted vest use during WL on indicators of bone health compared with WL alone and WL plus resistance training (RT). Design, Setting, and Participants:This single-blind, 12-month randomized clinical trial of older adults living with obesity was conducted at an academic medical center from September 1, 2019, to April 30, 2024. Interventions:WL (caloric restriction targeting 10% WL with adequate calcium, vitamin D, and protein), WL plus weighted vest (WL+VEST; 8 h/d, weight replacement titrated up to 10% total WL), or WL plus progressive RT (WL+RT; supervised 3 sessions weekly). Main Outcomes and Measures:Main outcomes included 12-month change in computed tomography-acquired trabecular volumetric bone mineral density (vBMD) and dual-energy X-ray absorptiometry-acquired areal bone mineral density (aBMD) of the total hip. Secondary outcomes included change in additional computed tomography- and dual-energy X-ray absorptiometry-acquired measures of musculoskeletal health and bone turnover biomarkers. Results:A total of 150 older (mean [SD] age, 66.4 [4.6] years) adults (112 [74.7%] women) living with obesity (mean [SD] body mass index, 33.6 [3.3]) were randomized (50 to WL, 50 to WL+VEST, and 50 to WL+RT), with 133 (88.7%) completing the trial. Similar significant WL, ranging from 9.0% to 11.2%, was achieved in all groups. During 12 months, mean (SD) self-reported weighted vest wear time was 7.1 (1.5) h/d, with 78.0% (29.9%) of lost weight replaced in the vest; participants randomized to the WL+RT group attended a mean (SD) of 71.4% (19.1%) of sessions. A significant decrease in total hip trabecular vBMD was observed at 12 months in all treatment groups (ranging from -1.2% to -1.9%), with no difference between the WL+VEST and WL groups (estimated treatment difference, +0.91 mg/cm3; 97.5% CI, -0.27 to 2.09 mg/cm3; P = .13) and noninferiority of WL+VEST compared with WL+RT (estimated treatment difference, +0.29 mg/cm3; 98.75% lower bound, -1.05 mg/cm3). Similar effects were observed for total hip aBMD. Conclusions and Relevance:In this 12-month randomized clinical trial, neither weighted vest use nor progressive RT was able to mitigate WL-associated bone loss at the hip in older adults living with obesity. This study highlights the need for alternative or adjunctive strategies to prevent bone loss in older adults experiencing WL because exercise may be insufficient on its own. Trial Registration:ClinicalTrials.gov Identifier: NCT04076618.

OBJECTIVE:The objective of this study was to examine associations of computed tomography (CT)-derived musculoskeletal measures with demographics and traditional musculoskeletal characteristics. METHODS:The Incorporating Nutrition, Vests, Education, and Strength Training (INVEST) in Bone Health trial (NCT04076618) acquired a battery of musculoskeletal measures in 150 older-aged adults living with overweight or obesity. At baseline, CT (i.e., volumetric bone mineral density, cortical thickness, muscle radiomics, and muscle/intermuscular adipose tissue [IMAT] area and density), dual-energy x-ray absorptiometry (DXA; i.e., areal bone mineral density, total body fat mass, appendicular lean mass, and lean body mass), and strength assessments (i.e., grip and knee extensor strength) were collected, along with demographic and clinical characteristics. Analyses employed linear regression and mixed-effects models along with factor analysis for dimensionality reduction of the radiomics data. RESULTS:Participants were older-aged (mean [SD] age: 66 [5] years), mostly female (75%), and were living with overweight or obesity (mean [SD] BMI: 33.6 [3.3] kg/m2). Age was not significantly associated with most CT-derived bone, IMAT, or muscle measures. BMI was significantly associated with DXA and CT-derived muscle and IMAT measures, which were higher in male than female individuals (all p < 0.01). For the midthigh, muscle size was significantly related to grip and knee extensor strength (both p < 0.01). CONCLUSIONS:Machine learning-derived CT metrics correlated strongly with DXA and muscle strength, with higher BMI linked to greater IMAT and poorer muscle quality.

BACKGROUND:The automated segmentation of computed tomography (CT) images has made their opportunistic use more feasible, yet, the association of muscle area and density from multiple anatomical regions with functional outcomes and mortality risk in older adults has not been fully explored. We aimed to determine if muscle area and density at the L1 and L3 vertebra and right and left proximal thigh were similarly related to functional outcomes and 10-year mortality risk. METHODS:Men from the Osteoporotic Fractures in Men (MrOS) study who had CT images, measures of grip strength, 6 m walking speed, and leg power (Nottingham Power Rig) at the baseline visit were included in the analyses (n = 3290, 73.7 ± 5.8 years). CT images were automatically segmented to derive muscle area and muscle density. Deaths were centrally adjudicated over a 10-year follow-up. Linear regression and proportional hazards were used to model relationships of CT muscle metrics with functional outcomes and mortality, respectively, while adjusting for covariates. RESULTS:Muscle area and density were positively related to functional outcomes regardless of anatomical region, with the most variance explained in leg power (adjusted R 2 = 0.40-0.46), followed by grip strength (adjusted R 2 = 0.25-0.29) and walking speed (adjusted R 2 = 0.18-0.20). A one-unit SD increase in muscle area and density was associated with a 5%-13% and 8%-21% decrease in the risk of all-cause mortality, respectively, with the strongest associations observed at the right and left thigh. CONCLUSION:Automated measures of CT muscle area and density are related to functional outcomes and risk of mortality in older men, regardless of CT anatomical region.

OBJECTIVE:Distal tibia fractures occur in approximately 4% of police-reported crashes where at least 1 vehicle was towed in the U.S., and frequently result in complications like infection, nonunion, and osteoarthritis. This study used real-world crash data to train a random forest algorithm to predict distal tibia fracture types, identifying key demographic, vehicle, and crash factors contributing to the model predictions. METHODS:Crash Injury Research and Engineering Network (CIREN) cases (2005-2024) with computed tomography (CT) radiology of a distal tibia fracture were identified. Frontal, non-rollover crashes with non-pregnant, non-ejected occupants older than 13 years were selected, resulting in 94 cases (90 unilateral, 2 bilateral fractures) included for analysis. Fractures were labeled by 3 trained researchers as extraarticular, partial articular, or complete articular using the AO Foundation-Orthopedic Trauma Association (AO/OTA) compendium, which has an established relationship with clinical outcomes. An orthopedic surgeon graded a subset (N = 20) for validation. CIREN injury mechanisms and contributing factors - delta-v, vehicle model year, body type, and safety restraints, as well as occupant age, sex, BMI, and comorbidities - were collected to train a random forest classifier to predict AO/OTA fracture type. SHapley Additive exPlanations were used to examine how demographic, vehicle, and crash factors influenced the probability of random forest predictions, which allowed for the association of key factors from real-world crash data with AO/OTA fracture types. RESULTS:The agreement between the 3 graders (Fleiss' Kappa of 0.78) and between the ground truth classifications and the orthopedic surgeon (Cohen's Kappa of 0.76) were substantial. Random forest correctly determined the AO/OTA distal tibia fracture type in 75.5% of cases. Toe-pan intrusion as a contributing factor and delta-v greater than 30 kph were associated with increased random forest prediction probability of complete articular fractures. Knee bolster airbag deployment was associated with decreased probability of partial articular fractures, often linked with rotational injury mechanisms, suggesting they induce increased mechanisms of compression. Concomitantly, the random forest found that rotational mechanisms were associated with increased probability of partial articular fractures. CONCLUSIONS:Despite not using radiology, the random forest predicted distal tibia fracture type with similar accuracy to human graders, demonstrating the potential to support in areas like post-crash triage. Finally, the random forest characterized underlying relationships between factors from real-world crash data and AO/OTA fracture types, demonstrating its usefulness as an explanatory model.

Higher cardiorespiratory fitness may be associated with better bone health in older age, though this has not been investigated using state-of-the-science VO2peak and HR-pQCT bone density, strength, and microarchitecture measures. We found that higher VO2peak associated with higher bone strength in men, but not women, which may inform fracture prevention interventions. Maintaining cardiorespiratory fitness among older adults holds potential benefits for bone health, though this association has not been investigated using gold-standard measures of VO2peak and state-of-the-science measures of bone density, strength, and microarchitecture. Participants included 123 men (age 76.2 ± 4.4 years, 93