Comparison of QCT and DEXA findings for lumbar vertebra in young adults and the elderly.

BACKGROUND: The use of dual-energy X-ray absorptiometry (DEXA) and quantitative computed tomography (QCT) methods are important for the diagnosis and follow-up of osteoporosis, and are used especially in cases to determine the degree of osteoporosis and the risk of fracture, monitoring the effectiveness of the treatment applied. PURPOSE: To compare the parameters measured using the DEXA method from the lumbar (L1-L4) vertebrae and the Hounsfield unit (HU) values measured with QCT at the same levels among young adults and the elderly. MATERIAL AND METHODS: The study included 155 patients (age range = 26-93 years). A total of 57 (36.8%) patients (age range = 26-64 years) were defined as the first group, and 98 (63.2%) patients (aged ≥65 years) were defined as the second group. T-test and correlation analysis were performed to compare bone mineral density (BMD), T score, and HU values measured using DEXA and QCT. RESULTS: A statistically significant difference was found between T score, lumbar total BMD, and HU values according to age and sex (P < 0.05). When the values measured from lumbar vertebrae were compared using both DEXA and CT, a high correlation was found between them. CONCLUSION: In the study, it was observed that QCT attenuation measurements of the lumbar spine measured between different age groups provided reliable results in terms of BMD scanning, as in DEXA. It should be noted that QCT has a longer imaging time and higher radiation dose compared to DEXA, and unnecessary scans should be avoided.

Osteoporotic Fractures: Diagnosis, Evaluation, and Significance From the International Working Group on DXA Best Practices.

Osteoporotic fractures, also known as fragility fractures, are reflective of compromised bone strength and are associated with significant morbidity and mortality. Such fractures may be clinically silent, and others may present clinically with pain and deformity at the time of the injury. Unfortunately, and even at the time of detection, most individuals sustaining fragility fractures are not identified as having underlying metabolic bone disease and are not evaluated or treated to reduce the incidence of future fractures. A multidisciplinary international working group with representation from international societies dedicated to advancing the care of patients with metabolic bone disease has developed best practice recommendations for the diagnosis and evaluation of individuals with fragility fractures. A comprehensive narrative review was conducted to identify key articles on fragility fractures and their impact on the incidence of further fractures, morbidity, and mortality. This document represents consensus among the supporting societies and harmonizes best practice recommendations consistent with advances in research. A fragility fracture in an adult is an important predictor of future fractures and requires further evaluation and treatment of the underlying osteoporosis. It is important to recognize that most fragility fractures occur in patients with bone mineral density T scores higher than -2.5, and these fractures confirm the presence of skeletal fragility even in the presence of a well-maintained bone mineral density. Fragility fractures require further evaluation with exclusion of contributing factors for osteoporosis and assessment of clinical risk factors for fracture followed by appropriate pharmacological intervention designed to reduce the risk of future fracture. Because most low-trauma vertebral fractures do not present with pain, dedicated vertebral imaging and review of past imaging is useful in identifying fractures in patients at high risk for vertebral fractures. Given the importance of fractures in confirming skeletal fragility and predicting future events, it is recommended that an established classification system be used for fracture identification and reporting.

A comparison between IBEX bone health applied to digital radiographs and dual-energy X-ray absorptiometry at the distal-third and ultra-distal regions of the radius.

BACKGROUND: In an ageing population, low impact fragility fractures are becoming increasingly common. However, fracture risk can be reduced where low bone density can be identified at an early stage. In this study we aim to demonstrate that IBEX Bone Health (IBEX BH) can provide a clinically useful prediction from wrist radiographs of aBMD and T-score at the ultra-distal (UD) and distal-third (DT) regions of the radius. METHODS: A 261-participant single-centre, non-randomised, prospective, study was carried out to compare a) IBEX BH, a quantitative digital radiography software device, to b) Dual-energy X-ray Absorptiometry (DXA). A total of 257 participants with wrist digital radiograph (DR), forearm DXA pairs were included in the analysis after exclusions. RESULTS: The adjusted R2 value for IBEX BH outputs to the radial areal bone mineral density (aBMD) produced by a GE Lunar DXA system for the UD region is 0.87 (99% Confidence Interval (CI) [0.84, 0.89]). The adjusted R2 value for IBEX BH outputs to aBMD for the DT region is 0.88 (99% CI [0.85, 0.90]). The Area Under the Receiver Operating Characteristic curve (AUC) for the forearm T-score ≤ - 2.5 risk prediction model at the UD region is 0.95 (99% CI [0.93, 0.98]). The AUC for the forearm T-score ≤ - 2.5 risk prediction model at the DT region is 0.98 (99% CI [0.97, 0.99]). CONCLUSION: From a DR of the wrist, IBEX BH provides a clinically useful i) estimate of aBMD at the two regions of interest on the radius and ii) risk prediction model of forearm T-score ≤ - 2.5 at the UD and DT regions.

Quantitative measurements of dual-energy CT parameters in the diagnosis of osteoporosis - a highly sensitive and specific technique: An observational study.

With the aging of the population in our society, osteoporosis (OP) has become one of the chronic diseases that seriously threaten the physical health of the elderly, leading to a heavy burden on healthcare. In recent years, with the continuous development of dual-energy CT (DECT) technology, quantitative measurements of DECT parameters, which is highly sensitive to OP, provides accurate results, is convenient and cost-effective, and is expected to be widely used in bone density testing. This study was aimed to explore the value of quantitative measurements of DECT parameters in diagnosing OP, in order to better guide clinical judgments and treatment. A total of 187 patients who underwent dual-energy X-ray and DECT examinations at Tianjin hospital between January 2022 and June 2023 were included as participants in this study. The bone mineral density (BMD) values of the lumbar spine (L1-L4) were determined using dual-energy X-ray absorptiometry. Simultaneously, CT scans of the lumbar spine (L1-L4) were conducted to measure the CT values of contrast media (CM), mixed-energy image CT values (regular CT value [rCT]), calcium concentration (CaD), as well as fat fraction (FF). Pearson correlation analysis was used to examine the relationship between the quantitative measurements of L1 to L4 vertebral bodies obtained from DECT and BMD. The values of CM, rCT, and CaD in the OP group were all lower than those in the non-OP group with statistical significance (P < .001). Conversely, the fat fraction parameter value in the OP group was significantly higher in contrast with the non-OP group (P = .004); there was a positive correlation between CM, rCT, CaD, and BMD values (R = 0.579, P < .001; R = 0.604, P < .001; R = 0.563, P < .001); CM, rCT, and CaD had high diagnostic value for OP, as evidenced by AUCs of 0.935 (95% CI: 0.900-0.971), 0.956 (95% CI: 0.925-0.987), and 0.926 (95% CI: 0.858-0.954), respectively, all with P values < .001. Quantitative measurement of DECT parameters showed a high sensitivity as well as a high specificity in the diagnosis of OP. It is also highly feasible and holds significant clinical diagnostic value, making it a suitable candidate for widespread application.

Correlation between serum trimethylamine-N-oxide and body fat distribution in middle-aged and older adults: a prospective cohort study.

BACKGROUND: Trimethylamine-N-oxide (TMAO) is linked with obesity, while limited evidence on its relationship with body fat distribution. Herein, we investigated the associations between serum TMAO and longitudinal change of fat distribution in this prospective cohort study. METHODS: Data of 1964 participants (40-75y old) from Guangzhou Nutrition and Health Study (GNHS) during 2008-2014 was analyzed. Serum TMAO concentration was quantified by HPLC-MS/MS at baseline. The body composition was assessed by dual-energy X-ray absorptiometry at each 3-y follow-up. Fat distribution parameters were fat-to-lean mass ratio (FLR) and trunk-to-leg fat ratio (TLR). Fat distribution changes were derived from the coefficient of linear regression between their parameters and follow-up duration. RESULTS: After an average of 6.2-y follow-up, analysis of covariance (ANCOVA) and linear regression displayed women with higher serum TMAO level had greater increments in trunk FLR (mean ± SD: 1.47 ± 4.39, P-trend = 0.006) and TLR (mean ± SD: 0.06 ± 0.24, P-trend = 0.011). Meanwhile, for women in the highest TMAO tertile, linear mixed-effects model (LMEM) analysis demonstrated the annual estimated increments (95% CI) were 0.03 (95% CI: 0.003 - 0.06, P = 0.032) in trunk FLR and 1.28 (95% CI: -0.17 - 2.73, P = 0.083) in TLR, respectively. In men, there were no similar significant observations. Sensitivity analysis yielded consistent results. CONCLUSION: Serum TMAO displayed a more profound correlation with increment of FLR and TLR in middle-aged and older community-dwelling women in current study. More and further studies are still warranted in the future. TRIAL REGISTRATION: NCT03179657.

Machine learning allows robust classification of visceral fat in women with obesity using common laboratory metrics.

The excessive accumulation and malfunctioning of visceral adipose tissue (VAT) is a major determinant of increased risk of obesity-related comorbidities. Thus, risk stratification of people living with obesity according to their amount of VAT is of clinical interest. Currently, the most common VAT measurement methods include mathematical formulae based on anthropometric dimensions, often biased by human measurement errors, bio-impedance, and image techniques such as X-ray absorptiometry (DXA) analysis, which requires specialized equipment. However, previous studies showed the possibility of classifying people living with obesity according to their VAT through blood chemical concentrations by applying machine learning techniques. In addition, most of the efforts were spent on men living with obesity while little was done for women. Therefore, this study aims to compare the performance of the multilinear regression model (MLR) in estimating VAT and six different supervised machine learning classifiers, including logistic regression (LR), support vector machine and decision tree-based models, to categorize 149 women living with obesity. For clustering, the study population was categorized into classes 0, 1, and 2 according to their VAT and the accuracy of each MLR and classification model was evaluated using DXA-data (DXAdata), blood chemical concentrations (BLDdata), and both DXAdata and BLDdata together (ALLdata). Estimation error and R 2 were computed for MLR, while receiver operating characteristic (ROC) and precision-recall curves (PR) area under the curve (AUC) were used to assess the performance of every classification model. MLR models showed a poor ability to estimate VAT with mean absolute error ≥ 401.40 and R 2 ≤ 0.62 in all the datasets. The highest accuracy was found for LR with values of 0.57, 0.63, and 0.53 for ALLdata, DXAdata, and BLDdata, respectively. The ROC AUC showed a poor ability of both ALLdata and DXAdata to distinguish class 1 from classes 0 and 2 (AUC = 0.31, 0.71, and 0.85, respectively) as also confirmed by PR (AUC = 0.24, 0.57, and 0.73, respectively). However, improved performances were obtained when applying LR model to BLDdata (ROC AUC ≥ 0.61 and PR AUC ≥ 0.42), especially for class 1. These results seem to suggest that, while a direct and reliable estimation of VAT was not possible in our cohort, blood sample-derived information can robustly classify women living with obesity by machine learning-based classifiers, a fact that could benefit the clinical practice, especially in those health centres where medical imaging devices are not available. Nonetheless, these promising findings should be further validated over a larger population.

Performance of Microsoft Azure Kinect DK as a tool for estimating human body segment lengths.

The Microsoft Kinect depth sensor, with its built-in software that automatically captures joint coordinates without markers, could be a potential tool for ergonomic studies. This study investigates the performance of Kinect in limb segment lengths using dual-energy X-ray absorptiometry (DXA) as a reference. Healthy children and adults (n = 76) were recruited for limb length measurements by Kinect and DXA. The results showed consistent ratios of arm, forearm, thigh, and leg lengths to height, which were 0.16, 0.14, 0.23, and 0.22 respectively, for both age groups and methods. Kinect exhibited perfect correlation among all limb lengths, indicating fixed proportions assumed by its algorithm. Comparing the two methods, there was a strong correlation (R = 0.850-0.985) and good to excellent agreement (ICC = 0.829-0.977), except for the right leg in adults, where agreement was slightly lower but still moderate (ICC = 0.712). The measurement bias between the methods ranged from - 1.455 to 0.536 cm. In conclusion, Kinect yields outcomes similar to DXA, indicating its potential utility as a tool for ergonomic studies. However, the built-in algorithm of Kinect assumes fixed limb proportions for individuals, which may not be ideal for studies focusing on investigating limb discrepancies or anatomical differences.

Vertebral HU value and the pectoral muscle index based on chest CT can be used to opportunistically screen for osteoporosis.

BACKGROUND: Existing studies have shown that computed tomography (CT) attenuation and skeletal muscle tissue are strongly associated with osteoporosis; however, few studies have examined whether vertebral HU values and the pectoral muscle index (PMI) measured at the level of the 4th thoracic vertebra (T4) are strongly associated with bone mineral density (BMD). In this study, we demonstrate that vertebral HU values and the PMI based on chest CT can be used to opportunistically screen for osteoporosis and reduce fracture risk through prompt treatment. METHODS: We retrospectively evaluated 1000 patients who underwent chest CT and DXA scans from August 2020-2022. The T4 HU value and PMI were obtained using manual chest CT measurements. The participants were classified into normal, osteopenia, and osteoporosis groups based on the results of dual-energy X-ray (DXA) absorptiometry. We compared the clinical baseline data, T4 HU value, and PMI between the three groups of patients and analyzed the correlation between the T4 HU value, PMI, and BMD to further evaluate the diagnostic efficacy of the T4 HU value and PMI for patients with low BMD and osteoporosis. RESULTS: The study ultimately enrolled 469 participants. The T4 HU value and PMI had a high screening capacity for both low BMD and osteoporosis. The combined diagnostic model-incorporating sex, age, BMI, T4 HU value, and PMI-demonstrated the best diagnostic efficacy, with areas under the receiver operating characteristic curve (AUC) of 0.887 and 0.892 for identifying low BMD and osteoporosis, respectively. CONCLUSIONS: The measurement of T4 HU value and PMI on chest CT can be used as an opportunistic screening tool for osteoporosis with excellent diagnostic efficacy. This approach allows the early prevention of osteoporotic fractures via the timely screening of individuals at high risk of osteoporosis without requiring additional radiation.

[Bone mineral density in women with rheumatoid arthritis: A link between immune and biochemical markers].

AIM: To study the association of bone mineral density (BMD) with serum biochemical and immunological markers in postmenopausal women with rheumatoid arthritis (RA). MATERIALS AND METHODS: The study included 173 women with RA (age 61.0 [56.0; 66.0] years). A survey, dual-energy X-ray absorptiometry to measure the BMD of the lumbar spine (LI-LIV), femoral neck (FN) and total hip (TH), routine blood chemistry, measurement of C-reactive protein (CRP), rheumatoid factor, cyclic citrullinated peptide antibodies (CCPA), parathyroid hormone (PTH), vitamin D3, myostatin, follistatin, interleukin-6 (IL-6), IL-6 receptors, insulin-like growth factor 1, adiponectin, leptin, fibroblast growth factor 23, and tumor necrosis factor SF12 were performed. RESULTS: PTH (ß=-0.22, -0.35 and -0.30 for LI-LIV, FN and TH, respectively), CRP (ß=-0.18, 0.23 and -0.22 for LI-LIV, FN and TH, respectively) and leptin (ß=0.35, 0.32 and 0.42 for LI-LIV, FN and TH, respectively) were shown a significant association with BMD in all sites of measurement. It was independent of age, body mass index and postmenopause duration. Associations were also found between adiponectin and BMD of LI-LIV and TH (ß=-0.36 and -0.28, respectively), CCPA and BMD of FN and TH (ß=-0.21, -0.24, respectively) and IL-6 and BMD of FN (ß=0.37). CONCLUSION: The study of biochemical and immunological markers in women with RA demonstrated that CRP, CCPA, PTH, IL-6, adiponectin, and leptin influenced BMD.

Radiofrequency echographic multi spectrometry (REMS) in the diagnosis and management of osteoporosis: state of the art.

Radiofrequency Echographic Multi Spectrometry (REMS) is a radiation-free, portable technology, which can be used for the assessment and monitoring of osteoporosis at the lumbar spine and femoral neck and may facilitate wider access to axial BMD measurement compared with standard dual-energy x-ray absorptiometry (DXA).There is a growing literature demonstrating a strong correlation between DXA and REMS measures of BMD and further work supporting 5-year prediction of fracture using the REMS Fragility Score, which provides a measure of bone quality (in addition to the quantitative measure of BMD).The non-ionising radiation emitted by REMS allows it to be used in previously underserved populations including pregnant women and children and may facilitate more frequent measurement of BMD.The portability of the device means that it can be deployed to measure BMD for frail patients at the bedside (avoiding the complications in transfer and positioning which can occur with DXA), in primary care, the emergency department, low-resource settings and even at home.The current evidence base supports the technology as a useful tool in the management of osteoporosis as an alternative to DXA.

Osteoporotic Precise Screening Using Chest Radiography and Artificial Neural Network: The OPSCAN Randomized Controlled Trial.

Background Diagnosing osteoporosis is challenging due to its often asymptomatic presentation, which highlights the importance of providing screening for high-risk populations. Purpose To evaluate the effectiveness of dual-energy x-ray absorptiometry (DXA) screening in high-risk patients with osteoporosis identified by an artificial intelligence (AI) model using chest radiographs. Materials and Methods This randomized controlled trial conducted at an academic medical center included participants 40 years of age or older who had undergone chest radiography between January and December 2022 without a history of DXA examination. High-risk participants identified with the AI-enabled chest radiographs were randomly allocated to either a screening group, which was offered fully reimbursed DXA examinations between January and June 2023, or a control group, which received usual care, defined as DXA examination by a physician or patient on their own initiative without AI intervention. A logistic regression was used to test the difference in the primary outcome, new-onset osteoporosis, between the screening and control groups. Results Of the 40 658 enrolled participants, 4912 (12.1%) were identified by the AI model as high risk, with 2456 assigned to the screening group (mean age, 71.8 years ± 11.5 [SD]; 1909 female) and 2456 assigned to the control group (mean age, 72.1 years ± 11.8; 1872 female). A total of 315 of 2456 (12.8%) participants in the screening group underwent fully reimbursed DXA, and 237 of 315 (75.2%) were identified with new-onset osteoporosis. After including DXA results by means of usual care in both screening and control groups, the screening group exhibited higher rates of osteoporosis detection (272 of 2456 [11.1%] vs 27 of 2456 [1.1%]; odds ratio [OR], 11.2 [95% CI: 7.5, 16.7]; P < .001) compared with the control group. The ORs of osteoporosis diagnosis were increased in screening group participants who did not meet formalized criteria for DXA compared with those who did (OR, 23.2 [95% CI: 10.2, 53.1] vs OR, 8.0 [95% CI: 5.0, 12.6]; interactive P = .03). Conclusion Providing DXA screening to a high-risk group identified with AI-enabled chest radiographs can effectively diagnose more patients with osteoporosis. Clinical trial registration no. NCT05721157 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Smith and Rothenberg in this issue.

Can we screen opportunistically for low bone mineral density using CT scans of the shoulder and artificial intelligence?

OBJECTIVE: To evaluate whether the CT attenuation of bones seen on shoulder CT scans could be used to predict low bone mineral density (BMD) (osteopenia/osteoporosis), and to compare the performance of two machine learning models to predict low BMD. METHODS: In this study, we evaluated 194 patients aged 50 years or greater (69.2 ± 9.1 years; 170 females) who underwent unenhanced shoulder CT scans and dual-energy X-ray absorptiometry within 1 year of each other between January 1, 2010, and December 31, 2021. The CT attenuation of the humerus, glenoid, coracoid, acromion, clavicle, first, second, and third ribs was obtained using 3D-Slicer. Support vector machines (SVMs) and k-nearest neighbours (kNN) were used to predict low BMD. DeLong test was used to compare the areas under the curve (AUCs). RESULTS: A CT attenuation of 195.4 Hounsfield Units of the clavicle had a sensitivity of 0.577, specificity of 0.781, and AUC of 0.701 to predict low BMD. In the test dataset, the SVM had sensitivity of 0.686, specificity of 1.00, and AUC of 0.857, while the kNN model had sensitivity of 0.966, specificity of 0.200, and AUC of 0.583. The SVM was superior to the CT attenuation of the clavicle (P = .003) but not better than the kNN model (P = .098). CONCLUSION: The CT attenuation of the clavicle was best for predicting low BMD; however, a multivariable SVM was superior for predicting low BMD. ADVANCES IN KNOWLEDGE: SVM utilizing the CT attenuations at many sites was best for predicting low BMD.

Computed tomography-based structural rigidity analysis can assess tumor- and treatment-induced changes in rat bones with metastatic lesions.

BACKGROUND: Breast cancer (BrCa) is a predominant malignancy, with metastasis occurring in one in eight patients, nearly half of which target the bone, leading to serious complications such as pain, fractures, and compromised mobility. Structural rigidity, crucial for bone strength, becomes compromised with osteolytic lesions, highlighting the vulnerability and increased fracture risk in affected areas. Historically, two-dimensional radiographs have been employed to predict these fracture risks; however, their limitations in capturing the three-dimensional structural and material changes in bone have raised concerns. Recent advances in CT-based Structural Rigidity Analysis (CTRA), offer a promising, more accurate non-invasive 3D approach. This study aims to assess the efficacy of CTRA in monitoring osteolytic lesions' progression and response to therapy, suggesting its potential superiority over existing methodologies in guiding treatment strategies. METHODS: Twenty-seven female nude rats underwent femoral intra-medullary inoculation with MDA-MB-231 human breast cancer cells or saline control. They were divided into Control, Cancer Control, Ibandronate, and Paclitaxel groups. Osteolytic progression was monitored weekly using biplanar radiography, quantitative computed tomography (QCT), and dual-energy X-ray absorptiometry (DEXA). CTRA was employed to predict fracture risk, normalized using the contralateral femur. Statistical analyses, including Kruskal-Wallis and ANOVA, assessed differences in outcomes among groups and over time. RESULTS: Biplanar radiographs showed treatment benefits over time; however, only certain time-specific differences between the Control and other treatment groups were discernible. Notably, observer subjectivity in X-ray scoring became evident, with significant inter-operator variations. DEXA measurements for metaphyseal Bone Mineral Content (BMC) did not exhibit notable differences between groups. Although diaphyseal BMC highlighted some variance, it did not reveal significant differences between treatments at specific time points, suggesting a limited ability for DEXA to differentiate between treatment effects. In contrast, the CTRA consistently demonstrated variations across different treatments, effectively capturing bone rigidity changes over time, and the axial- (EA), bending- (EI), and torsional rigidity (GJ) outcomes from the CTRA method successfully distinguished differences among treatments at specific time points. CONCLUSION: Traditional approaches, such as biplanar radiographs and DEXA, have exhibited inherent limitations, notably observer bias and time-specific inefficacies. Our study accentuates the capability of CTRA in capturing real-time, progressive changes in bone structure, with the potential to predict fractures more accurately and provide a more objective analysis. Ultimately, this innovative approach may bridge the existing gap in clinical guidelines, ushering in enhanced Clinical Decision Support Tool (CDST) for both surgical and non-surgical treatments.

Patients with Periprosthetic Femoral Hip Fractures are Commonly Classified as Having Osteoporosis Based on DXA Measurements.

Periprosthetic femoral hip fractures are subject to an increasing incidence and are often considered to be related to osteoporosis. However, there are no available studies that have determined the frequency of osteoporosis in affected patients using gold standard dual-energy X-ray absorptiometry (DXA). In this retrospective comparative study, we analyzed the DXA results of 40 patients with periprosthetic femoral hip fractures who were treated surgically in our department. DXA measurements were performed at the total hip and the lumbar spine to determine bone mineral density T-scores. Data were compared to two age-, sex-, and BMI-matched control groups in which patients underwent DXA prior to aseptic revision surgery for other causes or primary THA (consisting of 40 patients each). The mean T-score in the periprosthetic fracture cohort was significantly lower (- 1.78 ± 1.78) than that of the aseptic revision (- 0.65 ± 1.58, mean difference - 1.13 [95% CI - 1.88 to - 0.37]; p = 0.001) and the primary THA cohort (- 0.77 ± 1.34, mean difference - 1.01 [95% CI - 1.77 to - 0.26]; p = 0.005). Accordingly, osteoporosis was detected more frequently (45%) in the fracture cohort compared to patients undergoing aseptic revision (12.5%) and primary THA (10%). In conclusion, almost half of the patients with periprosthetic femoral hip fractures have osteoporosis according to DXA measurements. A regular assessment of bone health in THA enables identification of patients with osteoporosis who likely benefit from initiation of osteoporosis medication and cemented stem fixation.

Association of Sarcopenia and Oxygen Uptake Efficiency Slope in Male Patients With Heart Failure.

PURPOSE: Sarcopenia, the loss of muscle mass and function, is a common comorbidity in patients with heart failure (HF). The skeletal muscle modulates the respiratory response during exercise. However, whether ventilatory behavior is affected by sarcopenia is still unknown. METHODS: We enrolled 169 male patients with HF. Muscle strength was measured by a handgrip dynamometer. Body composition was measured with dual-energy X-ray absorptiometry. Sarcopenia was defined by handgrip strength <27 kg and appendicular lean mass divided by height squared (ALM/height 2 ) <7.0 kg/m 2 . Oxygen uptake efficiency slope (OUES), ventilation (VE), oxygen uptake (VO 2 ), and carbon dioxide output (VCO 2 ) were measured by a cardiopulmonary exercise test. RESULTS: Sarcopenia was identified in 29 patients (17%). At the first ventilatory threshold, VE/VO 2 (36.9 ± 5.9 vs 32.7 ± 6.5; P = .003) and VE/VCO 2 (39.8 ± 7.2 vs 35.3 ± 6.9; P = .004) were higher in patients with sarcopenia compared to those without sarcopenia. At the exercise peak, compared to patients without sarcopenia, patients with sarcopenia had lower OUES (1186 ± 295 vs 1634 ± 564; P < .001), relative VO 2 (16.2 ± 5.0 vs 19.5 ± 6.5 mL/kg/min; P = .01), and VE (47.3 ± 10.1 vs 63.0 ± 18.2 L/min; P < .0001), while VE/VCO 2 (42.9 ± 8.9 vs 38.7 ± 8.4; P = .025) was increased. OUES was positively correlated with ALM/height 2 ( r = 0.36; P < .0001) and handgrip strength ( r = 0.31; P < .001). Hemoglobin (OR = 1.149; 95% CI, 0.842-1.570; P = .038), ALM/height 2 (OR = 2.166; 95% CI, 1.338-3.504; P = .002), and VO 2peak (OR = 1.377; 95% CI, 1.218-1.557; P < .001) were independently associated with OUES adjusted by cofounders. CONCLUSIONS: Our results suggest that sarcopenia is related to impaired ventilatory response during exercise in patients with HF.

Accuracy of Volumetric Bone Mineral Density Measurement in Weight Bearing, Cone Beam Computed Tomography.

BACKGROUND: Weight bearing computed tomography (WBCT) utilizes cone beam CT technology to provide assessments of lower limb joint structures while they are functionally loaded. Grey-scale values indicative of X-ray attenuation that are output from cone beam CT are challenging to calibrate, and their use for bone mineral density (BMD) measurement remains debatable. To determine whether WBCT can be reliably used for cortical and trabecular BMD assessment, we sought to establish the accuracy of BMD measurements at the knee using modern WBCT by comparing them to measurements from conventional CT. METHODS: A hydroxyapatite phantom with three inserts of varying densities was used to systematically quantify signal uniformity and BMD accuracy across the acquisition volume. We evaluated BMD in vivo (n = 5, female) using synchronous and asynchronous calibration techniques in WBCT and CT. To account for variation in attenuation along the height (z-axis) of acquisition volumes, we tested a height-dependent calibration approach for both WBCT and CT images. RESULTS: Phantom BMD measurement error in WBCT was as high as 15.3% and consistently larger than CT (up to 5.6%). Phantom BMD measures made under synchronous conditions in WBCT improved measurement accuracy by up to 3% but introduced more variability in measured BMD. We found strong correlations (R = 0.96) as well as wide limits of agreement (-324 mgHA/cm3 to 183 mgHA/cm3) from Bland-Altman analysis between WBCT and CT measures in vivo that were not improved by height-dependent calibration. CONCLUSION: Whilst BMD accuracy from WBCT was found to be dependent on apparent density, accuracy was independent of the calibration technique (synchronous or asynchronous) and the location of the measurement site within the field of view. Overall, we found strong correlations between BMD measures from WBCT and CT and in vivo measures to be more accurate in trabecular bone regions. Importantly, WBCT can be used to distinguish between anatomically relevant differences in BMD, however future work is necessary to determine the repeatability and sensitivity of BMD measures in WBCT.

Synthetic phantoms enable calibration between abattoir based dual energy X-ray absorptiometers used for prediction of lamb carcass composition.

Dual energy x-ray absorptiometry (DXA) devices were installed at two Australian abattoirs to predict computed tomography (CT) determined fat % and lean % of lamb carcasses. This study tested three algorithms developed for these devices, termed ß1, ß2 and ß3, and assessed their accuracy and precision in predicting CT composition. Algorithm ß3 included the use of a plastic phantom calibration block scanned by both DXA devices to adjust prediction equations, resulting in superior accuracy to the algorithms without phantom calibration (ß1 and ß2). When compared to the gold-standard CT composition, the bias of the DXA predictions was lowest when using algorithm ß3 at the two sites (-1.17%, -0.49% for fat %, 0.11%, -0.37% for lean %). The difference of DXA composition predictions between sites was lowest when using algorithm ß3, which demonstrated between site differences of 0.59 CT fat %, and 0.46 CT lean%. In contrast, algorithm ß1 and ß2 produced differences of 23.7% and 30.8% for CT fat, and 17.3% and 21.9% for CT lean between the two DXA devices. There was a small difference of 0.78% between the fat predictions of the first DXA image compared to the second DXA image for each carcass. The precision of predictions improved slightly using algorithm ß3. This work demonstrates that the in-line DXA systems can produce comparable results across sites.

Osteoporosis management in adults with schizophrenia following index hip fracture event: a 10-year population-based retrospective cohort study, Ontario, Canada.

Little is known about the incidence of osteoporosis testing and treatment in individuals with schizophrenia, who may be more likely to fracture. Using competing risk models, we found that schizophrenia was associated with lower incidence of testing or treatment. Implications are for understanding barriers and solutions for this disadvantaged group. PURPOSE: Evidence suggests that individuals with schizophrenia may be more likely to experience hip fractures than the general population; however, little is known about osteoporosis management in this disadvantaged subpopulation. Our study objective was to compare bone mineral density (BMD) testing and pharmacologic treatment in hip fracture patients with versus without schizophrenia. METHODS: This was a retrospective population-based cohort study leveraging health administrative databases, and individuals aged 66-105 years with hip fracture between fiscal years 2009 and 2018 in Ontario, Canada. Schizophrenia was ascertained using a validated algorithm. The outcome was a composite measure of (1) pharmacologic prescription for osteoporosis; or (2) a BMD test. Inferential analyses were conducted using Fine-Gray subdistribution hazard regression, with mortality as the competing event. RESULTS: A total of 52,722 individuals aged 66 to 105 years who sustained an index hip fracture in Ontario during the study period were identified, of whom 1890 (3.6%) had schizophrenia. Hip fracture patients with vs without schizophrenia were more likely to be long-term care residents (44.3% vs. 18.1%; standardized difference, 0.59), frail (62.5% vs. 36.5%; standardized difference, 0.54) and without a primary care provider (9.2% vs. 4.8%; standardized difference, 0.18). In Fine-Gray models, schizophrenia was associated with a lower incidence of testing or treatment (0.795 (0.721, 0.877)). CONCLUSIONS: In this population-based retrospective cohort study, a schizophrenia diagnosis among hip fracture patients was associated with a lower incidence of testing or treatment, after accounting for mortality, and several enabling and predisposing factors. Further research is required to investigate barriers to osteoporosis management in this disadvantaged population.