Clinical observation of diminished bone quality and quantity through longitudinal HR-pQCT-derived remodeling and mechanoregulation.

High resolution peripheral quantitative computed tomography (HR-pQCT) provides methods for quantifying volumetric bone mineral density and microarchitecture necessary for early diagnosis of bone disease. When combined with a longitudinal imaging protocol and finite element analysis, HR-pQCT can be used to assess bone formation and resorption (i.e., remodeling) and the relationship between this remodeling and mechanical loading (i.e., mechanoregulation) at the tissue level. Herein, 25 patients with a contralateral distal radius fracture were imaged with HR-pQCT at baseline and 9-12 months follow-up: 16 patients were prescribed vitamin D3 with/without calcium supplement based on a blood biomarker measures of bone metabolism and dual-energy X-ray absorptiometry image-based measures of normative bone quantity which indicated diminishing (n = 9) or poor (n = 7) bone quantity and 9 were not. To evaluate the sensitivity of this imaging protocol to microstructural changes, HR-pQCT images were registered for quantification of bone remodeling and image-based micro-finite element analysis was then used to predict local bone strains and derive rules for mechanoregulation. Remodeling volume fractions were predicted by both average values of trabecular and cortical thickness and bone mineral density (R2 > 0.8), whereas mechanoregulation was affected by dominance of the arm and group classification (p < 0.05). Overall, longitudinal, extended HR-pQCT analysis enabled the identification of changes in bone quantity and quality too subtle for traditional measures

Precision of bone mechanoregulation assessment in humans using longitudinal high-resolution peripheral quantitative computed tomography in vivo.

Local mechanical stimuli in the bone microenvironment are essential for the homeostasis and adaptation of the skeleton, with evidence suggesting that disruption of the mechanically-driven bone remodelling process may lead to bone loss. Longitudinal clinical studies have shown the combined use of high-resolution peripheral quantitative computed tomography (HR-pQCT) and micro-finite element analysis can be used to measure load-driven bone remodelling in vivo; however, quantitative markers of bone mechanoregulation and the precision of these analyses methods have not been validated in human subjects. Therefore, this study utilised participants from two cohorts. A same-day cohort (n = 33) was used to develop a filtering strategy to minimise false detections of bone remodelling sites caused by noise and motion artefacts present in HR-pQCT scans. A longitudinal cohort (n = 19) was used to develop bone imaging markers of trabecular bone mechanoregulation and characterise the precision for detecting longitudinal changes in subjects. Specifically, we described local load-driven formation and resorption sites independently using patient-specific odds ratios (OR) and 99 % confidence intervals. Conditional probability curves were computed to link the mechanical environment to the remodelling events detected on the bone surface. To quantify overall mechanoregulation, we calculated a correct classification rate measuring the fraction of remodelling events correctly identified by the mechanical signal. Precision was calculated as root-mean-squared averages of the coefficient of variation (RMS-SD) of repeated measurements using scan-rescan pairs at baseline combined with a one-year follow-up scan. We found no significant mean difference (p < 0.01) between scan-rescan conditional probabilities. RMS-SD was 10.5 % for resorption odds, 6.3 % for formation odds, and 1.3 % for correct classification rates. Bone was most likely to be formed in high-strain and resorbed in low-strain regions for all participants, indicating a consistent, regulated response to mechanical stimuli. For each percent increase in strain, the likelihood of bone resorption decreased by 2.0 ± 0.2 %, and the likelihood of bone formation increased by 1.9 ± 0.2 %, totalling 38.3 ± 1.1 % of strain-driven remodelling events across the entire trabecular compartment. This work provides novel robust bone mechanoregulation markers and their precision for designing future clinical studies

Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation: As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and developm nt investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

Validation of HR-pQCT against micro-CT for morphometric and biomechanical analyses: A review

High-resolution peripheral quantitative computed-tomography (HR-pQCT) has the potential to become a powerful clinical assessment and diagnostic tool. Given the recent improvements in image resolution, from 82 to 61 μm, this technology may be used to accurately quantify in vivo bone microarchitecture, a key biomarker of degenerative bone diseases. However, computational methods to assess bone microarchitecture were developed for micro computed tomography (micro-CT), a higher-resolution technology only available for ex vivo studies, and validation of these computational analysis techniques against the gold-standard micro-CT has been inconsistent and incomplete. Herein, we review methods for segmentation of bone compartments and microstructure, quantification of bone morphology, and estimation of mechanical strength using finite-element analysis, highlighting the need throughout for improved standardization across the field. Studies have relied on homogenous datasets for validation, which does not allow for robust comparisons between methods. Consequently, the adaptation and validation of novel segmentation approaches has been slow to non-existent, with most studies still using the manufacturer's segmentation for morphometric analysis despite the existence of better performing alternative approaches. The promising accuracy of HR-pQCT for capturing morphometric indices is overshadowed by considerable variability in outcomes between studies. For finite element analysis (FEA) methods, the use of disparate material models and FEA tools has led to a fragmented ability to assess mechanical bone strength with HR-pQCT. Further, the scarcity of studies comparing 62 μm HR-pQCT to the gold standard micro-CT leaves the validation of this imaging modality incomplete. This review revealed that without standardization, the capabilities of HR-pQCT cannot be adequately assessed. The need for a public, extendable, heterogeneous dataset of HR-pQCT and corresponding gold-standard micro-CT images, which would allow HR-pQCT users to benchmark existing and novel methods and select optimal methods depending on the scientific question and data at hand, is now evident. With more recent advancements in HR-pQCT, the community must learn from its past and provide properly validated technologies to ensure that HR-pQCT can truly provide value in patient diagnosis and care.ISSN:2352-187

Clinical Data for Parametrization of In Silico Bone Models Incorporating Cell-Cytokine Dynamics: A Systematic Review of Literature

In silico simulations aim to provide fast, inexpensive, and ethical alternatives to years of costly experimentation on animals and humans for studying bone remodeling, its deregulation during osteoporosis and the effect of therapeutics. Within the varied spectrum of in silico modeling techniques, bone cell population dynamics and agent-based multiphysics simulations have recently emerged as useful tools to simulate the effect of specific signaling pathways. In these models, parameters for cell and cytokine behavior are set based on experimental values found in literature; however, their use is currently limited by the lack of clinical in vivo data on cell numbers and their behavior as well as cytokine concentrations, diffusion, decay and reaction rates. Further, the settings used for these parameters vary across research groups, prohibiting effective cross-comparisons. This review summarizes and evaluates the clinical trial literature that can serve as input or validation for in silico models of bone remodeling incorporating cells and cytokine dynamics in post-menopausal women in treatment, and control scenarios. The GRADE system was used to determine the level of confidence in the reported data, and areas lacking in reported measures such as binding site occupancy, reaction rates and cell proliferation, differentiation and apoptosis rates were highlighted as targets for further research. We propose a consensus for the range of values that can be used for the cell and cytokine settings related to the RANKL-RANK-OPG, TGF-β and sclerostin pathways and a Levels of Evidence-based method to estimate parameters missing from clinical trial literature.ISSN:2296-418

Evaluation of experimental, analytical, and computational methods to determine long-bone bending stiffness

Methods used to evaluate bone mechanical properties vary widely depending on the motivation and environment of individual researchers, clinicians, and industries. Further, the innate complexity of bone makes validation of each method difficult. Thus, the purpose of the present research was to quantify methodological error of the most common methods used to predict long-bone bending stiffness, more specifically, flexural rigidity (EI). Functional testing of a bi-material porcine bone surrogate, developed in a previous study, was conducted under four-point bending test conditions. The bone surrogate was imaged using computed tomography (CT) with an isotropic voxel resolution of 0.625 mm. Digital image correlation (DIC) of the bone surrogate was used to quantify the methodological error between experimental, analytical, and computational methods used to calculate EI. These methods include the application of Euler Bernoulli beam theory to mechanical testing and DIC data; the product of the bone surrogate composite bending modulus and second area moment of inertia; and finite element analysis (FEA) using computer-aided design (CAD) and CT-based geometric models. The methodological errors of each method were then compared. The results of this study determined that CAD-based FEA was the most accurate determinant of bone EI, with less than five percent difference in EI to that of the DIC and consistent reproducibility of the measured displacements for each load increment. CT-based FEA was most accurate for axial strains. Analytical calculations overestimated EI and mechanical testing was the least accurate, grossly underestimating flexural rigidity of long-bones.ISSN:1751-6161ISSN:1878-018

Meta-analysis of Diabetes Mellitus-Associated Differences in Bone Structure Assessed by High-Resolution Peripheral Quantitative Computed Tomography

Purpose of Review Diabetes mellitus is defined by elevated blood glucose levels caused by changes in glucose metabolism and, according to its pathogenesis, is classified into type 1 (T1DM) and type 2 (T2DM) diabetes mellitus. Diabetes mellitus is associated with multiple degenerative processes, including structural alterations of the bone and increased fracture risk. High-resolution peripheral computed tomography (HR-pQCT) is a clinically applicable, volumetric imaging technique that unveils bone microarchitecture in vivo. Numerous studies have used HR-pQCT to assess volumetric bone mineral density and microarchitecture in patients with diabetes, including characteristics of trabecular (e.g. number, thickness and separation) and cortical bone (e.g. thickness and porosity). However, study results are heterogeneous given different imaging regions and diverse patient cohorts. Recent Findings This meta-analysis assessed T1DM- and T2DM-associated characteristics of bone microarchitecture measured in human populations in vivo reported in PubMed- and Embase-listed publications from inception (2005) to November 2021. The final dataset contained twelve studies with 516 participants with T2DM and 3067 controls and four studies with 227 participants with T1DM and 405 controls. While T1DM was associated with adverse trabecular characteristics, T2DM was primarily associated with adverse cortical characteristics. These adverse effects were more severe at the radius than the load-bearing tibia, indicating increased mechanical loading may compensate for deleterious bone microarchitecture changes and supporting mechanoregulation of bone fragility in diabetes mellitus. Summary Our meta-analysis revealed distinct predilection sites of bone structure aberrations in T1DM and T2DM, which provide a foundation for the development of animal models of skeletal fragility in diabetes and may explain the uncertainty of predicting bone fragility in diabetic patients using current clinical algorithms.ISSN:1544-2241ISSN:1544-187

Bone Mechanoregulation Allows Subject-Specific Load Estimation Based on Time-Lapsed Micro-CT and HR-pQCT in Vivo

Patients at high risk of fracture due to metabolic diseases frequently undergo long-term antiresorptive therapy. However, in some patients, treatment is unsuccessful in preventing fractures or causes severe adverse health outcomes. Understanding load-driven bone remodelling, i.e., mechanoregulation, is critical to understand which patients are at risk for progressive bone degeneration and may enable better patient selection or adaptive therapeutic intervention strategies. Bone microarchitecture assessment using high-resolution peripheral quantitative computed tomography (HR-pQCT) combined with computed mechanical loads has successfully been used to investigate bone mechanoregulation at the trabecular level. To obtain the required mechanical loads that induce local variances in mechanical strain and cause bone remodelling, estimation of physiological loading is essential. Current models homogenise strain patterns throughout the bone to estimate load distribution in vivo, assuming that the bone structure is in biomechanical homoeostasis. Yet, this assumption may be flawed for investigating alterations in bone mechanoregulation. By further utilising available spatiotemporal information of time-lapsed bone imaging studies, we developed a mechanoregulation-based load estimation (MR) algorithm. MR calculates organ-scale loads by scaling and superimposing a set of predefined independent unit loads to optimise measured bone formation in high-, quiescence in medium-, and resorption in low-strain regions. We benchmarked our algorithm against a previously published load history (LH) algorithm using synthetic data, micro-CT images of murine vertebrae under defined experimental in vivo loadings, and HR-pQCT images from seven patients. Our algorithm consistently outperformed LH in all three datasets. In silico-generated time evolutions of distal radius geometries (n = 5) indicated significantly higher sensitivity, specificity, and accuracy for MR than LH (p < 0.01). This increased performance led to substantially better discrimination between physiological and extra-physiological loading in mice (n = 8). Moreover, a significantly (p < 0.01) higher association between remodelling events and computed local mechanical signals was found using MR [correct classification rate (CCR) = 0.42] than LH (CCR = 0.38) to estimate human distal radius loading. Future applications of MR may enable clinicians to link subtle changes in bone strength to changes in day-to-day loading, identifying weak spots in the bone microstructure for local intervention and personalised treatment approaches.ISSN:2296-418

Motion grading of high-resolution quantitative computed tomography supported by deep convolutional neural networks

Image quality degradation due to subject motion confounds the precision and reproducibility of measurements of bone density, morphology and mechanical properties from high-resolution peripheral quantitative computed tomography (HR-pQCT). Time-consuming operator-based scoring of motion artefacts remains the gold standard to determine the degree of acceptable motion. However, due to the subjectiveness of manual grading, HR-pQCT scans of poor quality, which cannot be used for analysis, may be accepted upon initial review, leaving patients with incomplete or inaccurate imaging results. Convolutional Neural Networks (CNNs) enable fast image analysis with relatively few pre-processing requirements in an operator-independent and fully automated way for image classification tasks. This study aimed to develop a CNN that can predict motion scores from HR-pQCT images, while also being aware of uncertain predictions that require manual confirmation. The CNN calculated motion scores within seconds and achieved a high F1-score (86.8 ± 2.8 %), with good precision (87.5 ± 2.7 %), recall (86.7 ± 2.9 %) and a substantial agreement with the ground truth measured by Cohen's kappa (κ = 68.6 ± 6.2 %); motion scores of the test dataset were predicted by the algorithm with comparable accuracy, precision, sensitivity and agreement as by the operators (p > 0.05). This post-processing approach may be used to assess the effect of motion scores on microstructural analysis and can be immediately implemented into clinical protocols, significantly reducing the time for quality assessment and control of HR-pQCT scans.ISSN:8756-328