A new approach for quantifying localized bone loss by measuring void spaces

Bone microarchitecture and strength assessment in adults with osteogenesis imperfecta using HR-pQCT: normative comparison and challenges

Data on bone microarchitecture in osteogenesis imperfecta (OI) are scarce. The aim of this cross-sectional study was to assess bone microarchitecture and strength in a large cohort of adults with OI using high-resolution peripheral quantitative computed tomography (HR-pQCT) and to evaluate challenges of using HR-pQCT in this cohort. Second-generation HR-pQCT scans were obtained at the distal radius and tibia in 118 men and women with Sillence OI type I, III, or IV using an extremity-length-dependent scan protocol. In total, 102 radius and 105 tibia scans of sufficient quality could be obtained, of which 11 radius scans (11%) and 14 tibia scans (13%) had a deviated axial scan angle as compared with axial angle data of 13 young women. In the scans without a deviated axial angle and compared with normative HR-pQCT data, Z-scores at the radius for trabecular bone mineral density (BMD), number, and separation were -1.6 ± 1.3, -2.5 ± 1.4, and -2.7 (IQR: 2.7), respectively. They were -1.4 ± 1.5 and -1.1 ± 1.2 for stiffness and failure load and between ±1 for trabecular thickness and cortical bone parameters. Z-scores were significantly lower for total and trabecular BMD, stiffness, failure load, and cortical area and thickness at the tibia. Additionally, local microarchitectural inhomogeneities were observed, most pronounced being trabecular void volumes. In the scans with a deviated axial angle, the proportion of Z-scores <-4 or >4 was significantly higher for trabecular BMD and separation (radius) or most total and trabecular bone parameters (tibia). To conclude, especially trabecular bone microarchitecture and bone strength were impaired in adults with OI. HR-pQCT may be used without challenges in most adults with OI, but approximately 12% of the scans may have a deviated axial angle in OI due to bone deformities or scan positioning limitations. Furthermore, standard HR-pQCT parameters may not always be reliable due to microarchitectural inhomogeneities nor fully reflect all inhomogeneities.

Characterizing Bone Phenotypes Related to Skeletal Fragility Using Advanced Medical Imaging

PURPOSE OF REVIEW

Summarize the recent literature that investigates how advanced medical imaging has contributed to our understanding of skeletal phenotypes and fracture risk across the lifespan.

RECENT FINDINGS

Characterization of bone phenotypes on the macro-scale using advanced imaging has shown that while wide bones are generally stronger than narrow bones, they may be more susceptible to age-related declines in bone strength. On the micro-scale, HR-pQCT has been used to identify bone microarchitecture phenotypes that improve stratification of fracture risk based on phenotype-specific risk factors. Adolescence is a key phase for bone development, with distinct sex-specific growth patterns and significant within-sex bone property variability. However, longitudinal studies are needed to evaluate how early skeletal growth impacts adult bone phenotypes and fracture risk. Metabolic and rare bone diseases amplify fracture risk, but the interplay between bone phenotypes and disease remains unclear. Although bone phenotyping is a promising approach to improve fracture risk assessment, the clinical availability of advanced imaging is still limited. Consequently, alternative strategies for assessing and managing fracture risk include vertebral fracture assessment from clinically available medical imaging modalities/techniques or from fracture risk assessment tools based on clinical risk factors. Bone fragility is not solely determined by its density but by a combination of bone geometry, distribution of bone mass, microarchitecture, and the intrinsic material properties of bone tissue. As such, different individuals can exhibit distinct bone phenotypes, which may predispose them to be more vulnerable or resilient to certain perturbations that influence bone strength.

Distribution of bone voids in the thoracolumbar spine in Chinese adults with and without osteoporosis: A cross-sectional multi-center study based on 464 vertebrae

Bone void is a novel intuitive morphological indicator to assess bone quality but its use in vertebrae has not been described. This cross-sectional and multi-center study aimed to investigate the distribution of bone voids in the thoracolumbar spine in Chinese adults based on quantitative computed tomography (QCT). A bone void was defined as a trabecular net region with extremely low bone mineral density (BMD) (<40 mg/cm³), detected by an algorithm based on phantom-less technology. A total of 464 vertebrae from 152 patients (51.8 ± 13.4 years old) were included. The vertebral trabecular bone was divided into eight sections based on the middle sagittal, coronal, and horizontal planes. Bone void of the whole vertebra and each section were compared between healthy, osteopenia, and osteoporosis groups and between spine levels. Receiver operator characteristic (ROC) curves were plotted and optimum cutoff points of void volume between the groups were obtained. The total void volumes of the whole vertebra were 124.3 ± 221.5 mm³, 1256.7 ± 928.7 mm^3, and 5624.6 ± 3217.7 mm³ in healthy, osteopenia, and osteoporosis groups, respectively. The detection rate of vertebrae with bone voids was higher and the normalized void volume was larger in the lumbar than in thoracic vertebrae. L3 presented the largest void (2165.0 ± 3396.0 mm³), while T12 had the smallest void (448.9 ± 699.4 mm³). The bone void was mainly located in the superior-posterior-right section (40.8 %). Additionally, bone void correlated positively with age and increased rapidly after 55 years. The most significant void volume increase was found in the inferior-anterior-right section whereas the least increase was found in the inferior-posterior-left section with aging. The cutoff points were 345.1 mm³ between healthy and osteopenia groups (sensitivity = 0.923, specificity = 0.932) and 1693.4 mm³ between osteopenia and osteoporosis groups (sensitivity = 1.000, specificity = 0.897). In conclusion, this study demonstrated the bone void distribution in vertebrae using clinical QCT data. The findings provide a new perspective for the description of bone quality and showed that bone void could guide clinical practice such as osteoporosis screening.

Automatic segmentation of trabecular and cortical compartments in HR-pQCT images using an embedding-predicting U-Net and morphological post-processing

High-resolution peripheral quantitative computed tomography (HR-pQCT) is an emerging in vivo imaging modality for quantification of bone microarchitecture. However, extraction of quantitative microarchitectural parameters from HR-pQCT images requires an accurate segmentation of the image. The current standard protocol using semi-automated contouring for HR-pQCT image segmentation is laborious, introduces inter-operator biases into research data, and poses a barrier to streamlined clinical implementation. In this work, we propose and validate a fully automated algorithm for segmentation of HR-pQCT radius and tibia images. A multi-slice 2D U-Net produces initial segmentation predictions, which are post-processed via a sequence of traditional morphological image filters. The U-Net was trained on a large dataset containing 1822 images from 896 unique participants. Predicted segmentations were compared to reference segmentations on a disjoint dataset containing 386 images from 190 unique participants, and 156 pairs of repeated images were used to compare the precision of the novel and current protocols. The agreement of morphological parameters obtained using the predicted segmentation relative to the reference standard was excellent (R² between 0.938 and > 0.999). Precision was significantly improved for several outputs, most notably cortical porosity. This novel and robust algorithm for automated segmentation will increase the feasibility of using HR-pQCT in research and clinical settings.

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. 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.

Hip Fractures in Older Adults Are Associated With the Low Density Bone Phenotype and Heterogeneous Deterioration of Bone Microarchitecture

Femoral neck areal bone mineral density (FN aBMD) is a key determinant of fracture risk in older adults; however, the majority of individuals who have a hip fracture are not considered osteoporotic according to their FN aBMD. This study uses novel tools to investigate the characteristics of bone microarchitecture that underpin bone fragility. Recent hip fracture patients (n = 108, 77% female) were compared with sex- and age-matched controls (n = 216) using high-resolution peripheral quantitative computed tomography (HR-pQCT) imaging of the distal radius and tibia. Standard morphological analysis of bone microarchitecture, micro-finite element analysis, and recently developed techniques to identify void spaces in bone microarchitecture were performed to evaluate differences between hip fracture patients and controls. In addition, a new approach for phenotyping bone microarchitecture was implemented to evaluate whether hip fractures in males and females occur more often in certain bone phenotypes. Overall, hip fracture patients had notable deterioration of bone microarchitecture and reduced bone mineral density compared with controls, especially at weight-bearing sites (tibia and femoral neck). Hip fracture patients were more likely to have void spaces present at either site and had void spaces that were two to four times larger on average when compared with non-fractured controls (p < 0.01). Finally, bone phenotyping revealed that hip fractures were significantly associated with the low density phenotype (p < 0.01), with the majority of patients classified in this phenotype (69%). However, female and male hip fracture populations were distributed differently across the bone phenotype continuum. These findings highlight how HR-pQCT can provide insight into the underlying mechanisms of bone fragility by using information about bone phenotypes and identification of microarchitectural defects (void spaces). The added information suggests that HR-pQCT can have a beneficial role in assessing the severity of structural deterioration in bone that is associated with osteoporotic hip fractures. © 2022 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

Development of a novel method to measure bone marrow fat fraction in older women using high-resolution peripheral quantitative computed tomography

Bone marrow adipose tissue (BMAT) has been implicated in a number of conditions associated with bone deterioration and osteoporosis. Several studies have found an inverse relationship between BMAT and bone mineral density (BMD), and higher levels of BMAT in those with prevalent fracture. Magnetic resonance imaging (MRI) is the gold standard for measuring BMAT, but its use is limited by high costs and low availability. We hypothesized that BMAT could also be accurately quantified using high-resolution peripheral quantitative computed tomography (HR-pQCT).

METHODS

In the present study, a novel method to quantify the tibia bone marrow fat fraction, defined by MRI, using HR-pQCT was developed. In total, 38 postmenopausal women (mean [standard deviation] age 75.9 [3.1] years) were included and measured at the same site at the distal (n = 38) and ultradistal (n = 18) tibia using both MRI and HR-pQCT. To adjust for partial volume effects, the HR-pQCT images underwent 0 to 10 layers of voxel peeling to remove voxels adjacent to the bone. Linear regression equations were then tested for different degrees of voxel peeling, using the MRI-derived fat fractions as the dependent variable and the HR-pQCT-derived radiodensity as the independent variables.

RESULTS

The most optimal HR-pQCT derived model, which applied a minimum of 4 layers of peeled voxel and with more than 1% remaining marrow volume, was able to explain 76% of the variation in the ultradistal tibia bone marrow fat fraction, measured with MRI (p < 0.001).

CONCLUSION

The novel HR-pQCT method, developed to estimate BMAT, was able to explain a substantial part of the variation in the bone marrow fat fraction and can be used in future studies investigating the role of BMAT in osteoporosis and fracture prediction.

An inverse technique to identify participant-specific bone adaptation from serial CT measurements

Simulated bone adaptation is framed as an interface evolution problem. The interface is extracted from a high-resolution computed tomography (CT) image of trabecular bone microarchitecture and modified by the level set equation. A model and its parameters determine the bone adaptation rate and thus the bone structure at any future time. This study develops an inverse problem and solver to identify model parameters from multiple high-resolution CT images of bone within the level set framework. We demonstrate the technique on a model of advection and mean curvature flow, termed curvature-driven adaptation. The inverse solver uses two CT scans to estimate model parameters, which map the bone surface from one image to the next. The solver was tested with synthetic images of bone changing according to the curvature-driven model with known model parameters. The algorithm recovered known model parameters excellently (R²  > .99, p < .001). A grid search indicated that the estimated model parameters were insensitive to hyper-parameter selection for learning rate 1e^-5≤η≤ 5e^-5 and gradient scaling factor 5e^-5≤γ≤ 5e^-4 . Finally, we tested the algorithm's sensitivity to salt-and-pepper noise of probability P , where .0 ≤P≤ .9. Model parameter accuracy did not change for P < .7, corresponding to Dice coefficients greater than .7. The inverse problem estimates bone adaptation parameters from multiple CT images of changing bone microarchitecture. In the future, this technique could be used to determine participant-specific bone adaptation parameters in vivo, validate bone adaptation models, and predict bone health.