High-resolution Peripheral Quantitative Computed Tomography Images Research Articles

Individual trabecula segmentation validation in first- and second-generation high-resolution peripheral computed tomography compared to micro-computed tomography in the distal radius and tibia.

High-resolution peripheral quantitative computed tomography (HR-pQCT) has been used for in vivo 3D visualization of trabecular microstructure. Second-generation HR-pQCT (HR-pQCT II) has been shown to have good agreement with first generation HR-pQCT (HR-pQCT I). Advanced Individual Trabecula Segmentation (ITS) decomposes the trabecula network into individual plates and rods. ITS based on HR-pQCT I showed a strong correlation to ITS based on micro-computed tomography (μCT) and identified trabecular changes in metabolic bone diseases. ITS based on HR-pQCT II has new potential because of the enhanced resolution but has yet to be validated. The objective of this study was to assess the agreement between ITS based on HR-pQCT I, HR-pQCT II, and μCT to assess the capability of ITS on HR-pQCT images as a tool for studying bone structure. Freshly frozen tibia and radius bones were scanned in the distal region using HR-pQCT I at 82μm, HR-pQCT II at 60.7μm, and μCT at 37μm. Images were registered, binarized, and ITS analysis was performed. Bone volume fraction (pBV/TV, rBV/TV), number density (pTb.N, rTb.N), thickness (pTb.Th, rTb.Th), and plate-to-rod (PR) ratio (pBV/rBV) of trabecular plates and rods were obtained. Paired Student's t-tests with post hoc Bonferroni analysis were used to examine the differences. Linear regression was used to determine the correlation coefficient. The HR-pQCT I parameters were different from the μCT measurements. The HR-pQCT II parameters were different from the μCT measurements except for rTb.N, and the HR-pQCT I parameters were different from the HR-pQCT II measurements except for pTb.Th. The strong correlation between HR-pQCT II and μCT microstructural analysis (R2 = 0.55-0.94) suggests that HR-pQCT II can be used to assess changes in plate and rod microstructure and that values from HR-pQCT I can be corrected.

A multi-stack registration technique to improve measurement accuracy and precision across longitudinal HR-pQCT scans.

Recent applications of high-resolution peripheral quantitative computed tomography (HR-pQCT) have demonstrated that changes in local bone remodelling can be quantified in vivo using longitudinal three-dimensional image registration. However, certain emerging applications, such as fracture healing and joint analysis, require larger multi-stack scan regions that can result in stack shift image artifacts. These artifacts can be detrimental to the accurate alignment of the bone structure across multiple timepoints. The purpose of this study was to establish a multi-stack registration protocol for evaluating longitudinal HR-pQCT images and to assess the accuracy and precision error in comparison with measures obtained using previously established three-dimensional longitudinal registration. Three same day multi-stack HR-pQCT scans of the radius (2 stacks in length) and tibia (3 stacks in length) were obtained from 39 healthy individuals who participated in a previous reproducibility study. A fully automated multi-stack registration algorithm was developed to re-align stacks within a scan by leveraging slight offsets between longitudinal scans. Stack shift severity before and after registration was quantified using a newly proposed stack-shift severity score. The false discovery rate for bone remodelling events and precision error of bone morphology and micro-finite element analysis parameters were compared between longitudinally registered scans with and without the addition of multi-stack registration. Most scans (82%) improved in stack alignment or maintained the lowest stack shift severity score when multi-stack registration was implemented. The false discovery rate of bone remodelling events significantly decreased after multi-stack registration, resulting in median false detection of bone formation and resorption fractions between 3.2 to 7.5% at the radius and 3.4 to 5.3% at the tibia. Further, precision error was significantly reduced or remained unchanged in all standard bone morphology and micro-finite element analysis parameters, except for total and trabecular cross-sectional areas. Multi-stack registration is an effective strategy for accurately aligning multi-stack HR-pQCT scans without modification of the image acquisition protocol. The algorithm presented here is a viable approach for performing accurate morphological analysis on multi-stack HR-pQCT scans, particularly for advanced application investigating local bone remodelling in vivo.

Erosion Identification in Metacarpophalangeal Joints in Rheumatoid Arthritis using High-Resolution Peripheral Quantitative Computed Tomography.

Bone erosions are a pathological feature of several forms of inflammatory arthritis including rheumatoid arthritis (RA). The increased presence and size of erosions are associated with poor outcomes, joint function, and disease progression. High-resolution peripheral quantitative computed tomography (HR-pQCT) provides unparalleled in vivo visualization of bone erosions. However, at this resolution, discontinuities in the cortical shell (cortical breaks) that are associated with normal physiological processes and pathology are also visible. The Study grouP for xtrEme Computed Tomography in Rheumatoid Arthritis previously used a consensus process to develop a definition of pathological erosion in HR-pQCT: a cortical break detected in at least two consecutive slices, in at least two perpendicular planes, non-linear in shape, with underlying trabecular bone loss. However, despite the availability of a consensus definition, erosion identification is a demanding task with challenges in inter-rater variability. The purpose of this work is to introduce a training tool to provide users with guidance on identifying pathological cortical breaks on HR-pQCT images for erosion analysis. The protocol presented here uses a custom-built module (Bone Analysis Module (BAM) - Training), implemented as an extension to an open-source image processing software (3D Slicer). Using this module, users can practice identifying erosions and compare their results to erosions annotated by expert rheumatologists.

Automatic 3D joint erosion detection for the diagnosis and monitoring of rheumatoid arthritis using hand HR-pQCT images.

Rheumatoid arthritis (RA) is a chronic inflammatory disease. It leads to bone erosion in joints and other complications, which severely affect patients' quality of life. To accurately diagnose and monitor the progression of RA, quantitative imaging and analysis tools are desirable. High-resolution peripheral quantitative computed tomography (HR-pQCT) is such a promising tool for monitoring disease progression in RA. However, automatic erosion detection tools using HR-pQCT images are not yet available. Inspired by the consensus among radiologists on the erosions in HR-pQCT images, in this paper we define erosion as the significant concave regions on the cortical layer, and develop a model-based 3D automatic erosion detection method. It mainly consists of two steps: constructing closed cortical surface, and detecting erosion regions on the surface. In the first step, we propose an initialization-robust region competition methods for joint segmentation, and then fill the surface gaps by using joint bone separation and curvature-based surface alignment. In the second step, we analyze the curvature information of each voxel, and then aggregate the candidate voxels into concave surface regions and use the shape information of the regions to detect the erosions. We perform qualitative assessments of the new method using 59 well-annotated joint volumes. Our method has shown satisfactory and consistent performance compared with the annotations provided by medical experts.

Machine learning applied to HR-pQCT images improves fracture discrimination provided by DXA and clinical risk factors.

Traditional analysis of High Resolution peripheral Quantitative Computed Tomography (HR-pQCT) images results in a multitude of cortical and trabecular parameters which would be potentially cumbersome to interpret for clinicians compared to user-friendly tools utilising clinical parameters. A computer vision approach (by which the entire scan is 'read' by a computer algorithm) to ascertain fracture risk, would be far simpler. We therefore investigated whether a computer vision and machine learning technique could improve upon selected clinical parameters in assessing fracture risk. Participants of the Hertfordshire Cohort Study (HCS) attended research visits at which height and weight were measured; fracture history was determined via self-report and vertebral fracture assessment. Bone microarchitecture was assessed via HR-pQCT scans of the non-dominant distal tibia (Scanco XtremeCT), and bone mineral density measurement and lateral vertebral assessment were performed using dual-energy X-ray absorptiometry (DXA) (Lunar Prodigy Advanced). Images were cropped, pre-processed and texture analysis was performed using a three-dimensional local binary pattern method. These image data, together with age, sex, height, weight, BMI, dietary calcium and femoral neck BMD, were used in a random-forest classification algorithm. Receiver operating characteristic (ROC) analysis was used to compare fracture risk identification methods. Overall, 180 males and 165 females were included in this study with a mean age of approximately 76years and 97 (28%) participants had sustained a previous fracture. Using clinical risk factors alone resulted in an area under the curve (AUC) of 0.70 (95% CI: 0.56-0.84), which improved to 0.71 (0.57-0.85) with the addition of DXA-measured BMD. The addition of HR-pQCT image data to the machine learning classifier with clinical risk factors and DXA-measured BMD as inputs led to an improved AUC of 0.90 (0.83-0.96) with a sensitivity of 0.83 and specificity of 0.74. These results suggest that using a three-dimensional computer vision method to HR-pQCT scanning may enhance the identification of those at risk of fracture beyond that afforded by clinical risk factors and DXA-measured BMD. This approach has the potential to make the information offered by HR-pQCT more accessible (and therefore) applicable to healthcare professionals in the clinic if the technology becomes more widely available.

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.

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.

Open-source image analysis tool for the identification and quantification of cortical interruptions and bone erosions in high-resolution peripheral quantitative computed tomography images of patients with rheumatoid arthritis.

Identification of bone erosions and quantification of erosion volume is important for rheumatoid arthritis diagnosis, and can add important information to evaluate disease progression and treatment effects. High-resolution peripheral quantitative computed tomography (HR-pQCT) is well suited for this purpose, however analysis methods are not widely available. The purpose of this study was to develop an open-source software tool for the identification and quantification of bone erosions using images acquired by HR-pQCT. The collection of modules, Bone Analysis Modules (BAM) - Erosion, implements previously published erosion analysis techniques as modules in 3D Slicer, an open-source image processing and visualization tool. BAM includes a module to automatically identify cortical interruptions, from which erosions are manually selected, and a hybrid module that combines morphological and level set operations to quantify the volume of bone erosions. HR-pQCT images of the second and third metacarpophalangeal (MCP) joints were acquired in patients with RA (XtremeCT, n=14, XtremeCTII, n=22). The number of cortical interruptions detected by BAM-Erosion agreed strongly with the previously published cortical interruption detection algorithm for both XtremeCT (r2=0.85) and XtremeCTII (r2=0.87). Erosion volume assessment by BAM-Erosion agreed strongly (r2=0.95) with the Medical Image Analysis Framework. BAM-Erosion provides an open-source erosion analysis tool that produces comparable results to previously published algorithms, with improved options for visualization. The strength of the tool is that it implements multiple image processing algorithms for erosion analysis on a single, widely available, open-source platform that can accommodate future updates.

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.

MO542: Bone Mineral Density, Bone Micro-Architecture Evolution After Kidney Transplantation: A Prospective Cohort Study

Abstract BACKGROUND AND AIMS Bone loss and mineral abnormalities are frequent in kidney transplant recipients (KTRs) and associated with a high risk of fracture, cardiovascular mortality and an increase in health care costs. In daily clinics, the detection of bone abnormalities after transplantation includes bone biomarkers and imaging technique [Dual Energy X-ray (DEXA)] to assess respectively the bone turnover and the bone mineral density (BMD), but with limitations. The high-resolution peripheral quantitative computed tomography (HR-pQCT) provides additional noninvasive information on bone microarchitecture and BMD with a better distinction between cortical and trabecular areas. The goal of our study is to evaluate the evolution of bone structure using HR-pQCT compared to standard technique (DXA) in a prospective cohort of KTRs. METHOD All patients referred for a single kidney transplant at the university hospital of Liège with no history of exposure to antiresorptive agents were eligible for inclusion (NCT04713774). Participants underwent baseline and 3-month biomarkers analysis, BMD measurements by DEXA. HR-pQCT images were obtained of the distal radius and distal tibia (non-dominant, non-fractured limb) using the XtremeCT device with standard protocols. HR-pQCT assessed quantitative measurement of the volumetric density of trabecular and cortical bone as well as bone structure (trabecular number or thickness or cortical porosity for instance). RESULTS A total of 26 patients were prospectively included. The mean age was 57.3 ± 12.1 years. The mean dialysis vintage was 27.5 ± 16.4 months before transplantation. Bone biomarkers showed a significant decrease at 3 months after transplantation. PTH decreased from 221.72 ng/L to 59.6 ng/L (P &amp;lt; 0.0001), P1NP from 211 ug/L to 72 ug/L (P &amp;lt; 0.013) and BLAP from 23 ug/L to 13 ug/L (P = 0.042). BMD was measured by DXA and HR-pQCT at 7 days [6; 8] and 102 days (90; 113) after transplantation. We observed a significant reduction of BMD by DXA at the hip site from 0.868 g/cm2 to 0.856 g/cm2 (P = 0.02), but not at the lumbar site. The HR-pQCT analysis demonstrated a significant reduction of the trabecular BMD from 152.62 mg HA/ccm to 150.80 mg HA/ccm (P &amp;lt; 0.0001) at the tibia site and from 159.09 mg HA/ccm to 156.25 mg HA/ccm (P &amp;lt; 0.0001) at the radius site. No change in bone structure have been observed at 3 months post-transplantation with the HR-pQCT analysis. CONCLUSION HR-pQCT is sensitive enough to show a significant decrease of BMD at the trabecular site, as soon as 3 months after transplantation compared to DEXA at the lumbar spine. However, no change in bone structure nor cortical bone volume has been observed. The sensibility of this technique might be higher than DEXA. The rapid assessment of bone structure (3 months post-transplantation) might be too soon to evaluate such abnormalities. Detecting properly rapid changes in bone density, as soon as 3 months after renal transplantation seems feasible. The impact on bone health management needs to be further studied.

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

SummaryBone 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).MethodsIn 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.ResultsThe 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).ConclusionThe 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.

Influence of loading conditions in finite element analysis assessed by HR-pQCT on ex vivo fracture prediction.

Many fractures occur in individuals with normal areal Bone Mineral Density (aBMD) measured by Dual X-ray Absorptiometry (DXA). High Resolution peripheral Quantitative Computed Tomography (HR-pQCT) allows for non-invasive evaluation of bone stiffness and strength through micro finite element (μFE) analysis at the tibia and radius. These μFE outcomes are strongly associated with fragility fractures but do not provide clear enhancement compared with DXA measurements. The objective of this study was to establish whether a change in loading conditions in standard μFE analysis assessed by HR-pQCT enhance the discrimination of low-trauma fractured radii (n=11) from non-fractured radii (n=16) obtained experimentally throughout a mechanical test reproducing a forward fall. Micro finite element models were created using HR-pQCT images, and linear analyses were performed using four different types of loading conditions (axial, non-axial with two orientations and torsion). No significant differences were found between the failure load assessed with the axial and non-axial models. The different loading conditions tested presented the same area under the receiver operating characteristic (ROC) curves of 0.79 when classifying radius fractures with an accuracy of 81.5%. In comparison, the area under the curve (AUC) is 0.77 from DXA-derived ultra-distal aBMD of the forearm with an accuracy of 85.2%. These results suggest that the restricted HR-pQCT scanned region seems not sensitive to loading conditions for the prediction of radius fracture risk based on ex vivo experiments (n=27).

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.

Effects of RANKL inhibition on promoting healing of bone erosion in rheumatoid arthritis using HR-pQCT: a 2-year, randomised, double-blind, placebo-controlled trial

ObjectiveTo evaluate the effects of denosumab on erosion healing at 2–4 metacarpophalangeal (MCP) head as determined by high-resolution peripheral quantitative CT (HR-pQCT) in patients with rheumatoid arthritis (RA) with stable...

Heterogenous bone response to biologic DMARD therapies in rheumatoid arthritis patients and their relationship to functional indices

Objectives: Previous studies of high-resolution peripheral quantitative computed tomography (HR-pQCT) imaging of hand joints in patients with rheumatoid arthritis (RA) have suggested that erosion healing may occur. Our objective was to examine changes in erosion volume, joint space width (JSW), bone mineral density (BMD), and bone remodelling, and their association with clinical outcomes and measures of patient hand function. Method: We examined 48 patients who achieved a good response to a newly initiated biologic therapy. HR-pQCT images of the dominant hands’ second and third metacarpophalangeal joints were obtained 3 and 12 months after therapy initiation. Bone erosion volume, JSW, BMD, and bone remodelling were quantified from HR-pQCT images, with improvement, no change (unchanged), or progression in these measures determined by least significant change. Disease activity and hand function measures were collected. Results: There were no significant group changes in HR-pQCT outcomes over the 9 month period. Twenty-two patients had total erosion volumes that remained unchanged, nine showed improvement, and two progressed. The majority of JSW and BMD measures remained unchanged. There was a significant association between the baseline Health Assessment Questionnaire score and the change in minimum JSW, but no other significant associations between HR-pQCT outcomes and function were observed. Conclusions: The vast majority of patients maintained unchanged JSW and BMD over the course of follow-up. Significant improvements in total erosion volume occurred in 27% of patients, suggesting that biologic therapies may lead to erosion healing in some patients, although this did not have an impact on self-reported and demonstrated hand function.

Automated segmentation of fractured distal radii by 3D geodesic active contouring of in vivo HR-pQCT images.

Radius fractures are among the most common fracture types; however, there is limited consensus on the standard of care. A better understanding of the fracture healing process could help to shape future treatment protocols and thus improve functional outcomes of patients. High-resolution peripheral quantitative computed tomography (HR-pQCT) allows monitoring and evaluation of the radius on the micro-structural level, which is crucial to our understanding of fracture healing. However, current radius fracture studies using HR-pQCT are limited by the lack of automated contouring routines, hence only including small number of patients due to the prohibitively time-consuming task of manually contouring HR-pQCT images. In the present study, a new method to automatically contour images of distal radius fractures based on 3D morphological geodesic active contours (3D-GAC) is presented. Contours of 60 HR-pQCT images of fractured and conservatively treated radii spanning the healing process up to one year post-fracture are compared to the current gold standard, hand-drawn 2D contours, to assess the accuracy of the algorithm. Furthermore, robustness was established by applying the algorithm to HR-pQCT images of intact radii of 73 patients and comparing the resulting morphometric indices to the gold standard patient evaluation including a threshold- and dilation-based contouring approach. Reproducibility was evaluated using repeat scans of intact radii of 19 patients. The new 3D-GAC approach offers contours within inter-operator variability for images of fractured distal radii (mean Dice score of 0.992±0.005 versus median operator Dice score of 0.992±0.006). The generated contours for images of intact radii yielded morphometric indices within the in vivo reproducibility limits compared to the current gold standard. Additionally, the 3D-GAC approach shows an improved robustness against failure (n=5) when dealing with cortical interruptions, fracture fragments, etc. compared with the automatic, default manufacturer pipeline (n=40). Using the 3D-GAC approach assures consistent results, while reducing the need for time-consuming hand-contouring.

Effect of radiographic disease severity in high-resolution quantitative computed tomography assessment of metacarpophalangeal joint erosion and cysts.

Bone erosions are the hallmark of rheumatoid arthritis (RA). High-resolution peripheral quantitative computed tomography (HR-pQCT) enables 3-dimensional visualization of arthritic bone erosions at a high resolution. However, the degree of erosive disease could influence the reliability of HR-pQCT evaluation. We aim to assess the intra- and inter-reader variability of identification of erosions in the metacarpophalangeal (MCP) joints using HR-pQCT in healthy controls and patients with RA, stratified according to van der Heijde-modified Sharp Score (HSS) of radiographic erosions. We analyzed HR-pQCT images from 78 patients with RA and 25 healthy controls. Patients were allocated to one of three groups of mild, moderate or severe disease according to HSS of MCP joints 2 and 3. Total HR-pQCT scans were analyzed twice in random order by three experienced readers, blinded to group distribution. The number of cortical interruptions and their classification as either erosions or cysts according to predefined criteria were recorded. Intraclass correlation coefficients (ICC) for cortical interruptions, erosions and cysts were calculated for each group using a 2-way random-effects model for inter-reader ICC and a 2-way mixed-effects model for intra-reader ICC. The intra- and inter-reader ICC were good to moderate for cortical interruptions and moderate for erosions throughout disease severity groups. The ICCs for the identification of cysts decreased with increasing degree of erosive disease. The detection of cortical interruptions is only minimally affected by the degree of erosive damage, whereas the distinction between erosions and cysts is more complex in patients with extensive erosive disease.

Multi-Modal Imaging to Assess the Interaction Between Inflammation and Bone Damage Progression in Inflammatory Arthritis.

Combining results from multiple imaging techniques (i.e., multi-modal imaging) through image registration can result in the better characterization of joint tissue characteristics. In the context of inflammatory arthritis conditions, high-resolution peripheral quantitative computed tomography (HR-pQCT) provides excellent bone contrast while magnetic resonance imaging (MRI) provides superior contrast and resolution of soft tissue and inflammatory characteristics. Superimposing these imaging results upon each other provides a robust characterization of the joint. In a preliminary study of nine rheumatoid arthritis (RA) participants in clinical remission, we acquired HR-pQCT and MR images of their 2nd and 3rd metacarpophalangeal (MCP) joints at two timepoints 6 months apart. We present the benefits of a multi-modal imaging approach, in which we demonstrate the ability to localize regions of inflammation with subtle changes in bone erosion volume. Using HR-pQCT and MRI to visualize bone damage and inflammation, respectively, will improve our understanding of the impact that subclinical inflammation has on bone damage progression, and demonstrating if bone repair occurs where inflammation is resolved. The presented multi-modal imaging technique has the potential to study the progression of bone damage in relation to inflammation that otherwise would not be possible with either imaging technique alone. The multi-modal image registration technique will be helpful to understanding the development and pathogenesis of RA-associated bone erosions. Additionally, multi-modal imaging may provide a technique to probe the tissue-level changes that occur as a result of treatment regimes.

Association of higher bone turnover with risk of curve progression in adolescent idiopathic scoliosis.

Emerging evidence suggest abnormal bone metabolism and defective bone qualities are associated to etipathogenesis of Adolescent Idiopathic Scoliosis (AIS). Systemic low bone mass is important prognosticator to predict risk of curve progression in AIS. The underlying mechanism is still unclear. We hypothesize that aberrant bone turnover correlates with bone qualities in AIS and associates to risk of curve progression. Two cohorts were included in this study. The case-control study recruited 161 AIS girls and 161 ethnic/age-matched healthy girls. The longitudinal cohort recruited 128 AIS girls with two-year follow-up. Areal bone mineral density (BMD) at femoral necks were measured with dual-energy x-ray absorptiometry (DXA), and bone qualities of distal radius by high-resolution peripheral quantitative computed tomography (HR-pQCT). Time-lapse analysis of registered HR-pQCT images estimated local bone remodeling quantitatively. Serum levels of CTX and P1NP were measured with ELISA kits. AIS presented significantly higher serum level of P1NP. In both AIS and control, the negative correlations were consistently observed between serum CTX/P1NP levels and most cortical bone quality parameters after adjustment to age. Significant correlation between serum bone turnover markers and trabecular bone parameters have been observed only in control. Progressive AIS has significant increase of serum P1NP level at first clinic visit. Time lapse register analysis showed high bone resorption and low net bone gain was associated with risk of progression in AIS. Our study characterized AIS with higher serum bone turnover markers, which may contribute to defective bone qualities in AIS. For the first time, we showed that progressive AIS had higher systemic bone turnover markers level and local bone remodeling. This fresh evidence indicated association between disrupted bone turnover and risk of progression of AIS, which set the foundation of new prognostic method and of novel treatment target to curve progression. This study demonstrated the importance of bone metabolism in developing disease management of AIS to achieve goal of early prediction and non-surgical modulation.

Bone mineral density and bone microarchitecture in a cohort of patients with Erdheim-Chester Disease

BackgroundErdheim-Chester Disease (ECD) is a rare type of non-Langerhans histiocytosis. Skeletal structures are affected in over 95% ECD patients. Due to the lack of proper imaging assessment tools, the alteration of bone microarchitecture in ECD has not been well studied. High-resolution peripheral quantitative computed tomography (HR-pQCT) is a newly developed assessment of bone mineral density and bone microarchitecture.MethodsWe performed a cross-sectional study with 13 patients diagnosed with ECD in Peking Union Medical College Hospital between October 2018 and June 2019. The diagnosis of ECD was based on typical pathological findings in the context of appropriate clinical and radiological manifestations. Bone geometry, volumetric bone mineral density and bone microarchitecture of those ECD patients were assessed using HR-pQCT at the non-dominant distal radius and distal tibia. Those HR-pQCT parameters were then compared to an ongoing population-based database of HR-pQCT for Mainland Chinese.ResultsAs a result, remarkable heterogeneity of osteosclerosis in the HR-pQCT images was found in ECD patients, ranging from apparent normal structure, scattered thickening of trabecula, to homogenous consolidation. In terms of quantitative measurements, total volumetric BMD (383.50 mg/cm3, 1.352 times of normal mean, p = 0.023) of the tibia differed significantly in ECD patients, due to the increased trabecular volumetric BMD (291 mg/cm3, 2.058 times of normal mean, p = 0.003). The increased trabecular volumetric BMD of tibia was associated with remarkably increased number of trabecula (1.7/mm, 1.455 times of normal mean, p = 0.002) and increased thickness of trabecula (0.37 mm, 1.466 times of normal mean, p = 0.003). These differences could be due to the existence of dense bone interposed in the trabecula.ConclusionThis study is the first to assess the volumetric bone mineral density and bone microstructure with HR-pQCT in a cohort of ECD patients and indicated that the application of HR-pQCT may help to reveal the nature of bone lesions in the disease.