erosion-identification-metacarpophalangeal-joints-rheumatoid

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 ...

University of Calgary

High resolution peripheral quantitative computed tomography (HR-pQCT) is a 3-dimensional imaging modality with superior sensitivity for bone changes and abnormalities. Recent advances have led to increased use of HR-pQCT in inflammatory arthritis to report quantitative volumetric measures of bone density, microstructure, local anabolic (e.g., osteophytes, enthesiophytes) and catabolic (e.g., erosions) bone changes and joint space width. These features may be useful for monitoring disease progression, response to therapy, and are responsive to differentiating between those with inflammatory arthritis conditions and healthy controls. We reviewed 69 publications utilizing HR-pQCT imaging of the metacarpophalangeal (MCP) and/or wrist joints to investigate arthritis conditions. Erosions are a marker of early inflammatory arthritis progression, and recent work has focused on improvement and application of techniques to sensitively identify erosions, as well as quantifying erosion volume changes longitudinally using manual, semi-automated and automated methods. As a research tool, HR-pQCT may be used to detect treatment effects through changes in erosion volume in as little as 3 months. Studies with 1-year follow-up have demonstrated progression or repair of erosions depending on the treatment strategy applied. HR-pQCT presents several advantages. Combined with advances in image processing and image registration, individual changes can be monitored with high sensitivity and reliability. Thus, a major strength of HR-pQCT is its applicability in instances where subtle changes are anticipated, such as early erosive progression in the presence of subclinical inflammation. HR-pQCT imaging results could ultimately impact decision making to uptake aggressive treatment strategies and prevent progression of joint damage. There are several potential areas where HR-pQCT evaluation of inflammatory arthritis still requires development. As a highly sensitive imaging technique, one of the major challenges has been motion artifacts; motion compensation algorithms should be implemented for HR-pQCT. New research developments will improve the current disadvantages including, wider availability of scanners, the field of view, as well as the versatility for measuring tissues other than only bone. The challenge remains to disseminate these analysis approaches for broader clinical use and in research.

High-Resolution Peripheral Quantitative Computed Tomography for Bone Evaluation in Inflammatory Rheumatic Disease.

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.

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

This study developed methods to quantify and improve the accuracy of dual-energy CT (DECT)-based bone marrow edema imaging using a clinical CT system. Objectives were: (a) to quantitatively compare DECT with gold-standard, fluid-sensitive MRI for imaging of edema-like marrow signal intensity (EMSI) and (b) to identify image analysis parameters that improve delineation of EMSI associated with acute knee injury on DECT images.

A quantitative assessment of dual energy computed tomography-based material decomposition for imaging bone marrow edema associated with acute knee injury.

The purpose of this review is to inform researchers and clinicians with the most recent imaging techniques that are employed (1) to opportunistically screen for osteoporosis and (2) to provide a better understanding into the disease etiology of osteoporosis.

Advancements in Osteoporosis Imaging, Screening, and Study of Disease Etiology.

The aim of this study was to assess the accuracy and precision of a novel application of 3-material decomposition (3MD) with virtual monochromatic images (VMIs) in the dual-energy computed tomography (DECT) assessment of monosodium urate (MSU) and hydroxyapatite (HA) phantoms compared with a commercial 2-material decomposition (2MD) and dual-thresholding (DT) material decomposition methods.

Assessing the Sensitivity of Dual-Energy Computed Tomography 3-Material Decomposition for the Detection of Gout.

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 (r = 0.85) and XtremeCTII (r = 0.87). Erosion volume assessment by BAM-Erosion agreed strongly (r = 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.

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.

Muscle weakness can lead to reduced physical function and quality of life. Computed tomography (CT) can be used to assess muscle health through measures of muscle cross-sectional area and density loss associated with fat infiltration. However, there are limited opportunities to measure muscle density in clinically acquired CT scans because a density calibration phantom, allowing for the conversion of CT Hounsfield units into density, is typically not included within the field-of-view. For bone density analysis, internal density calibration methods use regions of interest within the scan field-of-view to derive the relationship between Hounsfield units and bone density, but these methods have yet to be adapted for muscle density analysis. The objective of this study was to design and validate a CT internal calibration method for muscle density analysis.

Internal calibration for opportunistic computed tomography muscle density analysis.

The trapeziometacarpal (TMC) joint is a mechanically complex joint and is commonly affected by musculoskeletal diseases such as osteoarthritis. Quantifying in vivo TMC joint biomechanics, such as joint angles, with traditional reflective marker-based methods can be difficult due to the joint's location in the hand. Dynamic computed tomography (CT) can facilitate the quantification of TMC joint motion by continuously capturing three-dimensional volumes over time. However, post-processing of dynamic CT datasets can be time intensive and automated methods are needed to reduce processing times to allow for application to larger clinical studies. The purpose of this work is to introduce a fast, semi-automated pipeline to quantify joint angles from dynamic CT scans of the TMC joint and evaluate the associated error in joint angle and translation computation by means of a reproducibility and repeatability study.

Reproducibility and repeatability of a semi-automated pipeline to quantify trapeziometacarpal joint angles using dynamic computed tomography.

Hereditary hemochromatosis (HH) causes unbalanced iron deposition in many organs including the joints leading to severe cartilage loss and bone damage in the metacarpophalangeal joints (MCPJ). High-resolution peripheral quantitative computed tomography (HR-pQCT) and its joint space width (JSW) quantification algorithm quantifies in vivo 3D joint morphology. We therefore aimed to (i) determine feasibility and performance of the JSW algorithm in HH, (ii) quantify joint space morphology, and (iii) investigate the relationship between morphological and clinical parameters in HH. Here, we performed an exploratory study on 24 HH patients and sex- and age-matched controls using HR-pQCT imaging of MCPJ. Mineralized bone structure was automatically segmented from the grayscale image data and periosteal surface bone masks and joint space masks were generated. Mean, minimal, and maximal joint space width (JSW; JSW.MIN; JSW.MAX), JSW heterogeneity (JSW.SD), JSW asymmetry (JSW.AS), and joint space volume (JSV) were computed. Demographics and, for HH patients, disease-specific parameters were recorded. Segmentation of JS was very good with 79.7% of MCPJs successfully segmented at first attempt and 20.3% requiring semi-manual correction. HH men showed larger JSV at all MCPs (+ 25.4% < JSV <  + 41.8%, p < 0.05), larger JSW.MAX at MCP 3-4 (+ 14%, 0.006 < p < 0.062), and wider JSW (+ 13%, p = 0.043) at MCP 4 relative to HH women. Compared to controls, both HH men and HH women showed larger JSW.AS and smaller JSW.MIN at all MCP levels, reaching significance for HH men at MCP 2 and 3 (JSW.AS: + 323% < JSW.AS <  + 359%, 0.020 < p < 0.043; JSW.MIN: - 216% < JSW.MIN < - 225%, p < 0.043), and for women at MCP 3 (JSW.AS: + 180%, p = 0.025; JSW.MIN: - 41.8%, p = 0.022). Time since HH diagnosis was correlated positively with MCP 4 JSW.AS and JSW.SD (0.463 < ρ < 0.499, p < 0.040), and the number of phlebotomies since diagnosis was correlated with JSW.SD at all MCPs (0.432 < ρ < 0.535, p < 0.050). HR-pQCT-based JSW quantification in MCPJ of HH patients is feasible, performs well even in narrow JS, and allows to define the microstructural joint burden of HH.

Analysis of Hand Joint Space Morphology in Women and Men with Hereditary Hemochromatosis.

Computed tomography (CT) offers advanced biomedical imaging of the body and is broadly utilized for clinical diagnosis. Traditionally, clinical CT scans have not been used for volumetric bone mineral density (vBMD) assessment; however, computational advances can now leverage clinically obtained CT data for the secondary analysis of bone, known as opportunistic CT analysis. Initial applications focused on using clinically acquired CT scans for secondary osteoporosis screening, but opportunistic CT analysis can also be applied to answer research questions related to vBMD changes in response to various disease states. There are several considerations for opportunistic CT analysis, including scan acquisition, contrast enhancement, the internal calibration technique, and bone segmentation, but there remains no consensus on applying these methods. These factors may influence vBMD measures and therefore the robustness of the opportunistic CT analysis. Further research and standardization efforts are needed to establish a consensus and optimize the application of opportunistic CT analysis for accurate and reliable assessment of vBMD in clinical and research settings. This review summarizes the current state of opportunistic CT analysis, highlighting its potential and addressing the associated challenges.

Article	Year
High-Resolution Peripheral Quantitative Computed Tomography for Bone Evaluation in Inflammatory Rheumatic Disease. Frontiers in medicine\| PubMed ID: 32766262	2020
Multi-Modal Imaging to Assess the Interaction Between Inflammation and Bone Damage Progression in Inflammatory Arthritis. Frontiers in medicine\| PubMed ID: 33102498	2020
A quantitative assessment of dual energy computed tomography-based material decomposition for imaging bone marrow edema associated with acute knee injury. Medical physics\| PubMed ID: 33606278	2021
Advancements in Osteoporosis Imaging, Screening, and Study of Disease Etiology. Current osteoporosis reports\| PubMed ID: 34292468	2021
Assessing the Sensitivity of Dual-Energy Computed Tomography 3-Material Decomposition for the Detection of Gout. Investigative radiology\| PubMed ID: 35467564	2022
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... Bone\| PubMed ID: 36174928	2022
Internal calibration for opportunistic computed tomography muscle density analysis. PloS one\| PubMed ID: 36251648	2022
Reproducibility and repeatability of a semi-automated pipeline to quantify trapeziometacarpal joint angles using dynamic computed tomography. BMC medical imaging\| PubMed ID: 36348287	2022
Analysis of Hand Joint Space Morphology in Women and Men with Hereditary Hemochromatosis. Calcified tissue international\| PubMed ID: 36738308	2023
Addressing Challenges of Opportunistic Computed Tomography Bone Mineral Density Analysis. Diagnostics (Basel, Switzerland)\| PubMed ID: 37568935	2023

Justin J. Tse

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