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The utility of multi-stack alignment and 3D longitudinal image registration to assess bone remodeling in rheumatoid arthritis patients from second generation HR-pQCT scans.

ABSTRACT: BACKGROUND:Medical imaging plays an important role in determining the progression of joint damage in rheumatoid arthritis (RA). High resolution peripheral quantitative computed tomography (HR-pQCT) is a sensitive tool capable of evaluating bone microarchitecture and erosions, and 3D rigid image registration can be used to visualize and quantify bone remodeling over time. However, patient motion during image acquisition can cause a "stack shift" artifact resulting in loss of information and reducing the number of erosions that can be analyzed using HR-pQCT. The purpose of this study was to use image registration to improve the number of useable HR-pQCT scans and to apply image-based bone remodeling assessment to the metacarpophalangeal (MCP) joints of RA patients. METHODS:Ten participants with RA completed HR-pQCT scans of the 2nd and 3rd MCP joints at enrolment to the study and at a 6-month follow-up interval. At 6-months, an additional repeat scan was acquired to evaluate reliability. HR-pQCT images were acquired in three individual 1?cm acquisitions (stacks) with a 25% overlap. We completed analysis first using standard evaluation methods, and second with multi-stack registration. We assessed whether additional erosions could be evaluated after multi-stack registration. Bone remodeling analysis was completed using registration and transformation of baseline and follow-up images. We calculated the bone formation and resorption volume fractions with 6-month follow-up, and same-day repositioning as a negative control. RESULTS:13/57 (23%) of erosions could not be analyzed from raw images due to a stack shift artifact. All erosions could be volumetrically assessed after multi-stack registration. We observed that there was a median bone formation fraction of 2.1% and resorption fraction of 3.8% in RA patients over the course of 6?months. In contrast to the same-day rescan negative control, we observed median bone formation and resorption fractions of 0%. CONCLUSIONS:Multi-stack image registration is a useful tool to improve the number of useable scans when analyzing erosions using HR-pQCT. Further, image registration can be used to longitudinally assess bone remodeling. These methods could be implemented in future studies to provide important pathophysiological information on the progression of bone damage.

SUBMITTER: Brunet SC

PROVIDER: S-EPMC7140503 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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The utility of multi-stack alignment and 3D longitudinal image registration to assess bone remodeling in rheumatoid arthritis patients from second generation HR-pQCT scans.

Brunet Scott C SC Kuczynski Michael T MT Bhatla Jennifer L JL Lemay Sophie S Pauchard Yves Y Salat Peter P Barnabe Cheryl C Manske Sarah L SL

BMC medical imaging 20200407 1

<h4>Background</h4>Medical imaging plays an important role in determining the progression of joint damage in rheumatoid arthritis (RA). High resolution peripheral quantitative computed tomography (HR-pQCT) is a sensitive tool capable of evaluating bone microarchitecture and erosions, and 3D rigid image registration can be used to visualize and quantify bone remodeling over time. However, patient motion during image acquisition can cause a "stack shift" artifact resulting in loss of information a ...[more]

PMID: 32264872

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Project description:During aging, changes in endosteal and periosteal boundaries of cortical bone occur that differ between men and women. We here develop a new procedure that uses high-resolution peripheral quantitative CT (HR-pQCT) imaging and 3D registration to identify such changes within the timescale of longitudinal studies. A first goal was to test the sensitivity of the approach. A second goal was to assess differences in periosteal/endosteal expansion over time between men and women. Rigid 3D registration was used to transform baseline and all follow-up (FU) images to a common reference configuration for which the region consisting of complete slices (largest common height) was determined. Periosteal and endosteal contours were transformed to the reference position to determine the net periosteal and endosteal expansion distances. To test the sensitivity, images from a short-term reproducibility study were used (15 female, aged 21 to 47 years, scanned three times). To test differences between men and women, images from a subset of the Geneva Retirees Cohort were used (248 female, 61 male, average age 65 years, 3.5 and 7 years FU). The sensitivity study indicated a least significant change for detecting periosteal/endosteal expansion of 41/31 microns for the radius and 17/26 microns for the tibia. Results of the cohort study showed significant net endosteal retraction only in females at the radius and tibia after 3.5 years (38.0 and 38.4 microns, respectively) that further increased at 7 years FU (70.4 and 70.8 microns, respectively). No significant net periosteal changes were found for males or females at 7 years. The results demonstrate that it is possible to measure changes in endosteal contours in longitudinal studies within several years. For the investigated cohort, significant endosteal retraction was found in females but not in males. Whether these changes in cortical geometry are related to fracture risk remains to be investigated in larger cohorts © 2021 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

Project description:The investigation of cortical porosity is an important aspect of understanding biological, pathoetiological, and biomechanical processes occurring within the skeleton. With the emergence of HR-pQCT as a noninvasive tool suitable for clinical use, cortical porosity at appendicular sites can be directly visualized in vivo. The aim of this study was to introduce a novel topological analysis of the cortical pore network for HR-pQCT data and determine the influence of resolution on measures of cortical pore network microstructure and topology.Cadaveric radii were scanned using HR-pQCT at two different voxel sizes (41 and 82 μm) and also using μCT at a voxel size of 18 μm. HR-pQCT and μCT image sets were spatially coregistered. Segmentation and quantification of cortical porosity (Ct.Po) and mean pore diameter (Ct.Po.Dm) were achieved using an established extended cortical analysis technique. Topological classification of individual pores was performed using topology-preserving skeletonization and multicolor dilation algorithms. Based on the pore skeleton topological classification, the following parameters were quantified: total number of planar surface-skeleton canals (N.Slabs), tubular curve-skeleton canals (N.Tubes), and junction elements (N.Junctions), mean slab volume (Slab.Vol), mean tube volume (Tube.Vol), mean slab orientation (Slab.θ), mean tube orientation (Tube.θ), N.Slabs/N.Tubes, and integral (total) slab volume/integral tube volume (iSlab.Vol/iTube.Vol). An in vivo reproducibility study was also conducted to assess short-term precision of the topology parameters. Precision error was characterized using root mean square coefficient of variation (RMSCV%).Correlations to μCT values for Ct.Po were significant for both the 41 and 82 μm HR-pQCT data (41: r(2) = 0.82, p < 0.001, 82: r(2) = 0.75, p < 0.001). For Ct.Po.Dm, only the 41 μm data were significantly predictive of μCT values (r(2) = 0.72, p < 0.01) Data at both HR-pQCT voxel sizes were strongly predictive of the μCT values for N.Slabs (41: r(2) = 0.93, p < 0.001; 82: r(2) = 0.84, p < 0.001), N.Tubes (41: r(2) = 0.94, p < 0.001; 82: r(2) = 0.84, p < 0.001), and N.Junctions (41: r(2) = 0.93, p < 0.001; 82: r(2) = 0.78, p < 0.001), though proportional bias was evident in these correlations. Weak correlations were seen for iSlab.Vol/iTube.Vol at both voxel sizes (41: r(2) = 0.52, p < 0.01; 82: r(2) = 0.39, p < 0.05). Slab.Vol was significantly correlated to μCT data at 41 μm (r(2) = 0.60, p < 0.01) but not at 82 μm, while Tube.Vol was significantly correlated at both voxel sizes (41: r(2) = 0.79, p < 0.001; 82: r(2) = 0.68, p < 0.01). In vivo precision error for these parameters ranged from 2.31 to 9.68 RMSCV%.Strong correlations between μCT- and HR-pQCT-derived measurements were found, particularly in HR-pQCT images obtained at 41 μm. These data are in agreement with our previous study investigating the effect of voxel size on standard HR-pQCT metrics of trabecular and cortical microstructure, and extend our previous findings to include topological descriptors of the cortical pore network.

Project description:In-vivo bone microstructure measured by high-resolution peripheral quantitative computed tomography (HR-pQCT) is gaining importance in research and clinical practice. Second-generation HR-pQCT (XCT2) shows improved image quality and shorter measurement duration compared to the first generation (XCT1). Predicting and understanding the occurrence of motion artifacts is crucial for clinical practice. We retrospectively analyzed data from HR-pQCT measurements at the distal radius and tibia of 1,000 patients (aged 20 to 89) evenly distributed between both generations of HR-pQCT. Motion artifacts were graded between 1 (no motion) and 5 (severe motion), with grades greater 3 considered unusable. Additionally, baseline characteristics and patients' muscle performance and balance were measured. Various group comparisons between the two generations of HR-pQCT and regression analyses between patient characteristics and motion grading were performed. The study groups of XCT1 and XCT2 did not differ by age (XCT1: 64.9 vs. XCT2: 63.8 years, p = 0.136), sex (both 74.5% females, p > 0.999), or BMI (both 24.2 kg/m2, p = 0.911) after propensity score matching. XCT2 scans exhibited significantly lower motion grading in both extremities compared to XCT1 (Radius: p < 0.001; Tibia: p = 0.002). In XCT2 motion-corrupted scans were more than halved at the radius (XCT1: 35.3% vs. XCT2: 15.5%, p < 0.001), and at the tibia the frequency of best image quality scans was increased (XCT1: 50.2% vs. XCT2: 63.7%, p < 0.001). The strongest independent predictor for motion-corrupted images is the occurrence of high motion grading at the other scanning site during the same consultation. The association between high motion grading in one scan and a corresponding high motion grading in another scan within the same session suggests a non-resting patient. Additionally, aged, female, and patients with smaller stature tend towards higher motion grading, requiring special attention to a correct extremity fixation.

Project description:The aim of this study was to quantify the effect of four image registration methods on lung texture features extracted from serial computed tomography (CT) scans obtained from healthy human subjects.Two chest CT scans acquired at different time points were collected retrospectively for each of 27 patients. Following automated lung segmentation, each follow-up CT scan was registered to the baseline scan using four algorithms: (1) rigid, (2) affine, (3) B-splines deformable, and (4) demons deformable. The registration accuracy for each scan pair was evaluated by measuring the Euclidean distance between 150 identified landmarks. On average, 1432 spatially matched 32 × 32-pixel region-of-interest (ROI) pairs were automatically extracted from each scan pair. First-order, fractal, Fourier, Laws' filter, and gray-level co-occurrence matrix texture features were calculated in each ROI, for a total of 140 features. Agreement between baseline and follow-up scan ROI feature values was assessed by Bland-Altman analysis for each feature; the range spanned by the 95% limits of agreement of feature value differences was calculated and normalized by the average feature value to obtain the normalized range of agreement (nRoA). Features with small nRoA were considered "registration-stable." The normalized bias for each feature was calculated from the feature value differences between baseline and follow-up scans averaged across all ROIs in every patient. Because patients had "normal" chest CT scans, minimal change in texture feature values between scan pairs was anticipated, with the expectation of small bias and narrow limits of agreement.Registration with demons reduced the Euclidean distance between landmarks such that only 9% of landmarks were separated by ≥1 mm, compared with rigid (98%), affine (95%), and B-splines (90%). Ninety-nine of the 140 (71%) features analyzed yielded nRoA > 50% for all registration methods, indicating that the majority of feature values were perturbed following registration. Nineteen of the features (14%) had nRoA < 15% following demons registration, indicating relative feature value stability. Student's t-tests showed that the nRoA of these 19 features was significantly larger when rigid, affine, or B-splines registration methods were used compared with demons registration. Demons registration yielded greater normalized bias in feature value change than B-splines registration, though this difference was not significant (p = 0.15).Demons registration provided higher spatial accuracy between matched anatomic landmarks in serial CT scans than rigid, affine, or B-splines algorithms. Texture feature changes calculated in healthy lung tissue from serial CT scans were smaller following demons registration compared with all other algorithms. Though registration altered the values of the majority of texture features, 19 features remained relatively stable after demons registration, indicating their potential for detecting pathologic change in serial CT scans. Combined use of accurate deformable registration using demons and texture analysis may allow for quantitative evaluation of local changes in lung tissue due to disease progression or treatment response.

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Dataset Information

The utility of multi-stack alignment and 3D longitudinal image registration to assess bone remodeling in rheumatoid arthritis patients from second generation HR-pQCT scans.

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The utility of multi-stack alignment and 3D longitudinal image registration to assess bone remodeling in rheumatoid arthritis patients from second generation HR-pQCT scans.

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