D. Loeffen

Automated quantification of epicardial adipose tissue (EAT) in coronary CT angiography; comparison with manual assessment and correlation with coronary artery disease

BACKGROUND Epicardial adipose tissue (EAT) is emerging as a risk factor for coronary artery disease (CAD). OBJECTIVE The aim of this study was to determine the applicability and efficiency of automated EAT quantification. METHODS EAT volume was assessed both manually and automatically in 157 patients undergoing coronary CT angiography. Manual assessment consisted of a short-axis-based manual measurement, whereas automated assessment on both contrast and non-contrast-enhanced data sets was achieved through novel prototype software. Duration of both quantification methods was recorded, and EAT volumes were compared with paired samples t test. Correlation of volumes was determined with intraclass correlation coefficient; agreement was tested with Bland-Altman analysis. The association between EAT and CAD was estimated with logistic regression. RESULTS Automated quantification was significantly less time consuming than automated quantification (17 ± 2 seconds vs 280 ± 78 seconds; P < .0001). Although manual EAT volume differed significantly from automated EAT volume (75 ± 33 cm(³) vs 95 ± 45 cm(³); P < .001), a good correlation between both assessments was found (r = 0.76; P < .001). For all methods, EAT volume was positively associated with the presence of CAD. Stronger predictive value for the severity of CAD was achieved through automated quantification on both contrast-enhanced and non-contrast-enhanced data sets. CONCLUSION Automated EAT quantification is a quick method to estimate EAT and may serve as a predictor for CAD presence and severity.

An automated algorithm for the detection of cortical interruptions on high resolution peripheral quantitative computed tomography images of finger joints

Objectives To introduce a fully-automated algorithm for the detection of small cortical interruptions (≥0.246mm in diameter) on high resolution peripheral quantitative computed tomography (HR-pQCT) images, and to investigate the additional value of manual correction of the automatically obtained contours (semi-automated procedure). Methods Ten metacarpophalangeal joints from seven patients with rheumatoid arthritis (RA) and three healthy controls were imaged with HR-pQCT. The images were evaluated by an algorithm according to the fully- and semi-automated procedure for the number and surface of interruptions per joint. Reliability between the fully- and semi-automated procedure and between two independent operators was tested using intra-class correlation coefficient (ICC) and the proportion of matching interruptions. Validity of single interruptions detected was tested by comparing it to visual scoring, as gold standard. The positive predictive value (PPV) and sensitivity were calculated. Results The median number of interruptions per joint was 14 (range 2 to 59) and did not significantly differ between the fully- and semi-automated procedure (p = 0.37). The median interruption surface per joint was significantly higher with the fully- vs. semi-automated procedure (respectively, 8.6mm2 vs. 5.8mm2 and 6.1mm2, p = 0.01). Reliability was almost perfect between the fully- and semi-automated procedure for both the number and surface of interruptions (ICC≥0.95) and the proportion of matching interruptions was high (≥76%). Also the inter-operator reliability was almost perfect (ICC≥0.97, proportion of matching interruptions 92%). The PPV ranged from 27.6% to 29.9%, and sensitivity from 69.7% to 76.3%. Most interruptions detected with the algorithm, did show an interruption on a 2D grayscale image. However, this interruption did not meet the criteria of an interruption with visual scoring. Conclusion The algorithm for HR-pQCT images detects cortical interruptions, and its interruption surface. Reliability and validity was comparable for the fully- and semi-automated procedures. However, we advise the use of the semi-automated procedure to assure quality. The algorithm is a promising tool for a sensitive and objective assessment of cortical interruptions in finger joints assessed by HR-pQCT.

Structural damage and inflammation on radiographs or magnetic resonance imaging are associated with cortical interruptions on high-resolution peripheral quantitative computed tomography: a study in finger joints of patients with rheumatoid arthritis and healthy subjects.

Objectives: To study the relationship between structural damage and inflammatory features on magnetic resonance imaging (MRI) or radiography and other risk factors [anti-citrullinated protein antibody (ACPA) and/or rheumatoid factor (RF) seropositivity, hand dominance, disease duration] and the presence or number of cortical interruptions in finger joints on high-resolution peripheral quantitative computed tomography (HR-pQCT). Method: Finger joints of 38 healthy subjects and 39 patients with rheumatoid arthritis (RA) were examined through radiographs, MRI, and HR-pQCT. Radiographs were scored according to the Sharp/van der Heijde (SvH) method; MRI for the presence of cortical interruptions, bone marrow oedema (BMO), and synovitis; and HR-pQCT images for cortical interruptions. Descriptive statistics were calculated and associations examined using generalized estimating equations. Results: Cortical interruptions were found in healthy subjects and patients with RA on HR-pQCT (mean ± sd 0.33 ± 0.63 vs 0.38 ± 0.64 per joint quadrant, respectively, p < 0.01). Structural damage on MRI (cortical interruptions) or radiographs (SvH ≥ 1) was associated with the presence of cortical interruptions on HR-pQCT [odds ratio (OR) 12.4, 95% confidence interval (CI) 7.5–21.4, p < 0.01 and OR 4.8, 95% CI 1.9–11.7, respectively, p < 0.01]. The presence of BMO or synovitis was associated with more cortical interruptions on HR-pQCT (β 0.47, 95% CI 0.4–0.6, p < 0.01 and β 1.9, 95% CI 0.6–3.1, p < 0.01). In patients with RA, ACPA, and/or RF seropositivity, hand dominance and disease duration were not associated with more cortical interruptions on HR-pQCT. Conclusion: Structural damage and inflammatory features on MRI and radiographs are associated with cortical interruptions on HR-pQCT. No association between other risk factors and cortical interruptions was demonstrated.

Development of a scoring method to visually score cortical interruptions on high-resolution peripheral quantitative computed tomography in rheumatoid arthritis and healthy controls

Objectives To develop a scoring method to visually score cortical interruptions in finger joints on High-Resolution peripheral Quantitative Computed Tomography (HR-pQCT), determine its intra- and inter-reader reliability and test its feasibility. Methods The scoring method was developed by integrating results from in-depth discussions with experts, consensus meetings, multiple reading experiments and the literature. Cortical interruptions were scored by two independent readers in an imaging dataset with finger joints from patients with rheumatoid arthritis (RA) and healthy controls and assessed for adjacent trabecular distortion. Reliability for the total number of cortical interruptions per joint and per quadrant was calculated using intraclass correlation coefficient (ICC). Feasibility was tested by recording the time to analyze one joint. Results In 98 joints we identified 252 cortical interruptions, 17% had trabecular distortion. Mean diameter of the interruptions was significantly larger in patients with RA compared with healthy controls (0.88 vs 0.47 mm, p = 0.03). Intra-reader reliability was ICC 0.88 (95% CI 0.83;0.92) per joint and ICC 0.69 (95% CI 0.65;0.73) per quadrant. Inter-reader reliability was ICC 0.48 (95% CI 0.20;0.67) per joint and ICC 0.56 (95% CI 0.49;0.62) per quadrant. The time to score one joint was mean 9.2 (SD 4.9) min. Conclusions This scoring method allows detection of small cortical interruptions on HR-pQCT imaging of finger joints, which is promising for use in clinical studies.

Assessment of Cortical Interruptions in the Finger Joints of Patients With Rheumatoid Arthritis Using HR-pQCT, Radiography, and MRI: ASSESSMENT OF CORTICAL INTERRUPTIONS IN FINGER JOINTS OF PATIENTS WITH RA

Small cortical interruptions may be the first sign of an erosion, and more interruptions can be found in patients with rheumatoid arthritis (RA) compared with healthy subjects. First, we compared the number and size of interruptions in patients with RA with healthy subjects using high‐resolution peripheral quantitative CT (HR‐pQCT). Second, we investigated the association between structural damage and inflammatory markers on conventional radiography (CR) and MRI with interruptions on HR‐pQCT. Third, the added value of HR‐pQCT over CR and MRI was investigated. The finger joints of 39 patients with RA and 38 healthy subjects were examined through CR, MRI, and HR‐pQCT. CRs were scored using the Sharp/Van der Heijde method. MRI images were analyzed for the presence of erosions, bone marrow edema, and synovitis. HR‐pQCT images were analyzed for the number, surface area, and volume of interruptions using a semiautomated algorithm. Descriptives were calculated and associations were tested using generalized estimating equations. Significantly more interruptions and both a larger surface area and the volume of interruptions were detected in the metacarpophalangeal joints of patients with RA compared with healthy subjects (median, 2.0, 1.42 mm2, and 0.48 mm3 versus 1.0, 0.69 mm2, and 0.23 mm3, respectively; all p < 0.01). Findings on CR and MRI were significantly associated with more and larger interruptions on HR‐pQCT (prevalence ratios [PRs] ranging from 1.03 to 7.74; all p < 0.01) in all subjects, and were consistent in patients with RA alone. Having RA was significantly associated with more and larger interruptions on HR‐pQCT (PRs, 2.33 to 5.39; all p < 0.01), also after adjustment for findings on CR or MRI. More and larger cortical interruptions were found in the finger joints of patients with RA versus healthy subjects, also after adjustment for findings on CR or MRI, implying that HR‐pQCT imaging may be of value in addition to CR and MRI for the evaluation of structural damage in patients with RA.

FRI0662 Assessment of bone density, structure, and cortical interruptions of finger joints in patients with rheumatoid arthritis using high-resolution peripheral quantitative ct

Background Rheumatoid arthritis (RA) is characterized by peri-articular bone loss. In patients with RA, lower bone density and structural integrity, and an increased number of erosions compared to healthy controls (HCs) has been demonstrated using High-Resolution peripheral Quantitative CT (HR-pQCT) (1,2). To further characterize RA-related changes, we recently introduced a method for quantifying small cortical interruptions in finger joints (3). Objectives To investigate the cortical and trabecular bone density, structure, and cortical interruptions in MCP joints in early and late RA patients compared to HCs using HR-pQCT imaging. Methods The 2nd and 3rd MCP joint of 70 subjects (mean age 53.1 (SD 9.2) years) were evaluated by HR-pQCT (82μm isotropic voxel size): 38 HCs, 10 early RA (diagnosis ≤2 years ago) and 22 late RA (diagnosis ≥10 years ago). Images were analyzed for cortical interruptions, and for cortical and trabecular bone density and structure. Descriptives were analyzed per joint by one-way ANOVA with Bonferroni post-hoc testing or Kruskal-Wallis with Mann-Whitney post-hoc testing, as appropriate. Results Significant differences with respect to all parameters were found across the groups (Table 1). In early and late RA, the percentage of joints with at least 1 interruption was higher, and number of trabeculae, cortical thickness, total density and cortical density were lower than in HC. In addition, in late RA, number of interruptions, interruption volume and trabecular separation were higher, and trabecular density was lower than in HC. Bone loss at the cortical and trabecular bone was primarily observed at the rim of the joint (Figure 1, arrows).Table 1. Comparison of cortical interruptions, and bone density and structure parameters across early RA patients, late RA patients and HCs HC Early RA Late RA p-value Cortical interruption parameters n=82 n=39 n=73  Percentage of joints ≥1 interruption, % 69.5 89.7 * 82.2 0.025  Number of interruptions 1.50 (1.49) 2.64 (2.95) 5.22* (6.32) <0.001  Interruption volume, mm3 1.49 (5.16) 2.05 (6.76) 39.31* (78.51) <0.001 Bone density parameters n=50 n=31 n=68  Total vBMD, mg HA/cm3 327.3 (35.3) 295.8* (38.9) 286.4* (65.1) <0.001  Trabecular vBMD, mg HA/cm3 202.1 (20.6) 185.0 (21.6) 177.3* (42.0) <0.001  Cortical vBMD, mg HA/cm3 685.8 (42.8) 643.7* (58.2) 634.0* (73.3) <0.001 Bone structure parameters n=50 n=31 n=68  Trabecular number, mm1 1.68 (0.31) 1.45* (0.29) 1.52* (0.37) 0.004  Trabecular thickness, μm 102.3 (15.3) 109.1 (17.8) 98.6 (14.7) 0.009  Trabecular separation, μm 513.9 (116.9) 608.4 (132.3) 611.4* (220.6) 0.007  Distribution of trabecular separation, μm 550.6 (287.0) 728.5 (306.1) 689.4 (368.8) 0.029  Cortical thickness, μm 440.0 (99.2) 363.2* (90.2) 357.5* (132.8) <0.001 Values are displayed as mean (SD) or otherwise described. *Significantly different from HC, p<0.05. 1p-value obtained across the groups. vBMD, volumetric bone mineral density. Conclusions Bone density and structural integrity were impaired in early and late RA patients compared to HCs whereas the number of cortical interruptions is increased. The assessment of such parameters using HR-pQCT is, therefore, a promising tool for the follow-up of bone involvement in MCP joints in patients with RA. References Fouque-Aubert et al., ARD 2010. Stach et al., A&R 2010. Peters et al., ACR2016 (abstract). Disclosure of Interest M. Peters: None declared, A. Scharmga: None declared, A. van Tubergen: None declared, D. Loeffen: None declared, R. Weijers: None declared, B. van Rietbergen Consultant for: Scanco Medical AG, P. Geusens: None declared, J. van den Bergh: None declared

SAT0531 Can Histologically Defined Peri-Articular Vascular Channels Be Identified on High-Resolution Computed Tomography? A Study in Cadaveric Finger Joints

Background Several studies have indicated that High Resolution peripheral CT (HR-pQCT) scanning is more sensitive than radiography in detecting cortical breaks in destructive joint diseases like rheumatoid arthritis (RA)[1–3]. Cortical breaks are also seen in healthy controls, but the exact nature of these breaks is not known, and might represent vascular channels (VCs). No previous study has compared histology to HR-pQCT images in finger joints. We hypothesized that VCs seen on histology can also be detected by HR-pQCT imaging. Objectives To identify histologically defined VCs in cadaveric hand joints on HR-pQCT imaging. Methods Based on HR-pQCT, three regions in metacarpophalangeal joints from female cadavers with an unknown medical history (mean age 84.7, SD 5.5 years) were selected. These regions were extracted, embedded undecalcified in methylmetacrylate and histologically sectioned (thickness 15μm) parallel to the axial plane. Every second section (n=450) was stained with Goldner Trichrome. VCs were identified as a cortical break in one histological section which contained one or more vessels. HR-pQCT images (thickness 82μm) were independently scored by two trained readers for the presence of cortical breaks and if applicable categorized as VC. A break on HR-pQCT was defined as an interruption of the cortex seen on 2 consecutive slices in at least 2 orthogonal planes. A VC was defined as a break that is linear in shape with parallel lining. Finally, the histological sections were matched visually to corresponding axial HR-pQCT images. Results A total of 56 VCs were identified on histology. On HR-pQCT 20 breaks were identified, of which 7 were categorized as VC. Only 3 VCs matched with VCs on histology. Of the remaining 53 histologically identified VCs, 34 could be detected on HR-pQCT, but the interruption of the cortex was not seen on 2 consecutive slices therefore they were not classified as a break. Eight histologically VCs fulfilled the definition of a break on HR-pQCT, but were not categorized as a VC. Eleven histologically VCs could not be identified on HR-pQCT. Figure 1 demonstrates histology and HR-pQCT images. Conclusions VCs were frequently seen on histology. Only a minority of histologically defined VCs is interpreted as VC using a pre-specified definition on HR-pQCT images. Small histological VCs were often identified as an interruption but rarely considered a break according to the current definition of a VC on HR-pQCT. Therefore, additional criteria in order to diagnose the presence of VCs on HR-pQCT are warranted. References Stach CM, A&R.2010 Feb; 62(2):330–339. Srikhum W, JRheum.2013 Apr; 40(4):408–416. Fouque-Aubert A, ARD.2010 Sep; 69(9):1671–1676. Disclosure of Interest A. Scharmga: None declared, K. Keller: None declared, M. Peters: None declared, A. van Tubergen: None declared, J. van den Bergh: None declared, B. van Rietbergen Consultant for: Scanco Medical AG, R. Weijers: None declared, D. Loeffen: None declared, E. M. Hauge: None declared, P. Geusens: None declared

FRI0538 Validation of A Semi-Automatic Algorithm for Defining Cortical Breaks in Finger Joints Using High-Resolution Peripheral Quantitative CT by Microct

Background High-Resolution peripheral QCT (HR-pQCT) imaging has a higher sensitivity in the detection of breaks compared to conventional radiography (1). Cortical bone in the finger joints is very thin (

FRI0539 Reliability of A Semi-Automatic Algorithm in The Detection of Cortical Breaks in Finger Joints Using High Resolution Peripheral Quantitative CT

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FRI0576 Cross-Sectional Evaluation of High-Resolution CT Imaging Compared to MRI and Conventional Radiography for the Detection of Erosions in Rheumatoid Arthritis

100μm) and it is therefore possible that the HR-pQCT is not able to detect these thin structures. An automatic algorithm that is based on binary images can therefore falsely identify these regions as breaks. To investigate the extent of this error, cortical break detection on HR-pQCT was compared to that on μCT with a higher resolution. Objectives To investigate the proportion of falsely detected breaks with a semi-automatic algorithm on HR-pQCT compared to μCT. Methods Nineteen finger joints of ten human female cadaveric index fingers (mean age ± SD; 85.1 ± 9.6 years) with unknown medical history were imaged by HR-pQCT and μCT (82 and 18μm isotropic voxel sizes, respectively). A semi-automatic algorithm was applied to HR-pQCT and μCT for the detection of cortical breaks. First, the outer margin of the bone structure was contoured. Second, the bone within 0.25mm from this contour was selected as cortical region. Last, different sizes for defining a cortical break (>0.50mm, >0.66mm and >0.82mm) were applied and evaluated. μCT images were registered to HR-pQCT in order to compare the locations of the detected breaks. The false discovery rate (FDR) of breaks detected on HR-pQCT was calculated, with μCT as reference. Results The number of breaks depended on the image modality and chosen break size, and varied between 0.8 and 20.8 breaks per joint (table 1).Table 1. Comparison of the breaks detected on HR-pQCT and μCT by the algorithm using different break sizes Minimal break size Number of breaks per joint1 (n=19 joints) FDR of HR-pQCT2 HR-pQCT μCT μCT μCT same break size break size of >0.50mm >0.50mm 14.2±11.6 20.8±19.4 37.9% 37.9% >0.66mm 4.9±4.7 4.1±4.8 50.0% 6.4% >0.82mm 2.4±2.5 0.8±1.1 86.7% 4.4% 1Mean ± SD; 2μCT as reference. The locations of the detected breaks on HR-pQCT and μCT generally correspond well (Fig 1-I). On HR-pQCT, however, breaks may be detected as large breaks, whereas on μCT these large breaks appear to represent a combination of several small breaks (Fig 1-II). With larger break diameters as a cut-off for both techniques, this resulted in the detection of breaks on HR-pQCT which were not detected on μCT. Therefore, the FDR for the detection of a break of the same size was sufficient for small breaks (37.9%), but poor for large break sizes (86.7%). However, when comparing a larger break on HR-pQCT with the smallest minimal break size on μCT it was found that only 4.4% of the detected breaks on HR-pQCT were falsely detected (table 1). Conclusions Because of its limited resolution, a single break region detected on HR-pQCT can appear as several smaller breaks on μCT. When accounting for this effect, however, excellent agreement is found between cortical break detected with the algorithm using HR-pQCT and μCT. We thus conclude that the use of HR-pQCT in combination with our semi-automatic algorithm is a promising tool for early detection and monitoring of the number of small cortical breaks in finger joints. References Stach CM, A&R.2010 Feb; 62(2):330–339 Disclosure of Interest M. Peters: None declared, A. Scharmga: None declared, A. van Tubergen: None declared, B. van Rietbergen Consultant for: Scanco Medical AG, R. Weyers: None declared, D. Loeffen: None declared, J. Van den Bergh: None declared, P. Geusens: None declared