Anti-modified citrullinated vimentin antibody: a novel biomarker associated with cardiac systolic dysfunction in patients with rheumatoid arthritis.

BACKGROUND: Studies have demonstrated that seropositive patients with rheumatoid arthritis (RA) are susceptible to cardiovascular diseases (CVDs). In this study, we aimed to determine the association of autoantibodies with the echocardiographic parameters of systolic and diastolic dysfunction in such patients. METHODS: In this cross-sectional study, we evaluated patients with RA who were referred to our clinic from October 2017 to August 2018. After the exclusion of patients with concomitant CVD, all patients underwent transthoracic echocardiography and measurement of plasma autoantibodies. Moreover, possible confounders-including medications, CVD risk factors, Framingham risk score, disease activity score-28, duration of disease, simple disease activity index, and functional status-were assessed. RESULTS: We studied 135 patients with RA (mean age = 52.3 years; 111 (82.2%) females). We had missing data rates of up to 8.9% for some characteristics. E velocity was inversely correlated with rheumatoid factor (P = 0.009). Furthermore, the plasma levels of anti-citrullinated protein and anti-modified citrullinated vimentin (anti-MCV) antibodies were negatively correlated with left ventricular ejection fraction (LVEF) (P = 0.019 and P<0.001, respectively). After an adjustment for possible confounders, the linear regression model demonstrated that the anti-MCV level and the patient's age are significant predictors of LVEF. The receiver operating characteristic curve showed that anti-MCV antibody titer≥547.5 (IU/mL) signifies reduced LVEF (<50%) with a sensitivity of 85.7% and specificity of 93% (C-statistic = 0.843). CONCLUSIONS: Our findings showed a significant inverse correlation between anti-MCV antibody titer and LVEF. These results indicate that the application of anti-MCV is promising for the screening and early detection of cardiac systolic dysfunction. Future prospective studies will determine its role.

The evaluation of right ventricular function in patients with diabetes mellitus and significant stenosis at the proximal portion of the right coronary artery.

PURPOSE: Previous studies have indicated that right ventricular (RV) function is damaged in diabetes mellitus (DM); however, it is not clear whether in the presence of chronic ischemia, RV function is different between patients with and without DM (DM + and DM - , respectively). METHODS: This cross-sectional study enrolled 90 consecutive candidates for coronary artery bypass graft surgery and allocated them to 3 groups: 24 DM - patients with the absence of stenosis of more than 50% in the proximal and mid parts of the right coronary artery (the DM - RCA - group [control]), 33 DM - patients with the presence of significant stenosis (> 70%) in the proximal part of RCA (the DM - RCA + group), and 33 DM + patients with RCA + (the DM + RCA + group). RV function was evaluated based on longitudinal deformation markers, measured via the 2D speckle-tracking echocardiographic examination of right ventricular free wall (RVFW). RESULTS: The systolic strain value, systolic strain rate, and late diastolic strain rate of RVFW were not statistically significantly different between the three groups. Our adjusted post hoc analysis showed that the early diastolic strain rate of RVFW in the DM + RCA + group was lower than that in the DM - RCA + and DM - RCA - groups (1.5 s-1 ± 0.4 vs 1.7 s-1 ± 0.5 vs 1.7 s-1 ± 0.4). CONCLUSIONS: Diastolic function in the presence of DM was impaired irrespective of RCA - or RCA + . Additionally, RCA + had no effect on systolic and diastolic RV functions at rest in our DM - patients.

Automatic media-adventitia IVUS image segmentation based on sparse representation framework and dynamic directional active contour model.

Segmentation of the arterial wall boundaries from intravascular ultrasound images is an important image processing task in order to quantify arterial wall characteristics such as shape, area, thickness and eccentricity. Since manual segmentation of these boundaries is a laborious and time consuming procedure, many researchers attempted to develop (semi-) automatic segmentation techniques as a powerful tool for educational and clinical purposes in the past but as yet there is no any clinically approved method in the market. This paper presents a deterministic-statistical strategy for automatic media-adventitia border detection by a fourfold algorithm. First, a smoothed initial contour is extracted based on the classification in the sparse representation framework which is combined with the dynamic directional convolution vector field. Next, an active contour model is utilized for the propagation of the initial contour toward the interested borders. Finally, the extracted contour is refined in the leakage, side branch openings and calcification regions based on the image texture patterns. The performance of the proposed algorithm is evaluated by comparing the results to those manually traced borders by an expert on 312 different IVUS images obtained from four different patients. The statistical analysis of the results demonstrates the efficiency of the proposed method in the media-adventitia border detection with enough consistency in the leakage and calcification regions.