What does your profile picture say about you? The accuracy of thin-slice personality judgments from social networking sites made at zero-acquaintance

The myocardium exhibits heterogeneous nature due to scarring after Myocardial Infarction (MI). In Cardiac Magnetic Resonance (CMR) imaging, Late Gadolinium (LG) contrast agent enhances the intensity of scarred area in the myocardium. In this paper, we propose a probability mapping technique using Texture and Intensity features to describe heterogeneous nature of the scarred myocardium in Cardiac Magnetic Resonance (CMR) images after Myocardial Infarction (MI). Scarred tissue and non-scarred tissue are represented with high and low probabilities, respectively. Intermediate values possibly indicate areas where the scarred and healthy tissues are interwoven. The probability map of scarred myocardium is calculated by using a probability function based on Bayes rule. Any set of features can be used in the probability function. In the present study, we demonstrate the use of two different types of features. One is based on the mean intensity of pixel and the other on underlying texture information of the scarred and non-scarred myocardium. Examples of probability maps computed using the mean intensity of pixel and the underlying texture information are presented. We hypothesize that the probability mapping of myocardium offers alternate visualization, possibly showing the details with physiological significance difficult to detect visually in the original CMR image. The probability mapping obtained from the two features provides a way to define different cardiac segments which offer a way to identify areas in the myocardium of diagnostic importance (like core and border areas in scarred myocardiu

Vitamin D predicts all-cause and cardiac mortality in females with suspected acute coronary syndrome: a comparison with brain natriuretic peptide and high-sensitivity C-reactive protein

Vitamin D may not only reflect disease but may also serve as a prognostic indicator. Our aim was to assess the gender-specific utility of vitamin D measured as 25-hydroxy-vitamin D [25(OH)D] to predict all-cause and cardiac death in patients with suspected acute coronary syndrome (ACS) and to compare its prognostic utility to brain natriuretic peptide (BNP) and high-sensitivity C-reactive protein (hsCRP). Blood samples were harvested on admission in 982 patients. Forty percent were women (65.9 ± 12.6 years). Mortality was evaluated in quartiles of 25(OH)D, BNP, and hsCRP, respectively, during a 5-year follow-up, applying univariate and multivariate analyses. One hundred and seventy-three patients died; 78 were women. In 92 patients (37 women), death was defined as cardiac. In women, the univariate hazard ratio (HR) for total death of 25(OH)D in Quartile (Q) 2 versus Q1, Q3 versus Q1, and Q4 versus Q1 was 0.55 (95% CI 0.33–0.93), 0.29 (95% CI 0.15–0.55), and 0.13 (95% CI 0.06–0.32), respectively. In females, it was an independent predictor of total and cardiac death, whereas BNP and hsCRP were less gender-specific. No gender differences in 25(OH)D were noted in a reference material. Accordingly, vitamin D independently predicts mortality in females with suspected ACS.publishedVersio

Defining angular and radial positions and parameters for myocardial pixels in cardiac MR images

The article was originally published under a creative commons license in 2014 in Computing in Cardiology; http://www.cinc.org/archives/2014/.In this work we aimed to automatically produce a measure for the angular and radial position of all pixels within the myocardium in CMR images, left ventricle, short axis view. A reference axis is chosen in an anatomically meaningful way, and this makes the angular position measure easy to relate to the American Heart Association (AHA) 17 segment model. The angular and the radial position give values for each pixel so that each pixel can be represented by a 3D vector of information [intensity value, angular position, radial position]. Using this 3D representation of each pixel, interesting parameters can easily be defined. For example looking at LGE-CMR images for patients with myocardial scar, parameters for describing the localization of the scar segments can be found automatically and objectively, and can be used for further classification of patients

The localization and characterization of ischemic scars in relation to the infarct related coronary artery assessed by cardiac magnetic resonance and a novel automatic postprocessing method

This is an open access article originally published in Cardiology Research and Practice; see DOI: http://dx.doi.org/10.1155/2015/120874. Copyright © 2015 Leik Woie et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproductio n in any medium, provided the original work is properly cited.Aims . The correspondence between the localization and morphology of ischemic scars and the infarct related artery (IRA) by use of cardiac magnetic resonance imaging and a novel automatic postprocessing method. Methods and Results . Thirty-four patients with one-year-old single IRA myocardial infarction were examined. Endocardium, epicardium, and the point where right and left ventricles are coinciding were manually marked. All measurements were automatically assessed by the method. The following are results with manual assessments of scar properties in parenthesis: mean scar size (FWHM criterion): 7.8 ± 5.5 as %LV (17.4 ± 8.6%); mean endocardial extent of infarction: 44 ± 26 ∘ (124 ± 47 ∘ ); mean endocardial extent of infarction as %LV circumference: 9.7 ± 7.0% (34.6 ± 13.0%); and mean transmurality: 52 ± 20% of LV wall thickness (77 ± 23%).Scarslocatedinsegments1,2,7,8,13,and 14 by use of the automatic method were 96–100% specific for LAD occlusion. The highest specificities of RCA and LCX occlusions were segment 4 with 93% and segment 6 with 64%, respectively. The scar localization assessed automatically or manually was without major differences. Conclusion . The automatic method is applicable and able to assess localization, size, transmurality, and endocardial extent of ischemic scars

Texture-based probability mapping for automatic scar assessment in late gadolinium-enhanced cardiovascular magnetic resonance images

Purpose To evaluate a novel texture-based probability mapping (TPM) method for scar size estimation in LGE-CMRI. Methods This retrospective proof-of-concept study included chronic myocardial scars from 52 patients. The TPM was compared with three signal intensity-based methods: manual segmentation, full-width-half-maximum (FWHM), and 5-standard deviation (5-SD). TPM is generated using machine learning techniques, expressing the probability of scarring in pixels. The probability is derived by comparing the texture of the 3 × 3 pixel matrix surrounding each pixel with reference dictionaries from patients with established myocardial scars. The Sørensen-Dice coefficient was used to find the optimal TPM range. A non-parametric test was used to test the correlation between infarct size and remodeling parameters. Bland-Altman plots were performed to assess agreement among the methods. Results The study included 52 patients (76.9% male; median age 64.5 years (54, 72.5)). A TPM range of 0.328–1.0 was found to be the optimal probability interval to predict scar size compared to manual segmentation, median dice (25th and 75th percentiles)): 0.69(0.42–0.81). There was no significant difference in the scar size between TPM and 5-SD. However, both 5-SD and TPM yielded larger scar sizes compared with FWHM (p < 0.001 and p = 0.002). There were strong correlations between scar size measured by TPM, and left ventricular ejection fraction (LVEF, r = −0.76, p < 0.001), left ventricular end-diastolic volume index (r = 0.73, p < 0.001), and left ventricular end-systolic volume index (r = 0.75, p < 0.001). Conclusion The TPM method is comparable with current SI-based methods, both for the scar size assessment and the relationship with left ventricular remodeling when applied on LGE-CMRI.publishedVersio

Socioeconomic Assessment and Impact of Social Security on Outcome in Patients Admitted with Suspected Coronary Chest Pain in the City of Salta, Argentina

Low socioeconomic status is associated with increased mortality from coronary heart disease. We assessed total mortality, cardiac death, and sudden cardiac death (SCD) in relation to socioeconomic class and social security in 982 patients consecutively admitted with suspected coronary chest pain, living in the city of Salta, northern Argentina. Patients were divided into three socioeconomic classes based on monthly income, residential area, and insurance coverage. Five-year follow-up data were analyzed accordingly, applying univariate and multivariate analyses. At follow-up, 173 patients (17.6%) had died. In 92 patients (9.4%) death was defined as cardiac, of whom 59 patients (6.0%) were characterized as SCD. In the multivariate analysis, the hazard ratios (HRs) for all-cause and cardiac mortality in the highest as compared to the lowest socioeconomic class were 0.42 (95% confidence interval (CI), 0.22–0.80), P=0.008, and 0.39 (95% CI, 0.15–0.99), P=0.047, respectively. Comparing patients in the upper socioeconomic class to patients without healthcare coverage, HRs were 0.46 (95% CI, 0.23–0.94), P=0.032, and 0.37 (95% CI, 0.14–1.01), P=0.054, respectively. In conclusion, survival was mainly tied to socioeconomic inequalities in this population, and the impact of a social security program needs further attention