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.

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.

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%). Scars located in segments 1, 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.

Cardiac magnetic resonance image-based classification of the risk of arrhythmias in post-myocardial infarction patients.

INTRODUCTION: Patients surviving myocardial infarction (MI) can be divided into high and low arrhythmic risk groups. Distinguishing between these two groups is of crucial importance since the high-risk group has been shown to benefit from implantable cardioverter defibrillator insertion; a costly surgical procedure with potential complications and no proven advantages for the low-risk group. Currently, markers such as left ventricular ejection fraction and myocardial scar size are used to evaluate arrhythmic risk. METHODS: In this paper, we propose quantitative discriminative features extracted from late gadolinium enhanced cardiac magnetic resonance images of post-MI patients, to distinguish between 20 high-risk and 34 low-risk patients. These features include size, location, and textural information concerning the scarred myocardium. To evaluate the discriminative power of the proposed features, we used several built-in classification schemes from matrix laboratory (MATLAB) and Waikato environment for knowledge analysis (WEKA) software, including k-nearest neighbor (k-NN), support vector machine (SVM), decision tree, and random forest. RESULTS: In Experiment 1, the leave-one-out cross-validation scheme is implemented in MATLAB to classify high- and low-risk groups with a classification accuracy of 94.44%, and an AUC of 0.965 for a feature combination that captures size, location and heterogeneity of the scar. In Experiment 2 with the help of WEKA, nested cross-validation is performed with k-NN, SVM, adjusting decision tree and random forest classifiers to differentiate high-risk and low-risk patients. SVM classifier provided average accuracy of 92.6%, and AUC of 0.921 for a feature combination capturing location and heterogeneity of the scar. Experiment 1 and Experiment 2 show that textural features from the scar are important for classification and that localization features provide an additional benefit. CONCLUSION: These promising results suggest that the discriminative features introduced in this paper can be used by medical professionals, or in automatic decision support systems, along with the recognized risk markers, to improve arrhythmic risk stratification in post-MI patients.

The relationship between transmurality of ischemic scars and the heart rate of ventricular tachycardia.

AIMS: The relationship between the heart rate of ventricular tachycardia (VT) and the transmurality of ischemic scars was assessed by a new semiautomatic coordinate-based analysis of late gadolinium-enhanced cardiac magnetic resonance (LGE-CMR) images. METHODS AND RESULTS: Twenty patients assessed by LGE-CMR before implantation of implantable cardioverter defibrillator (ICD) with verified VT during the first year following ICD implantation were included. Scar was defined by pixels with a signal intensity ≥ 50% of maximum signal intensity. All pixels were assigned a coordinate position between endo- and epicardium (λ) and the angle of the heart axis (φ). Based upon the λ and φ values, multiple scar features were computed for all scarred areas. These features were correlated to VT heart rate across the complete range of transmurality. The strongest correlation with univariate regression was found between VT heart rate and the sum of transmurality when the maximum transmurality of these features was ≥ 90% (R-square = 0.47). In multiple regressions analysis, the strongest relationship with VT heart rate was found with a maximum transmurality ≥ 90% and by a combination of scar size, transmurality, and endocardial extent of infarction (R-square = 0.64). CONCLUSION: Transmurality is the strongest predictor of VT heart rate both in univariate and multivariate models. The strongest relationships were found at a transmurality level > 90%.

Comparing a novel automatic 3D method for LGE-CMR quantification of scar size with established methods.

Current methods for the estimation of infarct size by late-enhanced cardiac magnetic imaging are based upon 2D analysis that first determines the size of the infarction in each slice, and thereafter adds the infarct sizes from each slice to generate a volume. We present a novel, automatic 3D method that estimates infarct size by a simultaneous analysis of all pixels from all slices. In a population of 54 patients with ischemic scars, the infarct size estimated by the automatic 3D method was compared with four established 2D methods. The new 3D method defined scar as the sum of all pixels with signal intensity (SI) ≥35 % of max SI from the complete myocardium, border zone: SI 35-50 % of max SI and core as SI ≥50 % of max SI. The 3D method yielded smaller infarct size (-2.8 ± 2.3 %) and core size (-3.0 ± 1.7 %) than the 2D method most similar to ours. There was no difference in the size of the border zone (0.2 ± 1.4 %). The 3D method demonstrated stronger correlations between scar size and left ventricular (LV) remodelling parameters (LV ejection fraction: r = -0.71, p < 0.0005, LV end-diastolic index: r = 0.54, p < 0.0005, and LV end-systolic index: r = 0.59, p < 0.0005) compared with conventional 2D methods. Infarct size estimation by our novel 3D automatic method is without the need for manual demarcation of the scar; it is less time-consuming and has a stronger correlation with remodelling parameters compared with existing methods.

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.

Probability mapping of scarred myocardium using texture and intensity features in CMR images.

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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 myocardium).

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.

Omega-3 index and prognosis in acute coronary chest pain patients with a low dietary intake of omega-3.

BACKGROUND: The omega-3 index (eicosapentaenoic acid + docosahexaenoic acid) content in red blood cell membranes has been suggested as a novel risk marker for cardiac death. Objective. To assess the ability of the omega-3 index to predict all-cause mortality, cardiac death and sudden cardiac death following hospitalization with an acute coronary syndrome (ACS), and to include arachidonic acid (AA) in risk assessment. MATERIAL AND METHODS: The omega-3 index was measured in 572 consecutive patients (median 63 years and 59% males) admitted with chest pain and suspected ACS in an inland Northern Argentinean city with a dietary habit that was essentially based on red meat and a low intake of fish. Clinical endpoints were collected during a 5-year follow-up period, median 3.6 years, range 1 day to 5.5 years. Stepwise Cox regression analysis was employed to compare the rate of new events in the quartiles of the omega-3 index measured at inclusion. Multivariable analysis was performed. RESULTS: No statistical significant differences in baseline characteristics were noted between quartiles of the omega-3 index. The median of the adjusted omega-3 index was 3.6%. During the follow-up period, 100 (17.5%) patients died. Event rates were similar in all quartiles of the omega-3 index, with no statistical significant differences. AA added no prognostic information. CONCLUSION: In a population with a low intake of fish and fish oils, the adjusted omega-3 index did not predict fatal events following hospitalization in patients with acute chest pain and suspected ACS.

Serum 25(OH)D is a 2-year predictor of all-cause mortality, cardiac death and sudden cardiac death in chest pain patients from Northern Argentina.

BACKGROUND: Several studies have shown an association between vitamin D deficiency and cardiovascular risk. Vitamin D status is assessed by determination of 25-hydroxyvitamin D [25(OH)D] in serum. METHODS: We assessed the prognostic utility of 25(OH)D in 982 chest-pain patients with suspected acute coronary syndrome (ACS) from Salta, Northern Argentina. 2-year follow-up data including all-cause mortality, cardiac death and sudden cardiac death were analyzed in quartiles of 25(OH)D, applying univariate and multivariate analysis. RESULTS: There were statistically significant changes in seasonal 25(OH)D levels. At follow-up, 119 patients had died. The mean 25(OH)D levels were significantly lower among patients dying than in long-term survivors, both in the total population and in patients with a troponin T (TnT) release (n = 388). When comparing 25(OH)D in the highest quartile to the lowest quartile in a multivariable Cox regression model for all-cause mortality, the hazard ratio (HR) for cardiac death and sudden cardiac death in the total population was 0.37 (95% CI, 0.19-0.73), p = 0.004, 0.23 (95% CI, 0.08-0.67), p = 0.007, and 0.32 (95% CI, 0.11-0.94), p = 0.038, respectively. In patients with TnT release, the respective HR was 0.24 (95% CI, 0.10-0.54), p = 0.001, 0.18 (95% CI, 0.05-0.60), p = 0.006 and 0.25 (95% CI, 0.07-0.89), p = 0.033. 25(OH)D had no prognostic value in patients with no TnT release. CONCLUSION: Vitamin D was shown to be a useful biomarker for prediction of mortality when obtained at admission in chest pain patients with suspected ACS. TRIAL REGISTRATION: ClinicalTrials.gov NCT01377402.

B-type natriuretic peptide and high sensitive C-reactive protein predict 2-year all cause mortality in chest pain patients: a prospective observational study from Salta, Argentina.

BACKGROUND: Several mechanisms are involved in the pathophysiology of the Acute Coronary Syndrome (ACS). We have addressed whether B-type natriuretic peptide (BNP) and high-sensitive C-reactive protein (hsCRP) in admission samples may improve risk stratification in chest pain patients with suspected ACS. METHODS: We included 982 patients consecutively admitted with chest pain and suspected ACS at nine hospitals in Salta, Northern Argentina. Total and cardiac mortality were recorded during a 2-year follow up period. Patients were divided into quartiles according to BNP and hsCRP levels, respectively, and inter quartile differences in mortality were statistically evaluated applying univariate and multivariate analyses. RESULTS: 119 patients died, and the BNP and hsCRP levels were significantly higher among these patients than in survivors. In a multivariable Cox regression model for total death and cardiac death in all patients, the hazard ratio (HR) in the highest quartile (Q4) as compared to the lowest quartile (Q1) of BNP was 2.32 (95% confidence interval (CI), 1.24-4.35), p = 0.009 and 3.34 (95% CI, 1.26-8.85), p = 0.015, respectively. In the TnT positive patients (TnT > 0.01 ng/mL), the HR for total death and cardiac death in Q4 as compared to Q1 was 2.12 (95% CI, 1.07-4.18), p = 0.031 and 3.42 (95% CI, 1.13-10.32), p = 0.029, respectively.The HR for total death for hsCRP in Q4 as compared to Q1 was 1.97 (95% CI, 1.17-3.32), p = 0.011, but this biomarker did not predict cardiac death (p = 0.21). No prognostic impact of these two biomarkers was found in the TnT negative patients. CONCLUSION: BNP and hsCRP may act as clinically useful biomarkers when obtained at admission in a population with suspected ACS.

The heart rate of ventricular tachycardia following an old myocardial infarction is inversely related to the size of scarring.

AIMS: The purpose of the study was to examine the relationship between the initial cycle length (CL) of ventricular tachycardia (VT) and the size of the myocardial scar and its border zone in patients with old myocardial infarction (MI). METHODS AND RESULTS: Late gadolinium-enhancement cardiac magnetic resonance was performed prior to implantable cardioverter-defibrillator (ICD) implantation in 24 patients. The size of non-scared myocardium, scar, scar core, and border zone were measured as voxel numbers. The number of core islands, contour-regularity of scar and left-ventricular ejection fraction were also calculated. During the first year after ICD implantation, VT was recorded in 20 patients. With univariate regression analysis, the number of core islands had the highest correlation with the CL of VT (R = 0.614, adjusted R(2) = 0.342, P = 0.004). By multiple regression analyses, the highest correlation was found by the use of scar core and core islands (R = 0.721, adjusted R(2) = 0.464, P = 0.002). CONCLUSION: The heart rate of VT (bpm) in patients with old MI is inversely related to the properties of the densest parts of the myocardial scar.

Segmentation of scarred and non-scarred myocardium in LG enhanced CMR images using intensity-based textural analysis.

The Late Gadolinium (LG) enhancement in Cardiac Magnetic Resonance (CMR) imaging is used to increase the intensity of scarred area in myocardium for thorough examination. Automatic segmentation of scar is important because scar size is largely responsible in changing the size, shape and functioning of left ventricle and it is a preliminary step required in exploring the information present in scar. We have proposed a new technique to segment scar (infarct region) from non-scarred myocardium using intensity-based texture analysis. Our new technique uses dictionary-based texture features and dc-values to segment scarred and non-scarred myocardium using Maximum Likelihood Estimator (MLE) based Bayes classification. Texture analysis aided with intensity values gives better segmentation of scar from myocardium with high sensitivity and specificity values in comparison to manual segmentation by expert cardiologists.

Exploratory data analysis of image texture and statistical features on myocardium and infarction areas in cardiac magnetic resonance images.

The cardiac magnetic resonance (CMR) images from a group of patients with myocardial scars and implanted cardioverter-defibrillator (ICD) are divided into a group with low risk of arrhythmias (late incidents) and a group with high risk of arrhythmias (early incidents). Several hundred quantitative features describing sizes, statistics and textures of the segmented and defined areas of the images are computed from manually segmented images in an exploratory analysis. The method used to determine decision regions to discriminate the patients with low risk of arrhythmias from the patient with high risk of arrhythmias is a maximum likelihood estimation based Bayes classifiers described in [1]. The results presented can be interpreted as hypothesis of which features, and combinations of features, that might have discriminative power. A major hypothesis that arises is that there are important textural information in the scarred and non-scarred areas.