Left ventricular shape index and eccentricity index with ECG-gated Nitrogen-13 ammonia PET/CT in patients with myocardial infarction, ischemia, and normal perfusion.

BACKGROUND: LV geometry with shape index (SI) and eccentricity index (EI) measured by myocardial perfusion positron emission tomography/computed tomography (PET/CT) may allow the evaluation of left ventricular (LV) adverse remodeling. This first study aims to explore the relationship of SI and EI values acquired by Nitrogen-13 ammonia PET/CT in patients with normal perfusion, ischemia, and myocardial infarction. And evaluate the correlations between the variables of LV geometry, and with the variables of LV function. METHODS AND RESULTS: One hundred and forty patients who underwent an electrocardiogram (ECG)-gated PET/CT were selected and classified into 4 groups according to ischemia or infarction burden (normal perfusion, mild ischemia, moderate-severe ischemia, and infarction). The variables were automatically retrieved using dedicated software (QPS/QGS; Cedars-Sinai, Los Angeles, CA, USA). On multicomparison analysis (one-way ANOVA and Dunnett's Test), subjects in the infarction group had significant higher values of SI end-diastolic rest (P < 0.001), and stress (P = 0.003), SI end-systolic rest (P = 0.002) and stress (P < 0.001) as well as statistically significant lower values of EI rest (P < 0.001) and stress (P < 0.001) when compared with all other groups. Regarding Pearson correlation, in the infarcted group all the variables of SI and EI were significantly correlated (P < 0.001) with strong correlation coefficients (>0.60). SI end-systolic correlated significantly with the variables of LV function independently of the group of patients (P < 0.05). CONCLUSIONS: Shape and eccentricity indices differ in patients with myocardial infarction as compared to patients with ischemia or normal perfusion. This encourage further research in their potential for detecting LV adverse remodeling.

Visit-to-visit fasting plasma glucose variability is associated with left ventricular adverse remodeling in diabetic patients with STEMI.

BACKGROUND: Patients with type 2 diabetes mellitus (T2DM) are predisposed to poor cardiovascular outcomes after ST-segment elevation myocardial infarction (STEMI). Left ventricular adverse remodeling (LVAR) triggered upon myocardial infarction is recognized as the predominant pathological process in the development of heart failure. In the present study, we sought to investigate whether visit-to-visit fasting plasma glucose (FPG) variability is a potential predictor of LVAR in T2DM patients after STEMI. METHODS: From January 2014 to December 2018 in Ruijin Hospital, T2DM patients with STEMI who underwent primary percutaneous coronary intervention were consecutively enrolled and followed up for ~ 12 months. The changes in left ventricular geometric and functional parameters between baseline and 12-month follow-up were assessed by echocardiography. The incidence of LVAR, defined as 20% increase in indexed left ventricular end-diastolic volume (LVEDV), and its relationship with visit-to-visit FPG variability were analyzed. Multivariate regression models were constructed to test the predictive value of FPG variability for post-infarction LVAR. RESULTS: A total of 437 patients with type 2 diabetes and STEMI were included in the final analysis. During a mean follow-up of 12.4 ± 1.1 months, the incidence of LVAR was 20.6% and mean enlargement of indexed LVEDV was 3.31 ± 14.4 mL/m2, which was significantly increased in patients with higher coefficient variance (CV) of FPG (P = 0.002) irrespective of baseline glycemic levels. In multivariate analysis, FPG variability was independently associated with incidence of post-infarction LVAR after adjustment for traditional risk factors, baseline HbA1c as well as mean FPG during follow-up (OR: 3.021 [95% CI 1.081-8.764] for highest vs. lowest tertile of CV of FPG). Assessing FPG variability by other two measures, including standard deviation (SD) and variability independent of the mean (VIM), yielded similar findings. CONCLUSIONS: This study suggests that visit-to-visit FPG variability is an independent predictor of incidence of LVAR in T2DM patients with STEMI. Trial registration Trials number, NCT02089360; registered on March 17,2014.

Predicting Left Ventricular Adverse Remodeling After Transcatheter Aortic Valve Replacement: A Radiomics Approach.

RATIONALE AND OBJECTIVES: To develop a radiomics model based on cardiac computed tomography (CT) for predicting left ventricular adverse remodeling (LVAR) in patients with severe aortic stenosis (AS) who underwent transcatheter aortic valve replacement (TAVR). MATERIALS AND METHODS: Patients with severe AS who underwent TAVR from January 2019 to December 2022 were recruited. The cohort was divided into adverse remodeling group and non-adverse remodeling group based on LVAR occurrence, and further randomly divided into a training set and a validation set at an 8:2 ratio. Left ventricular radiomics features were extracted from cardiac CT. The least absolute shrinkage and selection operator regression was utilized to select the most relevant radiomics features and clinical features. The radiomics features were used to construct the Radscore, which was then combined with the selected clinical features to build a nomogram. The predictive performance of the models was evaluated using the area under the curve (AUC), while the clinical value of the models was assessed using calibration curves and decision curve analysis. RESULTS: A total of 273 patients were finally enrolled, including 71 with adverse remodeling and 202 with non-adverse remodeling. 12 radiomics features and five clinical features were extracted to construct the radiomics model, clinical model, and nomogram, respectively. The radiomics model outperformed the clinical model (training AUC: 0.799 vs. 0.760; validation AUC: 0.766 vs. 0.755). The nomogram showed highest accuracy (training AUC: 0.859, validation AUC: 0.837) and was deemed most clinically valuable by decision curve analysis. CONCLUSION: The cardiac CT-based radiomics features could predict LVAR after TAVR in patients with severe AS.

Non-Contrast Cine Cardiac Magnetic Resonance Derived-Radiomics for the Prediction of Left Ventricular Adverse Remodeling in Patients With ST-Segment Elevation Myocardial Infarction.

OBJECTIVE: To investigate the predictive value of radiomics features based on cardiac magnetic resonance (CMR) cine images for left ventricular adverse remodeling (LVAR) after acute ST-segment elevation myocardial infarction (STEMI). MATERIALS AND METHODS: We conducted a retrospective, single-center, cohort study involving 244 patients (random-split into 170 and 74 for training and testing, respectively) having an acute STEMI (88.5% males, 57.0 ± 10.3 years of age) who underwent CMR examination at one week and six months after percutaneous coronary intervention. LVAR was defined as a 20% increase in left ventricular end-diastolic volume 6 months after acute STEMI. Radiomics features were extracted from the one-week CMR cine images using the least absolute shrinkage and selection operator regression (LASSO) analysis. The predictive performance of the selected features was evaluated using receiver operating characteristic curve analysis and the area under the curve (AUC). RESULTS: Nine radiomics features with non-zero coefficients were included in the LASSO regression of the radiomics score (RAD score). Infarct size (odds ratio [OR]: 1.04 (1.00-1.07); P = 0.031) and RAD score (OR: 3.43 (2.34-5.28); P < 0.001) were independent predictors of LVAR. The RAD score predicted LVAR, with an AUC (95% confidence interval [CI]) of 0.82 (0.75-0.89) in the training set and 0.75 (0.62-0.89) in the testing set. Combining the RAD score with infarct size yielded favorable performance in predicting LVAR, with an AUC of 0.84 (0.72-0.95). Moreover, the addition of the RAD score to the left ventricular ejection fraction (LVEF) significantly increased the AUC from 0.68 (0.52-0.84) to 0.82 (0.70-0.93) (P = 0.018), which was also comparable to the prediction provided by the combined microvascular obstruction, infarct size, and LVEF with an AUC of 0.79 (0.65-0.94) (P = 0.727). CONCLUSION: Radiomics analysis using non-contrast cine CMR can predict LVAR after STEMI independently and incrementally to LVEF and may provide an alternative to traditional CMR parameters.

Predicted Value of MicroRNAs, Vascular Endothelial Growth Factor, and Intermediate Monocytes in the Left Adverse Ventricular Remodeling in Revascularized ST-Segment Elevation Myocardial Infarction Patients.

Background: Primary percutaneous coronary intervention (PPCI) in patients with ST-segment elevation myocardial infarction (STEMI) improves the survival of patients; nevertheless, some patients develop left ventricular adverse remodeling (LVAR) a few months after the intervention. The main objective of this study was to characterize the role of pro-inflammatory cell populations, related cytokines, and microRNAs (miRNAs) released after PPCI as reliable prognostic biomarkers for LVAR in patients with STEMI. Methods: We evaluated the level of pro-inflammatory subsets, before and after revascularization, 1 and 6 months after PPCI, using flow cytometry. We also performed a miRNA microarray in isolated peripheral blood mononuclear cells (PBMCs) and examined the levels of 27 cytokines in patients' serum of patients by multiplex ELISA. Results: We observed that the levels of classical and intermediate monocytes increased 6 h after PPCI in patients who developed LVAR later. Multivariate regression analysis and ROC curves indicated that intermediate monocytes, after PPCI, were the best monocyte subset that correlated with LVAR. Within the 27 evaluated cytokines evaluated, we found that the increase in the level of vascular endothelial growth factor (VEGF) correlated with LVAR. Furthermore, the microarray analysis of PBMCs determined that up to 1,209 miRNAs were differentially expressed 6 h after PPCI in LVAR patients, compared with those who did not develop LVAR. Using RT-qPCR we confirmed a significant increase in miR-16, miR-21-5p, and miR-29a-3p, suggested to modulate the expression of different cytokines, 6 h post-PPCI in LVAR patients. Interestingly, we determined that the combined analysis of the levels of the intermediate monocyte subpopulation, VEGF, and miRNAs gave a better association with LVAR appearance. Similarly, combined ROC analysis provided high accurate specificity and sensibility to identify STEMI patients who will develop LVAR. Conclusion: Our data suggest that the combined analysis of intermediate monocytes, VEGF, and miRNAs predicts LVAR in STEMI patients.