Mario Nuño-Ayala

Association of Myocardial T1-Mapping CMR With Hemodynamics and RV Performance in Pulmonary Hypertension

Early detection of right ventricular (RV) involvement in chronic pulmonary hypertension (PH) is essential due to prognostic implications. T1 mapping by cardiac magnetic resonance (CMR) has emerged as a noninvasive technique for extracellular volume fraction (ECV) quantification. We assessed the association of myocardial native T1 time and equilibrium contrast ECV (Eq-ECV) at the RV insertion points with pulmonary hemodynamics and RV performance in an experimental model of chronic PH. Right heart catheterization followed by immediate CMR was performed on 38 pigs with chronic PH (generated by surgical pulmonary vein banding) and 6 sham-operated controls. Native T1 and Eq-ECV values at the RV insertion points were both significantly higher in banded animals than in controls and showed significant correlation with pulmonary hemodynamics, RV arterial coupling, and RV performance. Eq-ECV values also increased before overt RV systolic dysfunction, offering potential for the early detection of myocardial involvement in chronic PH.

Noninvasive monitoring of serial changes in pulmonary vascular resistance and acute vasodilator testing using cardiac magnetic resonance.

OBJECTIVES The study sought to evaluate the ability of cardiac magnetic resonance (CMR) to monitor acute and long-term changes in pulmonary vascular resistance (PVR) noninvasively. BACKGROUND PVR monitoring during the follow-up of patients with pulmonary hypertension (PH) and the response to vasodilator testing require invasive right heart catheterization. METHODS An experimental study in pigs was designed to evaluate the ability of CMR to monitor: 1) an acute increase in PVR generated by acute pulmonary embolization (n = 10); 2) serial changes in PVR in chronic PH (n = 22); and 3) changes in PVR during vasodilator testing in chronic PH (n = 10). CMR studies were performed with simultaneous hemodynamic assessment using a CMR-compatible Swan-Ganz catheter. Average flow velocity in the main pulmonary artery (PA) was quantified with phase contrast imaging. Pearson correlation and mixed model analysis were used to correlate changes in PVR with changes in CMR-quantified PA velocity. Additionally, PVR was estimated from CMR data (PA velocity and right ventricular ejection fraction) using a formula previously validated. RESULTS Changes in PA velocity strongly and inversely correlated with acute increases in PVR induced by pulmonary embolization (r = -0.92), serial PVR fluctuations in chronic PH (r = -0.89), and acute reductions during vasodilator testing (r = -0.89, p ≤ 0.01 for all). CMR-estimated PVR showed adequate agreement with invasive PVR (mean bias -1.1 Wood units,; 95% confidence interval: -5.9 to 3.7) and changes in both indices correlated strongly (r = 0.86, p < 0.01). CONCLUSIONS CMR allows for noninvasive monitoring of acute and chronic changes in PVR in PH. This capability may be valuable in the evaluation and follow-up of patients with PH.

Metabolomics Reveals Metabolite Changes in Acute Pulmonary Embolism

Pulmonary embolism (PE) is a common cardiovascular emergency which can lead to pulmonary hypertension (PH) and right ventricular failure as a consequence of pulmonary arterial bed occlusion. The diagnosis of PE is challenging due to nonspecific clinical presentation, which results in relatively high mortality. Moreover, the pathological factors associated with PE are poorly understood. Metabolomics can provide new highlights which can help in the understanding of the processes and even propose biomarkers for its diagnosis. In order to obtain more information about PE and PH, acute PE was induced in large white pigs and plasma was obtained before and after induction of PE. Metabolic fingerprints from plasma were obtained with LC-QTOF-MS (positive and negative ionization) and GC-Q-MS. Data pretreatment and statistical analysis (uni- and multivariate) were performed in order to compare metabolic fingerprints and to select the metabolites that showed higher loading for the classification (28 from LC and 19 from GC). The metabolites found differentially distributed among groups are mainly related to energy imbalance in hypoxic conditions, such as glycolysis-derived metabolites, ketone bodies, and TCA cycle intermediates, as well as a group of lipidic mediators that could be involved in the transduction of the signals to the cells such as sphingolipids and lysophospholipids, among others. Results presented in this report reveal that combination of LC-MS- and GC-MS-based metabolomics could be a powerful tool for diagnosis and understanding pathophysiological processes due to acute PE.

Impact of Left Ventricular Hypertrophy on Troponin Release During Acute Myocardial Infarction: New Insights From a Comprehensive Translational Study

Background Biomarkers are frequently used to estimate infarct size (IS) as an endpoint in experimental and clinical studies. Here, we prospectively studied the impact of left ventricular (LV) hypertrophy (LVH) on biomarker release in clinical and experimental myocardial infarction (MI). Methods and Results ST‐segment elevation myocardial infarction (STEMI) patients (n=140) were monitored for total creatine kinase (CK) and cardiac troponin I (cTnI) over 72 hours postinfarction and were examined by cardiac magnetic resonance (CMR) at 1 week and 6 months postinfarction. MI was generated in pigs with induced LVH (n=10) and in sham‐operated pigs (n=8), and serial total CK and cTnI measurements were performed and CMR scans conducted at 7 days postinfarction. Regression analysis was used to study the influence of LVH on total CK and cTnI release and IS estimated by CMR (gold standard). Receiver operating characteristic (ROC) curve analysis was performed to study the discriminatory capacity of the area under the curve (AUC) of cTnI and total CK in predicting LV dysfunction. Cardiomyocyte cTnI expression was quantified in myocardial sections from LVH and sham‐operated pigs. In both the clinical and experimental studies, LVH was associated with significantly higher peak and AUC of cTnI, but not with differences in total CK. ROC curves showed that the discriminatory capacity of AUC of cTnI to predict LV dysfunction was significantly worse for patients with LVH. LVH did not affect the capacity of total CK to estimate IS or LV dysfunction. Immunofluorescence analysis revealed significantly higher cTnI content in hypertrophic cardiomyocytes. Conclusions Peak and AUC of cTnI both significantly overestimate IS in the presence of LVH, owing to the higher troponin content per cardiomyocyte. In the setting of LVH, cTnI release during STEMI poorly predicts postinfarction LV dysfunction. LV mass should be taken into consideration when IS or LV function are estimated by troponin release.