Regional Myocardial Work Measured by Echocardiography for the Detection of Myocardial Ischemic Segments: A Comparative Study With Invasive Fractional Flow Reserve

The clinical value of noninvasive left ventricular myocardial work in the diagnosis of myocardial ischemia in coronary heart disease: a comparative study with coronary flow reserve fraction

The prompt and precise identification of hemodynamically significant coronary artery lesions remains an ongoing challenge. This study investigated the diagnostic value of non-invasive global left ventricular myocardial work indices by echocardiography in functional status of coronary artery disease (CAD) patients with myocardial ischemia using fractional flow reserve (FFR) as the gold standard. A total of 77 consecutive patients with clinically suspected CAD were prospectively enrolled. All participants sequentially underwent echocardiography, invasive coronary angiography (ICA) and FFR measurement. According to the results of ICA, patients were divided into myocardial ischemia group (FFR ≤ 0.8, n = 27) and non-myocardial ischemia group (FFR > 0.8, n = 50). Myocardial work indices including global work index (GWI), global constructive work (GCW), global wasted work (GWW), global work efficiency (GWE), global positive work (GPW), global negative work (GNW), global systolic constructive work (GSCW) and global systolic wasted work (GSWW) were obtained by using the non-invasive left ventricular pressure strain loop (PSL) technique. Compared with the non-myocardial ischemia group, GWI, GCW, GPW and GSCW were significantly decreased in the myocardial ischemia group at either the 18-segment level or the 12-segment level (P < 0.001). At the 18-segment level, GWI < 1783.6 mmHg%, GCW < 1945.4 mmHg%, GPW < 1788.7 mmHg% and GSCW < 1916.5 mmHg% were optimal cut-off value to detect myocardial ischemia with an FFR ≤ 0.8. Global left ventricular myocardial work indices by echocardiography exhibited a good diagnostic value in patients with CAD and may have a good clinical significance for the screening of suspected myocardial ischemia.

Incremental value of non-invasive myocardial work for the evaluation and prediction of coronary microvascular dysfunction in angina with no obstructive coronary artery disease

Background

Evidence suggests that patients suffering from angina with no obstructive coronary artery disease (ANOCA) experience coronary microvascular dysfunction (CMD). We aimed to understand the diagnosis value of noninvasive myocardial work indices (MWIs) with left ventricular pressure-strain loop (LV PSL) by echocardiography in ANOCA patients with CMD.

Methods

97 patients with ANOCA were recruited. All subjects underwent standard echocardiography with traditional ultrasound parameters, two-dimensional speckle-tracking echocardiography with global longitudinal strain (GLS), LV PSL with MWIs include global work index (GWI), global constructive work (GCW), global waste work (GWW) and global work efficiency (GWE). In addition, all enrolled cases underwent high-dose adenosine stress echocardiography (SE) with coronary flow velocity reserve (CFVR). CMD was defined as CFVR <2.0.

Results

Of the 97 patients with ANOCA, 52 were placed in the CMD group and 45 in the control group. GWI and GCW were decreased significantly in the CMD group compared with the control group (P < 0.001 for both). GWI and GCW were moderately correlated with CFVR (r = 0.430, P < 0.001 and r = 0.538, P < 0.001, respectively). In the multiple logistic regression analyses, GCW was identified as the only independent echocardiography parameter associated with CMD after adjusting for age and baseline APV [OR (95%CI) 1.009 (1.005-1.013); P < 0.001]. Moreover, the best predictor of CMD in patients with ANOCA using receiver operating characteristic (ROC) curve was GWI and GCW, with an area under the curve (AUC) of 0.800 and 0.832, sensitivity of 67.3% and 78.8%, specificity of 80.0% and 75.6%, respectively.

Conclusion

MWIs with LV PSL is a new method to detect LV systolic function noninvasively in ANOCA patients with CMD.

Machine learning-enhanced echocardiography for screening coronary artery disease

BACKGROUND

Since myocardial work (MW) and left atrial strain are valuable for screening coronary artery disease (CAD), this study aimed to develop a novel CAD screening approach based on machine learning-enhanced echocardiography.

METHODS

This prospective study used data from patients undergoing coronary angiography, in which the novel echocardiography features were extracted by a machine learning algorithm. A total of 818 patients were enrolled and randomly divided into training (80%) and testing (20%) groups. An additional 115 patients were also enrolled in the validation group.

RESULTS

The superior diagnosis model of CAD was optimized using 59 echocardiographic features in a gradient-boosting classifier. This model showed that the value of the receiver operating characteristic area under the curve (AUC) was 0.852 in the test group and 0.834 in the validation group, with high sensitivity (0.952) and low specificity (0.691), suggesting that this model is very sensitive for detecting CAD, but its low specificity may increase the high false-positive rate. We also determined that the false-positive cases were more susceptible to suffering cardiac events than the true-negative cases.

CONCLUSIONS

Machine learning-enhanced echocardiography can improve CAD detection based on the MW and left atrial strain features. Our developed model is valuable for estimating the pre-test probability of CAD and screening CAD patients in clinical practice.

TRIAL REGISTRATION

Registered as NCT03905200 at ClinicalTrials.gov. Registered on 5 April 2019.

miR-146a-5p, miR-223-3p and miR-142-3p as Potential Predictors of Major Adverse Cardiac Events in Young Patients with Acute ST Elevation Myocardial Infarction-Added Value over Left Ventricular Myocardial Work Indices

Acute ST elevation myocardial infarction (STEMI) remains a leading cause of morbidity and mortality worldwide despite continuous advances in diagnostic, prognostic and therapeutic methods. Myocardial work (MW) indices and miRNAs have both emerged as potential prognostic markers in acute coronary syndromes in recent years. In this study we aim to assess the prognostic role of myocardial work indices and of a group of miRNAs in young patients with STEMI. We enrolled 50 young patients (<55 years) with STEMI who underwent primary PCI and 10 healthy age-matched controls. We performed standard 2D and 3D echocardiography; we also calculated left ventricular global longitudinal strain (GLS) and the derived myocardial work indices. Using RT-PCR we determined the plasmatic levels of six miRNAs: miR-223-3p, miR-142-3p, miR-146a-5p, miR-125a-5p, miR-486-5p and miR-155-5p. We assessed the occurrence of major adverse cardiac events (MACE) at up to one year after STEMI. Out of 50 patients, 18% experienced MACE at the one-year follow-up. In a Cox univariate logistic regression analysis, myocardial work indices were all significantly associated with MACE. The ROC analysis showed that GWI, GCW and GWE as a group have a better predictive value for MACE than each separately (AUC 0.951, p = 0.000). Patients with higher miRNAs values at baseline (miR-223-3p, miR-142-3p and miR-146a-5p) appear to have a higher probability of developing adverse events at 12 months of follow-up. ROC curves outlined for each variable confirmed their good predictive value (AUC = 0.832, p = 0.002 for miR-223-3p; AUC = 0.732, p = 0.031 for miR-142-3p and AUC = 0.848, p = 0.001 for miR-146a-5p); the group of three miRNAs also proved to have a better predictive value for MACE together than separately (AUC = 0.862). Moreover, adding each of the miRNAs (miR-233, miR-142-3p and miR-146a-5p) or all together over the myocardial work indices in the regression models improved their prognostic value. In conclusion, both myocardial work indices (GWI, GCW and GWE) and three miRNAs (miR-223-3p, miR-142-3p and miR-146a-5p) have the potential to be used as prognostic markers for adverse events after acute myocardial infarction. The combination of miRNAs and MW indices (measured at baseline) rather than each separately has very good predictive value for MACE in young STEMI patients (C-statistic 0.977).