Assessment of Left Ventricular Global Myocardial Work in Patients With Different Degrees of Coronary Artery Stenosis by Pressure-Strain Loops Analysis

Global myocardial work in coronary artery disease patients without regional wall motion abnormality: Correlation with Gensini-score

BACKGROUND

Early detection of coronary atherosclerotic diseases (CAD) without regional wall motion abnormality (RWMA) is important for improving the outcome of cardiovascular events. Global myocardial work (GMW), including global myocardial work index (GWI), global constructive work (GCW), global wasted work (GWW), and global myocardial work efficiency (GWE), offer comprehensive quantitative assessment of myocardial function in CAD.

HYPOTHESIS

We hypothesized that GMW could provide incremental value in detecting CAD without RWMA.

METHODS

One hundred and twenty-four patients referred for coronary angiography (CAG) without resting RWMA were enrolled in this study. Global longitudinal strain (GLS), GWI, GCW, GWW, GWE were quantified. The severity of coronary lesions was evaluated by Gensini score (GS) based on CAG. We further divided CAG-confirmed CAD patients into three subgroups according to the tertiles of GS: low 0 < GS ≤ 17, mid 17 < GS ≤ 38, and high GS > 38.

RESULTS

Compared with control, CAD patients showed decreased GLS, GWE, GWI, GCW but an increased GWW. Compared to low-GS group, GWW was increased in the mid-GS group. GLS, GWE, GWI and GCW were decreased in the high-GS group while GWW was increased. Receiver operator characteristic curve analysis demonstrated that GWE was the most powerful predictor of high-GS and was superior to GLS. GWE under 92.0% had the optimal sensitivity and specificity for identifying high-GS.

CONCLUSION

The proposed GWE, which outperformed the conventional GLS, could be considered as a potential predictive indicator to help to detect severe coronary disease in non-RWMA CAD patients.

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.

Which is the best Myocardial Work index for the prediction of coronary artery disease? A data meta-analysis

BACKGROUND

Early diagnosis of Coronary Artery Disease (CAD) plays a key role to prevent adverse cardiac events such as myocardial infarction and Left Ventricular (LV) dysfunction. Myocardial Work (MW) indices derived from echocardiographic speckle tracking data in combination with non-invasive blood pressure recordings seems promising to predict CAD even in the absence of impairments of standard echocardiographic parameters. Our aim was to compare the diagnostic accuracy of MW indices to predict CAD and to assess intra- and inter-observer variability of MW through a meta-analysis.

METHODS

Electronic databases were searched for observational studies evaluating the MW indices diagnostic accuracy for predicting CAD and intra- and inter-observer variability of MW indices. Pooled sensitivity, specificity, and Summary Receiver Operating Characteristic (SROC) curves were assessed.

RESULTS

Five studies enrolling 501 patients met inclusion criteria. Global Constructive Work (GCW) had the best pooled sensitivity (89%) followed by GLS (84%), Global Work Index (GWI) (82%), Global Work Efficiency (GWE) (80%), and Global Wasted Work (GWW) (75%). GWE had the best pooled specificity (78%) followed by GWI (75%), GCW (70%), GLS (68%), and GWW (61%). GCW had the best accuracy according to SROC curves, with an area under the curve of 0.86 compared to 0.84 for GWI, 0.83 for GWE, 0.79 for GLS, and 0.74 for GWW. All MW indices had an excellent intra- and inter-observer variability.

CONCLUSIONS

GCW is the best MW index proving best diagnostic accuracy in the prediction of CAD with an excellent reproducibility.

A noninvasive method of estimating patient-specific left ventricular pressure waveform

BACKGROUND AND OBJECTIVE

The left ventricular pressure waveform is indispensable for the construction of the pressure strain loop when investigating coronary artery disease (CAD) patients. In previous studies by others, exclusion of CAD patients has not allowed a reliable estimation of the left ventricular pressure waveform from the pressure strain loop of these patients. To remedy this, we propose a patient-specific noninvasive method for the estimation of left ventricular pressure.

METHODS

A simplified systemic circulation model consisting primarily of a single fiber model and a 1D simulation of the arterial tree was used. Sensitivity analysis based on the Morris method was performed to select a subset of the important parameters. Following this, the important parameter subset and the set of all the parameters were identified in the model using the pressure waveform of a peripheral artery as input, in a two-step process. In addition, the left ventricular pressure waveform was estimated using the set of all parameters.

RESULTS

Reducing the size of the parameter subset significantly decreases the computational cost of parameter optimization in the first step and greatly simplifies the identification of the full parameter set in the second step. Comparison with the reference left ventricular pressure waveform from CAD patients, showed that the proposed method provides a good estimate of the reference left ventricular pressure waveform. The correlation coefficients between the estimated and reference were r = 0.907, r = 0.904 and r = 0.780 for systolic blood pressure, pulse pressure and mean blood pressure, respectively.

CONCLUSIONS

This work may provide a convenient surrogate for the estimation of the left ventricular pressure waveform.

Assessment of Myocardial Work of the Left Ventricle before and after PCI in Patients with Non-ST-Segment Elevation Acute Coronary Syndrome by Pressure-Strain Loop Technology

Objectives

Noninvasive left ventricular pressure-strain loop (PSL) is a new method for quantitative evaluation of myocardial work, which is developed on the basis of speckle tracking echocardiography. It is necessary to fit the noninvasive left ventricular pressure and the strain by speckle tracking echocardiography to construct a pressure-strain loop. Compared with traditional left ventricular ejection fraction (LVEF) and global longitudinal strain (GLS), it has potential application value and is a useful supplement for clinical evaluation of left ventricular systolic function. We perform this study to evaluate the changes of myocardial function in patients with non-ST-segment elevation acute coronary syndrome (NSTE-ACS) before and after percutaneous coronary intervention (PCI) with noninvasive left ventricular pressure-strain loop (PSL).

Methods

33 NSTE-ACS patients admitted to the Department of Cardiovascular Medicine of the Affiliated Lianyungang Hospital of Xuzhou Medical University who successfully underwent early PCI were included as the PCI group. At the same time, 30 healthy patients matched in age and sex were selected as the control group. All patients received routine echocardiography. The parameters such as GWI, GCW, GWW, and GWE were obtained by EchoPAC 203 software. The differences in the general clinical data and echocardiographic parameters between the two groups, including controls and patients 1 day before surgery and 1 month after surgery, were compared.

Results

Compared with the control group, GWI, GCW, and GWI in the PCI group were decreased 1 day before surgery and 1 month after surgery, while GWW was increased, with statistical significance (P < 0.05). In the PCI group, compared with 1 day before surgery, GWI and GCW were all increased 1 month after surgery (P < 0.05), and GWW and GWE were not significantly different between the two groups (P > 0.05).

Conclusion

The noninvasive left ventricular PSL technology can early and accurately evaluate the myocardial function impairment in NSTE-ACS patients and the recovery of myocardial function after PCI, providing a new noninvasive method for clinical postoperative myocardial function evaluation.

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

Purpose

This study is to assess the diagnostic value of noninvasive regional myocardial work (MW) by echocardiography for detecting the functional status of coronary stenosis using fractional flow reserve (FFR) as a standard criterion.

Methods

A total of 84 consecutive patients were included in this study, among which 92 vessels were identified with ≥50% stenosis confirmed by invasive coronary angiography. Patients were investigated by invasive FFR and transthoracic echocardiography. Regional MW indices including myocardial work index (MWI), myocardial constructive work (MCW), myocardial wasted work, and myocardial work efficiency were calculated.

Results

MWI and MCW were significantly impaired in the FFR ≤ 0.75 group compared with the FFR > 0.75 group (both p < 0.01). There were significant positive associations between MWI and MCW with FFR. In total group, MWI <1,623.7 mmHg% [sensitivity, 78.4%; specificity, 72.2%; area under the curve value, 0.768 (0.653-0.883)] and MCW <1,962.4 mmHg% [77.0%; 72.2%; 0.767 (0.661-0.872)], and in single-vessel subgroup, MWI <1,412.1 mmHg% [93.5%; 63.6%; 0.808 (0.652-0.965)] and MCW <1,943.3 mmHg% [(84.8%; 72.7%; 0.800 (0.657-0.943)] were optimal to detect left ventricular segments with an FFR ≤ 0.75. MWI and MCW significantly increased after percutaneous coronary intervention in 13 cases.

Conclusion

In patients with coronary artery disease, especially those with single-vessel stenosis, the regional MW measured by echocardiography exhibited a good diagnostic value in detecting significant myocardial ischemia compared to the standard FFR approach.

Application value of myocardial work technology by non-invasive echocardiography in evaluating left ventricular function in patients with chronic heart failure

BACKGROUND

Accurate evaluation of left ventricular (LV) systolic function is the premise for diagnosing and treating chronic heart failure. This study aimed to explore the incremental value of echocardiographic myocardial work in evaluating the LV systolic dysfunction in patients with chronic heart failure.

METHODS

A total of 206 participants were enrolled, including 155 patients with chronic heart failure and 51 healthy controls (HC). The chronic heart failure patients were divided into three groups according to LV ejection fraction (LVEF): Heart failure with preserved ejection fraction (HFpEF group, 54 cases, LVEF ≥50%), heart failure with mid-range ejection fraction (HFmrEF group, 50 cases, 40%≤ LVEF <50%), and heart failure with reduced ejection fraction (HFrEF group, 51 cases, LVEF <40%). Except for the conventional echocardiographic parameters, the left ventricular myocardial work parameters, including the global myocardial work index (GWI), global constructive work (GCW), global wasted work (GWW), and global work efficiency (GWE), were calculated in the study participants. One-way analysis of variance test followed by Fisher's least significant difference (LSD) t-test were used to obtain parameters with significant differences, which were then fed into a machine learning model established for subsequent multi-classification of the four groups. The selected myocardial work parameters with high importance rankings resulting from the machine learning model were further compared with the traditional LVEF in the multi-classification of the four groups.

RESULTS

All conventional echocardiographic parameters were significantly different between the HFmrEF and HFrEF groups, but only E/e', left atrium showed notable differences between the HFpEF and HC groups (P<0.05). All myocardial work parameters were markedly different between the four groups (P<0.05). LVEF and GWI were more important than the other parameters according to the multi-classification machine learning model. The multi-classification diagnostic performances of LVEF, GWI, and LVEF + GWI were 82%, 88%, and 98%, respectively, which confirmed that GWI + LVEF could complementarily improve the diagnosis accuracy in classifying the four groups, with a performance increase of approximately 10% than each individually.

CONCLUSIONS

GWI can play a complementary role to LVEF in the early diagnosis of HFpEF patients from the HC group and improve the clinical evaluation accuracy in chronic heart failure patients. Echocardiographic myocardial work should be utilized along with conventional LVEF to evaluate the systolic function of chronic heart failure patients in clinical practice.

Afterload-related reference values for myocardial work indices

BACKGROUND

The novel noninvasive pressure-strain loop (PSL) is a reliable tool that reflects myocardial work (MW). Systolic blood pressure (SBP) is the only independent factor for MW indices. However, afterload-related reference values have not been previously reported. The aim of the present study was to establish reference values for MW parameters by wide range SBP grading.

METHODS

We prospectively selected healthy individuals and subjects with SBP ≥ 140 mmHg at the time of study without myocardial remodeling. MW parameters were collected and the reference values achieved were grouped by SBP in 10-mmHg.

RESULTS

Significant differences were noted among the SBP-groups for global work index (GWI) and global constructive work (GCW). The majority of statistical comparisons of the differences in GWI and GCW were significant at each SBP-group. With SBP ranging from 90 to 189 mmHg, the parameters GWI and GCW tended to increase linearly with afterload. Overall, the global wasted work (GWW) tended to rise as SBP was increased, but not all of the differences noted in GWW were significant for each SBP-group. Global work efficiency (GWE) remained stable across all SBP-groups, with the exception of a slight drop noted when it exceeded 160 mmHg.

CONCLUSIONS

The amount of MW but not the work efficiency varied greatly according to the different afterload. This finding cannot be ignored during clinical research or diagnosis and afterload-related reference values are required to make a reasonable judgment on the myocardial function.