Predictive value of the echocardiographic noninvasive myocardial work index for left ventricular reverse remodeling in patients with multivessel coronary artery disease after percutaneous coronary intervention

Usability of myocardial work parameters in demonstrating myocardial involvement in INOCA patients

BACKGROUND

Myocardial work (MW) is a novel echocardiographic modality, which has been shown to have diagnostic and prognostic values in patients with cardiovascular diseases, patients with obstructive coronary artery disease, in particular. However, only a handful of studies have examined the MW analysis in ischemia with nonobstructive coronary artery (INOCA) disease. This study, therefore, aimed to detect the early left ventricular involvement in INOCA patients diagnosed by an invasive coronary angiography performing the MW analysis.

METHODS

This study included a total of 119 patients with nonobstructive coronary artery disease diagnosed by invasive coronary angiography, who were checked for prior ischemia tests performing myocardial perfusion scintigraphy. Out of these 119 patients, 49 patients developed ischemia (i.e., ischemic group) diagnosed using cardiac single-photon emission computed tomography, whereas 70 patients did not (i.e., nonischemic group). The subjects were divided into three groups based on the global MW tertiles. The groups were compared in terms of the conventional, longitudinal strain, and MW findings by conducting echocardiographic examinations.

RESULTS

The study subjects were divided into three groups based on the global constrictive work (GCW) value. The three groups were not statistically different in terms of the mean age of the patients (53.0 ± 12 vs. 52.4 ± 13.3 vs. 52.1 ± 12.3; p = 0.96). Furthermore, the three groups were not statistically different regarding the gender, height, weight, and laboratory parameters of the patients except albumin. There was no statistically difference among the tertiles of GCW groups in the measurements of cardiac chambers, LA diameter, interventricular septum, E wave, and A wave. Also, there was no statistical difference in tissue Doppler recordings. The parameters associated with MW were examined, three groups were not statistically different in terms of the global waste work (GWW) (116 ± 92, 122 ± 73, 135 ± 62, p = 0.52, respectively). In contrast, the three groups were different regarding the Global work index (GWI) (1716 ± 300, 1999 ± 130, 2253 ± 195, p < 0.001, respectively), GCW (1888 ± 206, 2298 ± 75, 2614 ± 155, p < 0.001, respectively), and Global work efficiency parameters (92.8 ± 3.6, 94.4 ± 3.2, 95.1 ± 1.8 p = 0.004, respectively).

CONCLUSION

It was concluded that the MW parameters GCW and GWI may have been used for predicting INOCA in patients.

Automated detection and classification of coronary atherosclerotic plaques on coronary CT angiography using deep learning algorithm

Background

Coronary artery disease (CAD) is the leading cause of mortality worldwide. Recent advances in deep learning technology promise better diagnosis of CAD and improve assessment of CAD plaque buildup. The purpose of this study is to assess the performance of a deep learning algorithm in detecting and classifying coronary atherosclerotic plaques in coronary computed tomographic angiography (CCTA) images.

Methods

Between January 2019 and September 2020, CCTA images of 669 consecutive patients with suspected CAD from Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine were included in this study. There were 106 patients included in the retrospective plaque detection analysis, which was evaluated by a deep learning algorithm and four independent physicians with varying clinical experience. Additionally, 563 patients were included in the analysis for plaque classification using the deep learning algorithm, and their results were compared with those of expert radiologists. Plaques were categorized as absent, calcified, non-calcified, or mixed.

Results

The deep learning algorithm exhibited higher sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy {92% [95% confidence interval (CI): 89.5-94.1%], 87% (95% CI: 84.2-88.5%), 79% (95% CI: 76.1-82.4%), 95% (95% CI: 93.4-96.3%), and 89% (95% CI: 86.9-90.0%)} compared to physicians with ≤5 years of clinical experience in CAD diagnosis for the detection of coronary plaques. The algorithm's overall sensitivity, specificity, PPV, NPV, accuracy, and Cohen's kappa for plaque classification were 94% (95% CI: 92.3-94.7%), 90% (95% CI: 88.8-90.3%), 70% (95% CI: 68.3-72.1%), 98% (95% CI: 97.8-98.5%), 90% (95% CI: 89.8-91.1%) and 0.74 (95% CI: 0.70-0.78), indicating strong performance.

Conclusions

The deep learning algorithm has demonstrated reliable and accurate detection and classification of coronary atherosclerotic plaques in CCTA images. It holds the potential to enhance the diagnostic capabilities of junior radiologists and junior intervention cardiologists in the CAD diagnosis, as well as to streamline the triage of patients with acute coronary symptoms.

Evaluation of global and regional myocardial work in hypertrophic cardiomyopathy patients by left ventricular pressure-strain loop

OBJECTIVE

This study aimed to investigate the value of left ventricular (LV) press-strain loop (PSL) in evaluating global and regional myocardial work (MW) in hypertrophic cardiomyopathy (HCM) patients.

METHODS

A total of 30 HCM patients with interventricular septum hypertrophy (HCM group) and 35 healthy subjects (control group) were selected from First Hospital of Qinhuangdao. The general clinical data and conventional ultrasound parameters of two groups were acquired. The MW parameters were analyzed using LV PSL. The regional MW parameters in the HCM group were compared between ventricular septum and the free walls of left ventricle.

RESULTS

The epicardial adipose tissue thickness of the HCM group was significantly greater than that of the control group (P < 0.05). Global work efficiency was significantly reduced, while global wasted work was increased in patients with HCM compared with controls (all P < 0.05). The HCM group was compared in the group, to be specific, in the HCM group, the work index, the work efficiency, and the longitudinal strain on the interventricular septum were lower than those on the free wall (all P < 0.05).

CONCLUSION

PSL is more effective than LVEF in assessing left ventricular systolic function in HCM and is able to quantify regional myocardial work in the ventricular septum in HCM patients with preserved LVEF, suggesting a novel idea for clinical diagnosis and assessment.

Prognosis value of EAS index in patients with obstructive coronary artery disease

Background

EAS index is reported to be an adjunctive tool for risk stratification in addition to left ventricular ejection fraction (LVEF). This study aimed to verify the predictive value of EAS index among coronary artery disease (CAD) patients with different cardiac systolic function levels.

Methods

A total of 477 patients with obstructive CAD were included in the exploratory analysis of a prospective cohort between October 2017 and January 2018 at Guangdong Provincial People's Hospital. EAS index, e'/(a' × s'), is a novel parameter assessed by tissue Doppler imaging (TDI) indicating combined diastolic and systolic performance. Any occurrence of major adverse cardiovascular event (MACE) was recorded, including first onset of myocardial infarction, stroke, readmission for heart failure, coronary revascularization, or cardiovascular death that occurred within 6 months of the first admission. Kaplan-Meier survival and Cox regression analyses were applied to testify the predictive value of EAS index for cardiovascular outcome.

Results

A total of 415 patients (87.2%) completed the follow-up (median, 25.9 months) and experienced 101 (24.3%) MACEs, 17 (4.0%) deaths, and 139 (33.4%) composite events. Elevated EAS index was significantly associated with a higher incidence of MACE, even after adjustment for age, sex, body mass index, N-terminal pro brain natriuretic peptide, high-sensitivity troponin T, high-density lipoprotein, stenosis degree, and other TDI parameters [Model 3, hazard ratio: 1.81, 95% confidence interval (CI): 1.15-2.85]. For different levels of cardiac function, Kaplan-Meier survival analysis revealed that elevated EAS index was associated with higher MACE incidence only in patients with LVEF ≥50% (P<0.05).

Conclusions

EAS index is an independent predictor of MACE in patients with obstructive CAD, which could be utilized as a tool for risk stratification in CAD patients or incorporated into a prediction model to improve efficacy.

Myocardial Work in Echocardiography

Myocardial work is an emerging tool in echocardiography that incorporates left ventricular afterload into global longitudinal strain analysis. Myocardial work correlates with myocardial oxygen consumption, and work efficiency can also be assessed. Myocardial work has been evaluated in a variety of clinical conditions to assess the added value of myocardial work compared to left ventricular ejection fraction and global longitudinal strain. This review showcases the current use of myocardial work in adult echocardiography and its possible role in cardiac pathologies.