Multimodality imaging for evaluation of chest pain using strain analysis at rest and peak exercise

Myocardial Strain Imaging With Electrocardiogram-Gated and Coherent Compounding for Early Diagnosis of Coronary Artery Disease

Myocardial elastography (ME) is an ultrasound-based technique that uses radiofrequency signals for 2-D cardiac motion tracking and strain imaging at a high frame rate. Early diagnosis of coronary artery disease (CAD) is critical for timely treatment and improvement of patient outcome. The objective of this study was to assess the performance of ME radial and circumferential strains in the detection and characterization of CAD in patients. In this study, 86 patients suspected of CAD were imaged with ME prior to invasive coronary angiography (ICA). End-systolic radial and circumferential left ventricular strains were estimated in all patients in each of their perfusion territories: left anterior descending (LAD), left circumflex (LCX) and right coronary artery (RCA). ME radial strains were capable of differentiating the obstructive CAD group (55.3 ± 29.8%) from the non-obstructive CAD (72.5 ± 46.8%, p < 0.05) and no CAD groups (73.4 ± 30.4%, p < 0.05) in the RCA territory. ME circumferential strains were capable of differentiating the obstructive CAD group (-3.1 ± 7.5%) from the non-obstructive CAD (-7.2 ± 6.8%, p < 0.05) and normal (-6.9 ± 8.0%, p < 0.05) groups in the LAD territory and to differentiate the normal group (-17.1 ± 8.2%) from the obstructive (-12.8 ± 7.2%, p < 0.05) and non-obstructive CAD (-13.6 ± 8.5%, p < 0.05) groups in the RCA territory. ME circumferential strain performed better than ME radial strain in differentiating normal, non-obstructive and obstructive perfusion territories. In the LCX territory, both ME radial and circumferential strains decreased when the level of stenosis was higher. However, it was not statistically significant. The findings presented herein indicate that ME radial and circumferential estimation obtained from ECG-gated and compounded acquisitions is a promising tool for early, non-invasive and radiation-free detection of CAD in patients.

Automated Echocardiographic Detection of Severe Coronary Artery Disease Using Artificial Intelligence

OBJECTIVES

The purpose of this study was to establish whether an artificially intelligent (AI) system can be developed to automate stress echocardiography analysis and support clinician interpretation.

BACKGROUND

Coronary artery disease is the leading global cause of mortality and morbidity and stress echocardiography remains one of the most commonly used diagnostic imaging tests.

METHODS

An automated image processing pipeline was developed to extract novel geometric and kinematic features from stress echocardiograms collected as part of a large, United Kingdom-based prospective, multicenter, multivendor study. An ensemble machine learning classifier was trained, using the extracted features, to identify patients with severe coronary artery disease on invasive coronary angiography. The model was tested in an independent U.S.

STUDY

How availability of an AI classification might impact clinical interpretation of stress echocardiograms was evaluated in a randomized crossover reader study.

RESULTS

Acceptable classification accuracy for identification of patients with severe coronary artery disease in the training data set was achieved on cross-fold validation based on 31 unique geometric and kinematic features, with a specificity of 92.7% and a sensitivity of 84.4%. This accuracy was maintained in the independent validation data set. The use of the AI classification tool by clinicians increased inter-reader agreement and confidence as well as sensitivity for detection of disease by 10% to achieve an area under the receiver-operating characteristic curve of 0.93.

CONCLUSION

Automated analysis of stress echocardiograms is possible using AI and provision of automated classifications to clinicians when reading stress echocardiograms could improve accuracy, inter-reader agreement, and reader confidence.

Speckle Tracking Stress Echocardiography on Treadmill in Assessment of the Functional Significance of the Degree of Coronary Artery Disease

Aim        To determine diagnostic capabilities of left ventricular (LV) global longitudinal systolic strain (GLSS) in stress echocardiography (stress-EchoCG) with a treadmill test for diagnosing the functional significance of the degree of coronary stenosis.Material and methods        The study included 121 patients (73 men aged 68.3±7.7 years) with suspected or previously diagnosed ischemic heart disease (IHD). Speckle-tracking stress-EchCG (method of tracking speckles on two-dimensional gray-scale ultrasonic images) with a treadmill test and coronarography was performed for all patients. The patients were divided into 3 groups based on the severity of coronary artery (CA) stenosis according to the Gensini scale.Results   LV GLSS at rest did not significantly differ between the study groups. After the exercise, LV GLSS was significantly lower in patients with pronounced CA stenosis than in patients without or with moderate CA stenosis (15.9±4.6 % vs. 20.6±3.7 % (p&lt;0.001) and 19.6±3.0 % (p=0.003), respectively). Postexercise LV GLSS &lt;16.9% suggested a pronounced CA stenosis with a sensitivity of 80% and a specificity of 70% (area under the curve, AUC, 0.76±0.06 at 95 % confidence interval, CI, 0.63-0.89; р&lt;0.001). In the patient group without CA stenosis, LV GLSS showed a significant increase after completion of the exercise (from 19.1±3.1 to 20.6±3.7; p=0.04).Conclusion            Evaluation of LV GLSS and its dynamics in stress-EchoCG with a treadmill test may be promising in patients with IHD, since in most patients with pronounced CA stenosis, LV GLSS is reduced at baseline and further reduces in response to exercise. In patients without CA stenosis, LV GLSS increases after completing the exercise.

Speckle tracking stress echocardiography: A valuable diagnostic technique or a burden for everyday practice?

Non-invasive screening for early diagnosis of coronary artery disease (CAD) represents a key element in the never-ending challenge to reduce cardiac death. Stress/rest electrocardiogram often lacks diagnostic accuracy, especially in asymptomatic patients, in fact the latest guidelines for the diagnosis and management of chronic coronary syndromes (CCS) stated the superiority of functional imaging techniques for the detection of subtle myocardial ischemia and the evaluation of myocardial viability (MV). Stress echocardiography is the most accessible and inexpensive imaging method for the study of CAD, either with pharmacological or with exercise provocative stress, based on visual wall-motion assessment. However, in some cases, such as small coronary lesions or microvascular angina, it loses its diagnostic power, therefore requiring a more sensitive approach. Accordingly, in the last years many authors investigated the possible additive value provided by the integration of an advanced but easy-to-obtain technique, that is speckle tracking imaging, to stress echocardiography, reaching promising results; nevertheless, its use is not included in the latest recommendations for CCS. The present review discusses the potential benefits from using a combination of speckle tracking and stress echocardiography for the early detection of myocardial ischemia and the assessment of MV and its suitability in different clinical scenarios, basing on the available evidence.

Role of left ventricle deformation analysis in stress echocardiography for significant coronary artery disease detection: A diagnostic study meta-analysis

BACKGROUND

We compared the diagnostic accuracy of longitudinal strain (LS) imaging during stress echocardiography with visual assessment of wall motion (WM) for detecting significant coronary artery disease (CAD).

METHODS

Our systematic search included studies reporting diagnostic measures for LS imaging and visual assessment of WM for detecting significant CAD during stress echocardiography. Summary diagnostic accuracy measures including area under the curve (AUC), sensitivity, specificity, diagnostic odds ratio (DOR), and likelihood ratios (LRs) were estimated.

RESULTS

In thirteen studies with 978 patients, ten studies used invasive coronary angiography as the reference standard. Pooled AUC for diagnosing significant CAD was 0.92 (95% confidence interval [CI] 0.89-0.94) for LS imaging as compared to 0.83 (95% CI 0.80-0.86), P < 0.001 for visual assessment of WM. LS imaging had higher sensitivity (88% [95% CI 84-92] vs 74% [95% CI 68-80], P < 0.001) and comparable specificity to visual assessment of WM (80% [95% CI 72-87] vs 83% [95% CI 74-90], P = 0.592). The DOR for LS imaging and visual assessment of WM was 31 and 15, P = 0.254, respectively. The positive LR was 4.5 for both; negative LR was 0.14 and 0.31, P = 0.002 for LS imaging and visual assessment of WM, respectively.

CONCLUSIONS

Longitudinal strain imaging during stress echocardiography has better diagnostic accuracy for detecting significant CAD as compared to visual assessment of WM. Studies using larger sample size and standardized techniques of strain measurement are required to further ascertain the added advantage of strain measurement over visual assessment alone.