Deep Learning for Improved Precision and Reproducibility of Left Ventricular Strain in Echocardiography: A Test-Retest Study.

AIMS: Assessment of left ventricular (LV) function by echocardiography is hampered by modest test-retest reproducibility. A novel artificial intelligence (AI) method based on deep learning provides fully automated measurements of LV global longitudinal strain (GLS) and may improve the clinical utility of echocardiography by reducing user-related variability. The aim of this study was to assess within-patient test-retest reproducibility of LV GLS measured by the novel AI method in repeated echocardiograms recorded by different echocardiographers and to compare the results to manual measurements. METHODS: Two test-retest data sets (n = 40 and n = 32) were obtained at separate centers. Repeated recordings were acquired in immediate succession by 2 different echocardiographers at each center. For each data set, 4 readers measured GLS in both recordings using a semiautomatic method to construct test-retest interreader and intrareader scenarios. Agreement, mean absolute difference, and minimal detectable change (MDC) were compared to analyses by AI. In a subset of 10 patients, beat-to-beat variability in 3 cardiac cycles was assessed by 2 readers and AI. RESULTS: Test-retest variability was lower with AI compared with interreader scenarios (data set I: MDC = 3.7 vs 5.5, mean absolute difference = 1.4 vs 2.1, respectively; data set II: MDC = 3.9 vs 5.2, mean absolute difference = 1.6 vs 1.9, respectively; all P < .05). There was bias in GLS measurements in 13 of 24 test-retest interreader scenarios (largest bias, 3.2 strain units). In contrast, there was no bias in measurements by AI. Beat-to-beat MDCs were 1,5, 2.1, and 2.3 for AI and the 2 readers, respectively. Processing time for analyses of GLS by the AI method was 7.9 ± 2.8 seconds. CONCLUSION: A fast AI method for automated measurements of LV GLS reduced test-retest variability and removed bias between readers in both test-retest data sets. By improving the precision and reproducibility, AI may increase the clinical utility of echocardiography.

Increased deformation of the left ventricle during exercise test measured by global longitudinal strain can rule out significant coronary artery disease in patients with suspected unstable angina pectoris.

BACKGROUND: Noninvasive identification of significant coronary artery disease (CAD) in patients with unstable angina pectoris (UAP) is challenging. Exercise stress testing has been used for years in patients with suspected CAD but has low diagnostic accuracy. The use of Global longitudinal strain (GLS) by speckle tracking echocardiography is a highly sensitive and reproducible parameter for detection of myocardial ischemia. Our aim was to study if identification of normal or ischemic myocardium by measurement of GLS immediately after an ordinary bicycle exercise stress testing in patients with suspected UAP could identify or rule out significant CAD. METHODS: Seventy-eight patients referred for coronary angiography from outpatient clinics and the emergency department with chest pain, inconclusive ECG and normal values of Troponin-T was included. All patients underwent echocardiographic examination at rest and immediately after maximum stress by exercise on a stationary bicycle. Significant CAD was defined by diameter stenosis > 90% by coronary angiography. In patients with coronary stenosis between 50-90%, fractional flow reserve (FFR) was measured and defined abnormal < .80. Analysis of echocardiographic data were performed blinded for angiographic data. Patients were discharged diagnosed with CAD (n = 34) or non-coronary chest pain (NCCP, n = 44). RESULTS: In patients with NCCP, GLS at rest was -21.1 ± 1.7% and -25.5 ± 2.6% at maximum stress (P < .01). In patients with CAD, GLS at rest was -16.8 ± 4.0% and remained unchanged at maximum stress (-16.6 ± 4.6%, P = .69). In patients with NCCP, LVEF was 56.1% ± 6.0 and increased to 61.8% 5.2, P < .01. In CAD patients, LVEF at rest was 54.7% ± 8.6 and increased to 58.2% ± 9.5 during stress, P = .16. In NCCP patients, Wall Motion Score index decreased .02 ± .07, P = .03 during stress and was without significant changes in patients with CAD. Area under the curve (AUC) for distinguishing CAD for was .97 (.95-1.00), .63 (.49-.76), and .71 (.59-.83) for GLS, LVEF, and WMSi, respectively. CONCLUSION: In patients with suspected UAP, increased deformation of the left ventricle measured by GLS immediately after exercise stress testing identified normal myocardium without CAD. Reduced LV contractile function by GLS without increase after exercise identified significant CAD.

Strain echocardiography improves prediction of arrhythmic events in ischemic and non-ischemic dilated cardiomyopathy.

BACKGROUND: Recent evidence suggests that an implantable cardioverter defibrillator (ICD) in non-ischemic cardiomyopathy (NICM) may not offer mortality benefit. We aimed to investigate if etiology of heart failure and strain echocardiography can improve risk stratification of life threatening ventricular arrhythmia (VA) in heart failure patients. METHODS: This prospective multi-center follow-up study consecutively included NICM and ischemic cardiomyopathy (ICM) patients with left ventricular ejection fraction (LVEF) <40%. We assessed LVEF, global longitudinal strain (GLS) and mechanical dispersion (MD) by echocardiography. Ventricular arrhythmia was defined as sustained ventricular tachycardia, sudden cardiac death or appropriate shock from an ICD. RESULTS: We included 290 patients (67 ± 13 years old, 74% males, 207(71%) ICM). During 22 ± 12 months follow up, VA occurred in 32(11%) patients. MD and GLS were both markers of VA in patients with ICM and NICM, whereas LVEF was not (p = 0.14). MD independently predicted VA (HR: 1.19; 95% CI 1.08-1.32, p = 0.001), with excellent arrhythmia free survival in patients with MD <70 ms (Log rank p < 0.001). Patients with NICM and MD <70 ms had the lowest VA incidence with an event rate of 3%/year, while patients with ICM and MD >70 ms had highest VA incidence with an event rate of 16%/year. CONCLUSION: Patients with NICM and normal MD had low arrhythmic event rate, comparable to the general population. Patients with ICM and MD >70 ms had the highest risk of VA. Combining heart failure etiology and strain echocardiography may classify heart failure patients in low, intermediate and high risk of VA and thereby aid ICD decision strategies.

Artificial Intelligence for Automatic Measurement of Left Ventricular Strain in Echocardiography.

OBJECTIVES: This study sought to examine if fully automated measurements of global longitudinal strain (GLS) using a novel motion estimation technology based on deep learning and artificial intelligence (AI) are feasible and comparable with a conventional speckle-tracking application. BACKGROUND: GLS is an important parameter when evaluating left ventricular function. However, analyses of GLS are time consuming and demand expertise, and thus are underused in clinical practice. METHODS: In this study, 200 patients with a wide range of left ventricle (LV) function were included. Three standard apical cine-loops were analyzed using the AI pipeline. The AI method measured GLS and was compared with a commercially available semiautomatic speckle-tracking software (EchoPAC v202, GE Healthcare. RESULTS: The AI method succeeded to both correctly classify all 3 standard apical views and perform timing of cardiac events in 89% of patients. Furthermore, the method successfully performed automatic segmentation, motion estimates, and measurements of GLS in all examinations, across different cardiac pathologies and throughout the spectrum of LV function. GLS was -12.0 ± 4.1% for the AI method and -13.5 ± 5.3% for the reference method. Bias was -1.4 ± 0.3% (95% limits of agreement: 2.3 to -5.1), which is comparable with intervendor studies. The AI method eliminated measurement variability and a complete GLS analysis was processed within 15 s. CONCLUSIONS: Through the range of LV function this novel AI method succeeds, without any operator input, to automatically identify the 3 standard apical views, perform timing of cardiac events, trace the myocardium, perform motion estimation, and measure GLS. Fully automated measurements based on AI could facilitate the clinical implementation of GLS.

Global longitudinal strain is a more reproducible measure of left ventricular function than ejection fraction regardless of echocardiographic training.

BACKGROUND: Left ventricular ejection fraction (LVEF) is an established method for evaluation of left ventricular (LV) systolic function. Global longitudinal strain (GLS) by speckle tracking echocardiography seems to be an important additive method for evaluation of LV function with improved reproducibility compared with LVEF. Our aim was to compare reproducibility of GLS and LVEF between an expert and trainee both as echocardiographic examiner and analyst. METHODS: Forty-seven patients with recent Acute Coronary Syndrome (ACS) underwent echocardiographic examination by both an expert echocardiographer and a trainee. Both echocardiographers, blinded for clinical data and each other's findings, performed image analysis for evaluation of intra- and inter- observer variability. GLS was measured using speckle tracking echocardiography. LVEF was calculated by Simpson's biplane method. RESULTS: The trainee measured a GLS of - 19.4% (±3.5%) and expert - 18.7% (±3.2%) with an Intra class correlation coefficient (ICC) of 0.89 (0.74-0.95). LVEF by trainee was 50.3% (±8.2%) and by expert 53.6% (±8.6%), ICC coefficient was 0.63 (0.32-0.80). For GLS the systematic difference was 0.21% (- 4.58-2.64) vs. 4.08% (- 20.78-12.62) for LVEF. CONCLUSION: GLS is a more reproducible method for evaluation of LV function than LVEF regardless of echocardiographic training.

Early assessment of strain echocardiography can accurately exclude significant coronary artery stenosis in suspected non-ST-segment elevation acute coronary syndrome.

BACKGROUND: Many patients with suspected non-ST-segment elevation acute coronary syndrome (NSTE-ACS) do not have significant coronary artery disease. The current diagnostic approach of repeated electrocardiography and cardiac biomarker assessment requires observation for >6 to 12 hours. This strategy places a heavy burden on hospital facilities. The objective of this study was to investigate whether myocardial strain assessment by echocardiography could exclude significant coronary artery stenosis in patients presenting with suspected NSTE-ACS. METHODS: Sixty-four patients presenting to the emergency department with suspected NSTE-ACS without known coronary artery disease, inconclusive electrocardiographic findings, and normal cardiac biomarkers at arrival were enrolled. Twelve-lead electrocardiography, troponin T assay, and echocardiography were performed at arrival, and all patients underwent coronary angiography. Significant coronary stenosis was defined as >50% luminal narrowing. Global myocardial peak systolic longitudinal strain was measured using speckle-tracking echocardiography. Left ventricular ejection fraction and wall motion score index were calculated. RESULTS: No significant stenosis in any coronary artery was found in 35 patients (55%). Global peak systolic longitudinal strain was superior to conventional echocardiographic parameters in distinguishing patients with and without significant coronary artery stenosis (area under the curve, 0.87). Sensitivity and specificity were calculated as 0.93 and 0.78, respectively, and positive predictive value and negative predictive value as 0.74 and 0.92, respectively. Feasibility of the strain measurements was excellent, with 97% of segments analyzed. CONCLUSIONS: Myocardial strain by echocardiography may facilitate the exclusion of significant coronary artery stenosis among patients presenting with suspected NSTE-ACS with inconclusive electrocardiographic findings and normal cardiac biomarkers.