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Optimal threshold of three-dimensional echocardiographic fully automated software for quantification of left ventricular volumes and ejection fraction: Comparison with cardiac magnetic resonance disk-area summation method and feature tracking method.

ABSTRACT: AIMS:Novel fully automated left chamber quantification software for three-dimensional echocardiography (3DE) has a potential for reliable measurement of left ventricular (LV) volumes and ejection fraction (LVEF). However, the optimal setting of global LV endocardial border threshold has not been settled. METHODS AND RESULTS:We performed LV volumes and LVEF analysis using fully automated left chamber quantification software (Dynamic HeartModelA.I., Philips Medical Systems) in 65 patients who had undergone both 3DE and cardiac magnetic resonance (CMR) examinations on the same day. We recorded LV end-diastolic volume (LVEDV) and LV end-systolic volume (LVESV) according to the change in LV global border threshold settings from 0-point to 100-point with each increment of 10-point. These values were compared to the corresponding values of CMR with disk-area summation method and feature tracking (FT) method. Coverage probability (CP) was calculated as an index of accuracy and reliability. Fully automated software provided LV volumes and LVEF in 57 patients (Feasibility: 88%). LVEDV and LVESV increased steadily according to the increase in border threshold and reached minimal bias when border threshold setting was 80 against CMR disk-summation method and 90 against CMR FT method. Corresponding CP of LVEF was 0.74 and 0.84 against disk-area summation method and FT method. CONCLUSIONS:With CMR values as a reference, LV endocardial border threshold value can be set around 80 to 90 with the same number of LV end-diastole and end-systole threshold to approximate LVEDV, LVESV and LVEF with clinically acceptable CP values of LVEF.

SUBMITTER: Wu VC

PROVIDER: S-EPMC6349335 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Optimal threshold of three-dimensional echocardiographic fully automated software for quantification of left ventricular volumes and ejection fraction: Comparison with cardiac magnetic resonance disk-area summation method and feature tracking method.

Wu Victor Chien-Chia VC Kitano Tetuji T Nabeshima Yosuke Y Otani Kyoko K Chu Pao-Hsien PH Takeuchi Masaaki M

PloS one 20190128 1

<h4>Aims</h4>Novel fully automated left chamber quantification software for three-dimensional echocardiography (3DE) has a potential for reliable measurement of left ventricular (LV) volumes and ejection fraction (LVEF). However, the optimal setting of global LV endocardial border threshold has not been settled.<h4>Methods and results</h4>We performed LV volumes and LVEF analysis using fully automated left chamber quantification software (Dynamic HeartModelA.I., Philips Medical Systems) in 65 pa ...[more]

PMID: 30689657

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Project description:BackgroundManual interpretation of echocardiographic data is time-consuming and operator-dependent. With the advent of artificial intelligence (AI), there is a growing interest in its potential to streamline echocardiographic interpretation and reduce variability. This study aimed to compare the time taken for measurements by AI to that by human experts after converting the acquired dynamic images into DICOM data.MethodsTwenty-three consecutive patients were examined by a single operator, with varying image quality and different medical conditions. Echocardiographic parameters were independently evaluated by human expert using the manual method and the fully automated US2.ai software. The automated processes facilitated by the US2.ai software encompass real-time processing of 2D and Doppler data, measurement of clinically important variables (such as LV function and geometry), automated parameter assessment, and report generation with findings and comments aligned with guidelines. We assessed the duration required for echocardiographic measurements and report creation.ResultsThe AI significantly reduced the measurement time compared to the manual method (159 ± 66 vs. 325 ± 94 s, p < 0.01). In the report creation step, AI was also significantly faster compared to the manual method (71 ± 39 vs. 429 ± 128 s, p < 0.01). The incorporation of AI into echocardiographic analysis led to a 70% reduction in measurement and report creation time compared to manual methods. In cases with fair or poor image quality, AI required more corrections and extended measurement time than in cases of good image quality. Report creation time was longer in cases with increased report complexity due to human confirmation of AI-generated findings.ConclusionsThis fully automated software has the potential to serve as an efficient tool for echocardiographic analysis, offering results that enhance clinical workflow by providing rapid, zero-click reports, thereby adding significant value.

Project description:Background and aimsPatients with heart failure (HF) with reduced left ventricular (LV) ejection fraction (EF) have a heterogeneous prognosis, and assessment of coronary physiology with coronary flow velocity (CFV) and coronary flow velocity reserve (CFVR) may complement established predictors based on wall motion and EF.Methods and resultsIn a prospective multicenter study design, we enrolled 1,408 HF patients (age 66 ± 12 years, 1,035 men), with EF <50%, 743 (53%) with coronary artery disease, and 665 (47%) with normal coronary arteries. Recruitment (years 2004-2022) involved 8 accredited laboratories, with inter-observer variability <10% for CFV measurement. Baseline CFV (abnormal value >31 cm/s) was obtained by pulsed-wave Doppler in mid-distal LAD. CFVR (abnormal value ≤2.0) was assessed with exercise (n = 99), dobutamine (n = 100), and vasodilator stress (dipyridamole in 1,149, adenosine in 60). Inducible myocardial ischemia was identified with wall motion score index (WMSI) stress > rest (cut-off Δ ≥ 0.12). LV contractile reserve (CR) was identified with WMSI stress < rest (cutoff Δ ≥ 0.25). Test response ranged from score 0 (EF > 30%, CFV ≥ 32 cm/s, CFVR > 2.0, LVCR present, ischemia absent) to score 5 (all steps abnormal). All-cause death was the only endpoint. Results. During a median follow-up of 990 days, 253 patients died. Independent predictors of death were EF (HR: 0.956, 95% CI: 0.943-0.968, p < 0.0001), CFV (HR: 2.407, 95% CI: 1.871-3.096, p < 0.001), CFVR (HR: 3.908, 95% CI: 2.903-5.260, p < 0.001), stress-induced ischemia (HR: 2.223, 95% CI: 1.642-3.009, p < 0.001), and LVCR (HR: 0.524, 95% CI: 0.324-.647, p = 0.008). The annual mortality rate was lowest (1.2%) in patients with a score of 0 (n = 61) and highest (31.9%) in patients with a score of 5 (n = 15, p < 0.001).ConclusionHigh resting CFV is associated with worse survival in ischemic and nonischemic HF with reduced EF. The value is independent and additive to resting EF, CFVR, LVCR, and inducible ischemia.

Dataset Information

Optimal threshold of three-dimensional echocardiographic fully automated software for quantification of left ventricular volumes and ejection fraction: Comparison with cardiac magnetic resonance disk-area summation method and feature tracking method.

Publications

Optimal threshold of three-dimensional echocardiographic fully automated software for quantification of left ventricular volumes and ejection fraction: Comparison with cardiac magnetic resonance disk-area summation method and feature tracking method.

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