Background: Study on automated three-dimensional (3D) quantification of left heart parameters by using Heartmodel software is still in the early stage and fully automatic analysis was not clearly achieved. The aim of our study was to evaluate the performance of this new technology in measuring left ventricular (LV) volume and ejection fraction (EF) in patients with a variety of heart diseases on the basis of rationally determining the default endocardial border values.

Methods: Subjects with a variety of heart diseases were included prospectively. High quality Heartmodel images were selected to determine the end-diastolic and end-systolic default values of endocardial border. The accuracy and reproducibility of automated three-dimensional echocardiography (3DE) for measuring LV end-diastolic volume (EDV), end-systolic volume (ESV) and EF were evaluated with the traditional manual 3DE as the relative standard.

Results: Ninety seven subjects were enrolled in the study. The default endocardial border values were determined as 66% and 40% for end-diastole (ED) and end-systole (ES), respectively. Most of the subjects (84/97) were automatically analyzed by Heartmodel software without manual adjustment, revealing a close correlation of automated 3DE with manual 3DE in measuring EDV, ESV and EF (r-values: EDV: 0.96, ESV: 0.97, EF: 0.96). The EDV and ESV values obtained by automated 3DE were higher than those measured by manual 3DE (biases: EDV: 16 ± 18 ml, ESV: 11 ± 12 ml). The intra- and inter-observer reproducibility of automated 3DE was better than that of manual 3DE. Automated 3DE with manual adjustment showed good consistency with manual 3DE in assessing the impairment degree of systolic function in patients with wall motion abnormalities (n = 58), (Kappa = 0.74, P = 0.00).

Conclusion: Fully automated 3DE quantification of LV volume and EF could be achieved in most patients. Since automated 3DE was accurate and more reproducible, it could replace the existing manual 3DE technology and be routinely used in clinical practice.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5778731PMC
http://dx.doi.org/10.1186/s12947-017-0121-8DOI Listing

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