Comparing HeartModel and Cardiac Magnetic Resonance Imaging for Left Ventricular Volume and Function Evaluation in Patients with Dilated Cardiomyopathy

Overview

Journal BMC Cardiovasc Disord

Publisher Biomed Central

Specialty Cardiology & Vascular Diseases

Date 2024 Nov 23

PMID 39580388

Authors

Mahboobeh Sheikh

Sahar Asl Fallah

Muhammadhosein Moradi

Arash Jalali

Ahmad Vakili-Basir

Mohammad Sahebjam

Haleh Ashraf

Arezou Zoroufian

Affiliations

Soon will be listed here.

Abstract

Background: Integration of artificial intelligence enhances precision, yielding dependable evaluations of left ventricular volumes and ejection fraction despite image quality variations. Commercial software like HeartModel provides fully automated 3DE quantification, simplifying the measurement of left chamber volumes and ejection fraction. In this manuscript, we present a cross-sectional study to assess and compare the diagnostic accuracy of automated 3D echocardiography (HeartModel) to the standard Cardiac Magnetic Resonance Imaging in patients with dilated cardiomyopathy.

Methods: In this cross-sectional study, 30 patients with dilated cardiomyopathy referring to the Tehran Heart Center with cardiac magnetic resonance imaging and comprehensive 3D transthoracic echocardiography within 24 h were included. All 3D volume analysis was performed with fully automated quantification software (HeartModel) using 3D images of 2,3, and 4-chamber views at the end of systole and diastole.

Results: Excellent Inter- and Intra-observer correlation coefficient was reported for HeartModel software for all indexes. HeartModel displayed a remarkable correlation with cardiac magnetic resonance for left ventricular end-systolic volume index (r = 0.918 and r = 0.911); nevertheless, it underestimated left ventricular end-systolic volume index and left ventricular end-diastolic volume index. Conversely, ejection fraction, stroke volume, and left ventricular mass were overestimated. It was found that manual contour correction can enhance the accuracy of automated model estimations, particularly concerning EF in participants needing correction.

Conclusion: HeartModel software emerges as a rapid and viable imaging approach for evaluating the left ventricle's structure and function. In our study, LV volumes assessed by HeartModel demonstrated strong correlations with cardiac magnetic resonance imaging.

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