Comparing HeartModelAI and cardiac magnetic resonance imaging for left ventricular volume and function evaluation in patients with dilated cardiomyopathy

被引:0
作者
Sheikh, Mahboobeh [1 ]
Fallah, Sahar Asl [2 ]
Moradi, Muhammadhosein [3 ]
Jalali, Arash [3 ,4 ]
Vakili-Basir, Ahmad [2 ,4 ]
Sahebjam, Mohammad [2 ]
Ashraf, Haleh [3 ]
Zoroufian, Arezou [2 ,5 ]
机构
[1] Zabol Univ Med Sci, Zabol, Iran
[2] Univ Tehran Med Sci, Cardiovasc Dis Res Inst, Tehran Heart Ctr, Tehran, Iran
[3] Univ Tehran Med Sci, Cardiovasc Dis Res Inst, Cardiac Primary Prevent Res Ctr, Tehran, Iran
[4] Univ Tehran Med Sci, Sch Publ Hlth, Dept Epidemiol & Biostat, Tehran, Iran
[5] Univ Tehran Med Sci, Cardiovasc Dis Res Inst, Tehran Heart Ctr, Echocardiog Dept, Tehran, Iran
来源
BMC CARDIOVASCULAR DISORDERS | 2024年 / 24卷 / 01期
关键词
Dilated cardiomyopathy; Magnetic resonance imaging; Echocardiography; AUTOMATED QUANTIFICATION; CHAMBER QUANTIFICATION; ECHOCARDIOGRAPHY; FEASIBILITY; SOFTWARE;
D O I
10.1186/s12872-024-04355-3
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
BackgroundIntegration of artificial intelligence enhances precision, yielding dependable evaluations of left ventricular volumes and ejection fraction despite image quality variations. Commercial software like HeartModelAI 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 (HeartModelAI) to the standard Cardiac Magnetic Resonance Imaging in patients with dilated cardiomyopathy.MethodsIn 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 (HeartModelAI) using 3D images of 2,3, and 4-chamber views at the end of systole and diastole.ResultsExcellent Inter- and Intra-observer correlation coefficient was reported for HeartModelAI software for all indexes. HeartModelAI 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.ConclusionHeartModelAI 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 HeartModelAI demonstrated strong correlations with cardiac magnetic resonance imaging.
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页数:11
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