Real-Time 3D Fusion Echocardiography

• Published in: JACC. Cardiovascular imaging 2010-07, Vol.3 (7), p.682-690
• Main Authors: Szmigielski, Cezary, MD, PhD, Rajpoot, Kashif, PhD, Grau, Vicente, PhD, Myerson, Saul G., MD, Holloway, Cameron, MBBS, Noble, J. Alison, MA, DPhil, Kerber, Richard, MD, Becher, Harald, MD, PhD
• Format: Article
• Language: English
• Subjects: Adolescent; Adult; Cardiovascular; Echocardiography, Three-Dimensional - instrumentation; Female; Heart Diseases - diagnostic imaging; Heart Diseases - physiopathology; Humans; Image Interpretation, Computer-Assisted; Magnetic Resonance Imaging; Male; Middle Aged; Phantoms, Imaging; Pilot Projects; Predictive Value of Tests; Reproducibility of Results; Stroke Volume; Ventricular Function, Left; Young Adult
• ISSN: 1936-878X; 1876-7591
• DOI: 10.1016/j.jcmg.2010.03.010

Objectives This study assessed 3-dimensional fusion echocardiography (3DFE), combining several real-time 3-dimensional echocardiography (RT3DE) full volumes from different transducer positions, for improvement in quality and completeness of the reconstructed image. Background The RT3DE technique has limited image quality and completeness of datasets even with current matrix transducers. Methods RT3DE datasets were acquired in 32 participants (mean age 33.7 ± 18.8 years; 27 men, 5 women). The 3DFE technique was also performed on a cardiac phantom. The endocardial border definition of RT3DE and 3DFE segments was graded for quality: good (2), intermediate (1), poor (0), or out of sector. Short-axis and apical images were compared in RT3DE and 3DFE, yielding 2,048 segments. The images were processed to generate 3DFE and then compared with cardiac magnetic resonance. Results In the heart phantom, fused datasets showed improved contrast to noise ratio from 49.4 ± 25.1 (single dataset) to 125.4 ± 25.1 (6 datasets fused together). In subjects, more segments were graded as good quality with 3DFE (805 vs. 435; p < 0.0001) and fewer as intermediate (184 vs. 283; p = 0.017), poor (31 vs. 265; p < 0.0001), or out of sector (4 vs. 41; p < 0.001) compared with the single 3-dimensional dataset. End-diastolic volume (EDV) and end-systolic volume (ESV) obtained from 3-dimensional fused datasets were equivalent to those from single datasets (EDV 118.2 ± 39 ml vs. 119.7 ± 43 ml; p = 0.41; ESV 48.1 ± 30 ml vs. 48.4 ± 35 ml; p = 0.87; ejection fraction [EF] 61.0 ± 10% vs. 61.8 ± 10%; p = 0.44). Bland-Altman analysis showed good 95% limits of agreement for the nonfused datasets (EDV ±46 ml; ESV ±36 ml; EF ±14%) and the fused datasets (EDV ±45 ml; ESV ±35 ml; EF ±16%), when compared with cardiac magnetic resonance. Conclusions Fusion of full-volume datasets resulted in an improvement in endocardial borders, image quality, and completeness of the datasets.