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J Am Coll Cardiol Img, 2010; 3:682-690, doi:10.1016/j.jcmg.2010.03.010
© 2010 by the American College of Cardiology Foundation
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Real-Time 3D Fusion Echocardiography

Cezary Szmigielski, MD, PhD*,{dagger}, Kashif Rajpoot, PhD{ddagger}, Vicente Grau, PhD{ddagger},§, Saul G. Myerson, MD*, Cameron Holloway, MBBS*, J. Alison Noble, MA, DPhil{ddagger}, Richard Kerber, MD||, Harald Becher, MD, PhD*,*

* Department of Cardiovascular Medicine, University of Oxford, Oxford, United Kingdom
{dagger} Department of Internal Medicine, Hypertension and Vascular Diseases, The Medical University of Warsaw, Warsaw, Poland
{ddagger} Department of Engineering Science, University of Oxford, Oxford, United Kingdom
§ Oxford e-Research Centre (OeRC), University of Oxford, Oxford, United Kingdom
|| Cardiovascular Division, University of Iowa, Iowa City, Iowa

* Reprint requests and correspondence: Dr. Harald Becher, Mazankowski Alberta Heart Institute, University of Alberta Hospital, 8440-112 Street, Edmonton, T6G 2B7, Canada (Email: harald{at}ualberta.ca).

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.

Key Words: echocardiography • ultrasonics • imaging

Abbreviations and Acronyms
  2DE = 2-dimensional echocardiography
  3DFE = 3-dimensional fusion echocardiography
  EDV = end-diastolic volume
  EF = ejection fraction
  ESV = end-systolic volume
  LV = left ventricle/ventricular
  RT3DE = real-time 3-dimensional echocardiography




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[Abstract] [Full Text] [PDF]



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