Real-Time 3D Fusion Echocardiography
Cezary Szmigielski, MD, PhD*, ,
Kashif Rajpoot, PhD ,
Vicente Grau, PhD , ,
Saul G. Myerson, MD*,
Cameron Holloway, MBBS*,
J. Alison Noble, MA, DPhil ,
Richard Kerber, MD||,
Harald Becher, MD, PhD*,*
* Department of Cardiovascular Medicine, University of Oxford, Oxford, United Kingdom
Department of Internal Medicine, Hypertension and Vascular Diseases, The Medical University of Warsaw, Warsaw, Poland
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
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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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J. A. Noble, N. Navab, and H. Becher
Ultrasonic image analysis and image-guided interventions
Interface Focus,
August 6, 2011;
1(4):
673 - 685.
[Abstract]
[Full Text]
[PDF]
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