Evaluation of valvular regurgitation severity using digital acquisition of echocardiographic images.
BACKGROUND
Digital acquisition is a technique for storing echocardiographic data that offers advantages over conventional videotape (VT); however, limited information is available on its accuracy for the evaluation of valvular regurgitation.


METHODS
We evaluated 102 patients with at least 1 regurgitant lesion. Data were obtained on VT and in 1 cardiac cycle stored digitally (1C). To assess for incremental improvement with acquisition of multiple cycles, digital images were also acquired with 2 (2C) or 3 cardiac cycles (3C). Both digital and VT images were graded for regurgitant severity as absent, trivial, mild, moderate, or severe. Kappa statistics were used to assess agreement.


RESULTS
A total of 171 valvular regurgitant lesions (mild or greater) were evaluated. The overall agreement between 1C and VT images was kappa = 0.61. With multiple cycle acquisition, there was no improvement in agreement (kappa = 0.56 and 0.57 for 2C and 3C, respectively). When subgrouped, the level of agreement between 1C and VT was slightly lower for the aortic valve than for the mitral or tricuspid valves (kappa = 0.49, 0.63, 0.64, respectively).


CONCLUSIONS
The 1C technique has substantial agreement and correlation with standard VT for the evaluation of regurgitant lesions with the use of color flow Doppler. The acquisition of multiple cardiac cycles does not provide incremental improvement over single beat acquisition.
Shah
Dipan J
DJ
Division of Cardiology, Northwestern University Medical School, Chicago, Illinois, USA.
Diluzio
Silvia
S
Ambardekar
Amrut V
AV
Smulevitz
Beverly
B
Smith
Gwenlyn L
GL
Nagaraj
Ashwin
A
Hamilton
Andrew J
AJ
McPherson
David D
DD
Rigolin
Vera H
VH
D018618:Echocardiography, Doppler, Color / Q000379:methods*; D006349:Heart Valve Diseases / Q000000981:diagnostic imaging* / Q000503:physiopathology*; D006439:Hemodynamics; D006801:Humans; D015588:Observer Variation; D012720:Severity of Illness Index; D012815:Signal Processing, Computer-Assisted