A novel fully automated method for mitral regurgitant orifice area quantification

• Published in: International journal of cardiology 2013-07, Vol.166 (3), p.688-695
• Main Authors: Moraldo, Michela, Bergamini, Corinna, Malaweera, Anura S.N, Dhutia, Niti M, Pabari, Punam A, Willson, Keith, Baruah, Resham, Manisty, Charlotte, Davies, Justin E, Xu, Xiao Y, Hughes, Alun D, Francis, Darrel P
• Format: Article
• Language: English
• Subjects: Aged; Automated analysis; Automation, Laboratory - methods; Biological and medical sciences; Blood flow velocity; Cardiology. Vascular system; Cardiovascular; Cardiovascular system; Echocardiography; Echocardiography - methods; Endocardial and cardiac valvular diseases; Female; Heart; Humans; Investigative techniques, diagnostic techniques (general aspects); Male; Medical sciences; Mitral Valve Insufficiency - diagnostic imaging; Mitral Valve Insufficiency - physiopathology; Mitral valve regurgitation; Single-Blind Method; Ultrasonic investigative techniques; Video Recording - methods
• ISSN: 0167-5273; 1874-1754
• DOI: 10.1016/j.ijcard.2011.11.104

Abstract Background Effective regurgitant orifice area (EROA) in mitral regurgitation (MR) is difficult to quantify. Clinically it is measured using the proximal isovelocity surface area (PISA) method, which is intrinsically not automatable, because it requires the operator to manually identify the mitral valve orifice. We introduce a new fully automated algorithm, (“AQURO”), which calculates EROA directly from echocardiographic colour M-mode data, without requiring operator input. Methods Multiple PISA measurements were compared to multiple AQURO measurements in twenty patients with MR. For PISA analysis, three mutually blinded observers measured EROA from the four stored video loops. For AQURO analysis, the software automatically processed the colour M-mode datasets and analysed the velocity field in the flow-convergence zone to extract EROA directly without any requirement for manual radius measurement. Results Reproducibility, measured by intraclass correlation (ICC), for PISA was 0.80, 0.83 and 0.83 (for 3 observers respectively). Reproducibility for AQURO was 0.97. Agreement between replicate measurements calculated using Bland-Altman standard deviation of difference (SDD) was 21,17 and 17mm2 for the three respective observers viewing independent video loops using PISA. Agreement between replicate measurements for AQURO was 6, 5 and 7mm2 for automated analysis of the three pairs of datasets. Conclusions By eliminating the need to identify the orifice location, AQURO avoids an important source of measurement variability. Compared with PISA, it also reduces the analysis time allowing analysis and averaging of data from significantly more beats, improving the consistency of EROA quantification. AQURO, being fully automated, is a simple, effective enhancement for EROA quantification using standard echocardiographic equipment.