QUANTIFICATION OF VALVULAR REGURGITATION: A REVIEW
3
Author(s):
N. CHIDAMBARAM, G.N. BALAJI, T.S. SUBASHINI
Vol - 9, Issue- 3 ,
Page(s) : 204 - 210
(2018 )
DOI : https://doi.org/10.32804/IRJMST
Abstract
Valvular regurgitation (VR) is considered to be the mainreason behindmorbidity and mortality among cardiac patients. Although physical examination is enough for a clinician to find out the presenceof regurgitation, diagnostic methods are necessary to assessthe seriousness of VR and the changes in cardiac chambers as a resultof the volume overload. Recently, echocardiography with Doppler proved to be the most useful to have the noninvasive recognition and assessment of severity besides etiology of the regurgitation of the valves. The measurements of the regurgitation help in assessingthe progressof the disease, which is criticalin determiningthe correcttime for surgical treatment or any particulartreatment. Doppler echocardiography plays the vital role in giving valuable information on the severity of VR. Today, in clinical cardiology a very high quantification precision is needed for medical application, which is provided by the color Doppler echocardiographic images. This articlereviews several comprehensive methods that are presented in the literature to assessand quantify mitral regurgitation and aortic regurgitation through two-dimensional (2D) color Doppler echocardiographic images, which is the resultof proximal flow convergence method.
- Laurent Philippe et al., "Evaluation of Valvular Regurgitation by Factor Analysis of First-Pass Angiography," The Journal of Nuclear Medicine, Vol. 29, 1988, pp.159-167.
- André Schmidt et al., "Valvular Regurgitation by Color Doppler Echocardiography," Arq Bras Cardiol., Vol. 74, No. 3, 2000, pp. 273-281.
- Sandeep Bhachu, "A New Method to Quantify Mitral Regurgitation," 4th year
- Medicine, TSMJ, Review Article, Vol.5, April 2004, pp. 37-40.
- Eustachio Agricola et al., "Ischemic mitral regurgitation: mechanisms and echocardiographic classification," European Journal of Echocardiography, Vol. 9, No. 2, 2007, pp. 207-221.
- Paul A.Grayburn and Ronald M. Peshock, "Noninvasive Quantification of Valvular Regurgitation: Getting to the Core of the Matter," Circulation, Vol. 94, 1996, pp. 119-121.
- Min Pu et al., "Quantification of Mitral Regurgitation by the Proximal Convergence Method Using Transesophageal Echocardiography," Circulation, Vol. 92, 1995, pp. 2169-2177.
- Bülent Mutlu et al., "Evaluation of the Proximal Isovelocity Surface Area Method and Vena Contracta Width in Mitral Regurgitation with the Transthoracic and Transesophageal Echocardiography," Turkish Society of Cardiology, Vol. 31, No. 7, July 2003, pp. 361-370.
- Baspinar et al., "PISA method for assessment of mitral regurgitation in children," The Anatolian journal of cardiology, Vol. 5, 2005, pp. 168-71.
- Stephen H.Little et al., "Three-Dimensional Color Doppler Echocardiography for Direct Measurement of Vena Contracta Area in Mitral Regurgitation: In Vitro Validation and Clinical Experience," JACC: Cardiovascular Imaging, Vol.1, No. 6, 2008, pp. 695-704.
- Nina Ajmone Marsan et al., "Quantification of Functional Mitral Regurgitation by Real-Time 3D Echocardiography: Comparison With 3D Velocity-Encoded Cardiac Magnetic Resonance," JACC: Cardiovascular Imaging, Vol. 2, No. 11, 2009, pp. 1245-1252.
- Sochman J and Peregrin J. H, "Catheter-Based Management of Aortic Valve Regurgitation in Experimental Cardiology," Physiological research, Vol. 57, No.3, 2008, pp.321-326.
- Simon Biner et al., "Reproducibility of Proximal Isovelocity Surface Area, Vena Contracta, and Regurgitant Jet Area for Assessment of Mitral Regurgitation Severity," JACC: Cardiovascular Imaging, Vol. 3, No.3, March 2010, pp. 235-243.
- Maryam Esmaeilzadeh et al., "Quantification of Aortic Regurgitation Severity by Left Ventricular to Right Ventricular Stroke Volume Ratio," The Journal of Tehran University Heart Center, Vol. 2, 2009, pp. 85- 90.
- Balodi, Arun, et al. "Texture based classification of the severity of mitral regurgitation." Computers in biology and medicine 73 (2016): 157-164.
- Balaji, G. N., T. S. Subashini, and N. Chidambaram. "Automatic Detection of Mitral Regurgitant Jet by k-means clustering." International Journal of Applied Engineering Research 9.20: 2014.
- Elbedwehy, Mona Nagy, et al. "Detection of heart disease using binary particle swarm optimization." Computer Science and Information Systems (FedCSIS), 2012 Federated Conference on. IEEE, 2012.
|