Comparison and Agreement of Echocardiographic Volumetric Methods for Quantifying Mitral Regurgitation in Dogs with Myxomatous Mitral Valve Disease

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Authors: Shimpei Kawai, Ryohei Suzuki, Yohei MOCHIZUKI, Yunosuke Yuchi, Shuji Satomi, Arata Kitazawa, Takahiro Teshima, Hirotaka Matsumoto
Cited by: 1
References: 26

Abstract

Quantitative assessment of mitral regurgitation (MR) in dogs with myxomatous mitral valve disease (MMVD) is influenced by the method used to estimate left ventricular volume. This study aimed to evaluate the impact of different left ventricular volume estimation methods on quantitative MR assessment, using the modified Simpson's method of discs (Disc method) as a reference. Echocardiographic data from 167 dogs with MMVD and 19 healthy control dogs were analyzed. Regurgitant volume (RVol), body size-normalized RVol, and regurgitant fraction (RF) were calculated using diameter-based methods (Cube, Gibson, Meyer, and Teichholz) and compared with values obtained using the Disc method. All diameter-based methods showed significant positive correlations with the Disc method. However, Bland-Altman analyses demonstrated wide limits of agreement and systematic bias. Between-method discrepancies increased with advancing disease stage, with diameter-based methods tending to overestimate RVol and RF, particularly in dogs classified as American College of Veterinary Internal Medicine (ACVIM) stages B2 and C/D. Although relative trends in regurgitant indices were consistent across methods, substantial differences were observed in absolute values. These findings indicate that diameter-based methods are not interchangeable with the Disc method for absolute quantification of MR severity in dogs with MMVD, especially in advanced disease stages.

Fields of Study & Subjects

Cardiovascular Conditions and Treatments Cardiac Valve Diseases and Treatments Cardiovascular Function and Risk Factors

Publication details

Journal / source
Animals
Publisher
MDPI AG
Volume
16
Issue
8
Pages
1249–1249
Publication date
18 April 2026
Language
EN