Key result
3D Auto CFQ yielded fewer severe mitral regurgitation classifications (16.2% vs 53.3%, P<0.001) and lower regurgitant volume than 2D PISA, with superior agreement to cardiac magnetic resonance.
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Why the study?
Accurate quantification of mitral regurgitation remains challenging with conventional 2D echocardiography due to geometric assumptions and single-frame analysis.
Does automated 3D color flow quantification improve the accuracy of mitral regurgitation assessment compared to 2D PISA in patients undergoing TEE?
Cohort (n=185)
Does automated 3D color flow quantification improve the accuracy of mitral regurgitation assessment compared to 2D PISA in patients undergoing TEE?
Absolute Event Rate: 16.2% vs 53.3%
p-value: p=<0.001
3D Auto CFQ is a feasible and reproducible method for MR quantification that shows higher agreement with CMR than conventional 2D PISA, often resulting in lower MR severity grading.
BACKGROUND: Accurate quantification of mitral regurgitation (MR) remains challenging with conventional two-dimensional (2D) echocardiography because of geometric assumptions and single-frame analysis. We aimed to evaluate the feasibility and performance of a novel automated three-dimensional color flow quantification (3D Auto CFQ) tool for MR assessment. METHODS: We retrospectively analyzed 185 consecutive patients with MR who underwent transesophageal echocardiography (TEE). MR severity and regurgitant volume (RVol) were quantified by 2D proximal isovelocity surface area (PISA) and by 3D Auto CFQ, which integrates real-time 3D TEE color Doppler with a fluid-dynamics-based model. In a CMR subgroup cohort of 29 patients, cardiac magnetic resonance (CMR) served as the reference. Subgroup analyses were prespecified by MR etiology, jet direction/duration, rhythm, and number of jets. RESULTS: 3D Auto CFQ showed excellent feasibility (97.3%) and strong reproducibility (intra-observer intraclass correlation coefficient [ICC] 0.96; inter-observer ICC 0.91). Compared with 2D PISA, 3D Auto CFQ yielded lower RVol (36.3 ± 25.2 mL vs. 65.9 ± 38.7 mL, p < 0.001) and fewer severe MR classifications (16.2% vs. 53.3%, p < 0.001). Agreement with CMR was superior for 3D Auto CFQ (r = 0.860, ICC = 0.92) than for 2D PISA (r = 0.694, ICC = 0.64), with a significant difference between correlations (Fisher's Z, p < 0.001). Subgroup analyses showed consistent performance of 3D Auto CFQ across various MR etiologies, jet characteristics, and rhythms, though correlation was weaker in atrial fibrillation (p = 0.005). CONCLUSION: 3D Auto CFQ is a feasible and reproducible method for MR quantification. Its use resulted in lower MR severity grade classification than 2D PISA. In the CMR subgroup, 3D Auto CFQ showed higher agreement with CMR than 2D PISA.
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Kim et al. (2026) conducted a cohort in Mitral regurgitation (n=185). 3D Auto CFQ vs. 2D PISA was evaluated on Severe MR classification (p=<0.001). 3D Auto CFQ yielded fewer severe mitral regurgitation classifications (16.2% vs 53.3%, P<0.001) and lower regurgitant volume than 2D PISA, with superior agreement to cardiac magnetic resonance.
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