Publication Details

AFRICAN RESEARCH NEXUS

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medicine

A Novel Angiographic Quantification of Aortic Regurgitation After TAVR Provides an Accurate Estimation of Regurgitation Fraction Derived From Cardiac Magnetic Resonance Imaging

JACC: Cardiovascular Interventions, Volume 11, No. 3, Year 2018

Objectives: This study sought to compare a new quantitative angiographic technique to cardiac magnetic resonance-derived regurgitation fraction (CMR-RF) for the quantification of prosthetic valve regurgitation (PVR) after transcatheter aortic valve replacement (TAVR). Background: PVR after TAVR is challenging to quantify, especially during the procedure. Methods: Post-replacement aortograms in 135 TAVR recipients were analyzed offline by videodensitometry to measure the ratio of the time-resolved contrast density in the left ventricular outflow tract to that in the aortic root (videodensitometric aortic regurgitation [VD-AR]). CMR was performed within an interval of ≤30 days (11 ± 6 days) after the procedure. Results: The average CMR-RF was 6.7 ± 7.0% whereas the average VD-AR was 7.0 ± 7.0%. The correlation between VD-AR and CMR-RF was substantial (r = 0.78, p < 0.001). On receiver-operating characteristic curves, a VD-AR ≥10% corresponded to >mild PVR as defined by CMR-RF (area under the curve: 0.94; p < 0.001; sensitivity 100%, specificity 83%), whereas a VD-AR ≥25% corresponded to moderate-to-severe PVR (area under the curve: 0.99; p = 0.004; sensitivity 100%, specificity 98%). Intraobserver reproducibility was excellent for both techniques (for CMR-RF, intraclass correlation coefficient: 0.91, p < 0.001; for VD-AR intraclass correlation coefficient: 0.93, p < 0.001). The difference on rerating was –0.04 ± 7.9% for CMR-RF and –0.40 ± 6.8% for VD-AR. Conclusions: The angiographic VD-AR provides a surrogate assessment of PVR severity after TAVR that correlates well with the CMR-RF. © 2018 American College of Cardiology Foundation

Statistics
Citations: 32
Authors: 9
Affiliations: 7
Identifiers
Research Areas
Noncommunicable Diseases
Study Approach
Quantitative