Michael F Morris1, Alejandro Pena2, Aneesh Kalya2, Abhishek C Sawant2, Kapildeo Lotun3, Timothy Byrne4, H Kenith Fang2, Ashish Pershad2. 1. Cardiovascular Institute, Banner University Medical Center, Phoenix, United States. Electronic address: Michael.morris@bannerhealth.com. 2. Cardiovascular Institute, Banner University Medical Center, Phoenix, United States. 3. Division of Cardiology, Banner University Medical Center, Tucson, United States. 4. Cardiovascular Institute, Banner University Medical Center, Phoenix, United States; Abrazo Arizona Heart Hospital, United States.
Abstract
BACKGROUND: There is limited data identifying patients at risk for significant mitral regurgitation (MR) after transcatheter mitral valve replacement (TMVR). We hypothesized that software modeling based on computed tomography angiography (CTA) can predict the risk of moderate or severe MR after TMVR. METHODS: 58 consecutive patients underwent TMVR at two institutions, including 31 valve-in-valve, 16 valve-in-ring, and 11 valve-in-mitral annular calcification. 12 (20%) patients developed moderate or severe MR due to paravalvular leak (PVL). RESULTS: The software model correctly predicted 8 (67%) patients with significant PVL, resulting in sensitivity of 67%, specificity 96%, positive predictive value 89%, and negative predictive value 86%. There was excellent agreement between CTA readers using software modeling to predict PVL (kappa 0.92; p < 0.01). On univariate analysis, CTA predictors of moderate or severe PVL included presence of a gap between the virtual valve and mitral annulus on the software model (OR 48; p < 0.01), mitral annular area (OR 1.02; p 0.01), and % valve oversizing (OR 0.9; p 0.01). On multivariate analysis, only presence of a gap on the software model remained significant (OR 36.8; p < 0.01). CONCLUSIONS: Software modeling using pre-procedural CTA is a straightforward method for predicting the risk of moderate and severe MR due to PVL after TMVR.
BACKGROUND: There is limited data identifying patients at risk for significant mitral regurgitation (MR) after transcatheter mitral valve replacement (TMVR). We hypothesized that software modeling based on computed tomography angiography (CTA) can predict the risk of moderate or severe MR after TMVR. METHODS: 58 consecutive patients underwent TMVR at two institutions, including 31 valve-in-valve, 16 valve-in-ring, and 11 valve-in-mitral annular calcification. 12 (20%) patients developed moderate or severe MR due to paravalvular leak (PVL). RESULTS: The software model correctly predicted 8 (67%) patients with significant PVL, resulting in sensitivity of 67%, specificity 96%, positive predictive value 89%, and negative predictive value 86%. There was excellent agreement between CTA readers using software modeling to predict PVL (kappa 0.92; p < 0.01). On univariate analysis, CTA predictors of moderate or severe PVL included presence of a gap between the virtual valve and mitral annulus on the software model (OR 48; p < 0.01), mitral annular area (OR 1.02; p 0.01), and % valve oversizing (OR 0.9; p 0.01). On multivariate analysis, only presence of a gap on the software model remained significant (OR 36.8; p < 0.01). CONCLUSIONS: Software modeling using pre-procedural CTA is a straightforward method for predicting the risk of moderate and severe MR due to PVL after TMVR.
Authors: Todd C Villines; Subhi J Al'Aref; Daniele Andreini; Marcus Y Chen; Andrew D Choi; Carlo N De Cecco; Damini Dey; James P Earls; Maros Ferencik; Heidi Gransar; Harvey Hecht; Jonathon A Leipsic; Michael T Lu; Mohamed Marwan; Pál Maurovich-Horvat; Edward Nicol; Gianluca Pontone; Jonathan Weir-McCall; Seamus P Whelton; Michelle C Williams; Armin Arbab-Zadeh; Gudrun M Feuchtner Journal: J Cardiovasc Comput Tomogr Date: 2021-02-22
Authors: Jonathan R Weir-McCall; Kelley Branch; Maros Ferencik; Ron Blankstein; Andrew D Choi; Brian B Ghoshhajra; Kavitha Chinnaiyan; Purvi Parwani; Edward Nicol; Koen Nieman Journal: J Cardiovasc Comput Tomogr Date: 2020-10-01