Predicting paravalvular leak after transcatheter mitral valve replacement using commercially available software modeling.
Aged
Aged, 80 and over
Arizona
Cardiac Catheterization
/ adverse effects
Computed Tomography Angiography
Coronary Angiography
Female
Heart Valve Prosthesis Implantation
/ adverse effects
Humans
Male
Middle Aged
Mitral Valve
/ diagnostic imaging
Mitral Valve Insufficiency
/ diagnostic imaging
Patient-Specific Modeling
Predictive Value of Tests
Retrospective Studies
Risk Assessment
Risk Factors
Severity of Illness Index
Software
Treatment Outcome
Computed tomography
Mitral regurgitation
Paravalvular leak
Software modeling
Journal
Journal of cardiovascular computed tomography
ISSN: 1876-861X
Titre abrégé: J Cardiovasc Comput Tomogr
Pays: United States
ID NLM: 101308347
Informations de publication
Date de publication:
Historique:
received:
31
10
2019
revised:
25
02
2020
accepted:
15
04
2020
pubmed:
16
5
2020
medline:
6
1
2021
entrez:
16
5
2020
Statut:
ppublish
Résumé
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. 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). 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). Software modeling using pre-procedural CTA is a straightforward method for predicting the risk of moderate and severe MR due to PVL after TMVR.
Sections du résumé
BACKGROUND
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
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
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
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.
Identifiants
pubmed: 32409265
pii: S1934-5925(20)30137-4
doi: 10.1016/j.jcct.2020.04.007
pii:
doi:
Types de publication
Journal Article
Multicenter Study
Langues
eng
Sous-ensembles de citation
IM
Pagination
495-499Commentaires et corrections
Type : CommentIn
Informations de copyright
Copyright © 2020 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of competing interest The authors have no conflicts of interest to declare.