Predicting paravalvular leak after transcatheter mitral valve replacement using commercially available software modeling

Michael F. Morris, Alejandro Pena, Aneesh Kalya, Abhishek C. Sawant, Kapildeo Lotun, Timothy Byrne, H. Kenith Fang, Ashish Pershad

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)495-499
Number of pages5
JournalJournal of Cardiovascular Computed Tomography
Issue number6
StatePublished - Nov 1 2020


  • Computed tomography
  • Mitral regurgitation
  • Paravalvular leak
  • Software modeling

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Cardiology and Cardiovascular Medicine


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