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Validating a prediction modeling tool for left ventricular outflow tract ( LVOT ) obstruction after transcatheter mitral valve replacement ( TMVR )
Author(s) -
Wang Dee Dee,
Eng Marvin H.,
Greenbaum Adam B.,
Myers Eric,
Forbes Michael,
Karabon Patrick,
Pantelic Milan,
Song Thomas,
Nadig Jeff,
Guerrero Mayra,
O'Neill William W.
Publication year - 2018
Publication title -
catheterization and cardiovascular interventions
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.988
H-Index - 116
eISSN - 1522-726X
pISSN - 1522-1946
DOI - 10.1002/ccd.27447
Subject(s) - ventricular outflow tract , mitral valve replacement , medicine , ventricular outflow tract obstruction , cardiology , mitral valve , stenosis , embolization , radiology
Objective Demonstrate proof‐of‐concept validation of a computed tomography (CT) computer‐aided design prediction modeling tool to identify patients at risk for left ventricular outflow tract (LVOT) obstruction in transcatheter mitral valve replacement (TMVR). Background LVOT obstruction is a significant and even fatal consequence of TMVR. Methods From August 2013 to August 2017, 38 patients in 5 centers underwent TMVR with compassionate use of balloon‐expandable valves for severe mitral valve dysfunction because of degenerative surgical mitral ring, bioprosthesis, or severe native mitral stenosis from to severe mitral annular calcification. All patients had preprocedural CT scans performed for anatomic screening, intraprocedural TEE and invasive hemodynamics performed. Preprocedural prediction modeling was performed utilizing computer‐aided design (CAD) of the neo‐LVOT post‐TMVR. Post‐TMVR CT scans were obtained and compared to pre‐TMVR LVOT modeling datasets for validation. Results All patients underwent successful TMVR without device embolization. Seven of the 38 patients experienced LVOT obstruction, defined as an increase of ≥10 mmHg LVOT peak gradient post‐TMVR. Anatomic screening using CT was validated in 20/38 patients as preprocedural predicted neo‐LVOT surface area correlated well with post‐TMVR measurements ( R 2 = 0.8169, P < 0.0001). A receiver operating curve curve found a predicted neo‐LVOT surface area of ≤ 189.4 mm 2 to have 100% sensitivity and 96.8% specificity for predicting TMVR‐induced LVOT obstruction. Conclusion CAD design and CT postprocessing are indispensable tools in predicting LVOT obstruction and necessary for anatomic screening in percutaneous TMVR.