BACKGROUND: Transcatheter aortic valve replacement (TAVR) can be complicated by significant paravalvular leak (PVL). Optimal selection of TAVR prosthesis size can minimize the risk of clinically significant PVL. The aim of this study was to assess the utility of a proprietary software package, HeartNavigator (Philips), in selecting TAVR prosthesis to minimize PVL. METHODS: All consecutive TAVR patients were considered for inclusion. HeartNavigator assessment was compared to three conventional (average, area-based, and circumference- based) computed tomography (CT) scan measurements of annulus diameter. The primary endpoint was clinically important (≥2+) aortic insufficiency (AI). RESULTS: Fifty-six patients were suitable for analysis. The incidence of clinically important AI was 25%. The overall predictive value was identical for HeartNavigator (80.4%) and the three conventional CT parameters. Each method correctly identified a majority of patients destined for AI. Although HeartNavigator accurately identified a numerically greater portion of patients with AI (64.3%), this was not significantly different from the conventional CT parameters. CONCLUSIONS: As compared to conventional CT-based measurements, HeartNavigator offers an accurate method for selecting TAVR prostheses, comparable to conventional CT measurements.
BACKGROUND: Transcatheter aortic valve replacement (TAVR) can be complicated by significant paravalvular leak (PVL). Optimal selection of TAVR prosthesis size can minimize the risk of clinically significant PVL. The aim of this study was to assess the utility of a proprietary software package, HeartNavigator (Philips), in selecting TAVR prosthesis to minimize PVL. METHODS: All consecutive TAVR patients were considered for inclusion. HeartNavigator assessment was compared to three conventional (average, area-based, and circumference- based) computed tomography (CT) scan measurements of annulus diameter. The primary endpoint was clinically important (≥2+) aortic insufficiency (AI). RESULTS: Fifty-six patients were suitable for analysis. The incidence of clinically important AI was 25%. The overall predictive value was identical for HeartNavigator (80.4%) and the three conventional CT parameters. Each method correctly identified a majority of patients destined for AI. Although HeartNavigator accurately identified a numerically greater portion of patients with AI (64.3%), this was not significantly different from the conventional CT parameters. CONCLUSIONS: As compared to conventional CT-based measurements, HeartNavigator offers an accurate method for selecting TAVR prostheses, comparable to conventional CT measurements.
Authors: Alexander Meyer; Markus Kofler; Matteo Montagner; Axel Unbehaun; Simon Sündermann; Semih Buz; Christoph Klein; Christof Stamm; Natalia Solowjowa; Maximilian Y Emmert; Volkmar Falk; Jörg Kempfert Journal: Sci Rep Date: 2020-07-01 Impact factor: 4.379