ArticleClinical research in cardiology : official journal of the German Cardiac Society2026
Impact of fully-automated AI based CT-analysis on pre-procedural TAVI planning.
Article in Clinical research in cardiology : official journal of the German Cardiac Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundAccurate pre-procedural computed tomography (CT) analysis is essential for optimal valve sizing and clinical outcomes in transcatheter aortic valve implantation (TAVI). Recently, fully automated, artificial intelligence (AI)-based CT analysis platforms have been developed to simplify and standardize this process.
aimsThe aim of the study was to investigate the clinical impact of this new analysis method on the selection of valve prosthesis size.
methodsOverall, 247 patients with symptomatic severe aortic stenosis were enrolled. Patients underwent TAVI procedures at two different heart centres. The pre-procedural datasets were analysed by a standard TAVI CT-analysis software (3M, Pie Medical Imaging BV, The Netherlands) and a fully-automated CT-analysis-platform employing a deep-learning based algorithm. Key annular measurements and simulated prosthesis size selection were compared between both methods.
resultsThe mean aortic annulus diameter was 24.5 ± 2.3 mm (3mensio) and 24.4 ± 2.4 mm (AI), respectively, with a mean absolute error (MAE) of 0.6 mm and mean absolute percentage error (MAPE) of 2.6%. Annulus perimeter (76.9 ± 7.0 mm vs. 74.6 ± 7.3 mm; MAE: 2.0 mm; MAPE: 2.6%) and annulus area (458.4 ± 87.2 mm
conclusionsIn this retrospective study, fully automated AI-based CT analysis demonstrated excellent agreement with conventional semi-automated measurements of the aortic annulus. Nevertheless, similar to established planning workflows, expert interpretation remains crucial to integrate the broader anatomical and clinical context required for optimal prosthesis size selection.
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