Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions · 2026
Validation of an Automated Artificial Intelligence-Driven Planner for Transcatheter Aortic Valve Replacement.
СтатьяВалидационное исследованиеНазвание и аннотация: Перевод пока не подготовлен
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van den Dorpel Mark M P, Uchoa de Assis Lucas, van Niekerk Jenna, Deckx Sophie, Sherman Matthew, Schrot Janelle, Kozak Anna, Kardys Isabella, Hirsch Alexander, Daemen Joost, Nuis Rutger Jan, Van Mieghem Nicolas M
Аннотация
BACKGROUND: Preprocedural planning with multislice computed tomography (MSCT) is an essential prerequisite for successful transcatheter aortic valve replacement (TAVR). However, preprocedural planning is time-consuming and may contain clinically meaningful interobserver variability. Artificial intelligence (AI) based automated planning methods may provide anatomical MSCT measurements while reducing the time load required for the analysis. Previous studies on the validation of AI-based TAVR planning methods excluded anatomical variants or lacked data on actual TAVR prosthesis size agreement. Mimics for TAVR (Materialise, Leuven, Belgium) is a new, AI-driven TAVR planning platform based on patient-specific 3D anatomical models and automated measurements through a web-based user interface.
AIMS: To validate the Mimics for TAVR planning tool in clinical practice.
METHODS: Key planning assessments were performed on pre-TAVR MSCT datasets using Mimics for TAVR and a commercially available semi-automated software package. Agreement between the two planning methods was assessed using intraclass correlation coefficients and Bland-Altman plots.
RESULTS: A total of 126 consecutive patients (mean age 80 [74-85]; 56% male) who underwent MSCT as part of their TAVR work-up were included. Mimics for TAVR derived measurements showcased high accuracy and excellent agreement for the area of the aortic annulus (mean error ± SD: -1.9 ± 3.3%, ICC: 0.976 [95% CI: 0.966-0.984]), left ventricular outflow (-2.7 ± 3.8%, ICC: 0.970 [0.957-0.983]), sinotubular junction (-2.6 ± 4.2%, ICC: 0.953 [0.921-0.971]), coronary heights (LCA -3.5 ± 4.8%, ICC: 0.900 (0.859-0.928). RCA -3.9 ± 4.7%, ICC: 0.928 [0.898-0.949]) and membranous septum length (-5.0 ± 9.2%, ICC: 0.919 [0.880-0.940]). Mimics for TAVR assessment significantly reduced the time required for pre-TAVR analysis (1.03 ± 0.15 min vs. 9.55 ± 3.16 min per case, respectively (p = 0.001).
CONCLUSION: The automated AI-driven Mimics for TAVR planner is an accurate alternative to existing semiautomated TAVR planning platforms and may enhance overall workflow efficiency.
AIMS: To validate the Mimics for TAVR planning tool in clinical practice.
METHODS: Key planning assessments were performed on pre-TAVR MSCT datasets using Mimics for TAVR and a commercially available semi-automated software package. Agreement between the two planning methods was assessed using intraclass correlation coefficients and Bland-Altman plots.
RESULTS: A total of 126 consecutive patients (mean age 80 [74-85]; 56% male) who underwent MSCT as part of their TAVR work-up were included. Mimics for TAVR derived measurements showcased high accuracy and excellent agreement for the area of the aortic annulus (mean error ± SD: -1.9 ± 3.3%, ICC: 0.976 [95% CI: 0.966-0.984]), left ventricular outflow (-2.7 ± 3.8%, ICC: 0.970 [0.957-0.983]), sinotubular junction (-2.6 ± 4.2%, ICC: 0.953 [0.921-0.971]), coronary heights (LCA -3.5 ± 4.8%, ICC: 0.900 (0.859-0.928). RCA -3.9 ± 4.7%, ICC: 0.928 [0.898-0.949]) and membranous septum length (-5.0 ± 9.2%, ICC: 0.919 [0.880-0.940]). Mimics for TAVR assessment significantly reduced the time required for pre-TAVR analysis (1.03 ± 0.15 min vs. 9.55 ± 3.16 min per case, respectively (p = 0.001).
CONCLUSION: The automated AI-driven Mimics for TAVR planner is an accurate alternative to existing semiautomated TAVR planning platforms and may enhance overall workflow efficiency.
Предметные рубрики MeSH
HumansPredictive Value of TestsMultidetector Computed TomographyReproducibility of ResultsAortic ValveAged, 80 and overTranscatheter Aortic Valve ReplacementMaleFemaleRadiographic Image Interpretation, Computer-AssistedAortic Valve StenosisAgedObserver VariationArtificial IntelligencePatient-Specific ModelingHeart Valve ProsthesisProsthesis DesignAutomationTreatment Outcome