ArticleDiagnostics (Basel, Switzerland)2023
TAVI-PREP: A Deep Learning-Based Tool for Automated Measurements Extraction in TAVI Planning.
Article in Diagnostics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed, 17 citations in OpenAlex.
- Impact of fully-automated AI based CT-analysis on pre-procedural TAVI planning.Clinical research in cardiology : official journal of the German Cardiac Society · 2026Article
- AMR-VSF: an adaptive memory correction framework for robust 3D CT aorta segmentation.International journal of computer assisted radiology and surgery · 2026Article
- Evolving capabilities of computed tomography imaging for transcatheter valvular heart interventions - new opportunities for precision medicine.The international journal of cardiovascular imaging · 2026Review
- Computed tomography-based prediction of commissural positions facilitates valve-sparing aortic root replacement.JTCVS techniques · 2026Article
- Cardiac Computed Tomography in Structural Heart Interventions: From Preprocedural Planning to Procedural Strategy.Reviews in cardiovascular medicine · 2025Review
- Great debate: artificial intelligence will replace much of what cardiologists do.European heart journal · 2025Article
- Precision TAVR quantification- AI-accelerated TAVR planning reduces assessment time by 80% in bicuspid aortic stenosis.European heart journal. Imaging methods and practice · 2025Article
- Uncertainty-Guided Active Learning for Access Route Segmentation and Planning in Transcatheter Aortic Valve Implantation.Journal of imaging · 2025Article
- State-of-the-art artificial intelligence methods for pre-operative planning of cardiothoracic surgery and interventions: a narrative review.Journal of thoracic disease · 2025Review
- Transcatheter tricuspid valve implantation with LuX-Valve utilizing a novel patient-specific virtual and physical simulator: a case report.European heart journal. Case reports · 2024Article
- Review
- Validation Study of Two Artificial Intelligence-Based Preplanning Methods for Transcatheter Aortic Valve Replacement Procedures.Journal of the Society for Cardiovascular Angiography & Interventions · 2024Article
- Artificial Intelligence in Transcatheter Aortic Valve Replacement: Its Current Role and Ongoing Challenges.Diagnostics (Basel, Switzerland) · 2024Review
- The Current Landscape of Artificial Intelligence in Imaging for Transcatheter Aortic Valve Replacement.Current radiology reports · 2024Article
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Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTranscatheter aortic valve implantation (TAVI) is a less invasive alternative to open-heart surgery for treating severe aortic stenosis. Despite its benefits, the risk of procedural complications necessitates careful preoperative planning.
methodsThis study proposes a fully automated deep learning-based method, TAVI-PREP, for pre-TAVI planning, focusing on measurements extracted from computed tomography (CT) scans. The algorithm was trained on the public MM-WHS dataset and a small subset of private data. It uses MeshDeformNet for 3D surface mesh generation and a 3D Residual U-Net for landmark detection. TAVI-PREP is designed to extract 22 different measurements from the aortic valvular complex. A total of 200 CT-scans were analyzed, and automatic measurements were compared to the ones made manually by an expert cardiologist. A second cardiologist analyzed 115 scans to evaluate inter-operator variability.
resultsHigh Pearson correlation coefficients between the expert and the algorithm were obtained for most parameters (0.90-0.97), except for left and right coronary height (0.8 and 0.72, respectively). Similarly, the mean absolute relative error was within 5% for most measurements, except for left and right coronary height (11.6% and 16.5%, respectively). A greater consensus was observed among experts than when compared to the automatic approach, with TAVI-PREP showing no discernable bias towards either the lower or higher ends of the measurement spectrum.
conclusionsTAVI-PREP provides reliable and time-efficient measurements of the aortic valvular complex that could aid clinicians in the preprocedural planning of TAVI procedures.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.