ArticleScientific reports2020
Application and Evaluation of Highly Automated Software for Comprehensive Stent Analysis in Intravascular Optical Coherence Tomography.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 22 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
22 citing papers in PubMed, 1 synthesis or guideline pooled it, 26 citations in OpenAlex.
- Automated Coronary Optical Coherence Tomography Feature Extraction with Application to Three-Dimensional Reconstruction.Tomography (Ann Arbor, Mich.) · 2022Pooled it
- Case Report: The "metal ring" phenomenon: a rare cause of recurrent in-stent restenosis.Frontiers in cardiovascular medicine · 2026Article
- Computational Analysis of Intravascular OCT Images for Future Clinical Support: A Comprehensive Review.IEEE reviews in biomedical engineering · 2026Review
- Automated Artificial Intelligence Mapping of Coronary Plaque Calcification: A Comparison with Manual Intravascular Image Analysis.Journal of clinical medicine · 2025Article
- Artificial Intelligence-Based Algorithm for Stent Coverage Assessments.Journal of personalized medicine · 2025Article
- Enhancing percutaneous coronary intervention using TriVOCTNet: a multi-task deep learning model for comprehensive intravascular optical coherence tomography analysis.Physical and engineering sciences in medicine · 2025Article
- Harnessing Artificial Intelligence for Innovation in Interventional Cardiovascular Care.Journal of the Society for Cardiovascular Angiography & Interventions · 2025Review
- Revolutionising Acute Cardiac Care With Artificial Intelligence: Opportunities and Challenges.The Canadian journal of cardiology · 2024Review
- Assessment of Effectiveness of the Algorithm for Automated Quantitative Analysis of Metallic Strut Tissue Short-Term Coverage with Intravascular Optical Coherence Tomography.Journal of clinical medicine · 2024Article
- Importance of Short-Term Neointimal Coverage of Drug-Eluting Stents in the Duration of Dual Antiplatelet Therapy.Journal of clinical medicine · 2024Review
- Deep learning segmentation of fibrous cap in intravascular optical coherence tomography images.Scientific reports · 2024Article
- Prediction of stent under-expansion in calcified coronary arteries using machine learning on intravascular optical coherence tomography images.Scientific reports · 2023Article
- Advances in Diagnosis, Therapy, and Prognosis of Coronary Artery Disease Powered by Deep Learning Algorithms.JACC. Asia · 2023Review
- Article
- Automated analysis of fibrous cap in intravascular optical coherence tomography images of coronary arteries.Scientific reports · 2022Article
- Automated Segmentation of Microvessels in Intravascular OCT Images Using Deep Learning.Bioengineering (Basel, Switzerland) · 2022Article
- Guest Edited Collection: Quantitative and computational techniques in optical coherence tomography.Scientific reports · 2022Article
- Neoatherosclerosis prediction using plaque markers in intravascular optical coherence tomography images.Frontiers in cardiovascular medicine · 2022Article
- Stent detection with very thick tissue coverage in intravascular OCT.Biomedical optics express · 2021Article
- [Structural design and biomechanical numerical analysis of body-fitted stent in stenotic vessels].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2021Article
Corrections and comments
- Erratum issued
Authors and funding
7 authors at 5 institutions in 3 countries.
Funding
Abstract
Intravascular optical coherence tomography (IVOCT) is used to assess stent tissue coverage and malapposition in stent evaluation trials. We developed the OCT Image Visualization and Analysis Toolkit for Stent (OCTivat-Stent), for highly automated analysis of IVOCT pullbacks. Algorithms automatically detected the guidewire, lumen boundary, and stent struts; determined the presence of tissue coverage for each strut; and estimated the stent contour for comparison of stent and lumen area. Strut-level tissue thickness, tissue coverage area, and malapposition area were automatically quantified. The software was used to analyze 292 stent pullbacks. The concordance-correlation-coefficients of automatically measured stent and lumen areas and independent manual measurements were 0.97 and 0.99, respectively. Eleven percent of struts were missed by the software and some artifacts were miscalled as struts giving 1% false-positive strut detection. Eighty-two percent of uncovered struts and 99% of covered struts were labeled correctly, as compared to manual analysis. Using the highly automated software, analysis was harmonized, leading to a reduction of inter-observer variability by 30%. With software assistance, analysis time for a full stent analysis was reduced to less than 30 minutes. Application of this software to stent evaluation trials should enable faster, more reliable analysis with improved statistical power for comparing designs.
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Registered trials
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.