ReviewNature reviews. Cardiology2024
Roadmap on the use of artificial intelligence for imaging of vulnerable atherosclerotic plaque in coronary arteries.
Review in Nature reviews. Cardiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06025305 (Development and Validation of Multi-scale Deep Neural Network-Based CT Intelligent Diagnosis System for Coronary Vulnerable Plaques), which is not on this map. Cited by 56 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Development and Validation of Multi-scale Deep Neural Network-Based CT Intelligent Diagnosis System for Coronary Vulnerable Plaques: A Chinese Multicenter Study
Who cites it
56 citing papers in PubMed, 1 synthesis or guideline pooled it, 91 citations in OpenAlex.
- Application of artificial intelligence in non-invasive cardiovascular imaging for coronary artery disease: a systematic review and meta-analysis.Frontiers in cardiovascular medicine · 2025Pooled it
- Relationship between the circulating N-terminal pro B-type natriuretic peptide and the risk of carotid artery plaque in different glucose metabolic states in patients with coronary heart disease: a CSCD-TCMCardiovascular diabetology · 2023Trial
- Intracoronary imaging in percutaneous coronary intervention: why, when, how and which from large, randomized trials.Nature reviews. Cardiology · 2026Review
- Detection of calcified plaques: comparison between coronary CT angiography and thin-slice non-contrast CT with deep learning-aided image registration.European radiology · 2026Article
- Advancing Coronary Risk Assessment Through Combined Radiomic, Mechanical, and Hemodynamic Analysis.Annals of biomedical engineering · 2026Article
- Cardiovascular disease prevention in China: challenges and opportunities in the artificial intelligence-enabled digital health era.Nature reviews. Cardiology · 2026Review
- Plaque Progression and Rupture in Obstructive Coronary Artery Disease: A Review of Current Imaging Modalities.Reviews in cardiovascular medicine · 2026Review
- Artificial intelligence-powered automatic coronary computed tomography angiography plaque quantification: comparison against optical coherence tomography.European heart journal. Digital health · 2026Article
- Intracoronary Imaging for the Management of Vulnerable Plaques.Journal of clinical medicine · 2026Review
- Myocardial infarction, stroke and arterial stenosis: time to reassess a major misunderstanding.Nature reviews. Cardiology · 2026Review
- Coronary CT angiography evaluation with artificial intelligence for individualized medical treatment of atherosclerosis: a Consensus Statement from the QCI Study Group.Nature reviews. Cardiology · 2026Review
- Artificial Intelligence in Coronary Plaque Characterization: Clinical Implications, Evidence Gaps, and Future Directions.Journal of clinical medicine · 2026Review
- Improving Clinical Diagnostics and Patient Care through Artificial Intelligence and Biosensor Technologies.ACS omega · 2026Review
- Artificial Intelligence-Based Automated Analysis for Pleural Effusion Detection on Thoracic Ultrasound: A Systematic Review.Diagnostics (Basel, Switzerland) · 2026Review
- Ultrasound in cardiovascular care: a perspective on preventive, diagnostic, and monitoring applications.Frontiers in cardiovascular medicine · 2026Article
- The application of artificial intelligence in the intersection of metabolic dysfunction-associated steatotic liver disease and cardiovascular diseases.Frontiers in immunology · 2026Review
- Nanotechnology for atherosclerotic plaque stabilisation: bridging innovation and clinical practice.EBioMedicine · 2026Review
- Challenges and opportunities in assessing right ventricular structure and function: a Roadmap for standardization, clinical implementation and research.Nature reviews. Cardiology · 2026Review
- Innovations in Diagnosis and Treatment of Coronary Artery Disease.Diagnostics (Basel, Switzerland) · 2025Review
- Deciphering age- and sex-specific patterns of coronary artery atherosclerosis from a large Chinese cohort.Nature communications · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors at 12 institutions in 7 countries.
Funding
Abstract
Artificial intelligence (AI) is likely to revolutionize the way medical images are analysed and has the potential to improve the identification and analysis of vulnerable or high-risk atherosclerotic plaques in coronary arteries, leading to advances in the treatment of coronary artery disease. However, coronary plaque analysis is challenging owing to cardiac and respiratory motion, as well as the small size of cardiovascular structures. Moreover, the analysis of coronary imaging data is time-consuming, can be performed only by clinicians with dedicated cardiovascular imaging training, and is subject to considerable interreader and intrareader variability. AI has the potential to improve the assessment of images of vulnerable plaque in coronary arteries, but requires robust development, testing and validation. Combining human expertise with AI might facilitate the reliable and valid interpretation of images obtained using CT, MRI, PET, intravascular ultrasonography and optical coherence tomography. In this Roadmap, we review existing evidence on the application of AI to the imaging of vulnerable plaque in coronary arteries and provide consensus recommendations developed by an interdisciplinary group of experts on AI and non-invasive and invasive coronary imaging. We also outline future requirements of AI technology to address bias, uncertainty, explainability and generalizability, which are all essential for the acceptance of AI and its clinical utility in handling the anticipated growing volume of coronary imaging procedures.
Indexed as
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What OpenQuestion holds
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.