Trial reportRadiology. Cardiothoracic imaging2024
Diagnostic Performance of AI-enabled Plaque Quantification from Coronary CT Angiography Compared with Intravascular Ultrasound.
Trial report in Radiology. Cardiothoracic imaging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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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
16 citing papers in PubMed.
- Artificial intelligence in cardiology: an evidence map across subspecialties, 2014-26.European heart journal. Digital health · 2026Article
- Advanced quantitative CT for coronary artery disease: integrating stenosis quantification, plaque quantification, and fractional flow reserve-CT.The British journal of radiology · 2026Review
- Coronary Plaque Burden in South Asian Adults: Insights From the DILWALE Registry.JACC. Advances · 2026Article
- Quantitative CCTA Plaque Differences Between Japanese and Non-Japanese Patients: Insights From ADVANCE.JACC. Advances · 2026Article
- Clinical Applications of Artificial Intelligence in Cardiac CT: From Coronary CT Angiography to CT-Derived Fractional Flow Reserve and Myocardial Perfusion Imaging.Korean journal of radiology · 2026Review
- Inherited risk of coronary artery disease: redefining care with imaging and genetics.Nature reviews. Cardiology · 2026Review
- Reproducibility of AI-Informed Coronary Computed Tomography Angiography-Derived Coronary Plaque Volume Quantification.JACC. Advances · 2026Article
- From Electrocardiography to the Catheterization Laboratory: A Multimodal Artificial Intelligence Framework for Acute Coronary Syndrome Detection and Risk Stratification.Diagnostics (Basel, Switzerland) · 2026Review
- Artificial intelligence across the cardiovascular diagnostic pathway: a case-based narrative review.Cardiovascular diagnosis and therapy · 2026Review
- Coronary Computed Tomography and Artificial Intelligence-based Plaque Analysis.Current atherosclerosis reports · 2026Review
- Innovations In Artificial Intelligence-Guided Atherosclerosis Cardiovascular Imaging: From Detection to Prognosis.Current atherosclerosis reports · 2026Review
- Artificial intelligence in coronary CT angiography: transforming the diagnosis and risk stratification of atherosclerosis.The international journal of cardiovascular imaging · 2025Review
- AI-Quantitative CT Coronary Plaque Features Associate With a Higher Relative Risk in Women: CONFIRM2 Registry.Circulation. Cardiovascular imaging · 2025Observational
- Computed Tomography Angiography in the Catheterization Laboratory: A Guide Towards Optimizing Coronary Interventions.Journal of cardiovascular development and disease · 2025Review
- The Impact of Preoperative Risk Factors on Delayed Discharge in Day Surgery: A Meta-Analysis.Healthcare (Basel, Switzerland) · 2025Review
- Efficacy and prognosis of multimodal angiography-interventions for chronic pulmonary artery stenosis and pulmonary hypertension.American journal of translational research · 2025Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose To assess the diagnostic performance of a coronary CT angiography (CCTA) artificial intelligence (AI)-enabled tool (AI-QCPA; HeartFlow) to quantify plaque volume, as compared with intravascular US (IVUS). Materials and Methods A retrospective subanalysis of a single-center prospective registry study was conducted in participants with ST-elevation myocardial infarction treated with primary percutaneous coronary intervention of the culprit vessel. Participants with greater than 50% stenosis in nonculprit vessels underwent CCTA, invasive coronary angiography, and IVUS of nonculprit lesion(s) between 2 and 40 days after primary percutaneous coronary intervention. Comparisons of plaque volumes obtained using AI-QCPA (HeartFlow) and IVUS were assessed using Spearman rank correlation (ρ) and Bland-Altman analysis. Results Thirty-three participants (mean age, 59.1 years ± 8.8 [SD]; 27 [82%] male and six [18%] female participants) and 67 vessels were included for analysis. There was strong agreement between AI-QCPA and IVUS in vessel (ρ = 0.94) and lumen volumes (ρ = 0.97). High agreement between AI-QCPA and IVUS was also found for total plaque volume (ρ = 0.92), noncalcified plaque (ρ = 0.91), and calcified plaque (ρ = 0.87). Bland-Altman analysis demonstrated AI-QCPA underestimated total plaque volume (-9.4 mm
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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.