ReviewKorean journal of radiology2024
Application of Quantitative Assessment of Coronary Atherosclerosis by Coronary Computed Tomographic Angiography.
Review in Korean journal of radiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Accuracy of deep learning in the differential diagnosis of coronary artery stenosis: a systematic review and meta-analysis.BMC medical imaging · 2024Pooled it
- Semi-Automated Plaque Assessment in Cardiac CT: Prognostic Value in Long-Term Follow-Up of Intermediate Stenosis.Diagnostics (Basel, Switzerland) · 2026Article
- MG-HGLNet: A Mixed-Grained Hierarchical Geometric-Semantic Learning Framework with Dynamic Prototypes for Coronary Artery Lesions Assessment.Bioengineering (Basel, Switzerland) · 2026Article
- Hemodynamic Study of Plaque Progression and Regression Based on Coronary CTA Imaging using Computational Fluid Dynamics Method: Preliminary Results.Journal of cardiovascular translational research · 2026Article
- Coronary CT Angiography-Derived Fractional Flow Reserve in Asia and the United States: 2025 Status Update.Korean journal of radiology · 2026Review
- When AI Meets Coronary CT: Overcoming Challenges and Enhancing Accuracy in CAD-RADS Reporting.Korean journal of radiology · 2025Article
- Research on Denoising Methods for Magnetocardiography Signals in a Non-Magnetic Shielding Environment.Sensors (Basel, Switzerland) · 2025Article
- Artificial intelligence in coronary CT angiography: transforming the diagnosis and risk stratification of atherosclerosis.The international journal of cardiovascular imaging · 2025Review
- Multidimensional excavation of the current status and trends of mechanobiology in cardiovascular homeostasis and remodeling within 20 years.Mechanobiology in medicine · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Coronary computed tomography angiography (CCTA) has emerged as a pivotal tool for diagnosing and risk-stratifying patients with suspected coronary artery disease (CAD). Recent advancements in image analysis and artificial intelligence (AI) techniques have enabled the comprehensive quantitative analysis of coronary atherosclerosis. Fully quantitative assessments of coronary stenosis and lumen attenuation have improved the accuracy of assessing stenosis severity and predicting hemodynamically significant lesions. In addition to stenosis evaluation, quantitative plaque analysis plays a crucial role in predicting and monitoring CAD progression. Studies have demonstrated that the quantitative assessment of plaque subtypes based on CT attenuation provides a nuanced understanding of plaque characteristics and their association with cardiovascular events. Quantitative analysis of serial CCTA scans offers a unique perspective on the impact of medical therapies on plaque modification. However, challenges such as time-intensive analyses and variability in software platforms still need to be addressed for broader clinical implementation. The paradigm of CCTA has shifted towards comprehensive quantitative plaque analysis facilitated by technological advancements. As these methods continue to evolve, their integration into routine clinical practice has the potential to enhance risk assessment and guide individualized patient management. This article reviews the evolving landscape of quantitative plaque analysis in CCTA and explores its applications and limitations.
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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.