ArticleBioengineering (Basel, Switzerland)2023
Pericoronary Adipose Tissue Radiomics from Coronary Computed Tomography Angiography Identifies Vulnerable Plaques.
Article in Bioengineering (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.
- The Machine Learning Models in Major Cardiovascular Adverse Events Prediction Based on Coronary Computed Tomography Angiography: Systematic Review.Journal of medical Internet research · 2025Pooled it
- Hybrid deep learning time-to-event modeling of major adverse cardiovascular events using coronary artery calcium score scans.European journal of radiology artificial intelligence · 2026Article
- Pericoronary Radiomics Signature for Non-Culprit Lesion Progression and Revascularization Decision in NSTE-ACS.Diagnostics (Basel, Switzerland) · 2026Article
- Identification of NFE2L2 as a key biomarker associated with pyroptosis in gliomas through bioinformatics and experiments.Scientific reports · 2026Article
- SGLT2 Inhibitors After Myocardial Infarction: Evidence, Mechanisms and Gaps in Knowledge.Journal of clinical medicine · 2026Review
- A new insight on imaging characteristics of pericoronary adipose tissue for cardiovascular risk.Cardiovascular ultrasound · 2026Review
- Computational Analysis of Intravascular OCT Images for Future Clinical Support: A Comprehensive Review.IEEE reviews in biomedical engineering · 2026Review
- Epicardial Adipose Tissue: A Multimodal Imaging Diagnostic Perspective.Medicina (Kaunas, Lithuania) · 2025Review
- A Scoping Review of Machine-Learning Derived Radiomic Analysis of CT and PET Imaging to Investigate Atherosclerotic Cardiovascular Disease.Tomography (Ann Arbor, Mich.) · 2024Article
- Plaque Characteristics Derived from Intravascular Optical Coherence Tomography That Predict Cardiovascular Death.Bioengineering (Basel, Switzerland) · 2024Article
- Radiomics analysis of lesion-specific pericoronary adipose tissue to predict major adverse cardiovascular events in coronary artery disease.BMC medical imaging · 2024Article
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
Pericoronary adipose tissue (PCAT) features on Computed Tomography (CT) have been shown to reflect local inflammation and increased cardiovascular risk. Our goal was to determine whether PCAT radiomics extracted from coronary CT angiography (CCTA) images are associated with intravascular optical coherence tomography (IVOCT)-identified vulnerable-plaque characteristics (e.g., microchannels (MC) and thin-cap fibroatheroma (TCFA)). The CCTA and IVOCT images of 30 lesions from 25 patients were registered. The vessels with vulnerable plaques were identified from the registered IVOCT images. The PCAT-radiomics features were extracted from the CCTA images for the lesion region of interest (PCAT-LOI) and the entire vessel (PCAT-Vessel). We extracted 1356 radiomic features, including intensity (first-order), shape, and texture features. The features were reduced using standard approaches (e.g., high feature correlation). Using stratified three-fold cross-validation with 1000 repeats, we determined the ability of PCAT-radiomics features from CCTA to predict IVOCT vulnerable-plaque characteristics. In the identification of TCFA lesions, the PCAT-LOI and PCAT-Vessel radiomics models performed comparably (Area Under the Curve (AUC) ± standard deviation 0.78 ± 0.13, 0.77 ± 0.14). For the identification of MC lesions, the PCAT-Vessel radiomics model (0.89 ± 0.09) was moderately better associated than the PCAT-LOI model (0.83 ± 0.12). In addition, both the PCAT-LOI and the PCAT-Vessel radiomics model identified coronary vessels thought to be highly vulnerable to a similar standard (i.e., both TCFA and MC; 0.88 ± 0.10, 0.91 ± 0.09). The most favorable radiomic features tended to be those describing the texture and size of the PCAT. The application of PCAT radiomics can identify coronary vessels with TCFA or MC, consistent with IVOCT. Furthermore, the use of CCTA radiomics may improve risk stratification by noninvasively detecting vulnerable-plaque characteristics that are only visible with IVOCT.
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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 Socratic graph.