ArticleJournal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology2021
Fluorine-18 fluorodeoxyglucose positron emission tomography-based textural features for prediction of event prone carotid atherosclerotic plaques.
Article in Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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
10 citing papers in PubMed, 22 citations in OpenAlex.
- Assessment of carotid atherosclerotic plaque vulnerability with multi-radiotracer PET/CT: a scoping review.European radiology · 2026Article
- A Machine Learning Model Based on Radiomic Features as a Tool to Identify Active Giant Cell Arteritis on [Diagnostics (Basel, Switzerland) · 2025Article
- A Scoping Review of Machine-Learning Derived Radiomic Analysis of CT and PET Imaging to Investigate Atherosclerotic Cardiovascular Disease.Tomography (Ann Arbor, Mich.) · 2024Article
- Molecular Imaging of Fibroblast Activation in Rabbit Atherosclerotic Plaques: a Preclinical PET/CT Study.Molecular imaging and biology · 2024Article
- Quality assessment of radiomics models in carotid plaque: a systematic review.Quantitative imaging in medicine and surgery · 2024Review
- 2022 Artificial intelligence primer for the nuclear cardiologist.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2023Review
- Gestational week-specific of uterine artery Doppler indices in predicting preeclampsia: a hospital-based retrospective cohort study.BMC pregnancy and childbirth · 2021Article
- Hiding beyond plain sight: Textural analysis of positron emission tomography to identify high-risk plaques in carotid atherosclerosis.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2021Article
- Serum Ceramides as Prognostic Biomarkers of Large Thrombus Burden in Patients with STEMI: A Micro-Computed Tomography Study.Journal of personalized medicine · 2021Article
- Role ofWorld journal of nuclear medicineReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 5 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTexture analysis has been increasingly used in the field of positron emission tomography (PET)/computed tomography (CT) imaging with Fluorine-18 fluorodeoxyglucose (18F-FDG), aiming at assessing tumor heterogeneity. The purpose of the present study is to examine the feasibility of performing texture analysis in carotid arteries, investigate the value of textural features as predictors of potential plaque vulnerability using as reference standards histological and immunohistochemical data and compare their performance with conventional uptake measurements.
methods67 different 18F-FDG PET-based textural features were extracted from carotid images of 21 patients with high-grade carotid stenosis undergoing endarterectomy. To identify the more reliable predictors, univariate logistic regression analysis was performed. The accuracy was satisfactory in case of an Area Under the Receiver Operating Characteristic (ROC) curve (AUC) ≥ 0.80.
resultsFirst measure of information correlation (AUC = 0.87, P < 0.001), large zone low gray level emphasis (AUC = 0.87, P < 0.001), and normalized run length non-uniformity (AUC = 0.84, P < 0.001) were the most optimal textural features for identifying characteristics of plaque vulnerability based on histological analysis. Addition of textural features to target-to-background ratio (TBR) (AUC = 0.74, P = 0.031) resulted in an AUC = 0.92 (P < 0.001), however, this did not reach statistical significance (P
conclusionTexture analysis can be applied in 18F-FDG PET carotid imaging providing valuable information for plaque characterization.
Indexed as
Identifiers
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.