ArticleThe international journal of cardiovascular imaging2010
Coronary plaque imaging with 256-slice multidetector computed tomography: interobserver variability of volumetric lesion parameters with semiautomatic plaque analysis software.
Article in The international journal of cardiovascular imaging, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 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
15 citing papers in PubMed, 33 citations in OpenAlex.
- Quantitative assessment of coronary peri-vascular fat attenuation index using dual-layer spectral CT for differentiating high-risk plaques in coronary artery disease.BMC medical imaging · 2026Article
- Characterization of Atherosclerotic Plaque in Coronary CT Angiography and Some Related Factors in Patients with Coronary Artery Disease Referred to Farshchian Heart Hospital in Hamadan in 2023 :.Galen medical journal · 2025Article
- Machine Learning for Evaluating Vulnerable Plaque on Coronary Computed Tomography Using Spectral Imaging.Circulation reports · 2024Article
- Comparison of Two Contemporary Quantitative Atherosclerotic Plaque Assessment Tools for Coronary Computed Tomography Angiography: Single-Center Analysis and Multi-Center Patient Cohort Validation.Diagnostics (Basel, Switzerland) · 2024Article
- Coronary plaque characteristics and epicardial fat tissue in long term survivors of type 1 diabetes identified by coronary computed tomography angiography.Cardiovascular diabetology · 2019Article
- Effects of long-term statin-treatment on coronary atherosclerosis in patients with inflammatory joint diseases.PloS one · 2019Article
- Associations between coronary and carotid artery atherosclerosis in patients with inflammatory joint diseases.RMD open · 2017Article
- Three-dimensional reconstruction of coronary arteries and plaque morphology using CT angiography--comparison and registration with IVUS.BMC medical imaging · 2016Article
- Comprehensive plaque assessment by coronary CT angiography.Nature reviews. Cardiology · 2014Review
- Role of computed tomography for diagnosis and risk stratification of patients with suspected or known coronary artery disease.Arteriosclerosis, thrombosis, and vascular biology · 2014Review
- On mixed reality environments for minimally invasive therapy guidance: systems architecture, successes and challenges in their implementation from laboratory to clinic.Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society · 2013Article
- Automated versus manual segmentation of atherosclerotic carotid plaque volume and components in CTA: associations with cardiovascular risk factors.The international journal of cardiovascular imaging · 2012Article
- Prognostic value of non-invasive coronary computed tomography angiography: where are we now?The international journal of cardiovascular imaging · 2011Article
- Cardiovascular imaging 2010 in the International Journal of Cardiovascular Imaging.The international journal of cardiovascular imaging · 2011Review
- Reproducibility in the assessment of noncalcified coronary plaque with 256-slice multi-detector CT and automated plaque analysis software.The international journal of cardiovascular imaging · 2010Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The purpose of this study was to evaluate the potential clinical value of coronary plaque imaging with a new generation CT scanner and the interobserver variability of coronary plaque assessment with a new semiautomatic plaque analysis application. Thirty-five isolated plaques of the left anterior descending coronary artery from 35 patients were evaluated with a new semiautomatic plaque analysis application. All patients were scanned with a 256-slice MDCT scanner (Brilliance iCT, Philips Healthcare, Cleveland OH, USA). Two independent observers evaluated lesion volume, maximum plaque burden, lesion CT number mean and standard deviation, and relative lesion composition. We found 10 noncalcified, 16 mixed, and 9 calcified lesions in our study cohort. Relative interobserver bias and variability for lesion volume were -37%, -13%, -49%, -44% and 28%, 16%, 37%, and 90% for all, noncalcified, mixed, and calcified lesions, respectively. Absolute interobserver bias and variability for relative lesion composition were 1.2%, 0.5%, 1.5%, 1.3% and 3.3%, 4.5%, 7.0%, and 4.4% for all, noncalcified, mixed, and calcified lesions, respectively. While mixed and calcified lesions demonstrated a high degree of lesion volume interobserver variability, noncalcified lesions had a lower degree of lesion volume interobserver variability. In addition, relative noncalcified lesion composition had a very low interobserver variability. Therefore, there may a role for MDCT in serial noncalcified plaque assessment with semiautomatic analysis software.
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.