ReviewCardiovascular diagnosis and therapy2017
The role of advanced reconstruction algorithms in cardiac CT.
Review in Cardiovascular diagnosis and therapy, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 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
18 citing papers in PubMed.
- Coronary Artery Anomalies and Anatomical Variants: Cross-Sectional Diagnostic Imaging and Clinical Background.Journal of imaging · 2026Review
- Coronary Computed Tomography Angiography for the Diagnosis and Revascularization Guidance of Coronary Bifurcation Lesions: A Contemporary Review.Journal of clinical medicine · 2026Review
- Reliability of Immersive Virtual Reality for Pre-Procedural Planning for TAVI: A CT-Based Validation.Journal of cardiovascular development and disease · 2025Article
- High-resolution deep learning reconstruction for coronary CTA: compared efficacy of stenosis evaluation with other methods at in vitro and in vivo studies.European radiology · 2025Article
- Deep learning image reconstruction and adaptive statistical iterative reconstruction on coronary artery calcium scoring in high risk population for coronary heart disease.BMC medical informatics and decision making · 2025Article
- Clinical Advances in Cardiovascular Computed Tomography: From Present Applications to Promising Developments.Current cardiology reports · 2024Review
- Photon-Counting Computed Tomography Angiography of Carotid Arteries: A Topical Narrative Review with Case Examples.Diagnostics (Basel, Switzerland) · 2024Review
- Stent appearance in a novel silicon-based photon-counting CT prototype: ex vivo phantom study in head-to-head comparison with conventional energy-integrating CT.European radiology experimental · 2023Article
- Low-dose ultra-high-pitch computed tomography coronary angiography: identifying the optimum combination of iteration strength and radiation dose reduction strategies to achieve true submillisievert scansDiagnostic and interventional radiology (Ankara, Turkey) · 2023Article
- Improvement in Image Quality and Visibility of Coronary Arteries, Stents, and Valve Structures on CT Angiography by Deep Learning Reconstruction.Korean journal of radiology · 2022Article
- Influence of deep learning image reconstruction and adaptive statistical iterative reconstruction-V on coronary artery calcium quantification.Annals of translational medicine · 2021Article
- Coronary Computer Tomography Angiography in 2021-Acquisition Protocols, Tips and Tricks and Heading beyond the Possible.Diagnostics (Basel, Switzerland) · 2021Review
- Extraction of Coronary Atherosclerotic Plaques From Computed Tomography Imaging: A Review of Recent Methods.Frontiers in cardiovascular medicine · 2021Review
- Technical development in cardiac CT: current standards and future improvements-a narrative review.Cardiovascular diagnosis and therapy · 2020Review
- Physiology and coronary artery disease: emerging insights from computed tomography imaging based computational modeling.The international journal of cardiovascular imaging · 2020Review
- Contrast-to-Noise Ratio Optimization in Coronary Computed Tomography Angiography: Validation in a Swine Model.Academic radiology · 2019Article
- Coronary computed tomography angiography using model-based iterative reconstruction algorithms in the detection of significant coronary stenosis: how the plaque type influences the diagnostic performance.Polish journal of radiology · 2019Article
- Advances in cardiac CT.Cardiovascular diagnosis and therapy · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Non-linear iterative reconstruction (IR) algorithms have been increasingly incorporated into clinical cardiac CT protocols at institutions around the world. Multiple IR algorithms are available commercially from various vendors. IR algorithms decrease image noise and are primarily used to enable lower radiation dose protocols. IR can also be used to improve image quality for imaging of obese patients, coronary atherosclerotic plaques, coronary stents, and myocardial perfusion. In this article, we will review the various applications of IR algorithms in cardiac imaging and evaluate how they have changed practice.
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.