ArticleJournal of magnetic resonance imaging : JMRI2021
Reducing Contrast Agent Dose in Cardiovascular MR Angiography with Deep Learning.
Article in Journal of magnetic resonance imaging : JMRI, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
What it found
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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
19 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 citations in OpenAlex.
- Society for Cardiovascular Magnetic Resonance recommendations toward environmentally sustainable cardiovascular magnetic resonance.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2025Guideline
- Generation of contrast-enhanced cardiac MRI from contrast-free scans: a multi-center, multi-manufacturer study.European radiology · 2026Article
- The role of artificial intelligence in pediatric cardiovascular imaging: clinical applications and future directions in computed tomography and magnetic resonance imaging.Pediatric radiology · 2026Review
- Coronary Artery Anomalies and Anatomical Variants: Cross-Sectional Diagnostic Imaging and Clinical Background.Journal of imaging · 2026Review
- Artificial Intelligence in Pediatric Cardiology: Present Applications and Future Directions.Pediatric reports · 2026Review
- Factors Affecting the Quality of Non-contrast Coronary Magnetic Resonance Angiography Images: Challenges and Change.Reviews in cardiovascular medicine · 2025Review
- Accelerated intracranial time-of-flight MR angiography with image-based deep learning image enhancement reduces scan times and improves image quality at 3-T and 1.5-T.Neuroradiology · 2025Article
- AI for image quality and patient safety in CT and MRI.European radiology experimental · 2025Review
- Low-iodine-dose computed tomography coupled with an artificial intelligence-based contrast-boosting technique in children: a retrospective study on comparison with conventional-iodine-dose computed tomography.Pediatric radiology · 2024Article
- Deep Learning-Based High-Resolution Magnetic Resonance Angiography (MRA) Generation Model for 4D Time-Resolved Angiography with Interleaved Stochastic Trajectories (TWIST) MRA in Fast Stroke Imaging.Diagnostics (Basel, Switzerland) · 2024Article
- Time conditioning for arbitrary contrast phase generation in interventional computed tomography.Physics in medicine and biology · 2024Article
- Review of strategies to reduce the contamination of the water environment by gadolinium-based contrast agents.Insights into imaging · 2024Review
- A deep learning method for the automated assessment of paradoxical pulsation after myocardial infarction using multicenter cardiac MRI data.European radiology · 2023Article
- Multi-phase synthetic contrast enhancement in interventional computed tomography for guiding renal cryotherapy.International journal of computer assisted radiology and surgery · 2023Article
- Article
- Artificial Intelligence in Pediatric Cardiology: A Scoping Review.Journal of clinical medicine · 2022Article
- Magnetic resonance imaging contrast enhancement synthesis using cascade networks with local supervision.Medical physics · 2022Article
- Analysis of Cardiovascular Disease Angiography Process Based on Rough Set and Internet of Things.Journal of healthcare engineering · 2022Article
- ΔR1Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic ResonanceArticle
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 at 2 institutions in 1 country.
Funding
Abstract
backgroundContrast-enhanced magnetic resonance angiography (MRA) is used to assess various cardiovascular conditions. However, gadolinium-based contrast agents (GBCAs) carry a risk of dose-related adverse effects. PURPOSE: To develop a deep learning method to reduce GBCA dose by 80%. STUDY TYPE: Retrospective and prospective. POPULATION: A total of 1157 retrospective and 40 prospective congenital heart disease patients for training/validation and testing, respectively. FIELD STRENGTH/SEQUENCE: A 1.5 T, T1-weighted three-dimensional (3D) gradient echo. ASSESSMENT: A neural network was trained to enhance low-dose (LD) 3D MRA using retrospective synthetic data and tested with prospective LD data. Image quality for LD (LD-MRA), enhanced LD (ELD-MRA), and high-dose (HD-MRA) was assessed in terms of signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and a quantitative measure of edge sharpness and scored for perceptual sharpness and contrast on a 1-5 scale. Diagnostic confidence was assessed on a 1-3 scale. LD- and ELD-MRA were assessed against HD-MRA for sensitivity/specificity and agreement of vessel diameter measurements (aorta and pulmonary arteries). STATISTICAL TESTS: SNR, CNR, edge sharpness, and vessel diameters were compared between LD-, ELD-, and HD-MRA using one-way repeated measures analysis of variance with post-hoc t-tests. Perceptual quality and diagnostic confidence were compared using Friedman's test with post-hoc Wilcoxon signed-rank tests. Sensitivity/specificity was compared using McNemar's test. Agreement of vessel diameters was assessed using Bland-Altman analysis.
resultsSNR, CNR, edge sharpness, perceptual sharpness, and perceptual contrast were lower (P < 0.05) for LD-MRA compared to ELD-MRA and HD-MRA. SNR, CNR, edge sharpness, and perceptual contrast were comparable between ELD and HD-MRA, but perceptual sharpness was significantly lower. Sensitivity/specificity was 0.824/0.921 for LD-MRA and 0.882/0.960 for ELD-MRA. Diagnostic confidence was 2.72, 2.85, and 2.92 for LD, ELD, and HD-MRA, respectively (P DATA
conclusionDeep learning can improve contrast in LD cardiovascular MRA. LEVEL OF EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.
Indexed as
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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.