ReviewChest2021
The Clinical Use of Lung MRI in Cystic Fibrosis: What, Now, How?
Review in Chest, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.
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
25 citing papers in PubMed, 1 synthesis or guideline pooled it, 58 citations in OpenAlex.
- Non-contrast enhanced functional lung MRI in children: systematic review.Frontiers in pediatrics · 2025Pooled it
- Editorial for "RadiolGAN: Multicenter Feasibility Study of Synthetic CT From 3D Ultra-Short Echo Time MRI for Enhanced Pulmonary Radiologic Sign Visualization".Journal of magnetic resonance imaging : JMRI · 2026Article
- Comparison of Retrospective Motion Compensation Techniques for Pulmonary Dynamic Ultrashort Time to Echo MRI in Suspected Idiopathic Pulmonary Fibrosis.Journal of magnetic resonance imaging : JMRI · 2026Article
- Automated Ultrashort Echo Time (UTE) MRI Low Signal Volume Analysis in Stable Pediatric Cystic Fibrosis and After Elexacaftor/Tezacaftor/Ivacaftor Therapy.Journal of magnetic resonance imaging : JMRI · 2026Article
- Self-Supervised Joint Reconstruction and Denoising of T2-Weighted PROPELLER MRI of the Lung at 0.55T.Magnetic resonance in medicine · 2026Article
- 3D Automated Segmentation of Bronchial Abnormalities on Ultrashort Echo Time MRI: A Quantitative MR Outcome in Cystic Fibrosis.Journal of magnetic resonance imaging : JMRI · 2026Article
- Evaluating Stack-of-Stars and FLORET 3D Ultrashort Echo Time MRI to Assess Structural Pathology in Cystic Fibrosis Lung Disease.Academic radiology · 2026Article
- Magnetic Resonance Imaging in the Clinical Evaluation of Lung Disorders: Current Status and Future Prospects.Journal of magnetic resonance imaging : JMRI · 2025Review
- Evolution and Prognostic Variables of Cystic Fibrosis in Children and Young Adults: A Narrative Review.Diagnostics (Basel, Switzerland) · 2025Review
- Comparison of 3D UTE free-breathing lung MRI with hyperpolarizedMagnetic resonance in medicine · 2025Article
- Breaking new ground in COPD imaging: 3D-PREFUL MRI versus traditional techniques.European radiology · 2025Article
- Application of low-dose FDG-PET/MRI for quantification of lung changes in pediatric patients with cystic fibrosis: a new inflammatory index.Quantitative imaging in medicine and surgery · 2025Article
- Thoracic magnetic resonance imaging in non-tuberculous mycobacterial pulmonary disease: Characteristics and potential implementation.PloS one · 2025Article
- Ultrashort Echo Time and Zero Echo Time MRI and Their Applications at High Magnetic Fields: A Literature Survey.Investigative magnetic resonance imaging · 2024Article
- Primary immunodeficiency diseases of adults: a review of pulmonary complication imaging findings.European radiology · 2024Review
- Article
- Acquiring Hyperpolarized 129Xe Magnetic Resonance Images of Lung Ventilation.Journal of visualized experiments : JoVE · 2023Article
- Radiological Imaging in Chest Diseases: Moving Away from Conventional Modes.Indian journal of pediatrics · 2023Review
- Chest magnetic resonance imaging in cystic fibrosis: technique and clinical benefits.Pediatric radiology · 2023Review
- Roadmap for an imaging and modelling paediatric study in rural NZ.Frontiers in physiology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 2 countries.
Funding
Abstract
To assess airway and lung parenchymal damage noninvasively in cystic fibrosis (CF), chest MRI has been historically out of the scope of routine clinical imaging because of technical difficulties such as low proton density and respiratory and cardiac motion. However, technological breakthroughs have emerged that dramatically improve lung MRI quality (including signal-to-noise ratio, resolution, speed, and contrast). At the same time, novel treatments have changed the landscape of CF clinical care. In this contemporary context, there is now consensus that lung MRI can be used clinically to assess CF in a radiation-free manner and to enable quantification of lung disease severity. MRI can now achieve three-dimensional, high-resolution morphologic imaging, and beyond this morphologic information, MRI may offer the ability to sensitively differentiate active inflammation vs scarring tissue. MRI could also characterize various forms of inflammation for early guidance of treatment. Moreover, functional information from MRI can be used to assess regional, small-airway disease with sensitivity to detect small changes even in patients with mild CF. Finally, automated quantification methods have emerged to support conventional visual analyses for more objective and reproducible assessment of disease severity. This article aims to review the most recent developments of lung MRI, with a focus on practical application and clinical value in CF, and the perspectives on how these modern techniques may converge and impact patient care soon.
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.