ReviewThe international journal of cardiovascular imaging2020
Letter to the editor: is it time for imaging to level with pathology?
Review in The international journal of cardiovascular imaging, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed.
- Recent Clinical Updates of Hypertrophic Cardiomyopathy and Future Therapeutic Strategies.Reviews in cardiovascular medicine · 2025Review
- Investigating the Use of Generative Adversarial Networks-Based Deep Learning for Reducing Motion Artifacts in Cardiac Magnetic Resonance.Journal of multidisciplinary healthcare · 2025Article
- Interventricular septum involvement is related to right ventricular dysfunction in anterior STEMI patients without right ventricular infarction: a cardiovascular magnetic resonance study.The international journal of cardiovascular imaging · 2024Article
- Early detection of anthracycline-induced cardiotoxicity using [European journal of nuclear medicine and molecular imaging · 2024Article
- Granzyme B PET imaging inflammation and remodeling in myocardial infarction.European journal of nuclear medicine and molecular imaging · 2024Article
- Discrimination models with radiomics features derived from cardiovascular magnetic resonance images for distinguishing hypertensive heart disease from hypertrophic cardiomyopathy.Cardiovascular diagnosis and therapy · 2024Article
- Radiomics from Cardiovascular MR Cine Images for Identifying Patients with Hypertrophic Cardiomyopathy at High Risk for Heart Failure.Radiology. Cardiothoracic imaging · 2024Article
- Impact of systemic lupus erythematosus on cardiovascular morphologic and functional phenotypes: a Mendelian randomization analysis.Frontiers in cardiovascular medicine · 2024Article
- Association between late gadolinium enhancement and outcome in dilated cardiomyopathy: A meta-analysis.World journal of radiology · 2023Article
- Multiparametric cardiac magnetic resonance reveals persistent myocardial inflammation in patients with exertional heat illness.European radiology · 2023Article
- SARC Gene Mutation Is Associated With Myocardial Fibrosis Measured by Histopathology and Cardiac Magnetic Resonance in Patients With Hypertrophic Cardiomyopathy.Journal of the American Heart Association · 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
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
CMR provides pathology-like insights of myocardial abnormality, such as hyperemia, edema, necrosis and fibrosis, which is in-vivo, non-invasive and real-time. Hence, it is most likely to become one alternative tool for mimicking pathology, so-called pathologicalized imaging due to its extraordinary tissue characteristics. This article aims to call for a wider clinical application of CMR with more attention on its tissue characterization value.
Indexed as
Identifiers
32677022What 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.