Trial reportEuropean radiology2018
Late iodine enhancement computed tomography with image subtraction for assessment of myocardial infarction.
Trial report in European radiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06029400 (CT-based Myocardial Characterization), which is not on this map. Cited by 9 papers.
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.
CT-based Myocardial Characterization
Who cites it
9 citing papers in PubMed, 16 citations in OpenAlex.
- Coronary artery imaging in Kawasaki disease: recent updates in imaging techniques and clinical indications.The international journal of cardiovascular imaging · 2026Review
- Use of Electron Density Maps and Fused Images in Dual-Energy Cardiac Computed Tomography to Facilitate Detection of Late Iodine Enhancement.Circulation reports · 2025Article
- State of the art of CT myocardial perfusion.La Radiologia medica · 2025Review
- Review
- Imaging options for defining anomalous origin of the coronary artery from the pulmonary artery.Quantitative imaging in medicine and surgery · 2023Review
- [Beyond Coronary CT Angiography: CT Fractional Flow Reserve and Perfusion].Taehan Yongsang Uihakhoe chi · 2022Review
- Computed tomographic evaluation of myocardial ischemia.Japanese journal of radiology · 2020Review
- Late iodine enhancement cardiac computed tomography for detection of myocardial scars: impact of experience in the clinical practice.La Radiologia medica · 2020Observational
- Comparison of the different imaging time points in delayed phase cardiac CT for myocardial scar assessment and extracellular volume fraction estimation in patients with old myocardial infarction.The international journal of cardiovascular imaging · 2019Article
Corrections and comments
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo evaluate the feasibility of image subtraction in late iodine enhancement CT (LIE-CT) for assessment of myocardial infarction (MI).
methodsA comprehensive cardiac CT protocol and late gadolinium enhancement MRI (LGE-MRI) was used to assess coronary artery disease in 27 patients. LIE-CT was performed after stress CT perfusion (CTP) and CT angiography. Subtraction LIE-CT was created by subtracting the mask volume of the left ventricle (LV) cavity from the original LIE-CT using CTP dataset. The %MI volume was quantified as the ratio of LIE to entire LV volume, and transmural extent (TME) of LIE was classified as 0%, 1-24%, 25-49%, 50-74% or 75-100%. These results were compared with LGE-MRI using the Spearman rank test, Bland-Altman method and chi-square test.
resultsOne hundred twenty-five (29%) of 432 segments were positive on LGE-MRI. Correlation coefficients for original and subtraction LIE-CT to LGE-MRI were 0.79 and 0.85 for %MI volume. Concordances of the 5-point grading scale between original and subtraction LIE-CT with LGE-MRI were 75% and 84% for TME; concordance was significantly improved using the subtraction technique (p <0.05).
conclusionSubtraction LIE-CT allowed more accurate assessment of MI extent than the original LIE-CT. KEY POINTS: • Subtraction LIE-CT allows for accurate assessment of the extent of myocardial infarction. • Subtraction LIE-CT shows a close correlation with LGE-MRI in %MI volume. • Subtraction LIE-CT has significantly higher concordance with TME assessment than original LIE-CT.
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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.