Evidence map›Paper›PMID 38813029›Full record

ArticleTurkish journal of medical sciences2023

Which sequence should be used in the thorax magnetic resonance imaging of COVID-19: a comparative study.

Ayşe Şule Ateş, Burak Yağdiran, Onur Taydaş, Ömer Faruk Ateş

Abstract readComparative Study
In one paragraph

Article in Turkish journal of medical sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from 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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Ayşe Şule AteşDepartment of Chest Diseases, Faculty of Medicine, Sakarya University, Sakarya, Turkiye.ORCID https://orcid.org/0000-0002-8612-6899
Burak YağdiranDepartment of Radiology, Faculty of Medicine, Başkent University, Ankara, Turkiye.ORCID https://orcid.org/0000-0003-0825-581X
Onur TaydaşDepartment of Radiology, Faculty of Medicine, Sakarya University, Sakarya, Turkiye.ORCID https://orcid.org/0000-0002-9881-7240
Ömer Faruk AteşDepartment of Chest Diseases, Faculty of Medicine, Sakarya University, Sakarya, Turkiye.ORCID https://orcid.org/0000-0002-0281-1128

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and aim: To evaluate and compare magnetic resonance imaging (MRI) sequences that could potentially be used in the diagnosis of coronavirus disease 2019 (COVID-19). Materials and methods: Included in the study were 42 patient who underwent thorax computed tomography (CT) for COVID-19 pneumonia and thorax MRI for any reason within 24 h after CT. The T2-weighted fast spin echo periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) (T2W-FSE-P), fast imaging employing steady-state acquisition, T2 fat-saturated FSE, axial T1 liver acquisition with volume acceleration (LAVA) and single-shot FSE images were compared in terms of their ability to show COVID-19 findings. Results: The mean age of the patients was 47.2 ± 24 years. Of the patients, 22 were male (52.4%) and 20 (47.6%) were female. The interobserver intraclass coefficient (ICC) for the image quality score was the highest in the T2W-FSE-P sequence and lowest in the T1 LAVA sequence. All of the lesion-based evaluations of the interobserver agreement were statistically significant, with the kappa value varying between 0.798 and 0.998. Conclusion: All 5 sequences evaluated in the study were successful in showing the parenchymal findings of COVID-19. Since the T2W-FSE-P sequence had the best scores in both interobserver agreement and ICC for the image quality score, it was considered that it can be included in thorax MRI examinations to assist the diagnosis of COVID-19.

Indexed as

COVID-19Magnetic Resonance ImagingSARS-CoV-2AdultAgedFemaleHumansLungMaleMiddle AgedThoraxTomography, X-Ray ComputedCOVID-19interobserver agreementinterobserver intraclass coefficientsmagnetic resonance imagingsequence

Identifiers

PMID38813029
PMCPMC10763759

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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.