Evidence map›Paper›PMID 32491257›Full record

ArticleJournal of magnetic resonance imaging : JMRI2020

Clinical Potential of UTE-MRI for Assessing COVID-19: Patient- and Lesion-Based Comparative Analysis.

Shuyi Yang, Yunfei Zhang, Jie Shen, Yongming Dai, Yun Ling, Hongzhou Lu, Rengyin Zhang, Xueting Ding, Huali Qi, Yuxin Shi and 2 more

Abstract readComparative Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of magnetic resonance imaging : JMRI, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
–field-weighted citation impact
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

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.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
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  5. Article
  6. Review
  7. COVID-19 pneumonia: lessons learned, challenges, and preparing for the future.Diagnostic and interventional radiology (Ankara, Turkey) · 2022
    Article
  8. Review
  9. Review
  10. Article
  11. Article
  12. Article
  13. Covid-19 imaging: A narrative review.Annals of medicine and surgery (2012) · 2021
    Review
  14. Article
  15. Review
  16. Review
  17. Imaging of COVID-19: CT, MRI, and PET.Seminars in nuclear medicine · 2021
    Review
  18. Review
  19. Review
  20. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Shuyi YangDepartment of Radiology, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China.ORCID 0000-0002-0898-0088
Yunfei ZhangCentral Research Institute, United Imaging Healthcare, Shanghai, China.
Jie ShenDepartment of Radiology, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China.
Yongming DaiCentral Research Institute, United Imaging Healthcare, Shanghai, China.
Yun LingDepartment of Infectious Disease, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China.
Hongzhou LuDepartment of Infectious Disease, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China.
Rengyin ZhangDepartment of Radiology, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China.
Xueting DingDepartment of Radiology, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China.
Huali QiDepartment of Radiology, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China.
Yuxin ShiDepartment of Radiology, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China.
Zhiyong ZhangDepartment of Radiology, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China.
Fei ShanDepartment of Radiology, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China.ORCID 0000-0001-7519-2172

Funding

Novel Coronavirus Special Research Foundation of the Shanghai Municipal Science and Technology Commission 20441900600Research FoundationShanghai Municipal Science and Technology Commission
6 · The paper itself

Abstract

backgroundChest computed tomography (CT) has shown tremendous clinical potential for screening, diagnosis, and surveillance of COVID-19. However, safety concerns are warranted due to repeated exposure of X-rays over a short period of time. Recent advances in MRI suggested that ultrashort echo time MRI (UTE-MRI) was valuable for pulmonary applications. PURPOSE: To evaluate the effectiveness of UTE-MRI for assessing COVID-19. STUDY TYPE: Prospective. POPULATION: In all, 23 patients with COVID-19 and with an average interval of 2.81 days between hospital admission and image examination. FIELD STRENGTH/SEQUENCE: 3T; Respiratory-gated three-dimensional radial UTE pulse sequence. ASSESSMENT: Image quality score. Patient- and lesion-based interobserver and intermethod agreement for identifying the representative image findings of COVID-19. STATISTICAL TESTS: Wilcoxon-rank sum test, Kendall's coefficient of concordance (Kendall's W), intraclass coefficients (ICCs), and weighted kappa statistics.

resultsThere was no significant difference between the image quality of CT and UTE-MRI (CT vs. UTE-MRI: 4.3 ± 0.4 vs. 4.0 ± 0.5, P = 0.09). Moreover, both patient- and lesion-based interobserver agreement of CT and UTE-MRI for evaluating the image signs of COVID-19 were determined as excellent (ICC: 0.939-1.000, P < 0.05; Kendall's W: 0.894-1.000, P < 0.05.). In addition, the intermethod agreement of two image modalities for assessing the representative findings of COVID-19 including affected lobes, total severity score, ground glass opacities (GGO), consolidation, GGO with consolidation, the number of crazy paving pattern, and linear opacities, as well as pseudocavity were all determined as substantial or excellent (kappa: 0.649-1.000, P < 0.05; ICC: 0.913-1.000, P < 0.05). DATA

conclusionPulmonary MRI with UTE is valuable for assessing the representative image findings of COVID-19 with a high concordance to CT. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY STAGE: 3 J. Magn. Reson. Imaging 2020;52:397-406.

Indexed as

Magnetic Resonance ImagingRadiography, ThoracicTomography, X-Ray ComputedAdolescentAdultBetacoronavirusClinical Laboratory TechniquesCoronavirus InfectionsCOVID-19COVID-19 TestingFemaleHumansImage Processing, Computer-AssistedImaging, Three-DimensionalMaleMiddle Agedcomputed tomographyCOVID-19imaging-based diagnosismagnetic resonance imagingultrashort echo time MRI

Identifiers

PMID32491257
PMCPMC7300684

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

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.