Evidence map›Paper›PMID 38312594›Full record

ArticleHeliyon2024

The staging of nonalcoholic fatty liver disease fibrosis: A comparative study of MR elastography and the quantitative DCE-MRI exchange model.

Hao Ren, Dawei Yang, Hui Xu, Xiaofei Tong, Xinyan Zhao, Qianyi Wang, Yameng Sun, Xiaojuan Ou, Jidong Jia, Hong You and 2 more

Open access · goldAbstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.8field-weighted citation impact, top 30% of its field
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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. [Application and prospects of magnetic resonance imaging techniques in the diagnosis and evaluation of hepatocellular carcinoma].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2024
    Review
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

12 authors at 1 institution in 1 country.

Hao RenDepartment of Radiology, Beijing Friendship Hospital, Capital Medical University, Yongan Road 95, West District, Beijing, 100050, China.
Dawei YangDepartment of Radiology, Beijing Friendship Hospital, Capital Medical University, Yongan Road 95, West District, Beijing, 100050, China.
Hui XuDepartment of Radiology, Beijing Friendship Hospital, Capital Medical University, Yongan Road 95, West District, Beijing, 100050, China.
Xiaofei TongLiver Research Center, Beijing Friendship Hospital, Capital Medical University, No. 95 Yongan Road, West District, Beijing, 100050, China.
Xinyan ZhaoLiver Research Center, Beijing Friendship Hospital, Capital Medical University, No. 95 Yongan Road, West District, Beijing, 100050, China.
Qianyi WangLiver Research Center, Beijing Friendship Hospital, Capital Medical University, No. 95 Yongan Road, West District, Beijing, 100050, China.
Yameng SunLiver Research Center, Beijing Friendship Hospital, Capital Medical University, No. 95 Yongan Road, West District, Beijing, 100050, China.
Xiaojuan OuLiver Research Center, Beijing Friendship Hospital, Capital Medical University, No. 95 Yongan Road, West District, Beijing, 100050, China.
Jidong JiaLiver Research Center, Beijing Friendship Hospital, Capital Medical University, No. 95 Yongan Road, West District, Beijing, 100050, China.
Hong YouLiver Research Center, Beijing Friendship Hospital, Capital Medical University, No. 95 Yongan Road, West District, Beijing, 100050, China.
Zhenchang WangDepartment of Radiology, Beijing Friendship Hospital, Capital Medical University, Yongan Road 95, West District, Beijing, 100050, China.
Zhenghan YangDepartment of Radiology, Beijing Friendship Hospital, Capital Medical University, Yongan Road 95, West District, Beijing, 100050, China.
Capital Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: To evaluate the efficacy and image processing time of the dynamic contrast-enhanced MRI (DCE-MRI) exchange model in liver fibrosis staging and compare it to the efficacy of magnetic resonance elastography (MRE). Methods: The subjects were 45 patients with nonalcoholic fatty liver disease (NAFLD) who underwent MRE and DCE-MRI in our hospital. Liver biopsy results were available for all patients. Spearman rank correlation coefficients were used to compare the correlations among MRE, DCE-MRI and liver fibrosis parameters. Quantitative DCE-MRI parameters, MRE-derived liver stiffness measurement (LSM), and the results of a combined DCE-MRI + MRE logistic regression model were compared in terms of the area under the receiver operating characteristic curve (AUC). We also compared the scanning and postprocessing times of the MRE and DCE-MRI techniques. Results: The correlation coefficients between the following parameters of interest and liver fibrosis were as follows: capillary permeability-surface area product (PS; DCE-MRI parameter), -0.761; portal blood flow (Fp; DCE-MRI parameter), -0.754; MRE-LSM, 0.835. Some DCE-MRI parameters (PS, Fp) had slightly greater AUC values than MRE-LSM for diagnosing the presence or absence of liver fibrosis, and the combined model had the highest AUC value for all stages except F4, but there was no significant difference in the diagnostic efficacy of the DCE-MRI, MRE, and combined models for any stage of fibrosis. The average scanning times for MRE and DCE-MRI were 17 s and 330 s, respectively, and the average postprocessing times were 45.5 s and 342.7 s, respectively. Conclusions: In the absence of MRE equipment, DCE-MRI represents an alternative technique. However, MRE is a quicker and simpler method for assessing fibrosis than DCE-MRI in the clinic.

Indexed as

DCE-MRILiver fibrosisMRENAFLD

Identifiers

PMID38312594
PMCPMC10835329
OpenAlexW4390988110

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.