Evidence map›Paper›PMID 39145877›Full record

ArticleInsights into imaging2024

Dual-layer spectral-detector CT for detecting liver steatosis by using proton density fat fraction as reference.

Min Wang, Hongyu Chen, Yue Ma, Ruobing Bai, Sizhe Gao, Linlin Yang, Wenli Guo, Cong Zhang, Chengjun Kang, Yu Lan and 4 more

Abstract read
In one paragraph

Article in Insights into imaging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
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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

14 authors.

Min Wang *Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, P.R. China.
Hongyu Chen *Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, P.R. China.
Yue MaDepartment of Radiology, Shengjing Hospital of China Medical University, Shenyang, P.R. China.
Ruobing BaiDepartment of Radiology, Shengjing Hospital of China Medical University, Shenyang, P.R. China.
Sizhe GaoDepartment of Radiology, Shengjing Hospital of China Medical University, Shenyang, P.R. China.
Linlin YangDepartment of Radiology, Shengjing Hospital of China Medical University, Shenyang, P.R. China.
Wenli GuoDepartment of Radiology, Shengjing Hospital of China Medical University, Shenyang, P.R. China.
Cong ZhangDepartment of Radiology, Shengjing Hospital of China Medical University, Shenyang, P.R. China.
Chengjun KangDepartment of Radiology, Shengjing Hospital of China Medical University, Shenyang, P.R. China.
Yu LanDepartment of Radiology, Shengjing Hospital of China Medical University, Shenyang, P.R. China.
Yanqiu SunDepartment of Radiology, Qinghai Provincial People's Hospital, Qinghai, P.R. China.
Yonggao ZhangDepartment of Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, P.R. China.
Xigang XiaoDepartment of Radiology, The First Affiliated Hospital of Harbin Medical University, Harbin, P.R. China.
Yang HouDepartment of Radiology, Shengjing Hospital of China Medical University, Shenyang, P.R. China. houy2@sj-hospital.org.ORCID http://orcid.org/0000-0002-9184-5441

Funding

345 Talent Project in Shengjing Hospital of China Medical University 345 Talent ProjectInnovative Research Group Project of the National Natural Science Foundation of China 82071920Key Research and Development Program of Liaoning Province 2020JH2/10300037
6 · The paper itself

Abstract

objectivesTo evaluate the diagnostic accuracy of liver dual-layer spectral-detector CT (SDCT) derived parameters of liver parenchyma for grading steatosis with reference to magnetic resonance imaging-based proton density fat fraction (MRI-PDFF).

methodsAltogether, 320 consecutive subjects who underwent MRI-PDFF and liver SDCT examinations were recruited and prospectively enrolled from four Chinese hospital centers. Participants were classified into normal (n = 152), mild steatosis (n = 110), and moderate/severe(mod/sev) steatosis (n = 58) groups based on MRI-PDFF. SDCT liver parameters were evaluated using conventional polychromatic CT images (CT

resultsSDCT liver parameters demonstrated a strong correlation with PDFF, particularly Zeff (r

conclusionSDCT liver parameters, particularly Zeff, exhibit excellent diagnostic accuracy for grading steatosis. CRITICAL RELEVANCE STATEMENT: Dual-layer SDCT parameter, Zeff, as a more convenient and accurate imaging biomarker may serve as an alternative indicator for MRI-based proton density fat fraction, exploring the stage and prognosis of liver steatosis, and even metabolic risk assessment. KEY POINTS: Liver biopsy is the standard for grading liver steatosis, but is limited by its invasive nature. The diagnostic performance of liver steatosis using SDCT-Zeff outperforms conventional CT parameters. SDCT-Zeff accurately and noninvasively assessed the grade of liver steatosis.

Indexed as

Dual-layer spectral-detector CTLiver steatosisMRI proton density fat fraction

Identifiers

PMID39145877
PMCPMC11327236

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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.