Evidence map›Paper›PMID 41860367›Full record

ArticleRadiology. Imaging cancer2026

Clinical Utility of Deep Learning-based Multiple Arterial Phase MRI in Hepatocellular Carcinoma.

Kai Liu, Beixuan Zheng, Yunfei Zhang, Bin Wang, Jun Yang, Lu Wang, Mengsu Zeng, Ruofan Sheng

Abstract read
In one paragraph

Article in Radiology. Imaging cancer, 2026. 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
–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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Kai Liu *Department of Radiology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Xuhui District, Shanghai 200032, China.
Beixuan Zheng *Department of Radiology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Xuhui District, Shanghai 200032, China.
Yunfei ZhangDepartment of Radiology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Xuhui District, Shanghai 200032, China.
Bin WangDepartment of Radiology, Zhongshan Wusong Hospital, Shanghai, China.
Jun YangMR Business Unit, United Imaging Healthcare, Shanghai, China.
Lu WangMR Business Unit, United Imaging Healthcare, Shanghai, China.
Mengsu ZengDepartment of Radiology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Xuhui District, Shanghai 200032, China.ORCID 0000-0003-0030-9254
Ruofan ShengDepartment of Radiology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Xuhui District, Shanghai 200032, China.ORCID 0000-0003-4215-9450

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose To evaluate the clinical utility of deep learning-based ultrafast multiple arterial phase (AP) MRI for diagnosing hepatocellular carcinoma (HCC), compared with conventional single AP imaging, using both extracellular agents (ECAs) and hepatobiliary agents (HBAs). Materials and Methods This prospective study included participants with suspected HCC who underwent either ECA- or HBA-enhanced MRI between September 2024 and March 2025. Outcomes included late AP capture rate, image quality (overall quality, motion artifacts, noise, liver and lesion edge sharpness, and lesion conspicuity), diagnostic performance (lesion, arterial phase hyperenhancement [APHE], and HCC detection rates), and hepatic arterial visualization scoring. Wilcoxon rank sum, Pearson χ

Indexed as

Carcinoma, HepatocellularDeep LearningLiver NeoplasmsMagnetic Resonance ImagingAgedContrast MediaFemaleHumansMaleMiddle AgedProspective StudiesContrast MediaAbdomen/GILiverMR-Imaging

Identifiers

PMID41860367
PMCPMC13036681

What OpenQuestion holds

Textmetadata
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.