Evidence map›Paper›PMID 39267560›Full record

ReviewZhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology2024

[Research progress and prospects of the application of radiographic imaging in the precise diagnosis and treatment of hepatocellular carcinoma].

J Zhou, T W Chen, D J Guo

Abstract readReviewEnglish Abstract
In one paragraph

Review in Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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

3 authors.

J ZhouDepartment of Radiology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China.
T W ChenDepartment of Radiology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China.
D J GuoDepartment of Radiology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China.

Funding

Chongqing Science and Health Joint Key Project 2022ZDXM026National Natural Science Foundation of China 82271970
6 · The paper itself

Abstract

Hepatocellular carcinoma (HCC) is a highly heterogeneous kind of malignant tumor with a high recurrence rate and low five-year survival rate, which has become one of the major public health issues in China. Currently, HCC is the only solid tumor that can be solely diagnosed based on epidemiological history and typical imaging features without preoperative pathological confirmation. The paradigm for HCC imaging diagnosis has shifted in recent years from anatomy to function, from macroscopic to microscopic, and from diagnosis to prediction in the context of precision medicine, making it possible to study the microscopic processes such as HCC genes and their metabolic laws from the perspective of qualitative and quantitative imaging, thereby providing more accurate biological and imaging information for elucidating the occurrence, development, and clinical treatment decisions of HCC.This paper reviews the research progress of HCC imaging in recent years, demonstrating the rapid horizontal development and enormous potential of imaging in the vertical follow-up of HCC precision diagnosis and treatment. Simultaneously, it also puts forward the shortcomings of current HCC imaging research and looks forward to future development directions in order to be more accurately used in clinical decision support systems.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsHumansMagnetic Resonance ImagingTomography, X-Ray Computed

Identifiers

PMID39267560
PMCPMC12898882

What OpenQuestion holds

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Registered trials

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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.