Evidence map›Paper›PMID 42798324›Full record

SynthesisFrontiers in oncology2026

MRI-based radiomics for noninvasive prediction of GPC3 expression in hepatocellular carcinoma: a systematic review and meta-analysis.

Rui Gao, Xu Li

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in oncology, 2026. 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.

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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

2 authors.

Rui GaoPingliang Hospital of Traditional Chinese Medicine (Integrated Traditional Chinese and Western Medicine Hospital), Pingliang, Gansu, China.
Xu LiGansu Medical College Affiliated Hospital, Pingliang, Gansu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Hepatocellular carcinoma (HCC) is a leading cause of cancer death, and glypican-3 (GPC3) is a key diagnostic and therapeutic target currently assessed invasively. However, the overall diagnostic accuracy, between-study variability, and potential clinical relevance of Magnetic resonance imaging (MRI)-based radiomics models for predicting GPC3 expression have not been systematically quantified. Aim: Here, we systematically review and meta-analyze MRI-based radiomics models for noninvasive prediction of GPC3 expression in HCC. Methods: Studies developing or validating MRI-based radiomics models against histopathologic GPC3 expression were identified through database searches, and data on diagnostic accuracy, radiomics workflows, and study design were extracted for a bivariate random-effects meta-analysis and quality assessment using the adapted Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool and the METhodological RadiomICs Score (METRICS) tool. Results: Of 63 records, seven retrospective studies comprising 1,209 patients met the inclusion criteria for the systematic review, of which five studies contributing eight model estimates were included in the quantitative synthesis. The pooled sensitivity was 0.81 (95% CI: 0.68-0.89), the pooled specificity was 0.87 (95% CI: 0.79-0.92), and the summary receiver operating characteristic curve yielded an area under the curve (AUC) of 0.91 (95% CI: 0.88-0.93). Sensitivity showed substantial heterogeneity (I² = 87.4%), whereas no heterogeneity was observed for specificity (I² = 0%). METRICS scores ranged from 56.1% to 92.2%. Conclusions: This systematic review and meta-analysis demonstrate that MRI-based radiomics provides a previously inaccessible, noninvasive window on GPC3 expression in HCC. The synthesis establishes a benchmark evidence base that opens the door to standardized radiomics pipelines, radiogenomic-guided trials, and imaging biomarkers to select patients for GPC3-targeted therapies.

Indexed as

glypican-3 expressionhepatocellular carcinomaMRI-based radiomicsnoninvasive imaging biomarkersystematic review and meta-analysis

Identifiers

PMID42798324
PMCPMC13612196

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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.