Evidence map›Paper›PMID 40775800›Full record

Observational studyEuropean journal of medical research2025

Prediction models after hepatectomy for hepatocellular carcinoma-based ultrasonic radiomics: an observational study.

Dong Jiang, Jialun Ren, Yi Qian, Yijun Gu, Ru Wang, Hua Yu, Hui Dong, Dongyu Chen, Yan Chen, Haozheng Jiang and 1 more

Abstract readObservational Study
PubMed Full text at PMC Publisher
In one paragraph

Observational study in European journal of medical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

11 authors.

Dong Jiang *Department of Ultrasonography, Shanghai Eastern Hepatobiliary Surgery Hospital, The Third Affiliated Hospital of Naval Medical University, Shanghai, 200438, China.
Jialun Ren *Department of Ultrasonography, Shanghai Eastern Hepatobiliary Surgery Hospital, The Third Affiliated Hospital of Naval Medical University, Shanghai, 200438, China.
Yi Qian *Department of Ultrasonography, Shanghai Eastern Hepatobiliary Surgery Hospital, The Third Affiliated Hospital of Naval Medical University, Shanghai, 200438, China.
Yijun GuDepartment of Ultrasonography, Shanghai Eastern Hepatobiliary Surgery Hospital, The Third Affiliated Hospital of Naval Medical University, Shanghai, 200438, China.
Ru WangDepartment of Ultrasonography, Shanghai Eastern Hepatobiliary Surgery Hospital, The Third Affiliated Hospital of Naval Medical University, Shanghai, 200438, China.
Hua YuDepartment of Pathology, Shanghai Eastern Hepatobiliary Surgery Hospital, Shanghai, 200438, China.
Hui DongDepartment of Pathology, Shanghai Eastern Hepatobiliary Surgery Hospital, Shanghai, 200438, China.
Dongyu ChenDepartment of Ultrasonography, Shanghai Eastern Hepatobiliary Surgery Hospital, The Third Affiliated Hospital of Naval Medical University, Shanghai, 200438, China.
Yan ChenDepartment of Ultrasonography, Shanghai Eastern Hepatobiliary Surgery Hospital, The Third Affiliated Hospital of Naval Medical University, Shanghai, 200438, China.
Haozheng JiangDepartment of Anthropology, College of Arts and Sciences, Case Western Reserve University, Cleveland, OH, USA.
Yiran LiDepartment of Ultrasonography, Shanghai Eastern Hepatobiliary Surgery Hospital, The Third Affiliated Hospital of Naval Medical University, Shanghai, 200438, China. liyiranehsh@sina.com.

Funding

Eastern Hepatobiliary Surgery Hospital Youth Cultivation Project in Medical and Engineering Interdisciplinary Research 2022YGJC001the Eastern Hepatobiliary Surgery Hospital National Natural Science Foundation Youth Cultivation Project 2021GZR003
6 · The paper itself

Abstract

backgroundThis study aims to develop and validate predictive models for postoperative complications and early recurrence in hepatocellular carcinoma (HCC) patients.

methodsIn a 7:3 ratio, 633 post-hepatectomy HCC patients were modeled and validated. Using 1561 radiomic features from two-dimensional shear wave elastography (2D-SWE), predictive models for the Comprehensive Complication Index (CCI) and recurrence were constructed, refined by LASSO regression, and integrated with clinical and pathologic data. Model performance was assessed using calibration plots and AUCs.

resultsThe CCI model included Rad signature (P < 0.001), platelet count (P = 0.012), neutrophil levels (P = 0.032), Emax (P = 0.023), and differentiation status (P = 0.045), with AUCs of 0.896 for the modeling cohort and 0.832 for validation. The recurrence model included Rad signature (P < 0.001), arginase (P = 0.038), patient age (P = 0.001), adjacent tissue's Emean (P = 0.009), and blood flow (P = 0.03), with AUCs of 0.854 and 0.844 for modeling and validation cohorts, respectively. The Rad signature AUC of 0.884 surpassed the nomogram's AUC of 0.854 in the modeling set.

conclusionRadiomic-based CCI and recurrence models effectively predict complications and short-term recurrence in post-hepatectomy HCC patients, aiding in identifying high-risk individuals for timely intervention.

Indexed as

Carcinoma, HepatocellularHepatectomyLiver NeoplasmsNeoplasm Recurrence, LocalPostoperative ComplicationsAgedElasticity Imaging TechniquesFemaleHumansMaleMiddle AgedRadiomicsHepatocellular carcinomaLiver resectionUltrasound radiomics

Identifiers

PMID40775800
PMCPMC12333104

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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.