Evidence map›Paper›PMID 40229712›Full record

ArticleBMC cancer2025

Multiparametric MRI-based radiomics and clinical nomogram predicts the recurrence of hepatocellular carcinoma after postoperative adjuvant transarterial chemoembolization.

Xinyu Guo, Jingjing Song, Lingyi Zhu, Shuang Liu, Chaoming Huang, Lingling Zhou, Weiyue Chen, Guihan Lin, Zhongwei Zhao, Jianfei Tu and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC cancer, 2025. 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
  2. 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.

Xinyu Guo *Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Zhejiang Engineering Research Center of Interventional Medicine Engineering and Biotechnology, Zhejiang Key Laboratory of Imaging and Interventional Medicine, Lishui Hospital of Zhejiang University, Lishui, 323000, China.
Jingjing Song *Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Zhejiang Engineering Research Center of Interventional Medicine Engineering and Biotechnology, Zhejiang Key Laboratory of Imaging and Interventional Medicine, Lishui Hospital of Zhejiang University, Lishui, 323000, China.
Lingyi ZhuSecond Clinical Medical School, Zhejiang Chinese Medicine University, Hangzhou, 310003, Zhejiang, China.
Shuang LiuKey Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Zhejiang Engineering Research Center of Interventional Medicine Engineering and Biotechnology, Zhejiang Key Laboratory of Imaging and Interventional Medicine, Lishui Hospital of Zhejiang University, Lishui, 323000, China.
Chaoming HuangSecond Clinical Medical School, Zhejiang Chinese Medicine University, Hangzhou, 310003, Zhejiang, China.
Lingling ZhouKey Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Zhejiang Engineering Research Center of Interventional Medicine Engineering and Biotechnology, Zhejiang Key Laboratory of Imaging and Interventional Medicine, Lishui Hospital of Zhejiang University, Lishui, 323000, China.
Weiyue ChenKey Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Zhejiang Engineering Research Center of Interventional Medicine Engineering and Biotechnology, Zhejiang Key Laboratory of Imaging and Interventional Medicine, Lishui Hospital of Zhejiang University, Lishui, 323000, China.
Guihan LinKey Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Zhejiang Engineering Research Center of Interventional Medicine Engineering and Biotechnology, Zhejiang Key Laboratory of Imaging and Interventional Medicine, Lishui Hospital of Zhejiang University, Lishui, 323000, China.
Zhongwei ZhaoKey Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Zhejiang Engineering Research Center of Interventional Medicine Engineering and Biotechnology, Zhejiang Key Laboratory of Imaging and Interventional Medicine, Lishui Hospital of Zhejiang University, Lishui, 323000, China.
Jianfei TuKey Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Zhejiang Engineering Research Center of Interventional Medicine Engineering and Biotechnology, Zhejiang Key Laboratory of Imaging and Interventional Medicine, Lishui Hospital of Zhejiang University, Lishui, 323000, China.
Minjiang ChenKey Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Zhejiang Engineering Research Center of Interventional Medicine Engineering and Biotechnology, Zhejiang Key Laboratory of Imaging and Interventional Medicine, Lishui Hospital of Zhejiang University, Lishui, 323000, China.
Feng ChenDepartment of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, Zhejiang, China.
Liyun ZhengKey Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Zhejiang Engineering Research Center of Interventional Medicine Engineering and Biotechnology, Zhejiang Key Laboratory of Imaging and Interventional Medicine, Lishui Hospital of Zhejiang University, Lishui, 323000, China. liyunzheng1025@163.com.
Jiansong JiKey Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Zhejiang Engineering Research Center of Interventional Medicine Engineering and Biotechnology, Zhejiang Key Laboratory of Imaging and Interventional Medicine, Lishui Hospital of Zhejiang University, Lishui, 323000, China. jijiansong@zju.edu.cn.

Funding

Medical and Health Youth Innovation Project of Zhejiang Province 2023RC115
6 · The paper itself

Abstract

backgroundThis study was undertaken to develop and validate a radiomics model based on multiparametric magnetic resonance imaging (MRI) for predicting recurrence in patients with hepatocellular carcinoma (HCC) following postoperative adjuvant transarterial chemoembolization (PA-TACE).

methodsIn this retrospective study, 149 HCC patients (81 for training, 36 for internal validation, 32 for external validation) treated with PA-TACE were included in two medical centers. Multiparametric radiomics features were extracted from three MRI sequences. Least absolute shrinkage and selection operator (LASSO)-COX regression was utilized to select radiomics features. Optimal clinical characteristics selected by multivariate Cox analysis were integrated with Rad-score to develop a recurrence-free survival (RFS) prediction model. The model performance was evaluated by time-dependent receiver operating characteristic (ROC) curves, Harrell's concordance index (C-index), and calibration curve.

resultsFifteen optimal radiomic features were selected and the median Rad-score value was 0.434. Multivariate Cox analysis indicated that neutrophil-to-lymphocyte ratio (NLR) (hazard ratio (HR) = 1.49, 95% confidence interval (CI): 1.1-2.1, P = 0.022) and tumor size (HR = 1.28, 95% CI: 1.1-1.5, P = 0.001) were the independent predictors of RFS after PA-TACE. A combined model was established by integrating Rad-score, NLR, and tumor size in the training cohort (C-index 0.822; 95% CI 0.805-0.861), internal validation cohort (0.823; 95% CI 0.771-0.876) and external validation cohort (0.846; 95% CI 0.768-0.924). The calibration curve exhibited a satisfactory correspondence.

conclusionA multiparametric MRI-based radiomics model can predict RFS of HCC patients receiving PA-TACE and a nomogram can be served as an individualized tool for prognosis.

Indexed as

Carcinoma, HepatocellularChemoembolization, TherapeuticLiver NeoplasmsMultiparametric Magnetic Resonance ImagingNeoplasm Recurrence, LocalNomogramsAdultAgedFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedPrognosisRadiomicsRetrospective StudiesHepatocellular carcinomaNomogramPostoperative adjuvant transarterial chemoembolizationRadiomicsRecurrence

Identifiers

PMID40229712
PMCPMC11995621

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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.