Evidence map›Paper›PMID 40214697›Full record

ArticleAbdominal radiology (New York)2025

The nVR model: prediction of LI-RADS treatment response nonviable recurrence of hepatocellular carcinoma after primary transarterial chemoembolization.

Shuhang Zhang, Weilang Wang, Xiuming Zhang, Binyan Zhong, Feng Feng, Wu Cai, Binrong Li, Varsha Ajith Menon, Shuwei Zhou, Teng Zhang and 3 more

Registry-linked trialAbstract readMulticenter Study
PubMed Publisher
In one paragraph

Article in Abdominal radiology (New York), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03113955 (A Single-arm Trial of Transcatheter Arterial Chemoembolization With Tandem Microspheres in the Treatment of Localized Hepatocellular Carcinoma), which is not on this 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.

NCT03113955 nacompletednot on this map

A Single-arm Trial of Transcatheter Arterial Chemoembolization With Tandem Microspheres in the Treatment of Localized Hepatocellular Carcinoma

TypeinterventionalSponsorVarian Medical SystemsRan2017 to 2020Enrolled109ConditionsLocalized Hepatocellular CarcinomaArmsTandem Microsphere loaded with Epirubicin
3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
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

13 authors.

Shuhang ZhangDepartment of Radiology, Nurturing Center of Jiangsu Province for State Laboratory of AI Imaging & Interventional Radiology, Zhongda Hospital, Southeast University, Nanjing, China.ORCID 0009-0008-1459-2824
Weilang WangDepartment of Radiology, Nurturing Center of Jiangsu Province for State Laboratory of AI Imaging & Interventional Radiology, Zhongda Hospital, Southeast University, Nanjing, China.
Xiuming ZhangDepartment of Radiology, Jiangsu Cancer Hospital, Nanjing, China.
Binyan ZhongDepartment of Interventional Radiology, Zhejiang Cancer Hospital, Hangzhou, China.
Feng FengDepartment of Radiology, Nantong Tumor Hospital, Nantong, China.
Wu CaiDepartment of Radiology, Second Affiliated Hospital of Soochow University, Suzhou, China.
Binrong LiDepartment of Radiology, Nurturing Center of Jiangsu Province for State Laboratory of AI Imaging & Interventional Radiology, Zhongda Hospital, Southeast University, Nanjing, China.
Varsha Ajith MenonDepartment of Radiology, Nurturing Center of Jiangsu Province for State Laboratory of AI Imaging & Interventional Radiology, Zhongda Hospital, Southeast University, Nanjing, China.
Shuwei ZhouDepartment of Radiology, Nurturing Center of Jiangsu Province for State Laboratory of AI Imaging & Interventional Radiology, Zhongda Hospital, Southeast University, Nanjing, China.
Teng ZhangInstitute for Artificial Intelligence in Medicine, School of Artificial Intelligence, Nanjing University of Information Science and Technology, Nanjing, China.
Xunjun ChenThe Peoples Hospital of Xuyi County, Huaian, China.
Shenghong JuDepartment of Radiology, Nurturing Center of Jiangsu Province for State Laboratory of AI Imaging & Interventional Radiology, Zhongda Hospital, Southeast University, Nanjing, China.
Yuan-Cheng WangDepartment of Radiology, Nurturing Center of Jiangsu Province for State Laboratory of AI Imaging & Interventional Radiology, Zhongda Hospital, Southeast University, Nanjing, China. yuancheng_wang@seu.edu.cn.

Funding

National Natural Science Foundation of China 82271978National Natural Science Foundation of China 92359304"National Tutor System" Training Program for Health Youth Key Talents in Suzhou Qngg2021006
6 · The paper itself

Abstract

objectivesThis study aims to build a prediction model based on MRI features and clinical characteristics for early tumor recurrence (< 12 months) in lesions which evaluated as LR-TR nonviable at first follow up (1-2 months) after transaterial chemoembolization (TACE).

methodsThis multicenter retrospective study included consecutive patients with hepatocellular carcinoma (HCC) who underwent initial TACE from five centers between February 2015 and October 2022. Additionally, patients from a completed clinical trial (NCT03113955) were also included for this retrospective analysis. Nineteen baseline imaging features and six first follow-up imaging features were evaluated for lesions classified as LR-TR nonviable at the first post-TACE imaging assessment. A predictive model integrating clinical and MRI features for early recurrence of LR-TR nonviable lesions was developed with logistic regression analyses and validated on a 5-fold cross-validation. The model's performance was further validated by analyzing relapse-free survival (RFS) using Kaplan-Meier curves.

resultsNon-smooth margin (OR: 4.69; 95% CI: 1.91, 11.56; P = 0.001) and peritumoral hyperintensity on T2-weighted imaging or diffusion-weighted imaging (OR: 6.12; 95% CI: 2.53, 14.80; P < 0.001) were identified as independent risk factors for early recurrence of LR-TR nonviable lesions. The non-Viable Recurrence (nVR) model, developed using these two features, achieved area under the receiver operating characteristic curve of 0.759 (0.734, 0.784) in the training cohort and 0.765 (0.632, 0.898) in the validation cohort. Patients were stratified into high-risk and low-risk groups based on the Youden index, with RFS significantly differing between these groups in both the training (P < 0.001) and validation cohorts (P = 0.009).

conclusionBased on two radiologic features, the nVR model has demonstrated relatively reliable efficacy in predicting early post-TACE recurrence.

Indexed as

Carcinoma, HepatocellularChemoembolization, TherapeuticLiver NeoplasmsMagnetic Resonance ImagingNeoplasm Recurrence, LocalAgedClinical Trials as TopicFemaleHumansMaleMiddle AgedPredictive Value of TestsRetrospective StudiesTreatment OutcomeChemoembolizationHepatocellular carcinomaPrognosisRecurrence

Identifiers

PMID40214697

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Registered trials

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.