Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Volatility-induced of zinc: Tailoring lattice strain in high-entropy alloys for driving efficient peroxymonosulfate activation toward rapid emerging pollutant breakdown.

Journal of hazardous materials·2026

Same author

Tuning Ni-O/Ni-S coordination for efficient electrocatalytic oxidation of 5-hydroxymethylfurfural to 2,5-furandicarboxylic acid.

Chemical communications (Cambridge, England)·2026

Same author

A BpbZIP4 transcription factor enhances drought resistance and root development in <i>Betula platyphylla</i>: insights into a gene regulatory network.

Horticulture research·2026

Same author

Dual-targeted microspheres reshape the metabolic-immune microenvironment to reverse post-embolization dilemmas in hepatocellular carcinoma.

Cell reports. Medicine·2026

Same author

Systematic Review: Imaging-Based Morphological Criteria for Liver Cirrhosis-A Call to Standardise.

Alimentary pharmacology & therapeutics·2026

Same author

Stabilization of chitosan-based high internal phase emulsions via tannic acid-mediated physical crosslinking.

International journal of biological macromolecules·2026

Search research articles

Related Experiment Video

Updated: Mar 8, 2026

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

MR Radiomics Combined With Radiologic Features to Predict Recurrence Location in Nonviable Hepatocellular Carcinoma

Shuhang Zhang¹, Weilang Wang¹, Wu Cai²

¹Department of Radiology, Zhongda Hospital, Nurturing Center of Jiangsu Province for State Laboratory of AI Imaging & Interventional Radiology, School of Medicine, Southeast University, Nanjing, China.

Journal of Gastroenterology and Hepatology

|March 7, 2026

Summary

A new fusion model combining radiomics and radiologic features accurately predicts early recurrence locations in nonviable hepatocellular carcinoma (HCC) after transarterial chemoembolization (TACE). This approach aids in personalized follow-up and retreatment planning for HCC patients.

Keywords:

hepatocellular carcinoma prognosis radiomics transarterial chemoembolization

More Related Videos

Dual-phase Cone-beam Computed Tomography to See, Reach, and Treat Hepatocellular Carcinoma during Drug-eluting Beads Transarterial Chemo-embolization

Dual-phase Cone-beam Computed Tomography to See, Reach, and Treat Hepatocellular Carcinoma during Drug-eluting Beads Transarterial Chemo-embolization

Published on: December 2, 2013

Y-90 Radioembolization and PD-1 Inhibitor as Neoadjuvant Treatment in Hepatocellular Carcinoma

Y-90 Radioembolization and PD-1 Inhibitor as Neoadjuvant Treatment in Hepatocellular Carcinoma

Published on: May 24, 2024

Related Experiment Videos

Last Updated: Mar 8, 2026

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

Dual-phase Cone-beam Computed Tomography to See, Reach, and Treat Hepatocellular Carcinoma during Drug-eluting Beads Transarterial Chemo-embolization

Dual-phase Cone-beam Computed Tomography to See, Reach, and Treat Hepatocellular Carcinoma during Drug-eluting Beads Transarterial Chemo-embolization

Published on: December 2, 2013

Y-90 Radioembolization and PD-1 Inhibitor as Neoadjuvant Treatment in Hepatocellular Carcinoma

Y-90 Radioembolization and PD-1 Inhibitor as Neoadjuvant Treatment in Hepatocellular Carcinoma

Published on: May 24, 2024

Area of Science:

Radiology
Oncology
Medical Imaging Analysis

Background:

Hepatocellular carcinoma (HCC) recurrence after transarterial chemoembolization (TACE) is common.
Identifying early recurrence locations is crucial for effective patient management.

Purpose of the Study:

To develop and evaluate a predictive model integrating radiomics and radiologic features for early recurrence site identification in nonviable HCC post-TACE.
To compare the performance of a fusion model against standalone radiomics and radiologic models.

Main Methods:

A multicenter retrospective study involving HCC patients treated with TACE.
Radiomics features were extracted from a 1-cm peritumoral ring divided into eight sectors.
A fusion model combined radiomics features with nonsmooth margin and peritumoral hyperintensity.
Model performance was assessed using receiver operating characteristic (ROC) curves and the DeLong test.

Main Results:

The fusion model achieved superior performance compared to radiomics and radiologic models in the training cohort (AUC 0.843 vs. 0.771 and 0.787).
In the test cohort, the fusion model (AUC 0.774) outperformed the radiomics model (AUC 0.602) and showed comparable performance to the radiologic model (AUC 0.736).
The fusion model demonstrated statistically significant improvements in predictive performance.

Conclusions:

The developed fusion model effectively predicts early recurrence locations in nonviable HCC after TACE.
This model shows potential for supporting personalized follow-up strategies and optimizing retreatment planning for HCC patients.