Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

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

Shengxian decoction modulates gut microbiota and microbial metabolism in rats with chronic heart failure.

Frontiers in microbiology·2026
Same author

Study on the pharmacodynamic material basis of Buthus martensii Karsch in ameliorating chronic atrophic gastritis: Screening and experimental validation of protein-peptide bioactive components based on 4D label-free proteomics.

Journal of ethnopharmacology·2025
Same author

Neural network enhanced time-varying parameter estimation via weak measurement.

Optics express·2024
Same author

Incorporation of CEUS and SWE parameters into a multivariate logistic regression model for the differential diagnosis of benign and malignant TI-RADS 4 thyroid nodules.

Endocrine·2023
Same author

Stable supercapacitor electrode based on two-dimensional high nucleus silver nano-clusters as a green energy source.

Dalton transactions (Cambridge, England : 2003)·2021
Same author

New 3D Porous Silver Nanopolycluster as a Highly Effective Supercapacitor Electrode: Synthesis and Study of the Optical and Electrochemical Properties.

Inorganic chemistry·2021

Related Experiment Video

Updated: May 28, 2025

Author Spotlight: Advancing Hepatic Fibrosis Diagnosis Using Magnetic Resonance Elastography and AI
06:09

Author Spotlight: Advancing Hepatic Fibrosis Diagnosis Using Magnetic Resonance Elastography and AI

Published on: July 21, 2023

1.1K

Construction of nomogram model based on contrast-enhanced ultrasound parameters to predict the degree of pathological

Shu-Min Lian1, Hong-Jing Cheng2, Hong-Jing Li1

  • 1Department of Ultrasound, China-Japan Union Hospital of Jilin University, Changchun, Jilin, China.

Frontiers in Oncology
|February 11, 2025
PubMed
Summary

Contrast-enhanced ultrasound (CEUS) perfusion parameters effectively predict hepatocellular carcinoma (HCC) differentiation. A regression model combining multiple parameters improves diagnostic accuracy for HCC grading.

Keywords:
Edmondson-Steiner gradeVueBox® external perfusion softwarecontrast-enhanced ultrasoundnomogramprimary hepatocellular carcinoma

More Related Videos

Author Spotlight: Investigating Immune Cell Dynamics in the Tumor Microenvironment — Challenges and Innovations in Cancer Prognosis
07:32

Author Spotlight: Investigating Immune Cell Dynamics in the Tumor Microenvironment — Challenges and Innovations in Cancer Prognosis

Published on: April 12, 2024

1.2K
Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
04:09

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

Published on: October 10, 2018

8.2K

Related Experiment Videos

Last Updated: May 28, 2025

Author Spotlight: Advancing Hepatic Fibrosis Diagnosis Using Magnetic Resonance Elastography and AI
06:09

Author Spotlight: Advancing Hepatic Fibrosis Diagnosis Using Magnetic Resonance Elastography and AI

Published on: July 21, 2023

1.1K
Author Spotlight: Investigating Immune Cell Dynamics in the Tumor Microenvironment — Challenges and Innovations in Cancer Prognosis
07:32

Author Spotlight: Investigating Immune Cell Dynamics in the Tumor Microenvironment — Challenges and Innovations in Cancer Prognosis

Published on: April 12, 2024

1.2K
Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
04:09

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

Published on: October 10, 2018

8.2K

Area of Science:

  • Medical Imaging
  • Oncology
  • Ultrasound Technology

Background:

  • Hepatocellular carcinoma (HCC) grading is crucial for treatment decisions.
  • Accurate prediction of pathological differentiation is essential for patient management.
  • Current methods may require invasive procedures.

Purpose of the Study:

  • To predict the pathological differentiation grade of HCC.
  • To quantitatively analyze the correlation between contrast-enhanced ultrasound (CEUS) perfusion parameters and HCC pathological grades.
  • To develop a predictive model using CEUS data.

Main Methods:

  • 189 HCC patients underwent CEUS and liver biopsy.
  • Edmondson-Steiner classification used for grading (low-grade vs. high-grade).
  • Logistic regression model developed using training set (70%) and validated on testing set (30%).

Main Results:

  • A predictive model was constructed using mTTI, FT, and maximum lesion diameter.
  • The model achieved an AUC of 0.831 in the training set and 0.811 in the testing set.
  • High sensitivity and specificity were observed in both sets for predicting HCC differentiation.

Conclusions:

  • A regression model combining CEUS perfusion parameters enhances diagnostic performance for HCC pathological differentiation.
  • CEUS offers a non-invasive imaging method for predicting HCC grade.
  • Provides clinical basis and empirical support for CEUS in HCC assessment.