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REVIEW article

Front. Oncol.
Sec. Gastrointestinal Cancers: Hepato Pancreatic Biliary Cancers
Volume 15 - 2025 | doi: 10.3389/fonc.2025.1519703
This article is part of the Research Topic Liver Cancer Awareness Month 2024: Current Progress and Future Prospects on Advances in Primary Liver Cancer Investigation and Treatment View all 7 articles

Construction of Nomogram model based on contrast-enhanced ultrasound parameters to predict the degree of pathological differentiation of hepatocellular carcinoma

Provisionally accepted
Shu-Min Lian Shu-Min Lian Hong-Jing Cheng Hong-Jing Cheng Hong-Jing Li Hong-Jing Li Hui Wang Hui Wang *
  • China-Japan Union Hospital, Jilin University, Changchun, China

The final, formatted version of the article will be published soon.

    Objective: To predict the degree of pathological differentiation of hepatocellular carcinoma (HCC) by Quantitative analysis the correlation between the perfusion parameters of contrastenhanced ultrasound (CEUS) and the pathological grades of HCC using VueBox® software. Methods: We enrolled 189 patients who underwent CEUS and liver biopsy at our hospital from July 2019 to September 2024 and were pathologically confirmed with primary HCC. The Edmondson-Steiner pathological classification system was used as the gold standard for dividing the patients into the low-grade and high-grade groups. The patients were randomly divided into training set and testing set in a ratio of 7:3, in which the parameters of the training set were analyzed by univariate analysis and then stepwise regression to construct the prediction model, and the diagnostic efficacy of the validation model was evaluated by discrimination, calibration, and clinical applicability. Results: A total of 189 patients with primary hepatocellular carcinoma were enrolled, including 118 patients in the low-grade group and 71 patients in the high-grade group; they were randomly divided into training set of 128 patients and testing set of 61 patients. The prediction model was constructed by logistic regression in the training set, and the final model included three variables: mTTI, FT, and maximum diameter of a single lesion , resulting in the equation was 𝑌 = -2.360 + 1.674𝑋 1 +1.019𝑋 2 +0.753𝑋 3(2) +1.570𝑋 3(3) .The area under the ROC curve (AUC) of the training set was 0.831, with a sensitivity of 82.0% and a specificity of 79.5%; the area under the ROC curve (AUC) of the testing set was 0.811, with a sensitivity of 81.0% and a specificity of 70.0%.The regression model constructed by combining multiple parameters can effectively improve the diagnostic performance of CEUS in predicting the pathological differentiation grade of HCC, thus providing a clinical basis and empirical support for the use of CEUS as a diagnostic imaging method for this disease.

    Keywords: nomogram, contrast-enhanced ultrasound, Primary hepatocellular carcinoma, Edmondson-Steiner grade, VueBox® external perfusion software 1 Introduction

    Received: 30 Oct 2024; Accepted: 06 Jan 2025.

    Copyright: © 2025 Lian, Cheng, Li and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Hui Wang, China-Japan Union Hospital, Jilin University, Changchun, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.