Evidence map›Paper›PMID 42819116›Full record

ArticleFrontiers in medicine2026

Preoperative differentiation of benign and malignant gallbladder lesions using multimodal ultrasound radiomics: a retrospective study.

Xialing Zhu, Cui Wang, Jialun Ren, Yingying Liao, Yizheng Liu, Shuping Qu, Dong Jiang

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Article in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Xialing Zhu *Department of Ultrasound, Eastern Hepatobiliary Surgery Hospital, The Third Affiliated Hospital of Naval Medical University, Shanghai, China.
Cui Wang *Department of Ultrasound, The First Affiliated Hospital of Naval Medical University, Shanghai, China.
Jialun RenDepartment of Ultrasound, Eastern Hepatobiliary Surgery Hospital, The Third Affiliated Hospital of Naval Medical University, Shanghai, China.
Yingying LiaoDepartment of Ultrasound, Eastern Hepatobiliary Surgery Hospital, The Third Affiliated Hospital of Naval Medical University, Shanghai, China.
Yizheng LiuDepartment of Ultrasound, Eastern Hepatobiliary Surgery Hospital, The Third Affiliated Hospital of Naval Medical University, Shanghai, China.
Shuping QuDepartment of Comprehensive Treatment for Hepatobiliary Surgery, Eastern Hepatobiliary Surgery Hospital, The Third Affiliated Hospital of Naval Medical University, Shanghai, China.
Dong JiangDepartment of Ultrasound, Eastern Hepatobiliary Surgery Hospital, The Third Affiliated Hospital of Naval Medical University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: This study aims to develop and validate a multimodal ultrasound radiomics model to differentiate benign from malignant gallbladder lesions preoperatively by integrating conventional ultrasound, contrast-enhanced ultrasound (CEUS), and clinical indicators. Methods: This retrospective study included 166 patients with histopathologically confirmed gallbladder lesions (36 malignant and 130 benign), divided in a 4:1 ratio into a cross-validation set ( Results: Among the clinical and semantic ultrasound variables, maximum lesion diameter, CEUS-derived base width, triglyceride, and high-density lipoprotein cholesterol differed significantly between benign and malignant lesions. In the cross-validation set, the conventional ultrasound, CEUS, and combined models achieved AUCs of 0.814 (95% CI: 0.689-0.938), 0.848 (95% CI: 0.764-0.932), and 0.936 (95% CI: 0.887-0.986), respectively. In the independent test set, the corresponding AUCs were 0.820 (95% CI: 0.664-0.976), 0.915 (95% CI: 0.818-1.000), and 0.920 (95% CI: 0.823-1.000). The difference between the CEUS and combined models was not significant ( Conclusions: The combined conventional ultrasound and CEUS radiomics model showed favorable discrimination and a balanced sensitivity-specificity profile in differentiating benign from malignant gallbladder lesions. Although its AUC was comparable to that of the CEUS radiomics model and its statistical superiority was not established, multimodal feature integration may provide complementary diagnostic information. Integration of radiomics signatures with clinical and imaging variables may support individualized preoperative risk stratification, but the incremental clinical value of this approach requires prospective multicenter validation.

Indexed as

contrast-enhanced ultrasoundconventional ultrasoundgallbladder lesionsmachine learningmalignancynomogramradiomics

Identifiers

PMID42819116
PMCPMC13623621

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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.