Evidence map›Paper›PMID 41309973›Full record

ArticleScientific reports2025

A study on the value of ultrasound strain elastography-based radiomics nomogram in the differential diagnosis of breast masses.

Yunpei Zhu, Yanping Dou, Qifan Hu, Hui Wang

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Article in Scientific reports, 2025. 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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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Yunpei ZhuUltrasound department of the First Affiliated Hospital of Dalian Medical University, No. 5 Longbin Road, Jinzhou District, Dalian City, Liaoning Province, China.
Yanping DouUltrasound department of the First Affiliated Hospital of Dalian Medical University, No. 5 Longbin Road, Jinzhou District, Dalian City, Liaoning Province, China.
Qifan HuUltrasound department of the First Affiliated Hospital of Dalian Medical University, No. 5 Longbin Road, Jinzhou District, Dalian City, Liaoning Province, China.
Hui WangUltrasound department of the First Affiliated Hospital of Dalian Medical University, No. 5 Longbin Road, Jinzhou District, Dalian City, Liaoning Province, China. wanghui404262@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of this study was to construct a radiomics nomogram for prediction of breast masses (BMs) by analyzing the clinical characteristics of the patients as well as radiomics features of two-dimensional (2D) ultrasound images and strain elastography images. In this retrospective study, 219 patients diagnosed with BMs were enrolled and randomly divided into training set and testing set in a 7:3 ratio. Radiomics nomogram was constructed based on clinical features and Radscore to compare area under the receiver operating characteristic curve (AUC) with another models. The AUCs of the training set were 0.83, 0.91, 0.92, 0.96, and 0.99 for the clinical model, elastography radiomics model, 2D radiomics model, bimodal radiomics model, and nomogram, respectively, and the AUCs of the testing set were 0.86, 0.87, 0.91, 0.93, and 0.95, respectively. There were significant differences in AUC between nomogram and another models (p < 0.05). 2D ultrasound radiomics model and strain elastography radiomics model were of diagnostic value in identifying BMs. The bimodal radiomics model was superior to these two single-modal radiomics models. Nomogram can further enhance the diagnosis of BMs and contribute valuable information for clinical decision making.

Indexed as

Breast NeoplasmsElasticity Imaging TechniquesNomogramsUltrasonography, MammaryAdultAgedArea Under CurveBreastDiagnosis, DifferentialFemaleHumansMiddle AgedRadiomicsRetrospective StudiesROC CurveBreast massesRadiomicsStrain elastographyUltrasound

Identifiers

PMID41309973
PMCPMC12749759

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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.