Evidence map›Paper›PMID 41612246›Full record

ArticleBMC medical imaging2026

ABUS-based glandular tissue component classification for breast cancer risk prediction in Chinese women with dense breasts: a retrospective study.

Jia-Nan Huang, Hong-Ju Yan, Yu-Xuan Qiu, Chao-Chao Dai, Li-Fang Yu, Yan-Juan Tan, Ke-Yin Ye, Tong-Tong Gao, Ling-Yun Bao

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Article in BMC medical imaging, 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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5 · Who and what money

Authors and funding

9 authors.

Jia-Nan HuangThe Fourth School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou First People's Hospital, Hangzhou, China.
Hong-Ju YanDepartment of Ultrasound, Hangzhou First People's Hospital, Hangzhou, China.
Yu-Xuan QiuDepartment of Ultrasound, Affiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Hangzhou, China.
Chao-Chao DaiDepartment of Ultrasound, Hangzhou First People's Hospital, Hangzhou, China.
Li-Fang YuDepartment of Ultrasound, Hangzhou First People's Hospital, Hangzhou, China.
Yan-Juan TanDepartment of Ultrasound, Hangzhou First People's Hospital, Hangzhou, China.
Ke-Yin YeDepartment of Ultrasound, Hangzhou First People's Hospital, Hangzhou, China.
Tong-Tong GaoDepartment of Ultrasound, Hangzhou First People's Hospital, Hangzhou, China.
Ling-Yun BaoDepartment of Ultrasound, Hangzhou First People's Hospital, Hangzhou, China. baolingyun2021@163.com.

Funding

Hangzhou Biomedical and Health Industry Development Support Special Project (No.2022WJC248) and Hangzhou Key Medical Discipline Construction Fund Project (No.oo20200457) No.2022WJC248;No.oo20200457Hangzhou Biomedical and Health Industry Development Support Special Project(No.2023WJC142) 2023WJC142
6 · The paper itself

Abstract

backgroundMammographic density (MD) is a well-established independent risk factor for breast cancer. However, mammography (MG) exhibits limited sensitivity for detecting cancer in dense breasts. The ultrasound-based glandular tissue component (GTC) classification represents an emerging qualitative assessment approach, yet its predictive value for breast cancer risk in Chinese women remains to be further explored. Automated breast ultrasound (ABUS) provides a reproducible method for acquiring standardized volumetric data to support GTC assessment.

methodsThis retrospective case-control study included 414 women with heterogeneously or extremely dense breasts (203 breast cancer cases and 211 benign controls). Data on demographics, clinical indicators, and the BCSC 5-year risk score were collected. Two physicians independently performed GTC classification on the ABUS images, blinded to the group assignment and each other’s assessments. Univariate and multivariate logistic regression analyses were used to identify risk factors in the overall population and among postmenopausal women. Inter-observer agreement was assessed using the weighted kappa and the intraclass correlation coefficient (ICC).

resultsCompared to the benign group, the malignant group had significantly higher values for age, age at menarche, proportion of postmenopausal women, prevalence of positive family history, lesion size, BCSC 5-year risk, and GTC classification (all P < 0.05). Multivariate analysis showed that after adjusting for confounders, GTC classification was an independent risk factor for breast cancer (C: OR = 2.62; D: OR = 3.21, P < 0.001) and was positively associated with breast cancer risk (P < 0.001). This association was more pronounced in postmenopausal women (C: OR = 4.17; D: OR = 7.38). Inter-observer agreement for GTC classification was high (weighted k = 0.810, ICC = 0.888).

conclusionsAmong women with dense breasts, ABUS-based GTC classification is a significant, reproducible, and independent risk factor for breast cancer. The findings of this study provide a theoretical basis for future research to integrate GTC into existing risk models to optimize risk stratification.

Indexed as

Breast DensityBreast NeoplasmsUltrasonography, MammaryAdultAgedBreastCase-Control StudiesChinaEast Asian PeopleFemaleHumansMiddle AgedRetrospective StudiesRisk AssessmentRisk FactorsAutomated breast ultrasoundBCSC risk prediction modelBreast cancer riskGlandular tissue componentMammography

Identifiers

PMID41612246
PMCPMC12924221

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LicenceCC BY-NC-ND
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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.