Correlation between ultrasonography and elastography parameters and molecular subtypes of breast cancer in young women

To explore the differences of conventional ultrasound characteristics, elastic imaging parameters and clinicopathological characteristics of distinct molecular subtypes of breast cancer in young women, and to identify imaging parameters that exhibited significant associations with each molecular sub...

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Bibliographic Details
Published in:Annals of medicine (Helsinki) 2025-12, Vol.57 (1), p.2443041
Main Authors: Men, Dian-Xia, Li, Hui-Zhan, Dong, Juan, Xue, Meng-Hua, Wang, Zhi-Fen, Xiao, Wen-Li, Xue, Ji-Ping, Jia, Mei-Hong
Format: Article
Language:English
Subjects:
Adult
Breast - diagnostic imaging
Breast - pathology
Breast cancer
Breast Neoplasms - classification
Breast Neoplasms - diagnostic imaging
Breast Neoplasms - metabolism
Breast Neoplasms - pathology
Elasticity Imaging Techniques - methods
Female
Humans
Middle Aged
molecular subtype
Receptor, ErbB-2 - metabolism
Retrospective Studies
shear wave elastography
Triple Negative Breast Neoplasms - classification
Triple Negative Breast Neoplasms - diagnostic imaging
Triple Negative Breast Neoplasms - pathology
ultrasonography
Ultrasonography, Mammary - methods
Young Adult
young women
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Summary:To explore the differences of conventional ultrasound characteristics, elastic imaging parameters and clinicopathological characteristics of distinct molecular subtypes of breast cancer in young women, and to identify imaging parameters that exhibited significant associations with each molecular subtype. We performed a retrospective analysis encompassing 310 young women with breast cancer. Observations were made regarding the ultrasonography and elastography characteristics of the identified breast lesions. Subsequently, based on immunohistochemistry results patients were classified into five distinct molecular subtypes: luminal A, luminal B (HER2-), luminal B (HER2+), HER2+, and triple-negative breast cancer (TNBC). Clinical, pathological, and ultrasound imaging features were compared among these subtypes using binary logistic regression analysis. Statistically significant differences were observed in various parameters across the five molecular subtypes (  
ISSN:1365-2060
0785-3890
1365-2060
DOI:10.1080/07853890.2024.2443041