ArticleOncology letters2019
Association between digital breast tomosynthesis and molecular subtypes of breast cancer.
Article in Oncology letters, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Correlation between multimodality imaging features and molecular subtypes in breast cancer: a comparative study between young (≤30 years) and middle-aged (45-55 years) women.Quantitative imaging in medicine and surgery · 2025Article
- Deep Learning in Digital Breast Tomosynthesis: Current Status, Challenges, and Future Trends.MedComm · 2025Review
- Imaging Features of Breast Cancer Subtypes on Mammography and Ultrasonography: an Analysis of 479 Patients.Indian journal of surgical oncology · 2022Article
- Correlation between imaging features and molecular subtypes of breast cancer in young women (≤30 years old).Japanese journal of radiology · 2020Article
- Review
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Authors and funding
7 authors.
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Abstract
In recent years, with increasing prevalence, particularly in young patients, breast cancer is considered to be one of the most common malignancies. The aim of the present study was to evaluate the clinical value of digital breast tomosynthesis (DBT) in diagnosing molecular subtypes of breast cancer. The present study retrospectively analyzed 134 cases of breast cancer with data regarding surgery, complete pathology and immunohistochemistry, which were collected at The Second Clinical College of Fujian Medical University (Quanzhou, China) between May 2013 and October 2014. The patients were divided into the four following molecular subtypes: Luminal A, luminal B, triple-negative and human epidermal growth factor receptor 2 (HER-2) overexpression, according to the expression of estrogen receptor, progesterone hormone receptor, HER-2 and Ki67. The association between clinical characteristics of each molecular subtype and characteristics of DBT were assessed. Calcification scores and lymph node size were the indicators that exhibited a significant difference following comparison between the four molecular subtypes. The subgroup analysis based on tumor size, calcification scores and lymph node size identified a significant difference in the distribution between patients with breast cancer with lymph node size of ≥1.5 and <1.5 cm. The analysis also revealed that the molecular subtypes of breast cancer were significantly associated with variables of calcification scores and lymph node size. In conclusion, the diagnostic imaging features, including calcification score and lymph node size, determined using DBT could be used as assistant diagnostic markers of breast cancer molecular subtypes.
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