ArticleThe British journal of radiology2017
Imaging features of breast cancers on digital breast tomosynthesis according to molecular subtype: association with breast cancer detection.
Article in The British journal of radiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.
- Deep learning, radiomics and radiogenomics applications in the digital breast tomosynthesis: a systematic review.BMC bioinformatics · 2023Pooled it
- Predicting the molecular subtype of breast cancer and identifying interpretable imaging features using machine learning algorithms.European radiology · 2022Trial
- Diagnostic dilemma of lobular carcinoma: a mini-review of imaging modalities and the role of artificial intelligence and radiomics.Frontiers in oncology · 2025Review
- Breast cancer stage and molecular subtype distribution: real-world insights from a regional oncological center in Hungary.Discover oncology · 2024Article
- Imaging Features of Breast Cancer Subtypes on Mammography and Ultrasonography: an Analysis of 479 Patients.Indian journal of surgical oncology · 2022Article
- Clinical and X-ray characteristics for expressions of different receptors in patients with breast cancer.Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2021Article
- Predicting Molecular Subtypes of Breast Cancer with Mammography and Ultrasound Findings: Introduction of Sono-Mammometry Score.Radiology research and practice · 2021Article
- Article
- Detection of noncalcified breast cancer in patients with extremely dense breasts using digital breast tomosynthesis compared with full-field digital mammography.The British journal of radiology · 2019Article
- Digital breast tomosynthesis findings may be different in HER2 positive breast cancer patients according to hormone receptor status.The British journal of radiology · 2018Article
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7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo evaluate imaging features of breast cancers on digital breast tomosynthesis (DBT) according to molecular subtype and to determine whether the molecular subtype affects breast cancer detection on DBT.
methodsThis was an institutional review board--approved study with a waiver of informed consent. DBT findings of 288 invasive breast cancers were reviewed according to Breast Imaging Reporting and Data System lexicon. Detectability of breast cancer was quantified by the number of readers (0-3) who correctly detected the cancer in an independent blinded review. DBT features and the cancer detectability score according to molecular subtype were compared using Fisher's exact test and analysis of variance.
resultsOf 288 invasive cancers, 194 were hormone receptor (HR)-positive, 48 were human epidermal growth factor receptor 2 (HER2) positive and 46 were triple negative breast cancers. The most common DBT findings were irregular spiculated masses for HR-positive cancer, fine pleomorphic or linear branching calcifications for HER2 positive cancer and irregular masses with circumscribed margins for triple negative breast cancers (p < 0.001). Cancer detectability on DBT was not significantly different according to molecular subtype (p = 0.213) but rather affected by tumour size, breast density and presence of mass or calcifications.
conclusionBreast cancers showed different imaging features according to molecular subtype; however, it did not affect the cancer detectability on DBT. Advances in knowledge: DBT showed characteristic imaging features of breast cancers according to molecular subtype. However, cancer detectability on DBT was not affected by molecular subtype of breast cancers.
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