Imaging Characteristics of Breast Cancers Detected During MRI-Based Surveillance in Hereditary Breast and Ovarian Cancer Syndrome

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Authors: Tomoko Seki, Jitsuro Tsukada, Takamichi Yokoe, Aiko Nagayama, Maiko Takahashi, Kei Mizushima, Haruka Takeshita, Mizuki So, Masahiro Jinzaki, Tetsu Hayashida
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References: 7

Abstract

Abstract Background: Magnetic resonance imaging (MRI)-based surveillance plays a central role in breast cancer risk management for women with hereditary breast and ovarian cancer syndrome (HBOC). However, the multimodal imaging characteristics of breast cancers detected during surveillance remain insufficiently characterized, particularly in Japanese patients. Methods: We retrospectively reviewed 160 women with pathogenic variants in BRCA1 or BRCA2 who underwent MRI-based breast surveillance at a single institution between 2015 and 2024. Among them, 11 breast cancers newly detected during surveillance were analyzed with respect to imaging findings on MRI, digital breast tomosynthesis (DBT), and ultrasonography (US), as well as pathological features and biopsy approaches. Results: All 11 breast cancers were detected on contrast-enhanced MRI. Most lesions presented as small non-mass enhancements or low-grade ductal carcinoma in situ. In contrast, only two lesions were visible on DBT, both associated with calcifications, and four lesions were identified on second-look ultrasonography. The majority of cancers were BRCA2 -associated, luminal-type, and low- to intermediate-grade. All invasive cancers were ≤ 0.5 cm in size and node-negative. Conclusion: Breast cancers detected during MRI-based surveillance in HBOC patients frequently manifest as small, non-mass, and non-calcified lesions that are not detectable on DBT or US. Recognition of these imaging characteristics, together with practical biopsy localization strategies, is essential for optimizing early detection in high-risk women.

Fields of Study & Subjects

MRI in cancer diagnosis BRCA gene mutations in cancer Breast Lesions and Carcinomas

Publication details

Journal / source
Research Square
Publication date
10 March 2026
Language
EN
Document type
Preprint