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

Imaging Characteristics of Breast Cancers Detected During MRI-Based Surveillance in Hereditary Breast and Ovarian Cancer Syndrome | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Imaging Characteristics of Breast Cancers Detected During MRI-Based Surveillance in Hereditary Breast and Ovarian Cancer Syndrome Tomoko Seki, Jitsuro Tsukada, Yokoe Takamichi, Aiko Nagayama, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9004468/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version 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. Hereditary Breast and Ovarian Cancer syndrome (HBOC) breast MRI surveillance BRCA1 and BRCA2 Figures Figure 1 Figure 2 1. Introduction Hereditary breast and ovarian cancer syndrome (HBOC), caused mainly by pathogenic variants in BRCA1 and BRCA2 , confers a markedly increased lifetime risk of breast cancer, reported to range from approximately 48% to 76%, far exceeding that of the general female population (~ 11%) [ 1 ]. In Japan, partial public insurance coverage for HBOC-related genetic testing and management, primarily for individuals with a personal or family history suggestive of hereditary breast and ovarian cancer, was introduced in 2020 and has led to a steady increase in diagnosed cases. Given that breast cancer tends to occur at a younger age in BRCA1 carriers and somewhat later in BRCA2 carriers, early and sustained surveillance is indispensable for effective risk management. Breast magnetic resonance imaging (MRI) is recognized as the most sensitive imaging modality for the early detection of breast cancer in high-risk women. Previous prospective studies have demonstrated MRI sensitivities ranging from 77% to 94%, substantially outperforming mammography (MMG) and ultrasonography (US), which show sensitivities of approximately 33%–59% in this population [ 2 , 3 ]. Despite its advantages, MRI surveillance poses several challenges, including repeated exposure to gadolinium-based contrast agents, higher cost, longer examination times, and greater physical burden. Although risk-reducing mastectomy substantially reduces breast cancer risk, imaging-based surveillance is often favored in clinical practice in Japan, reflecting cosmetic, psychological, and social considerations. The imaging appearance of HBOC-associated breast cancer differs from that of sporadic disease and varies according to genetic background. BRCA1 -associated tumors frequently present as high-grade or triple-negative breast cancers, whereas BRCA2 -associated tumors are more commonly luminal-type and may manifest as ductal carcinoma in situ (DCIS), sometimes accompanied by calcifications on MMG [ 4 , 5 ]. While MRI plays a cornerstone role of surveillance for high-risk individuals, data characterizing the multimodal imaging features of HBOC-related breast cancers in Japanese patients remain limited. From January 2015 to December 2024, a total of 160 women with confirmed pathogenic variants in BRCA1 or BRCA2 underwent structured MRI-based breast surveillance at our institution. During follow-up, 11 breast cancers were newly diagnosed. Therefore, the purpose of this study was to characterize the multimodal imaging features of breast cancers detected during MRI-based surveillance in Japanese women with HBOC, comparing findings among MRI, mammography, and ultrasonography. This study was not designed to assess cancer detection rates or modality sensitivity, but rather to delineate characteristic imaging phenotypes and detectability patterns of MRI-detected lesions, particularly those occult on other imaging modalities. 2. Materials and Methods 2.1 Study population We retrospectively reviewed women with hereditary breast and ovarian cancer syndrome (HBOC) who underwent MRI-based breast surveillance at Keio University Hospital between January 2015 and December 2024. During this period, 160 women with confirmed pathogenic variants in BRCA1 or BRCA2 were enrolled in the surveillance program. Among them, 11 patients were newly diagnosed with breast cancer during follow-up and constituted the study cohort for detailed imaging and pathological analysis. 2.2 Imaging protocols All patients underwent breast MRI using a 3.0-T system with a dedicated breast coil. Dynamic contrast-enhanced MRI was performed according to institutional protocols, and imaging findings were interpreted in accordance with the BI-RADS MRI lexicon. Digital breast tomosynthesis (DBT) was performed in all cases. Standard bilateral craniocaudal (CC) and mediolateral oblique (MLO) views were reconstructed from tomosynthesis datasets. Whole-breast ultrasonography (US) was initially performed as a screening examination without reference to MRI or mammography findings, using a high-frequency linear transducer (12–18 MHz). For lesions detected on contrast-enhanced MRI but not identified during screening US, second-look ultrasonography was subsequently performed with reference to MRI findings, focusing on breast architecture and anatomical landmarks. In selected cases in which lesions were detected exclusively on MRI, MRI datasets, and CT datasets when available, were co-registered with real-time US using a Volume Navigation system (LOGIQ E9/E10, GE Healthcare) to facilitate targeted biopsy. 2.3 Imaging analysis All imaging studies were reviewed retrospectively by board-certified radiologists specializing in breast imaging with knowledge of pathological results for the purpose of imaging–pathology correlation. On MRI, lesion morphology (mass or non-mass enhancement), distribution pattern (focal, linear, or segmental), internal enhancement characteristics, and enhancement kinetics were evaluated according to the BI-RADS MRI lexicon. Findings on digital breast tomosynthesis (DBT) and ultrasonography (US) were categorized according to the appropriate BI-RADS classification system for each modality. Lesion visibility on DBT and US was recorded as either “visible” or “not visible.” In this study, lesion visibility on ultrasonography was defined based on findings at second-look ultrasonography performed with reference to MRI findings, rather than on the initial screening examination. Pathological correlation was performed for all lesions. 2.4 Statistical analysis Descriptive statistics were used to summarize patient characteristics, pathological findings, and lesion detection across imaging modalities. 3. Results 3.1 Patient and lesion characteristics Among 160 women with confirmed pathogenic variants in BRCA1 or BRCA2 who underwent MRI-based breast surveillance at our institution between 2015 and 2024, 11 breast cancers were newly detected (Table 1 ). The median age at diagnosis was 45 years (range, 31–49 years). Two patients were carriers of BRCA1 variants, while nine carried BRCA2 variants. Table 1 Clinical and pathological characteristics of breast cancers detected during MRI-based surveillance in HBOC patients Case BRCA Age (years) Personal history of BC Family history of BC Biopsy method Final pathology Tumor type Tumor size (cm) Nuclear grade HR HER2 Breast surgery Axillary surgery 1 BRCA1 31 Yes Yes Excisional DCIS DCIS 0.8 – N/A N/A NSM SLNB 2 BRCA2 42 Yes Yes ST-guided IDC IDC 0.3 2 Positive Negative BCS SLNB 3 BRCA2 47 No Yes US-guided IDC IDC 0.3 1 Positive Negative NSM SLNB 4 BRCA2 49 No Yes Excisional DCIS DCIS 1.1 Low N/A N/A BCS None 5 BRCA2 41 No Yes Excisional DCIS DCIS 3.8 Intermediate N/A N/A NSM None 6 BRCA2 47 No No US-guided DCIS + LCIS DCIS 0.5 Low N/A N/A BCS None 7 BRCA2 47 No No US-guided DCIS DCIS 1.4 High N/A N/A BCS SLNB 8 BRCA2 48 No Yes Excisional DCIS DCIS 1.0 Intermediate N/A N/A NSM SLNB 9 BRCA1 37 Yes Yes US-guided IDC IDC 0.5 3 Negative Negative NSM SLNB 10 BRCA2 37 No Yes US-guided DCIS DCIS 10.0 Intermediate N/A N/A NSM SLNB 11 BRCA2 45 No Yes US-guided DCIS DCIS 5.5 Intermediate N/A N/A BCS SLNB Footnotes • Tumor size represents the maximum pathological dimension. • Hormone receptor (HR) and HER2 status are shown only for invasive ductal carcinoma (IDC) cases. • One patient (Case 9 ) underwent non-contrast MRI due to contraindication to gadolinium-based contrast agents. Abbreviations HBOC, hereditary breast and ovarian cancer; BC, breast cancer; DCIS, ductal carcinoma in situ; IDC, invasive ductal carcinoma; LCIS, lobular carcinoma in situ; MRI, magnetic resonance imaging; US, ultrasound; ST, Streo NSM, nipple-sparing mastectomy; BCS, breast-conserving surgery; SLNB, sentinel lymph node biopsy; HR, hormone receptor; N/A, not applicable. All lesions were unilateral, and three patients had a prior history of breast cancer in the contralateral breast. Pathological examination revealed ductal carcinoma in situ (DCIS) in seven cases and invasive ductal carcinoma (IDC) in four cases. Most tumors were low- to intermediate-grade, estrogen receptor–positive and HER2-negative, consistent with a predominantly luminal phenotype. All invasive cancers were small (≤ 0.5 cm, pT1a) and node-negative. Surgical management included nipple-sparing mastectomy in six patients and breast-conserving surgery in five patients. Sentinel lymph node biopsy was performed in seven patients. 3.2 Imaging findings Imaging findings for all lesions are summarized in Table 2 . All 11 breast cancers were detected on MRI, including one case evaluated without contrast enhancement. On MRI, lesions most commonly presented as non-mass enhancement or small masses with irregular margins. Non-mass enhancement frequently showed linear or segmental distribution patterns, with clumped or heterogeneous internal enhancement. Enhancement kinetics were predominantly fast or medium in the initial phase, followed by persistent enhancement in most cases. Imaging findings in the non-contrast enhanced case were considered illustrative but were not directly comparable with those obtained using contrast-enhanced MRI. Table 2 Imaging characteristics of breast cancers detected during MRI-based surveillance Case MRI FGT BPE MRI size (mm) Location MRI presentation Distribution Internal enhancement Kinetic pattern DBT visible DBT findings DBT category US visible US findings US category 1 Heterogeneous Minimal 7.7 L, A/C NME — Homogeneous Fast–persistent No None 1 No — 1 2 Heterogeneous Minimal 3.8 R, E Mass — Homogeneous Fast–persistent Yes Calcifications 3 No — 1 3 Heterogeneous Minimal 30.0 R, A/C NME Segmental Clumped Medium–persistent Yes Calcifications 4 Yes Irregular mass 4 4 Heterogeneous Moderate 11.8 L, A/C Mass — Homogeneous Fast–washout No None 1 No — 1 5 Scattered Mild 13.1 L, D Mass — Heterogeneous Medium–persistent No None 1 No — 1 6 Heterogeneous Mild 12.0 R, A/B Mass — Homogeneous Medium–persistent No None 1 Yes Irregular mass 3 7 Heterogeneous Mild 14.4 L, D Mass — Heterogeneous Fast–persistent No None 1 Yes Irregular mass 3 8 Scattered Minimal 14.8 L, A NME Linear Clumped Slow–persistent No None 1 No — 1 9* — — — — — — — — No None 1 Yes Irregular mass 3 10 Scattered Moderate 41.4 R, C/D NME Segmental Heterogeneous Fast–persistent No None 1 No — 1 11 Heterogeneous Mild 46.7 R, B/D NME Segmental Heterogeneous Fast–persistent No None 1 No — 1 Footnotes Case 9 underwent non-contrast MRI due to contraindication to gadolinium-based contrast agents. Lesion visibility on ultrasonography refers to detectability on second-look ultrasonography performed with reference to MRI findings. Whole-breast ultrasonography was initially performed as a screening examination without reference to MRI or mammography findings. Abbreviations FGT, fibroglandular tissue; BPE, background parenchymal enhancement; MRI, magnetic resonance imaging; DBT, digital breast tomosynthesis; US, ultrasonography; NME, non-mass enhancement. In contrast, digital breast tomosynthesis (DBT) demonstrated limited detectability. Only two lesions were visible on DBT, both of which were associated with calcifications. No architectural distortion or focal density corresponding to MRI-detected non-mass enhancement was identified in the remaining cases. Ultrasonography showed poor detectability. At second-look ultrasonography performed with reference to MRI findings, lesions were identified in four cases, typically appearing as small, irregular hypoechoic masses. The remaining lesions were not visualized on ultrasonography despite targeted evaluation. Representative MRI-only lesions that were occult on both DBT and ultrasonography are shown in Figs. 1 and 2 . 3.3 Representative cases Representative imaging findings are shown in two cases in which lesions were detected exclusively on MRI and were occult on both digital breast tomosynthesis and ultrasonography. Case 1 was a 31-year-old woman with a pathogenic BRCA1 variant undergoing MRI-based surveillance. Contrast-enhanced MRI demonstrated a small area of focal non-mass enhancement in the left breast. No corresponding abnormality was identified on DBT or ultrasonography, including second-look examination. Excision biopsy revealed ductal carcinoma in situ. Case 5 was a 41-year-old woman with a pathogenic BRCA2 variant. Contrast-enhanced MRI showed non-mass enhancement with an irregular distribution pattern. The lesion was not visualized on DBT or on targeted second-look ultrasonography. Excisional biopsy confirmed ductal carcinoma in situ. 4. Discussion In this institutional series of 160 hereditary breast and ovarian cancer (HBOC) patients undergoing MRI-based surveillance, 11 breast cancers were detected between 2015 and 2024. All lesions were identified on MRI, highlighting its high sensitivity for early detection in this high-risk population. Most lesions presented as small non-mass enhancements (NMEs) or low-grade ductal carcinoma in situ (DCIS), indicating that MRI surveillance preferentially detects early-stage, clinically meaningful disease rather than incidental findings. Although the number of detected cancers was modest, HBOC surveillance cohorts are inherently limited, and our findings provide valuable imaging–pathology correlation data in a Japanese population. Our cohort showed a predominance of BRCA2 -associated cancers (82%), most of which were luminal-type and low- to intermediate-grade DCIS. This distribution is consistent with previous reports indicating that BRCA2 -related breast cancers frequently present as hormone receptor–positive disease or DCIS, whereas BRCA1 -associated cancers tend to be high-grade or triple-negative invasive carcinomas [ 4 , 5 ]. Notably, the BRCA1-associated lesion (case 1 ) in our cohort presented as MRI-only DCIS, illustrating that genotype-related imaging patterns may overlap and that MRI remains essential for detecting early intraductal disease across mutation subtypes. The superiority of MRI observed in our series mirrors findings from landmark prospective studies. Warner et al. reported MRI sensitivities of approximately 77% compared with 36% for mammography and 33% for ultrasound in BRCA1/2 mutation carriers [ 2 ], while Kriege et al. demonstrated significantly higher cancer detection rates with MRI than with mammography in women with hereditary or familial breast cancer risk [ 3 ]. Long-term experience from European HBOC surveillance programs further supports the central role of MRI in high-risk screening [ 6 ]. Our results emphasize that even digital breast tomosynthesis (DBT), despite improved contrast resolution, remains limited in detecting non-calcified NMEs. Representative MRI-only lesions in our cohort (Figs. 1 and 2 ) illustrate how subtle ductal or segmental enhancements within dense glandular tissue may remain undetectable on both DBT and US. From a clinical perspective, detection of such MRI-only DCIS lesions may be particularly relevant in HBOC patients, in whom early identification of precursor lesions can inform individualized risk-reduction strategies, including the timing and extent of surgery. The present study also highlights a practical challenge in HBOC surveillance: localization and biopsy of MRI-only lesions. MRI-guided biopsy systems are not widely available in Japan and many Asian clinical settings. In our practice, fusion-guided targeted ultrasonography using a Volume Navigation system enabled lesion localization and tissue sampling in selected MRI-detected lesions. By bridging the gap between high-sensitivity detection and tissue diagnosis, this approach offers a realistic diagnostic pathway in environments where MRI-guided biopsy is not readily accessible. Wider adoption of such techniques may improve the feasibility and effectiveness of MRI-based surveillance programs. The effectiveness of this imaging-based surveillance and biopsy strategy is further supported by surgical outcomes in our risk management practice. At our institution, only two occult carcinomas were identified among 43 risk-reducing mastectomy procedures (4.7%). This incidence is lower than that reported in the nationwide Japanese HBOC registry analysis by Yamauchi et al., who identified occult breast cancer in 6 of 53 prophylactic mastectomy specimens (11.3%) despite thorough preoperative assessment with mammography, ultrasonography, and MRI [ 7 ]. These findings suggest that high-quality MRI surveillance combined with lesion-directed biopsy strategies may improve preoperative disease detection and reduce unexpected pathological findings at risk-reducing surgery. This study has several limitations. It was retrospective and conducted at a single institution, and the number of detected cancers was limited. However, HBOC surveillance cohorts are inherently small, and the consistent MRI detectability and imaging–pathology concordance across cases strengthen the reliability of our observations. In addition, a single experienced breast radiologist performed imaging review, which may limit generalizability. Future studies incorporating multicenter data, quantitative MRI metrics such as apparent diffusion coefficient values, abbreviated MRI protocols [ 8 ], and artificial intelligence–assisted lesion matching may further refine surveillance strategies for high-risk women. In conclusion, breast cancers detected during MRI-based surveillance in HBOC patients frequently present as small, non-mass, and non-calcified lesions that are occult on DBT and ultrasonography. Recognition of these imaging characteristics, together with the implementation of practical lesion localization and biopsy strategies, is essential for optimizing early detection and risk-reduction management in hereditary breast cancer. 5. Conclusion This study expands on existing knowledge by delineating the distinct imaging characteristics of HBOC-related breast cancers detected during MRI surveillance in Japanese patients. Most lesions are small, non-mass enhancements detectable only by MRI. Recognizing these patterns and correlating them across imaging modalities may improve early diagnosis and support practical biopsy strategies in high-risk women. Declarations Compliance with Ethical Standards Conflict of Interest The authors declare that they have no conflict of interest. Ethical approval This study was approved by Institutional Review Board (IRB) at Keio University School of Medicine (#20150170). Patients were appropriately opted out of the research use of their clinical data in accordance with institutional guidelines. All procedures were conducted in compliance with the principles of the Declaration of Helsinki. Informed consent An opt-out approach was used to provide patients with the opportunity to refuse participation. References Momozawa Y, Sasai R, Usui Y, Shiraishi K, Iwasaki Y, Taniyama Y, et al. Expansion of Cancer Risk Profile for BRCA1 and BRCA2 Pathogenic Variants. JAMA Oncol. 2022;8:871–8. Warner E, Plewes DB, Hill KA, Causer PA, Zubovits JT, Jong RA, et al. Surveillance of BRCA1 and BRCA2 mutation carriers with magnetic resonance imaging, ultrasound, mammography, and clinical breast examination. JAMA. 2004;292:1317–1325. Kriege M, Brekelmans CT, Boetes C, Besnard PE, Zonderland HM, Obdeijn IM, et al. Efficacy of MRI and mammography for breast-cancer screening in women with a familial or genetic predisposition. N Engl J Med. 2004;351:427–437. Krammer J, Pinker-Domenig K, Robson ME, Gönen M, Bernard-Davila B, Morris EA, et al. Breast cancer detection and tumor characteristics in BRCA1 and BRCA2 mutation carriers. Breast Cancer Res Treat. 2017;163:565–571. Veltman J, Mann R, Kok T, Obdeijn IM, Hoogerbrugge N, Blickman JG, et al. Breast tumor characteristics of BRCA1 and BRCA2 gene mutation carriers on MRI. Eur Radiol. 2008;18:931–938. Bick U, Engel C, Krug B, Heindel W, Fallenberg EM, Rhiem K, et al. High-risk breast cancer surveillance with MRI: 10-year experience from the German Consortium for Hereditary Breast and Ovarian Cancer. Breast Cancer Res Treat. 2019;175:217–228. Yamauchi H, Okawa M, Yokoyama S, Nakagawa C, Yoshida R, Suzuki K, et al. High rate of occult cancer found in prophylactic mastectomy specimens despite thorough presurgical assessment with MRI and ultrasound: findings from the Hereditary Breast and Ovarian Cancer Registration 2016 in Japan. Breast Cancer Res Treat. 2018;172:679–687. Kuhl CK. Abbreviated breast MRI: state of the art and future directions. Radiology. 2024;311(1):12–27. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9004468","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":600373695,"identity":"3381af46-9d36-440d-8662-35d7bb7fc73e","order_by":0,"name":"Tomoko Seki","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAArklEQVRIiWNgGAWjYLACxgYGOQkQycBDhGoeqBZj0rUkziDaTfbs3WkPfu6wSZ/Z3tz4gEHmDhG28Jzdbth7Ji13Ns/BZgMGnmdEaJHI3SbB23Y4d55EYpsEA89h4rRI/m37ny4n/5AELdK8bQcSpCUYidVy5uw2adkzyYYzexKbDRKI8Qt7e+82ybc77OQljh9/+OBjDxEhhgoSew6QqoXhB+laRsEoGAWjYPgDAD9GOVyujUXHAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0009-0008-3292-2882","institution":"Keio University Hospital: Keio Gijuku Daigaku Byoin","correspondingAuthor":true,"prefix":"","firstName":"Tomoko","middleName":"","lastName":"Seki","suffix":""},{"id":600373696,"identity":"df37ddbb-f8be-43d8-b805-45e14cad520f","order_by":1,"name":"Jitsuro Tsukada","email":"","orcid":"","institution":"Keio University Hospital: Keio Gijuku Daigaku Byoin","correspondingAuthor":false,"prefix":"","firstName":"Jitsuro","middleName":"","lastName":"Tsukada","suffix":""},{"id":600373697,"identity":"4895fd35-de08-4cf0-a96d-f670a6ffe6be","order_by":2,"name":"Yokoe Takamichi","email":"","orcid":"","institution":"Keio University Hospital: Keio Gijuku Daigaku Byoin","correspondingAuthor":false,"prefix":"","firstName":"Yokoe","middleName":"","lastName":"Takamichi","suffix":""},{"id":600373698,"identity":"9a8aeecb-a6ab-41c0-8d1f-8132e49ad1d7","order_by":3,"name":"Aiko Nagayama","email":"","orcid":"","institution":"Keio University Hospital: Keio Gijuku Daigaku Byoin","correspondingAuthor":false,"prefix":"","firstName":"Aiko","middleName":"","lastName":"Nagayama","suffix":""},{"id":600373699,"identity":"c428a58c-5b53-43ec-b1ac-7b0e6f5e4311","order_by":4,"name":"Maiko Takahashi","email":"","orcid":"","institution":"Keio University Hospital: Keio Gijuku Daigaku Byoin","correspondingAuthor":false,"prefix":"","firstName":"Maiko","middleName":"","lastName":"Takahashi","suffix":""},{"id":600373700,"identity":"98dc114f-33c6-494e-871a-4e6715e2e519","order_by":5,"name":"Kei Mizushima","email":"","orcid":"","institution":"Keio University Hospital: Keio Gijuku Daigaku Byoin","correspondingAuthor":false,"prefix":"","firstName":"Kei","middleName":"","lastName":"Mizushima","suffix":""},{"id":600373701,"identity":"f213459f-93bc-403f-a9bd-6f1a284ac20a","order_by":6,"name":"Haruka Takeshita","email":"","orcid":"","institution":"Keio University Hospital: Keio Gijuku Daigaku Byoin","correspondingAuthor":false,"prefix":"","firstName":"Haruka","middleName":"","lastName":"Takeshita","suffix":""},{"id":600373703,"identity":"657a3cf0-703c-4b09-b68a-44bf46d91890","order_by":7,"name":"Mizuki So","email":"","orcid":"","institution":"Keio University Hospital: Keio Gijuku Daigaku Byoin","correspondingAuthor":false,"prefix":"","firstName":"Mizuki","middleName":"","lastName":"So","suffix":""},{"id":600373704,"identity":"37c60a26-e304-42ac-84f5-5a0193a19338","order_by":8,"name":"Masahiro Jinzaki","email":"","orcid":"","institution":"Keio University Hospital: Keio Gijuku Daigaku Byoin","correspondingAuthor":false,"prefix":"","firstName":"Masahiro","middleName":"","lastName":"Jinzaki","suffix":""},{"id":600373707,"identity":"ea940904-fc8c-4a6b-b677-48bd87bd9621","order_by":9,"name":"Tetsu Hayashida","email":"","orcid":"","institution":"Keio University Hospital: Keio Gijuku Daigaku Byoin","correspondingAuthor":false,"prefix":"","firstName":"Tetsu","middleName":"","lastName":"Hayashida","suffix":""}],"badges":[],"createdAt":"2026-03-02 01:10:04","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9004468/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9004468/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104310095,"identity":"17e26d7c-dc9f-422e-914a-5b816592e543","added_by":"auto","created_at":"2026-03-10 10:50:06","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":774300,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCase 1 imaging\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA 31-year-old \u003cem\u003eBRCA1\u003c/em\u003e carrier (Case 1) with a small, MRI-only lesion in the left breast (arrow).\u003c/p\u003e\n\u003cp\u003eContrast-enhanced MRI revealed a 7.7 mm irregular non-mass enhancement with spiculated margins and fast-persistent enhancement kinetics. Neither digital breast tomosynthesis (DBT) nor ultrasonography (US) demonstrated any corresponding finding. Histopathology confirmed ductal carcinoma in situ (DCIS, pTis, pN0).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9004468/v1/6114ad1d358fbc2dc60d2a98.png"},{"id":104310094,"identity":"e05840ff-0a33-42ed-937d-33ee31ed370d","added_by":"auto","created_at":"2026-03-10 10:50:06","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":571000,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCase 5 imaging\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA 41-year-old \u003cem\u003eBRCA2\u003c/em\u003e carrier (Case 5) showing non-mass enhancement (NME) exclusively on MRI in the left breast (arrow). The lesion displayed linear clumped enhancement with slow-persistent kinetics. No abnormality was detected on DBT or US. Surgical pathology confirmed ductal carcinoma in situ (DCIS, intermediate grade, pTis, pN0).\u003c/p\u003e\n\u003cp\u003eIn addition, a right-sided invasive carcinoma (arrowhead), diagnosed prior to genetic testing, is also visible on MRI but was not detected during surveillance and was therefore not included in the present analysis.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9004468/v1/77856c0ed3ca36692b79ba83.png"},{"id":106842299,"identity":"a776dd8b-7c9f-4590-96d6-562f7537c123","added_by":"auto","created_at":"2026-04-14 03:41:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2454955,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9004468/v1/3c687f26-a5c3-42b6-9a5f-ddb1a88b03d7.pdf"}],"financialInterests":"","formattedTitle":"Imaging Characteristics of Breast Cancers Detected During MRI-Based Surveillance in Hereditary Breast and Ovarian Cancer Syndrome","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eHereditary breast and ovarian cancer syndrome (HBOC), caused mainly by pathogenic variants in \u003cem\u003eBRCA1\u003c/em\u003e and \u003cem\u003eBRCA2\u003c/em\u003e, confers a markedly increased lifetime risk of breast cancer, reported to range from approximately 48% to 76%, far exceeding that of the general female population (~\u0026thinsp;11%) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In Japan, partial public insurance coverage for HBOC-related genetic testing and management, primarily for individuals with a personal or family history suggestive of hereditary breast and ovarian cancer, was introduced in 2020 and has led to a steady increase in diagnosed cases. Given that breast cancer tends to occur at a younger age in \u003cem\u003eBRCA1\u003c/em\u003e carriers and somewhat later in \u003cem\u003eBRCA2\u003c/em\u003e carriers, early and sustained surveillance is indispensable for effective risk management.\u003c/p\u003e \u003cp\u003eBreast magnetic resonance imaging (MRI) is recognized as the most sensitive imaging modality for the early detection of breast cancer in high-risk women. Previous prospective studies have demonstrated MRI sensitivities ranging from 77% to 94%, substantially outperforming mammography (MMG) and ultrasonography (US), which show sensitivities of approximately 33%\u0026ndash;59% in this population [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Despite its advantages, MRI surveillance poses several challenges, including repeated exposure to gadolinium-based contrast agents, higher cost, longer examination times, and greater physical burden. Although risk-reducing mastectomy substantially reduces breast cancer risk, imaging-based surveillance is often favored in clinical practice in Japan, reflecting cosmetic, psychological, and social considerations.\u003c/p\u003e \u003cp\u003eThe imaging appearance of HBOC-associated breast cancer differs from that of sporadic disease and varies according to genetic background. \u003cem\u003eBRCA1\u003c/em\u003e-associated tumors frequently present as high-grade or triple-negative breast cancers, whereas \u003cem\u003eBRCA2\u003c/em\u003e-associated tumors are more commonly luminal-type and may manifest as ductal carcinoma in situ (DCIS), sometimes accompanied by calcifications on MMG [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. While MRI plays a cornerstone role of surveillance for high-risk individuals, data characterizing the multimodal imaging features of HBOC-related breast cancers in Japanese patients remain limited.\u003c/p\u003e \u003cp\u003eFrom January 2015 to December 2024, a total of 160 women with confirmed pathogenic variants in \u003cem\u003eBRCA1\u003c/em\u003e or \u003cem\u003eBRCA2\u003c/em\u003e underwent structured MRI-based breast surveillance at our institution. During follow-up, 11 breast cancers were newly diagnosed. Therefore, the purpose of this study was to characterize the multimodal imaging features of breast cancers detected during MRI-based surveillance in Japanese women with HBOC, comparing findings among MRI, mammography, and ultrasonography. This study was not designed to assess cancer detection rates or modality sensitivity, but rather to delineate characteristic imaging phenotypes and detectability patterns of MRI-detected lesions, particularly those occult on other imaging modalities.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study population\u003c/h2\u003e \u003cp\u003e We retrospectively reviewed women with hereditary breast and ovarian cancer syndrome (HBOC) who underwent MRI-based breast surveillance at Keio University Hospital between January 2015 and December 2024. During this period, 160 women with confirmed pathogenic variants in \u003cem\u003eBRCA1\u003c/em\u003e or \u003cem\u003eBRCA2\u003c/em\u003e were enrolled in the surveillance program. Among them, 11 patients were newly diagnosed with breast cancer during follow-up and constituted the study cohort for detailed imaging and pathological analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Imaging protocols\u003c/h2\u003e \u003cp\u003eAll patients underwent breast MRI using a 3.0-T system with a dedicated breast coil. Dynamic contrast-enhanced MRI was performed according to institutional protocols, and imaging findings were interpreted in accordance with the BI-RADS MRI lexicon.\u003c/p\u003e \u003cp\u003eDigital breast tomosynthesis (DBT) was performed in all cases. Standard bilateral craniocaudal (CC) and mediolateral oblique (MLO) views were reconstructed from tomosynthesis datasets.\u003c/p\u003e \u003cp\u003eWhole-breast ultrasonography (US) was initially performed as a screening examination without reference to MRI or mammography findings, using a high-frequency linear transducer (12\u0026ndash;18 MHz).\u003c/p\u003e \u003cp\u003eFor lesions detected on contrast-enhanced MRI but not identified during screening US, second-look ultrasonography was subsequently performed with reference to MRI findings, focusing on breast architecture and anatomical landmarks.\u003c/p\u003e \u003cp\u003eIn selected cases in which lesions were detected exclusively on MRI, MRI datasets, and CT datasets when available, were co-registered with real-time US using a Volume Navigation system (LOGIQ E9/E10, GE Healthcare) to facilitate targeted biopsy.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Imaging analysis\u003c/h2\u003e \u003cp\u003eAll imaging studies were reviewed retrospectively by board-certified radiologists specializing in breast imaging with knowledge of pathological results for the purpose of imaging\u0026ndash;pathology correlation. On MRI, lesion morphology (mass or non-mass enhancement), distribution pattern (focal, linear, or segmental), internal enhancement characteristics, and enhancement kinetics were evaluated according to the BI-RADS MRI lexicon.\u003c/p\u003e \u003cp\u003eFindings on digital breast tomosynthesis (DBT) and ultrasonography (US) were categorized according to the appropriate BI-RADS classification system for each modality. Lesion visibility on DBT and US was recorded as either \u0026ldquo;visible\u0026rdquo; or \u0026ldquo;not visible.\u0026rdquo; In this study, lesion visibility on ultrasonography was defined based on findings at second-look ultrasonography performed with reference to MRI findings, rather than on the initial screening examination.\u003c/p\u003e \u003cp\u003ePathological correlation was performed for all lesions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Statistical analysis\u003c/h2\u003e \u003cp\u003eDescriptive statistics were used to summarize patient characteristics, pathological findings, and lesion detection across imaging modalities.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1 Patient and lesion characteristics\u003c/h2\u003e\n \u003cdiv class=\"BlockQuote\"\u003e\n \u003cp\u003eAmong 160 women with confirmed pathogenic variants in \u003cem\u003eBRCA1\u003c/em\u003e or \u003cem\u003eBRCA2\u003c/em\u003e who underwent MRI-based breast surveillance at our institution between 2015 and 2024, 11 breast cancers were newly detected (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). The median age at diagnosis was 45 years (range, 31\u0026ndash;49 years). Two patients were carriers of \u003cem\u003eBRCA1\u003c/em\u003e variants, while nine carried \u003cem\u003eBRCA2\u003c/em\u003e variants.\u0026nbsp;\u003c/p\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eClinical and pathological characteristics of breast cancers detected during MRI-based surveillance in HBOC patients\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCase\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eBRCA\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePersonal history of BC\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFamily history of BC\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBiopsy method\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFinal pathology\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTumor type\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTumor size (cm)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNuclear grade\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHER2\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBreast surgery\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAxillary surgery\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eBRCA1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eExcisional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDCIS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDCIS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSLNB\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eBRCA2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eST-guided\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIDC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIDC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBCS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSLNB\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eBRCA2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUS-guided\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIDC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIDC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSLNB\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eBRCA2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eExcisional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDCIS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDCIS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBCS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eBRCA2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eExcisional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDCIS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDCIS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIntermediate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eBRCA2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUS-guided\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDCIS\u0026thinsp;+\u0026thinsp;LCIS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDCIS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBCS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eBRCA2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUS-guided\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDCIS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDCIS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBCS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSLNB\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eBRCA2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eExcisional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDCIS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDCIS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIntermediate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSLNB\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eBRCA1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUS-guided\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIDC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIDC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSLNB\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eBRCA2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUS-guided\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDCIS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDCIS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIntermediate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSLNB\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eBRCA2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUS-guided\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDCIS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDCIS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIntermediate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBCS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSLNB\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"14\"\u003e\u003cstrong\u003eFootnotes\u003c/strong\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"14\"\u003e\u0026bull; Tumor size represents the maximum pathological dimension.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"14\"\u003e\u0026bull; Hormone receptor (HR) and HER2 status are shown only for invasive ductal carcinoma (IDC) cases.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"14\"\u003e\u0026bull; One patient (Case \u003cspan class=\"InternalRef\"\u003e9\u003c/span\u003e) underwent non-contrast MRI due to contraindication to gadolinium-based contrast agents.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"14\"\u003e\u003cstrong\u003eAbbreviations\u003c/strong\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"14\"\u003eHBOC, hereditary breast and ovarian cancer;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"14\"\u003eBC, breast cancer;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"14\"\u003eDCIS, ductal carcinoma in situ;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"14\"\u003eIDC, invasive ductal carcinoma;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"14\"\u003eLCIS, lobular carcinoma in situ;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"14\"\u003eMRI, magnetic resonance imaging;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"14\"\u003eUS, ultrasound;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"14\"\u003eST, Streo\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"14\"\u003eNSM, nipple-sparing mastectomy;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"14\"\u003eBCS, breast-conserving surgery;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"14\"\u003eSLNB, sentinel lymph node biopsy;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"14\"\u003eHR, hormone receptor;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"14\"\u003eN/A, not applicable.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003eAll lesions were unilateral, and three patients had a prior history of breast cancer in the contralateral breast. Pathological examination revealed ductal carcinoma in situ (DCIS) in seven cases and invasive ductal carcinoma (IDC) in four cases. Most tumors were low- to intermediate-grade, estrogen receptor\u0026ndash;positive and HER2-negative, consistent with a predominantly luminal phenotype. All invasive cancers were small (\u0026le;\u0026thinsp;0.5 cm, pT1a) and node-negative.\u003c/p\u003e\n \u003cp\u003eSurgical management included nipple-sparing mastectomy in six patients and breast-conserving surgery in five patients. Sentinel lymph node biopsy was performed in seven patients.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2 Imaging findings\u003c/h2\u003e\n \u003cdiv class=\"BlockQuote\"\u003e\n \u003cp\u003eImaging findings for all lesions are summarized in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. All 11 breast cancers were detected on MRI, including one case evaluated without contrast enhancement. On MRI, lesions most commonly presented as non-mass enhancement or small masses with irregular margins. Non-mass enhancement frequently showed linear or segmental distribution patterns, with clumped or heterogeneous internal enhancement. Enhancement kinetics were predominantly fast or medium in the initial phase, followed by persistent enhancement in most cases. Imaging findings in the non-contrast enhanced case were considered illustrative but were not directly comparable with those obtained using contrast-enhanced MRI.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eImaging characteristics of breast cancers detected during MRI-based surveillance\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCase\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMRI FGT\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBPE\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMRI size (mm)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLocation\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMRI presentation\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDistribution\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eInternal enhancement\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eKinetic pattern\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDBT visible\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDBT findings\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDBT category\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eUS visible\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eUS findings\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eUS category\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHeterogeneous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMinimal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eL, A/C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNME\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHomogeneous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFast\u0026ndash;persistent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHeterogeneous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMinimal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eR, E\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMass\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHomogeneous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFast\u0026ndash;persistent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCalcifications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHeterogeneous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMinimal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eR, A/C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNME\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSegmental\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eClumped\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedium\u0026ndash;persistent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCalcifications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIrregular mass\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHeterogeneous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eL, A/C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMass\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHomogeneous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFast\u0026ndash;washout\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eScattered\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMild\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eL, D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMass\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHeterogeneous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedium\u0026ndash;persistent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHeterogeneous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMild\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eR, A/B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMass\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHomogeneous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedium\u0026ndash;persistent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIrregular mass\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHeterogeneous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMild\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eL, D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMass\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHeterogeneous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFast\u0026ndash;persistent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIrregular mass\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eScattered\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMinimal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eL, A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNME\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLinear\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eClumped\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSlow\u0026ndash;persistent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIrregular mass\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eScattered\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eR, C/D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNME\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSegmental\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHeterogeneous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFast\u0026ndash;persistent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHeterogeneous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMild\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eR, B/D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNME\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSegmental\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHeterogeneous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFast\u0026ndash;persistent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"15\"\u003e\u003cstrong\u003eFootnotes\u003c/strong\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cul\u003e\n \u003cli\u003eCase 9 underwent non-contrast MRI due to contraindication to gadolinium-based contrast agents.\u003c/li\u003e\n \u003cli\u003eLesion visibility on ultrasonography refers to detectability on second-look ultrasonography performed with reference to MRI findings.\u003c/li\u003e\n \u003cli\u003eWhole-breast ultrasonography was initially performed as a screening examination without reference to MRI or mammography findings.\u003c/li\u003e\n \u003c/ul\u003e\n \u003cp\u003e\u003cstrong\u003eAbbreviations\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eFGT, fibroglandular tissue;\u003c/p\u003e\n \u003cp\u003eBPE, background parenchymal enhancement;\u003c/p\u003e\n \u003cp\u003eMRI, magnetic resonance imaging;\u003c/p\u003e\n \u003cp\u003eDBT, digital breast tomosynthesis;\u003c/p\u003e\n \u003cp\u003eUS, ultrasonography;\u003c/p\u003e\n \u003cp\u003eNME, non-mass enhancement.\u003c/p\u003e\n \u003cp\u003eIn contrast, digital breast tomosynthesis (DBT) demonstrated limited detectability. Only two lesions were visible on DBT, both of which were associated with calcifications. No architectural distortion or focal density corresponding to MRI-detected non-mass enhancement was identified in the remaining cases.\u003c/p\u003e\n \u003cp\u003eUltrasonography showed poor detectability. At second-look ultrasonography performed with reference to MRI findings, lesions were identified in four cases, typically appearing as small, irregular hypoechoic masses. The remaining lesions were not visualized on ultrasonography despite targeted evaluation.\u003c/p\u003e\n \u003cp\u003eRepresentative MRI-only lesions that were occult on both DBT and ultrasonography are shown in Figs.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3 Representative cases\u003c/h2\u003e\n \u003cp\u003eRepresentative imaging findings are shown in two cases in which lesions were detected exclusively on MRI and were occult on both digital breast tomosynthesis and ultrasonography.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eCase 1\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003ewas a 31-year-old woman with a pathogenic \u003cem\u003eBRCA1\u003c/em\u003e variant undergoing MRI-based surveillance. Contrast-enhanced MRI demonstrated a small area of focal non-mass enhancement in the left breast. No corresponding abnormality was identified on DBT or ultrasonography, including second-look examination. Excision biopsy revealed ductal carcinoma in situ.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eCase 5\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003ewas a 41-year-old woman with a pathogenic \u003cem\u003eBRCA2\u003c/em\u003e variant. Contrast-enhanced MRI showed non-mass enhancement with an irregular distribution pattern. The lesion was not visualized on DBT or on targeted second-look ultrasonography. Excisional biopsy confirmed ductal carcinoma in situ.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eIn this institutional series of 160 hereditary breast and ovarian cancer (HBOC) patients undergoing MRI-based surveillance, 11 breast cancers were detected between 2015 and 2024. All lesions were identified on MRI, highlighting its high sensitivity for early detection in this high-risk population. Most lesions presented as small non-mass enhancements (NMEs) or low-grade ductal carcinoma in situ (DCIS), indicating that MRI surveillance preferentially detects early-stage, clinically meaningful disease rather than incidental findings. Although the number of detected cancers was modest, HBOC surveillance cohorts are inherently limited, and our findings provide valuable imaging\u0026ndash;pathology correlation data in a Japanese population.\u003c/p\u003e \u003cp\u003eOur cohort showed a predominance of \u003cem\u003eBRCA2\u003c/em\u003e-associated cancers (82%), most of which were luminal-type and low- to intermediate-grade DCIS. This distribution is consistent with previous reports indicating that \u003cem\u003eBRCA2\u003c/em\u003e-related breast cancers frequently present as hormone receptor\u0026ndash;positive disease or DCIS, whereas \u003cem\u003eBRCA1\u003c/em\u003e-associated cancers tend to be high-grade or triple-negative invasive carcinomas [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Notably, the BRCA1-associated lesion (case \u003cspan refid=\"FPar1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) in our cohort presented as MRI-only DCIS, illustrating that genotype-related imaging patterns may overlap and that MRI remains essential for detecting early intraductal disease across mutation subtypes.\u003c/p\u003e \u003cp\u003eThe superiority of MRI observed in our series mirrors findings from landmark prospective studies. Warner et al. reported MRI sensitivities of approximately 77% compared with 36% for mammography and 33% for ultrasound in \u003cem\u003eBRCA1/2\u003c/em\u003e mutation carriers [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], while Kriege et al. demonstrated significantly higher cancer detection rates with MRI than with mammography in women with hereditary or familial breast cancer risk [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Long-term experience from European HBOC surveillance programs further supports the central role of MRI in high-risk screening [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Our results emphasize that even digital breast tomosynthesis (DBT), despite improved contrast resolution, remains limited in detecting non-calcified NMEs. Representative MRI-only lesions in our cohort (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) illustrate how subtle ductal or segmental enhancements within dense glandular tissue may remain undetectable on both DBT and US. From a clinical perspective, detection of such MRI-only DCIS lesions may be particularly relevant in HBOC patients, in whom early identification of precursor lesions can inform individualized risk-reduction strategies, including the timing and extent of surgery.\u003c/p\u003e \u003cp\u003eThe present study also highlights a practical challenge in HBOC surveillance: localization and biopsy of MRI-only lesions. MRI-guided biopsy systems are not widely available in Japan and many Asian clinical settings. In our practice, fusion-guided targeted ultrasonography using a Volume Navigation system enabled lesion localization and tissue sampling in selected MRI-detected lesions. By bridging the gap between high-sensitivity detection and tissue diagnosis, this approach offers a realistic diagnostic pathway in environments where MRI-guided biopsy is not readily accessible. Wider adoption of such techniques may improve the feasibility and effectiveness of MRI-based surveillance programs.\u003c/p\u003e \u003cp\u003eThe effectiveness of this imaging-based surveillance and biopsy strategy is further supported by surgical outcomes in our risk management practice. At our institution, only two occult carcinomas were identified among 43 risk-reducing mastectomy procedures (4.7%). This incidence is lower than that reported in the nationwide Japanese HBOC registry analysis by Yamauchi et al., who identified occult breast cancer in 6 of 53 prophylactic mastectomy specimens (11.3%) despite thorough preoperative assessment with mammography, ultrasonography, and MRI [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. These findings suggest that high-quality MRI surveillance combined with lesion-directed biopsy strategies may improve preoperative disease detection and reduce unexpected pathological findings at risk-reducing surgery.\u003c/p\u003e \u003cp\u003eThis study has several limitations. It was retrospective and conducted at a single institution, and the number of detected cancers was limited. However, HBOC surveillance cohorts are inherently small, and the consistent MRI detectability and imaging\u0026ndash;pathology concordance across cases strengthen the reliability of our observations. In addition, a single experienced breast radiologist performed imaging review, which may limit generalizability. Future studies incorporating multicenter data, quantitative MRI metrics such as apparent diffusion coefficient values, abbreviated MRI protocols [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], and artificial intelligence\u0026ndash;assisted lesion matching may further refine surveillance strategies for high-risk women.\u003c/p\u003e \u003cp\u003eIn conclusion, breast cancers detected during MRI-based surveillance in HBOC patients frequently present as small, non-mass, and non-calcified lesions that are occult on DBT and ultrasonography. Recognition of these imaging characteristics, together with the implementation of practical lesion localization and biopsy strategies, is essential for optimizing early detection and risk-reduction management in hereditary breast cancer.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThis study expands on existing knowledge by delineating the distinct imaging characteristics of HBOC-related breast cancers detected during MRI surveillance in Japanese patients. Most lesions are small, non-mass enhancements detectable only by MRI. Recognizing these patterns and correlating them across imaging modalities may improve early diagnosis and support practical biopsy strategies in high-risk women.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompliance with Ethical Standards\u003cbr\u003e\u0026nbsp;Conflict of Interest\u003cbr\u003e\u003c/strong\u003eThe authors declare that they have no conflict of interest.\u003cbr\u003e\u0026nbsp;\u003cstrong\u003e\u003cbr\u003e\u0026nbsp;Ethical approval\u003cbr\u003e\u003c/strong\u003eThis study was approved by Institutional Review Board (IRB) at Keio University School of Medicine (#20150170). Patients were appropriately opted out of the research use of their clinical data in accordance with institutional guidelines. All procedures were conducted in compliance with the principles of the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed consent\u003cbr\u003e\u003c/strong\u003eAn opt-out approach was used to provide patients with the opportunity to refuse participation.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eMomozawa Y, Sasai R, Usui Y, Shiraishi K, Iwasaki Y, Taniyama Y, et al. Expansion of Cancer Risk Profile for \u003cem\u003eBRCA1\u003c/em\u003e and \u003cem\u003eBRCA2\u003c/em\u003e Pathogenic Variants. JAMA Oncol. 2022;8:871\u0026ndash;8.\u003c/li\u003e\n \u003cli\u003eWarner E, Plewes DB, Hill KA, Causer PA, Zubovits JT, Jong RA, et al. Surveillance of \u003cem\u003eBRCA1\u003c/em\u003e and \u003cem\u003eBRCA2\u003c/em\u003e mutation carriers with magnetic resonance imaging, ultrasound, mammography, and clinical breast examination. JAMA. 2004;292:1317\u0026ndash;1325.\u003c/li\u003e\n \u003cli\u003eKriege M, Brekelmans CT, Boetes C, Besnard PE, Zonderland HM, Obdeijn IM, et al. Efficacy of MRI and mammography for breast-cancer screening in women with a familial or genetic predisposition. N Engl J Med. 2004;351:427\u0026ndash;437.\u003c/li\u003e\n \u003cli\u003eKrammer J, Pinker-Domenig K, Robson ME, G\u0026ouml;nen M, Bernard-Davila B, Morris EA, et al. Breast cancer detection and tumor characteristics in \u003cem\u003eBRCA1\u003c/em\u003e and \u003cem\u003eBRCA2\u003c/em\u003e mutation carriers. Breast Cancer Res Treat. 2017;163:565\u0026ndash;571.\u003c/li\u003e\n \u003cli\u003eVeltman J, Mann R, Kok T, Obdeijn IM, Hoogerbrugge N, Blickman JG, et al. Breast tumor characteristics of \u003cem\u003eBRCA1\u003c/em\u003e and \u003cem\u003eBRCA2\u003c/em\u003e gene mutation carriers on MRI. Eur Radiol. 2008;18:931\u0026ndash;938.\u003c/li\u003e\n \u003cli\u003eBick U, Engel C, Krug B, Heindel W, Fallenberg EM, Rhiem K, et al. High-risk breast cancer surveillance with MRI: 10-year experience from the German Consortium for Hereditary Breast and Ovarian Cancer. Breast Cancer Res Treat. 2019;175:217\u0026ndash;228.\u003c/li\u003e\n \u003cli\u003eYamauchi H, Okawa M, Yokoyama S, Nakagawa C, Yoshida R, Suzuki K, et al. High rate of occult cancer found in prophylactic mastectomy specimens despite thorough presurgical assessment with MRI and ultrasound: findings from the Hereditary Breast and Ovarian Cancer Registration 2016 in Japan. Breast Cancer Res Treat. 2018;172:679\u0026ndash;687.\u003c/li\u003e\n \u003cli\u003eKuhl CK. Abbreviated breast MRI: state of the art and future directions. Radiology. 2024;311(1):12\u0026ndash;27.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Hereditary Breast and Ovarian Cancer syndrome (HBOC), breast MRI, surveillance, BRCA1 and BRCA2","lastPublishedDoi":"10.21203/rs.3.rs-9004468/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9004468/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground:\u003c/h2\u003e \u003cp\u003eMagnetic 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.\u003c/p\u003e\u003ch2\u003eMethods:\u003c/h2\u003e \u003cp\u003eWe retrospectively reviewed 160 women with pathogenic variants in \u003cem\u003eBRCA1\u003c/em\u003e or \u003cem\u003eBRCA2\u003c/em\u003e 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.\u003c/p\u003e\u003ch2\u003eResults:\u003c/h2\u003e \u003cp\u003eAll 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 \u003cem\u003eBRCA2\u003c/em\u003e-associated, luminal-type, and low- to intermediate-grade. All invasive cancers were \u0026le;\u0026thinsp;0.5 cm in size and node-negative.\u003c/p\u003e\u003ch2\u003eConclusion:\u003c/h2\u003e \u003cp\u003eBreast 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.\u003c/p\u003e","manuscriptTitle":"Imaging Characteristics of Breast Cancers Detected During MRI-Based Surveillance in Hereditary Breast and Ovarian Cancer Syndrome","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-10 10:50:01","doi":"10.21203/rs.3.rs-9004468/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"65de01fe-bc5f-4370-a697-fe8ee71151d3","owner":[],"postedDate":"March 10th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-14T03:40:52+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-10 10:50:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9004468","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9004468","identity":"rs-9004468","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}