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Background: Supplemental screening with breast MRI is recommended annually for patients who have greater than 20% lifetime risk for breast cancer. While there is robust data regarding features of mammographic screen-detected breast cancers, there is limited data regarding MRI-screen-detected cancers.
Patients And Methods: Screening breast MRIs performed between August 1, 2016 and July 30, 2022 identified 50 screen-detected breast cancers in 47 patients. Clinical and imaging features of all eligible cancers were recorded.
Results: During the study period, 50 MRI-screen detected cancers were identified in 47 patients. The majority of MRI-screen detected cancers (32/50, 64%) were invasive. Pathology revealed ductal carcinoma in situ (DCIS) in 36% (18/50), invasive ductal carcinoma (IDC) in 52% (26/50), invasive lobular carcinoma in 10% (5/50), and angiosarcoma in 2% (1/50). The majority of patients (43/47, 91%) were stage 0 or 1 at diagnosis and there were no breast cancer-related deaths during the follow-up periods. Cancers presented as masses in 50% (25/50), nonmass enhancement in 48% (25/50), and a focus in 2% (1/50). DCIS was more likely to present as nonmass enhancement (94.4%, 17/18), whereas invasive cancers were more likely to present as masses (75%, 24/32) (P < .001). All cancers that were stage 2 at diagnosis were detected either on a baseline exam or more than 4 years since the prior MRI exam.
Conclusion: MRI screen-detected breast cancers were most often invasive cancers. Cancers detected by MRI screening had an excellent prognosis in our study population. Invasive cancers most commonly presented as a mass.
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http://dx.doi.org/10.1016/j.clbc.2023.09.012 | DOI Listing |
Eur J Radiol
August 2025
Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, PA, USA.
Purpose: To evaluate whether AI-assisted ipsilateral tissue matching in digital breast tomosynthesis (DBT) reduces localization errors beyond typical tumor boundaries, particularly for non-expert radiologists. The technology category is deep learning.
Materials And Methods: The study consisted of two parts.
Int J Cancer
August 2025
Division of Molecular Pathology, Netherlands Cancer Institute, Amsterdam, The Netherlands.
The lower all-cause mortality in women with Ductal carcinoma in situ (DCIS) compared with the general population has been hypothesized to be due to a "healthy-user effect," but this has not been studied in large cohorts. In a population-based, retrospective cohort study comprising 18,942 women with primary DCIS between 1999 and 2015 in the Netherlands, the cumulative incidence of breast cancer death (BCD) was estimated using death by other cause as a competing risk. The cause-specific mortality risk of women with DCIS was compared with that of the Dutch female population.
View Article and Find Full Text PDFActa Radiol
August 2025
Centre for Medical Image Science and Visualization (CMIV), Linköping University, Linköping Sweden.
BackgroundArtificial intelligence (AI)-based systems have the potential to increase the efficiency and effectiveness of breast cancer screening programs but need to be carefully validated before clinical implementation.PurposeTo retrospectively evaluate an AI system to safely reduce the workload of a double-reading breast cancer screening program.Material and MethodsAll digital mammography (DM) screening examinations of women aged 40-74 years between August 2021 and January 2022 in Östergötland, Sweden were included.
View Article and Find Full Text PDFLancet Digit Health
August 2025
Medical Imaging Department, Radboud University Nijmegen Medical Centre, Nijmegen, Netherlands; Department of Radiology, Antoni van Leeuwenhoek Netherlands Cancer Institute, Amsterdam, Netherlands.
Background: Breast cancer screening programmes have shown to reduce mortality, but current methods face challenges such as limited mammographic sensitivity, limited resources, and variability in radiologist expertise. Artificial intelligence (AI) offers potential to improve screening accuracy and efficiency. This study simulated different screening scenarios, evaluating the performance of population-based breast cancer screening when using an AI system as a stand-alone reader or second reader.
View Article and Find Full Text PDFActa Oncol
August 2025
Icelandic Cancer Registry, Icelandic Cancer Society, Reykjavik, Iceland; Faculty of Medicine, University of Iceland, Reykjavik, Iceland.
Background And Purpose: Organised mammography screening reduces breast cancer mortality by 30-40% in women aged 50-69. Despite limited evidence for women aged 40-49, screening guidelines are trending toward younger ages. Iceland has offered biennial screening to women aged 40-69 since 1987.
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