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Background
Breast cancer is the most frequently diagnosed cancer in the U.S. Introduction of screening mammography in 1976, and subsequent increases in its use, has led to significant increase in survival rates and decrease in mortality rates via early detection of malignancy. More recently in the 1990s, the introduction of digital breast tomosynthesis has led to better visibility of cancer. However, despite these advances in breast cancer screening, there are still missed cancers. BI-RADS defines false negatives as breast cancers that are diagnosed for up to 1 year after negative or benign mammograms. A total of 121,751 screening and diagnostic mammograms were performed between 2015 and 2020 across two large institutions in two different states and coasts. All cases of false negatives were reviewed and analyzed. The false negative rate was 0.1% (133/121,751). The cases were reviewed to ascertain possible causes for the false negative. Correlation was made with patient factors, imaging findings, cancer types, and hormone receptor status. The aim of this presentation is to review the data found at our institutions, and to provide a case-based review of false negative mammograms and provide solutions to help radiologists in detecting these cancers.

Educational Goals / Teaching Points
To review the basics of interpreting mammograms, including search patterns and technique, the reasons why errors in interpreting mammograms may occur, and the steps radiologists can take to avoid missing breast cancers when interpreting mammograms.

Key Anatomic/Physiologic Issues and Imaging Findings/Techniques
Of the 133 false negative mammogram cases, we found the patient age ranged from 24 to 89 years; 28% of cases had a prior history of breast cancer, and 51% had heterogeneously dense breasts. Cancers were mostly commonly missed on diagnostic mammograms (81%), and 77% of the mammograms had tomosynthesis. The most common imaging feature was one mass (49%), followed by calcification (19%) and asymmetry (13%). The most common type of cancer was invasive ductal carcinoma (54%). Most commonly, cancers were hormone receptor positive (56%). In 9% of cases, the lesion was not completely included on the image. Reasons why cancers may be missed can be divided into three broad categories: patient factors, healthcare team factors, and other factors. Patient factors include getting lost to follow up and the presence of dense breast tissue, as the sensitivity for mammography measures 30–64% for extremely dense breasts versus 76–98% for fatty breasts. Healthcare team factors include errors by radiologists and technologists, including errors due to biases. This presentation will cover cases and strategies to reduce these errors, including double reading, using multiple views, checklists, reducing distractions, and the use of new artificial intelligence tools. Other factors include tumor location and type, which will also be reviewed.

Conclusion
Missed breast cancers can delay access to life-saving therapies. With proper awareness of reasons why cancers are frequently missed on mammography and ways to mitigate this, radiologists may be better equipped to reduce their false negative rate.