When Enlarged Axillary Lymph Nodes Are NOT Cancer: A Radiology AI Case Study
Introduction In modern radiology, few findings generate as much diagnostic uncertainty—and potential medicolegal risk—as axillary lymphadenopathy detected during routine breast imaging. With the rapid integration of Artificial Intelligence (AI) into clinical workflows, radiologists now face a dual challenge: interpreting complex imaging patterns while leveraging AI tools to improve diagnostic accuracy. This case—a 48-year-old woman undergoing routine screening—highlights a critical reality in contemporary imaging: Not all enlarged lymph nodes are cancer. The rise of AI-powered clinical decision support systems is transforming how radiologists differentiate between malignant and benign etiologies, especially in ambiguous presentations such as bilateral axillary lymph node enlargement. Clinical Background Patient Story (High-Engagement Narrative) A 48-year-old woman presents for routine mammographic screening. Five years earlier, her mammogram was completely normal. ...