U.S. FDA as granted Paige Breakthrough Device Designation for Breast Lymph Node Cancer Detection

Paige, a renowned global leader in comprehensive digital pathology solutions and clinical AI applications for cancer diagnosis, has made a groundbreaking announcement. The U.S. Food and Drug Administration (FDA) has granted Paige Lymph Node1 the prestigious Breakthrough Device Designation. This pioneering AI application is specifically developed for the detection of breast cancer metastases within lymph node tissue.

This marks a historic milestone as Paige Lymph Node becomes the first AI application of its kind to receive the coveted Breakthrough Device Designation from the FDA. This designation is typically reserved for technologies that have the potential to significantly enhance the diagnosis or treatment of life-threatening or debilitating diseases, where timely availability is paramount due to either the absence of approved alternatives or the technology offering substantial advantages over existing approved options.

In the context of breast cancer, the assessment of lymph nodes is of vital importance for predicting patient outcomes and guiding treatment decisions. Nonetheless, the traditional pathologic assessment process is known to be time-consuming and prone to errors. Paige Lymph Node leverages the power of artificial intelligence to expedite and enhance this crucial evaluation. It provides valuable assistance to pathologists in swiftly and accurately identifying even small lymph node metastases, ensuring that breast cancer patients receive the most effective disease management.

Paige Lymph Node is classified as an in vitro diagnostic medical device software and is built upon a deep learning model trained on a substantial dataset of over 32,000 digitized hematoxylin & eosin (H&E) lymph node slides. This advanced AI application exhibits near-perfect sensitivity in detecting breast cancer metastases. Whenever suspicious regions are detected in the lymph node tissue, Paige Lymph Node expertly highlights them for further examination by the pathologist, streamlining the diagnostic

Process. This algorithm not only saves valuable time for pathologists but also equips them with vital information to support their diagnoses, particularly in the face of increasing demands and resource constraints.


Harvard Medical School - Leadership in Medicine Southeast Asia47th IHF World Hospital CongressHealthcare CNO SummitHealthcare CMO Summit