Artificial Intelligence-Based Sentinel Lymph Node Metastasis Detection in Cervical Cancer †

Abstract

Currently, pathologists use ultrastaging to detect whether cancer has spread to the lymph nodes. This process is time-consuming and expensive. Our pilot study explored the use of a deep learning algorithm to help detect cancer spread to lymph nodes of early-stage cervical cancer patients. Using this technology could make the detection process faster, more efficient, and less costly. We evaluated an algorithm that was originally designed to identify cancer spread to lymph nodes in breast and colon cancer in cervical cancer patients. The study included 21 women with different types of early-stage cervical cancer. The algorithm was used to analyze 47 lymph node samples and successfully identified all cases where cancer had spread, showing 100% accuracy. Although the algorithm was initially developed for other cancers, it proved highly effective in this new population. More prospective research in a larger group of patients is needed to confirm its cost-effectiveness.