AI-Powered Surgical Tool May Help Surgeons Detect Breast…

AI-Powered Surgical Tool May Help Surgeons Detect Breast Cancer Tissue in Real Time TALMedora News Desk Breast cancer surgery aims to remove all cancerous tissue while preserving as much healthy tissue as possible. However, achieving completely cancer-free surgical margins remains a significant challenge, particularly in patients with infiltrative tumor types where microscopic cancer cells can extend beyond what is visible during surgery. A new study published in Scientific Reports highlights an innovative technology that may help surgeons identify cancerous tissue instantly during an operation. Researchers demonstrated that a technique called Optical Emission Spectroscopy (OES), combined with machine learning, can differentiate between healthy and cancerous breast tissue while surgical cutting is taking place. The approach could potentially reduce repeat surgeries and improve surgical outcomes for patients with breast cancer. Surgical removal remains a cornerstone of treatment for early-stage breast cancer. One of the most important goals during surgery is achieving a clear margin, meaning no cancer cells remain at the edges of the removed tissue. When cancer cells are found at the surgical margin, patients often require a second operation to remove additional tissue. Depending on the tumor subtype, reoperation rates can range from approximately 16% to more than 40%. Repeat procedures can increase healthcare costs, delay further treatment, and create additional emotional and physical stress for patients. Modern breast surgery frequently uses electrosurgical instruments that cut tissue using electrical energy. During this process, tiny sparks are generated as tissue is divided. Researchers developed a system capable of analyzing the light emitted by these sparks in real time. This ligh