Intraoperative Detection of Breast Cancer by Electrosurgical Gas Analysis and Artificial Intelligence

Overview

The aim of this clinical trial is to assess the feasibility of training a device capable of distinguishing various gases emitted by tissues cauterized by an electrosurgical unit during a breast cancer resection surgery. The patients to be enrolled will be women over 18 years old diagnosed with breast cancer who are indicated for conservative breast cancer resection surgery as treatment. The main questions to be answered are: The specificity and sensitivity of the device in detecting margins compromised with tumor cells in resection surgeries. Evaluate the applicability of the device in breast cancer surgeries for real-time detection of margins. Evaluate the differences in the pattern of gases emitted in tumor cells vs normal cells. By consenting, the study patients will allow the investigative team to access the clinical record, results of images, post-surgical biopsies, recording of the surgery while preserving the patient's anonymity, and the installation of the gas detection device. This device does not alter the flow of the surgery and does not add additional risk to it.

The study will consist of measuring gases emitted during surgery. Prior to this, the device will be trained in the detection and recognition of the most prevalent gases in cancerous tissue. This will enable the AI to detect and classify cancerous breast tissue from healthy tissue. The study will include patients with different types and subtypes of breast cancer, such as ductal carcinoma in situ invasive ductal carcinoma, invasive lobular carcinoma, triple-negative breast cancer, human epidermal growth factor receptor 2 positive breast cancer, and hormone receptor-positive breast cancer. These types and subtypes reflect the diversity and complexity of breast cancer and may influence the performance and accuracy of the BCGC device. During the clinical testing phase, the laboratory-acquired tissue detection capability will be evaluated in a real situation. For this, the device will be connected to a sterile PVC hose directly connected to a smoke extractor associated with the electrosurgical unit that will cauterize the tissues. To evaluate the sensitivity, specificity, and accuracy of the device, the AI's detection will be compared with the quick biopsy and the deferred biopsy of the surgical piece. For this, access will be obtained to the histological reports and the surgery will be recorded to identify margins. The device will be calibrated once a month with gases of known nature, a maximum variability of 5% will be tolerated. If a greater variability is detected at the time of calibration, it will be changed to every 2 weeks. The information will be anonymized and stored on an SSD unit and will be deleted 5 years after the completion of the study.