AI analysis of electrosurgical smoke to detect cancer during breast-conserving surgery
Intraoperative Detection of Breast Cancer by Electrosurgical Gas Analysis and Artificial Intelligence
This project will test whether an AI-connected device can read gases from cauterized tissue to help surgeons find cancerous margins in women having breast-conserving surgery.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 30 (estimated) |
| Ages | 18 Years and up |
| Sex | Female |
| Sponsor | Pontificia Universidad Catolica de Chile Academic / other |
| Locations | 2 sites (Santiago, Santiago Centro and 1 other locations) |
| Trial ID | NCT07131735 on ClinicalTrials.gov |
What this trial studies
The device is first trained in the lab to recognize gases released from cancerous versus normal breast tissue, then connected during surgery to sample electrosurgical smoke via a sterile hose to a smoke extractor. The AI will classify tissue in real time and its calls will be compared with rapid intraoperative biopsies and final histology to measure sensitivity, specificity, and accuracy. The trial will include multiple breast cancer subtypes to capture biological variability and the surgeries will be recorded for margin mapping. The device will undergo monthly calibration with known gases to maintain performance within a 5% variability threshold.
Who should consider this trial
Good fit: Women aged 18 or older with histologically confirmed breast cancer who are scheduled for breast-conserving surgery at the participating centers and can give informed consent.
Not a fit: Pregnant or lactating women, patients allergic to device components, or those not undergoing breast-conserving surgery are unlikely to benefit from this device.
Why it matters
Potential benefit: If successful, the device could help surgeons identify cancer at surgical margins in real time, potentially reducing reoperation rates and improving margin clearance.
How similar studies have performed: Early research using volatile compound or electrosurgical smoke analysis with machine learning has shown promising preliminary results but remains experimental and not yet standard practice.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * Histologically confirmed diagnosis of malignant breast cancer * Scheduled for BCS at the Hospital UC * Able and willing to provide informed consent Exclusion Criteria: * Pregnant or lactating women * Patients with known hypersensitivity or allergy to any component of the BCGC device * Participation in another interventional clinical trial within 30 days prior to enrolment
Where this trial is running
Santiago, Santiago Centro and 1 other locations
- Hospital Clínico UC CHRISTUS — Santiago, Santiago Centro, Chile (Recruiting)
- Facultad de medicina UC — Santiago, Santiago Metropolitan, Chile (Active_not_recruiting)
Study contacts
- Study coordinator: Maximiliano L Mariné
- Email: maxmarine@uc.cl
- Phone: +56952084996
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.