Using AI to improve safety in minimally invasive surgery for uterine cancers
Implementation of Surgical Safety and Intraoperative Metastasis Identification Through Deep Learning: Multicentric Video Collection for Minimally Invasive Sentinel Lymph Node Dissection in Uterine Malignancies
Fondazione Policlinico Universitario Agostino Gemelli IRCCS · NCT06619002
This study is testing if using AI to analyze surgical videos can make minimally invasive surgeries for uterine cancers safer and help doctors spot problems during the operation.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 100 (estimated) |
| Ages | 18 Years to 99 Years |
| Sex | Female |
| Sponsor | Fondazione Policlinico Universitario Agostino Gemelli IRCCS (other) |
| Drugs / interventions | radiation |
| Locations | 2 sites (Roma and 1 other locations) |
| Trial ID | NCT06619002 on ClinicalTrials.gov |
What this trial studies
This study focuses on enhancing surgical safety and identifying intraoperative metastasis in patients undergoing minimally invasive sentinel lymph node dissection for endometrial and cervical cancers. By utilizing deep learning algorithms to analyze surgical videos, the research aims to document and quantify intraoperative events, thereby identifying potential complications and improving surgical outcomes. The study will collect multicentric video data to develop AI tools that can provide real-time decision support during surgeries. This innovative approach seeks to address the limitations of current sentinel lymph node procedures and improve patient management.
Who should consider this trial
Good fit: Ideal candidates for this study are women over 18 years old who are undergoing minimally invasive sentinel lymph node dissection for endometrial or cervical cancers.
Not a fit: Patients with previous pelvic radiotherapy treatments or severe endometriosis may not benefit from this study.
Why it matters
Potential benefit: If successful, this study could significantly reduce surgical complications and improve outcomes for patients with uterine malignancies.
How similar studies have performed: Other studies have shown promise in using AI for surgical video analysis, indicating potential success for this novel approach.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * Women undergoing MIS sentinel lymph node dissection for endometrial or cervical cancers * Availability of video * Age \>18 years * Willingness to participate in the study and to provide informed consent Exclusion Criteria: * Previous pelvic radiotherapy treatments * Severe endometriosis or other conditions able to alter the pelvic anatomy
Where this trial is running
Roma and 1 other locations
- Fondazione Policlinico Universitario A. Gemelli IRCCS — Roma, Italy (RECRUITING)
- Fondazione Policlinico Universitario A. Gemelli IRCCS — Rome, Italy (RECRUITING)
Study contacts
- Principal investigator: Matteo PAVONE, MD — Fondazione Policlinico Universitario A. Gemelli, IRCCS, Rome Italy; IHU Strasbourg; IRCAD Strasbourg; Icube Strasbourg;
- Study coordinator: Matteo PAVONE, MD
- Email: matteo.pavone@guest.policlinicogemelli.it
- Phone: 00390630151
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.
Conditions: Endometrial Cancer, Cervical Cancer, Deep Learning, Artificial Intelligence, endometrial cancer, cervical cancer, deep learning, computer vision