NCT07397000

AI-Based Real-Time Detection of Surgical Smoke Using Endoscopic Data

Development of AI-Based Approaches for Automated Real-Time Detection of Surgical Smoke Using Endoscopic Image and Video Data

• Status: Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 30 (estimated)
• Sponsor: University Hospital Tuebingen · Academic / Other
• Sex: Female
• Age: 18 Years
• Healthy volunteers: Not accepted

Summary

The goal of this observational, prospective monocentric pilot study is to generate a pilot dataset to train a computer-assisted model for automatic, intraoperative detection of surgical smoke gas. Women with indications for laparoscopic evaluation requiring the use of HF surgery (expecting the formation of smoke gas) and a smoke evacuation system (Karl Storz S-Pilot) are employed.

Detailed description

Detection of surgical smoke gas with an accuracy F1 score of \>= 0.8 on test datasets. The activation of the S-Pilot by clinic personnel will be used as the gold standard.

Conditions

• Detection of Surgical Smoke Gas Using AI

Timeline

• Start date: 2024-02-21
• Primary completion: 2025-05-26
• Completion: 2026-08-01
• First posted: 2026-02-09
• Last updated: 2026-02-09

Locations

1 site across 1 country: Germany