AI-assisted confocal imaging to guide removal of basal cell carcinoma
Official title: Intraoperative Confocal Laser Scanning Microscopy and Artificial Intelligence for Optimized Surgical Excision of Basal Cell Carcinoma
Run by LMU Klinikum · NCT06600165 · Data updated 2026-11-12
This project tests whether an AI tool can analyze confocal microscope images during basal cell carcinoma surgery to give surgeons real-time guidance on which tissue to remove.
Quick facts
| Study type | Observational |
|---|---|
| Sex | All |
| Enrollment | 1000 (estimated) |
| Sponsor | LMU Klinikum Academic / other |
| Locations | 1 site (Munich, Bavaria) |
| Status | Recruiting |
| Started | March 1, 2025 |
| Main results expected | December 31, 2026 |
| Study ends | December 31, 2027 |
| Registry record updated | August 26, 2026 |
| Trial ID | NCT06600165 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Adults with a confirmed basal cell carcinoma who can give informed consent and are scheduled for surgical excision at LMU Munich are ideal candidates.
✕Probably not a fit
Patients without basal cell carcinoma, those unable to consent, or those treated outside the participating clinic are unlikely to receive benefit from this protocol.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
In this observational project, surgeons will collect ex vivo confocal laser scanning microscopy (CLSM) images from tissue excised during routine basal cell carcinoma surgeries. An AI algorithm will be developed to classify image regions as tumor, inflammatory, or non-tumor tissue and to provide automated annotations in near real time. The goal is to integrate AI output into the intraoperative workflow to offer immediate feedback without altering standard surgical care. Collected AI predictions will be compared with standard histopathology and surgeon assessment to measure accuracy and potential workflow advantages.
Why it matters
Potential benefit: If successful, the technique could help surgeons remove cancer more precisely, reduce repeat surgeries, and shorten time spent on intraoperative tissue assessment.
How similar studies have gone: Confocal microscopy has demonstrated the ability to identify basal cell carcinoma features and early AI work in dermatopathology is promising, but real-time intraoperative AI guidance remains relatively novel.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * Patients with Basal Cell Carcinoma Exclusion Criteria: * Patient unable to consent
Where it's running
-
Clinic and Policlinic of Dermatology and Allergy, LMU Munich
Munich, Bavaria, Germany Recruiting
Study contacts
- Study coordinator: Maximilian Deußing, Dr.
- Email: maximilian.deussing@med.uni-muenchen.de
- Phone: +4989440056010
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.