Intraoperative Confocal Laser Scanning Microscopy With Use of AI for Optimized Surgical Excision of Basal Cell Carcinoma

NCT06600165 | Recruiting

• 1 other identifier: DFG 536381342
• Study Type: observational
• Target: 1,000
• Locations: 1 country
• Sites: 1

Brief Summary

The aim is to use AI to assist surgeons in analyzing CLSM tissue slide images obtained during BCC surgeries with the aim to integrate it in real time. We plan to use AI to analyze CLSM images of BCCs and distinguish between tumor tissue, inflammatory tissue, and non-tumor/non-inflammatory tissue. This approach would provide surgeons with real-time feedback and automated image analysis, leading to a more targeted and efficient approach to tissue analysis. By improving the accuracy and speed of tissue analysis, our proposal could ultimately improve operative patient outcomes and benefit healthcare professionals.

Conditions

Basal Cell Carcinoma

Outcome Measures

Primary Outcomes (1)

• Ex vivo confocal laser scanning microscopy

  Reaching the planned number of 1000 patients

  2 years

Interventions

Ex vivo confocal microscopy PROCEDURE

The aim is to use AI to assist surgeons in analyzing CLSM tissue slide images obtained during BCC surgeries with the aim to integrate it in real time. We plan to use AI to analyze CLSM images of BCCs and distinguish between tumor tissue, inflammatory tissue, and non-tumor/non-inflammatory tissue. This approach would provide surgeons with real-time feedback and automated image analysis, leading to a more targeted and efficient approach to tissue analysis. By improving the accuracy and speed of tissue analysis, our proposal could ultimately improve operative patient outcomes and benefit healthcare professionals.

Eligibility Criteria

• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

Patients with Basal Cell Carcinoma undergoing biopsy or surgery

You may qualify if:

• Patients with Basal Cell Carcinoma

You may not qualify if:

• Patient unable to consent

Sponsors & Collaborators

• LMU Klinikum: lead

Study Sites (1)

Clinic and Policlinic of Dermatology and Allergy, LMU Munich

Munich, Bavaria, 80337, Germany

RECRUITING

MeSH Terms

Conditions

Carcinoma, Basal Cell

Condition Hierarchy (Ancestors)

Carcinoma; Neoplasms, Glandular and Epithelial; Neoplasms by Histologic Type; Neoplasms; Neoplasms, Basal Cell

Central Study Contacts

Maximilian Deußing, Dr.

CONTACT

+4989440056010; maximilian.deussing@med.uni-muenchen.de

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: CROSS SECTIONAL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Principal Investigator

Study Record Dates

• First Submitted: September 11, 2024
• First Posted: September 19, 2024
• Study Start: March 1, 2025
• Primary Completion (Estimated): December 31, 2026
• Study Completion (Estimated): December 31, 2027
• Last Updated: September 9, 2025

Record last verified: 2025-03

Data Sharing

• IPD Sharing: Will not share

Locations

DE (1)