RecruitingNCT06600165

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

Intraoperative Confocal Laser Scanning Microscopy and Artificial Intelligence for Optimized Surgical Excision of Basal Cell Carcinoma


Sponsor

LMU Klinikum

Enrollment

1,000 participants

Start Date

Mar 1, 2025

Study Type

OBSERVATIONAL

Conditions

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.


Eligibility

Inclusion Criteria1

  • Patients with Basal Cell Carcinoma

Exclusion Criteria1

  • Patient unable to consent

Interventions

PROCEDUREEx vivo confocal microscopy

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.


Locations(1)

Clinic and Policlinic of Dermatology and Allergy, LMU Munich

Munich, Bavaria, Germany

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NCT06600165


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