Intraoperative Confocal Laser Scanning Microscopy With Use of AI for Optimized Surgical Excision of Basal Cell Carcinoma
NCT ID: NCT06600165
Last Updated: 2025-09-09
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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RECRUITING
1000 participants
OBSERVATIONAL
2025-03-01
2027-12-31
Brief Summary
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Detailed Description
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Conditions
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Study Design
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COHORT
CROSS_SECTIONAL
Interventions
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Ex 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.
Eligibility Criteria
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Inclusion Criteria
Exclusion Criteria
ALL
No
Sponsors
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LMU Klinikum
OTHER
Responsible Party
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Maximilian Deußing
Principal Investigator
Locations
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Clinic and Policlinic of Dermatology and Allergy, LMU Munich
Munich, Bavaria, Germany
Countries
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Central Contacts
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Facility Contacts
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Other Identifiers
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DFG 536381342
Identifier Type: -
Identifier Source: org_study_id
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