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Basal cell carcinomas (BCCs) are the most common human malignancy, affecting about 2 million Americans each year. Mohs micrographic surgery (MMS) removes tissue by sequential excision. Costs for MMS could be reduced if the number of necessary excision stages were decreased by a more accurate initial tumor margin assessment. The goal of this observational study is to learn if Optical Coherence Tomography (OCT) used in conjunction with artificial intelligence algorithms is accurate in the detection of superficial BCC margins prior to MMS. This study also aims to determine if AI-OCT guided margin delineation can reduce the number of stages in MMS. Researchers will first focus on validating AI-OCT as a method for accurately detecting BCCs. A follow-up study would then address the guided pre-surgical margin delineation.
Age
18 - No limit years
Sex
ALL
Healthy Volunteers
No
Start Date
March 1, 2026
Primary Completion Date
December 1, 2027
Completion Date
December 1, 2028
Last Updated
January 22, 2026
30
ESTIMATED participants
AI-OCT
DIAGNOSTIC_TEST
Lead Sponsor
Henry Ford Health System
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