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Artificial Intelligence Enhanced Optical Coherence Tomography (AI-OCT) Imaging for Pre-surgical Margin Detection of Basal Cell Carcinoma
Sponsor: Henry Ford Health System
Summary
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.
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
OBSERVATIONAL
Enrollment
30
Start Date
2026-03
Completion Date
2028-12
Last Updated
2026-01-22
Healthy Volunteers
No
Conditions
Interventions
AI-OCT
Optical Coherence Tomography augmented by artificial intelligence software