NCT07358637

Artificial Intelligence Enhanced Optical Coherence Tomography (AI-OCT) Imaging for Pre-surgical Margin Detection of Basal Cell Carcinoma

• Status: Not Yet Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 30 (estimated)
• Sponsor: Henry Ford Health System · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Not accepted

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.

Conditions

• Basal Cell Carcinoma of Skin

Interventions

Type	Name	Description
DIAGNOSTIC_TEST	AI-OCT	Optical Coherence Tomography augmented by artificial intelligence software

Timeline

• Start date: 2026-03-01
• Primary completion: 2027-12-01
• Completion: 2028-12-01
• First posted: 2026-01-22
• Last updated: 2026-01-22