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AI-enhanced OCT Imaging for Pre-surgical Margin Detection of Basal Cell Carcinoma

NCT07358637 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 30

Last updated 2026-05-06

No results posted yet for this study

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

DIAGNOSTIC_TEST

AI-OCT

Optical Coherence Tomography augmented by artificial intelligence software

Sponsors & Collaborators

  • Henry Ford Health System

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2026-09-30
Primary Completion
2027-12-31
Completion
2028-12-31

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07358637 on ClinicalTrials.gov