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

Henry Ford Health

Status: Begins enrollment this month

Conditions: Basal Cell Carcinoma of Skin

Treatments: Diagnostic Test: AI-OCT

Study type: Observational

Funder types: Other

Identifiers

NCT07358637

18605

Details and patient eligibility

About

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.

Enrollment: 30 estimated patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Male or Female, ages 18 or older
• at least one biopsy proven superficial or nodular BCC
• willingness to have photographs taken of the treatment area
• ability to understand and willingness to sign a written informed consent document

Exclusion criteria

• infiltrative, micronodular, or morpheaform BCC
• pregnant women
• subjects not willing to have a biopsy taken from the treatment area
• subjects with herpes simplex virus infection in the treatment area