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.
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
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
Adult patients with biopsy-confirmed BCC who are scheduled to receive Mohs micrographic surgery
Cohort
Prospective
AI-OCT
Diagnostic testOptical Coherence Tomography augmented by artificial intelligence software
Validation of AI-OCT as an accurate method for detecting basal cell carcinomas
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This trial is not recruiting at the moment. You can still explore other options:
