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NCT07682831
Machine Learning Analysis of Two-photon Fluorescence Microscopy of Dermatologic Biopsies
Conditions: Basal Cell Carcinoma of Skin, Squamous Cell Carcinoma (Skin)
Sex: All
Healthy volunteers: No
Phase: NA
Enrollment: 92
Sponsor: University of Rochester
Location: Rochester Dermatologic Surgery Victor New York
Summary
The goal of this study is to investigate the ability of a machine learning model to evaluate two-photon fluorescence microscopy images of dermatologic biopsies at point of care.
The main question it aims to answer is:
• How well do two-photon fluorescence images of biopsies taken in a clinic and evaluated by a machine learning model agree with conventional histology?
Eligibility Criteria
Inclusion Criteria:
* Punch, excisional or shave biopsy specimen
Exclusion Criteria:
* Biopsy indication includes melanoma or dysplastic/atypical nevus
* Excision thickness of less than 1 mm
* Excision longest dimension less than 2 mm
* Excision performed as multiple pieces in a single specimen container
Source: ClinicalTrials.gov (NCT07682831). StuddyBuddy aggregates publicly available trial information.
