Machine learning assessment of two-photon microscopy images from skin biopsies

Is this trial a fit for you?

A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.

What this trial studies

This study investigates whether a machine learning model can interpret two-photon fluorescence microscopy images of dermatologic biopsy specimens acquired at the point of care. Biopsies are scanned with TPFM, and the model assigns a diagnostic probability for basal cell carcinoma, squamous cell carcinoma, or non-cancer, flagging indeterminate cases for pathologist review. The gold standard diagnosis is later determined by conventional histology, which is used for comparison. Imaging is performed on small biopsy specimens, and the workflow aims to enable rapid, point-of-care diagnostic decisions if accuracy is sufficient. The study excludes melanomas and certain small or fragmented specimens.

Why it matters

Who can join: the full rules

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

Where it's running

• Rochester Dermatologic Surgery
  Victor, New York, United States Recruiting

Study contacts

• Study coordinator: Michael Giacomelli, Ph.D
• Email: mgiacome@ur.rochester.edu
• Phone: 5852766260

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How to take part

1. Review the eligibility criteria above with your treating physician.
2. Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
3. Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.