Machine Learning Analysis of Two-photon Fluorescence Microscopy of Dermatologic Biopsies

Part of paid clinical trials in Victor, New York.

Sponsor
University of Rochester
Study ID
NCT07682831
Status
Recruiting
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Conditions

  • Basal Cell Carcinoma of Skin
  • Squamous Cell Carcinoma (Skin)

Eligibility Criteria

Sex
ALL
Age
N/A - N/A
Healthy Volunteers
Not accepted

Interventions

  • Two photon microscopy imaging — DEVICE
    Ex vivo tissues will be imaged with two-photon microscopy and analyzed with machine learning for diagnosis

Study Details

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?

Key Dates

First listed
Jul 6, 2026
Start date
Jun 24, 2026
Status verified
Aug 2026
Primary completion
Jun 1, 2027
Completion
Jul 1, 2027

Study Design

Enrollment
92 participants (estimated)
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
DIAGNOSTIC

Arms

  • Experimental: TPFM imaging of biopsy
    Specimens will be imaged with TPFM and diagnosed using a machine learning model

Primary Outcome Measure

Sensitivity of Machine Learning Analysis of Two Photon Fluorescence Microscopy Images At Point of Care [ Time Frame: During or immediately following patient biopsy (same day) ]

Central Contacts

Locations (1)

FacilityCityStateZIPSite coordinators
Rochester Dermatologic SurgeryVictorNew York14654
Sherrif Ibrahim, M.D.-Ph.D.
[email protected]
585-222-1400

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Rochester Dermatologic Surgery· Victor, NY

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