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Not yet recruitingNCT07795242AI\MFUpdated Aug 31, 2026

AI in MF Diagnosis

An observational study in Mycosis Fungoides of Skin (Diagnosis) and Artificial Intelligence (AI) in Diagnosis, sponsored by Al-Azhar University. Not yet recruiting at 1 site in Egypt. Per ClinicalTrials.gov, last updated 2026-08-31.

Sponsored by Al-Azhar University · Observational

Study type
Observational
Model
Other
Time perspective
Retrospective
Enrollment
50
Sex
All
01

Study summary

The aim of this observational study is to evaluate the diagnostic performance of an AI algorithm in the histopathological diagnosis of MF compared to certified dermatopathologists.

Read the detailed description

Mycosis fungoides (MF) is the most common form of primary cutaneous T-cell lymphoma. Its early histological features may overlap with benign inflammatory dermatoses, making diagnosis challenging.

This observational study aims to evaluate the diagnostic performance of HistoGPT in the histopathological diagnosis of MF compared with certified dermatopathologists.

H\&E-stained skin biopsy slides will be digitized using a Leica Aperio GT450 whole-slide scanner at 40× magnification.

The resulting whole-slide images will be analyzed using HistoGPT, an AI-based histopathology platform.

The diagnostic performance of HistoGPT and certified dermatopathologists will be assessed and compared using appropriate diagnostic metrics, including accuracy, sensitivity, specificity, F1 score, and area under the ROC curve.

The findings of this study will help determine whether Artificial intelligence can serve as a diagnostic support tool for the histopathological diagnosis of mycosis fungoides.

02

Conditions studied

  • Mycosis Fungoides of Skin (Diagnosis)
  • Artificial Intelligence (AI) in Diagnosis

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03

Who can participate

Ages eligible
Child (0–17), Adult (18–64), Older adult (65+)
Sexes eligible
All
Accepts healthy volunteers
No
Sampling method
Non-probability sample

Study population

H\&E stained glass slides of MF cases will be collected from the pathology archive of Al hussein dermatopathology unit

Inclusion criteria

  • Slides will be included in the study if they meet the following criteria:

    • Histopathological slides diagnosed as MF.
    • Slides with adequate staining and preservation allowing clear visualization of histopathological features.

Exclusion criteria

Exclusion Criteria:

  • Slides will be excluded if they meet any of the following criteria:

    • Slides with poor staining quality or significant artifacts interfering with histopathological interpretation.
    • Slides that were damaged, faded, or inadequately preserved.
    • Slides with uncertain or inconclusive original diagnoses.
    • Slides that could not be successfully digitized due to technical limitations ex very short or too long slides.
04

Study design

Observational model
Other
Time perspective
Retrospective
Enrollment
50 participants (estimated)
Patient registry
No
Biospecimen retention
Samples without dna

Interventions

  • Otherthis study does not include any intervention

    Does not include intervention

05

What researchers measure

Primary outcomes

  1. The accuracy of artificial intelligence in histopathological diagnosis of Mycosis fungoides will be evaluated by sensitivity and specificity

    Time frame: 1 year

06

Study locations

1 site
  • Faculty of Medicine , Al Azhar university , Nasr city , Cairo , Egypt
    Cairo, Egypt
07

References and documents

Individual participant data

Plan to share: Undecided

No publications or documents are linked to this record.

08

Registry details

Key details

Study ID
NCT07795242
Lead sponsor
Al-Azhar University
Responsible party
Shimaa Ali Ahmed (Resident Dermatologist, Al-Azhar University) — Principal investigator
First posted
Aug 31, 2026
Start date
Oct 1, 2026 (estimated)
Primary completion
Oct 1, 2027 (estimated)
Completion
Dec 1, 2027 (estimated)
Last update
Aug 31, 2026

Study contacts

Shimaa Ali Ahmed, Resident of dermatology
Contact
shimaaali038@gmail.com
+201024466776
Shimaa Ali Ahmed
principal investigator · Al Azhar university for boys

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

Not currently enrolling

This study is not yet recruiting, as verified in Aug 2026. You cannot join it, but the record below documents what was studied.

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