Mycosis Fungoides of Skin (Diagnosis)AI\MFNCT07795242
AI in MF Diagnosis
An observational study of Mycosis Fungoides of Skin (Diagnosis) and Artificial Intelligence (AI) in Diagnosis, run by Al-Azhar University at 1 site in Egypt.
Trial 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 more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Mycosis Fungoides of Skin (Diagnosis), Artificial Intelligence (AI) in Diagnosis
- What is being tested?
- this study does not include any intervention
- How many people
- 50 participants
- Where
- 1 siteEgypt
- Study dates
- 1 Oct 2026to 1 Dec 2027
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Any age
- All sexes
- No healthy volunteers
- Child, Adult, Older adult
Study population: H\&E stained glass slides of MF cases will be collected from the pathology archive of Al hussein dermatopathology unit
Who may be able to join
- 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.
Who cannot join
- 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.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Egypt1 site
Faculty of Medicine , Al Azhar university , Nasr city , Cairo , Egypt
Cairo
About this study
Official title: Evaluation of Artificial Intelligence Algorithms Performance in the Histopathological Diagnosis of Mycosis Fungoides
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.
- Being tested
- this study does not include any intervention
- Medical subject headings
- Disease
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
this study does not include any interventionOther
Does not include intervention
What is being measured
The primary outcome is the main question the study is designed to answer.
The accuracy of artificial intelligence in histopathological diagnosis of Mycosis fungoides will be evaluated by sensitivity and specificity
Measured: 1 year
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted31 Aug 2026
- Study start1 Oct 2026 (estimated)
- Primary completion1 Oct 2027 (estimated)
- Study completion1 Dec 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Mycosis Fungoides of Skin (Diagnosis)Studies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Other
- Time perspective
- Retrospective
- Enrolment
- 50 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Al-Azhar University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Shimaa Ali Ahmed, Al-Azhar University
- Investigators
- Shimaa Ali Ahmed, Principal investigator, Al Azhar university for boys
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07795242
- Sponsor's protocol ID
- 302
- Acronym
- AI\MF
- Status last verified
- Aug 2026
- First submitted
- 25 Aug 2026
- Last updated
- 31 Aug 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 31 Aug 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Evaluation of Artificial Intelligence Algorithms Performance in the Histopathological Diagnosis of Mycosis Fungoides
- ClinicalTrials.gov ID
- NCT07795242
- Acronym / sponsor ID
- AI\MF / 302
- Study type
- Observational
- Recruitment status
- Not yet recruiting
- Enrolment
- 50 participants (estimated)
- Lead sponsor
- Al-Azhar UniversityUniversity, hospital or other
- Study start
- 1 Oct 2026 (estimated)
- Primary completion
- 1 Oct 2027 (estimated)
- Study completion
- 1 Dec 2027 (estimated)
- First posted
- 31 Aug 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
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.
Study design
- Observational model
- Other
- Time perspective
- Retrospective
Who may qualify
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
- Study population
- H\&E stained glass slides of MF cases will be collected from the pathology archive of Al hussein dermatopathology unit
Key inclusion criteria (3 listed)
- Slides will be included in the study if they meet the following criteria:
Key exclusion criteria (5 listed)
- Slides will be excluded if they meet any of the following criteria:
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| this study does not include any interventionDoes not include intervention | Other | – |
Primary outcome
The accuracy of artificial intelligence in histopathological diagnosis of Mycosis fungoides will be evaluated by sensitivity and specificity
Time frame: 1 year
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 31 Aug 2026.
- Individual participant dataSharing planned: Undecided
Related trials for Mycosis Fungoides of Skin (Diagnosis)
Active, not recruitingObservational study
Development of an AI-Assisted Diagnostic Tool for Mycosis Fungoides and Other Cutaneous Lymphoproliferative Diseases Using Microscopic Image Analysis: A Training and Validation Study
Cutaneous Lymphoproliferative Diseases, Mycosis Fungoides of Skin (Diagnosis)
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Shimaa Ali Ahmed principal investigator
Al Azhar university for boys
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Mycosis Fungoides of Skin (Diagnosis) and Artificial Intelligence (AI) in Diagnosis, run by Al-Azhar University at 1 site in Egypt.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 5 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 31 Aug 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Egypt. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Shimaa Ali Ahmed, Resident of dermatology (+201024466776, shimaaali038@gmail.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
The accuracy of artificial intelligence in histopathological diagnosis of Mycosis fungoides will be evaluated by sensitivity and specificity (time frame: 1 year). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 31 Aug 2026; AzTrials last refreshed its copy on 26 Oct 2026.