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AI reads skin biopsies to spot hidden lymphomas

NCT ID NCT07705386

Diagnosis Sponsor: Cairo University Source: ClinicalTrials.gov ↗

What the study statuses mean

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Recruitment status, easiest to join first

Recruiting now
This trial is taking on new participants right now.
Not yet recruiting
Registered, but not yet taking participants.
By invitation only
Not open to general applications. Only people the study team invites can take part.
Paused
Paused for now. It may or may not start again.
Ongoing This study
Running, but no longer taking on new participants.
Completed
The trial has finished. Results may not be published yet.
Stopped early
Stopped early, before it reached the end. That can be for many reasons, including safety.
Cancelled
Cancelled before anyone took part.

Expanded access (not trials)

Expanded access
Not a trial. This treatment can be requested outside a study, case by case, for people who qualify.
Expanded access (paused)
Not a trial. The treatment can normally be requested outside a study, but is unavailable right now.
Expanded access (ended)
Not a trial. The treatment could once be requested outside a study, but no longer can.
Approved
The treatment has been approved, so it is available normally rather than through this programme.

When the status isn't known

Details not published
The full record has not been published yet, so there is little to show here.
Status unknown
This status has not been confirmed recently, so it may be out of date.

First seen Jul 15, 2026 · Last updated Jul 16, 2026 · Updated 1 time

Summary

This study is developing and testing an artificial intelligence model that analyzes images of skin biopsies to tell the difference between malignant lymphomas (like mycosis fungoides) and benign conditions that look similar. The AI will be trained on hundreds of archived slides and compared against diagnoses made by expert dermatopathologists. If accurate, the tool could help doctors make faster, more consistent diagnoses, especially in places with limited access to specialists.

What this could mean

Our plain-language read of the trial. This is informational only, not medical advice or a prediction.

Active substance
AI-assisted histopathology image analysis
What this could lead to
If successful, this AI tool could help doctors diagnose rare skin lymphomas more accurately and quickly, reducing misdiagnosis and delays in treatment.
What could go wrong
The AI model is still in development and may not perform as well in real-world settings or on images from different sources. It also relies on archived slides, which may not represent all cases.

This is an AI summary of the original study and may miss details. Read our disclaimer.

Study facts

What this study's own registry entry says, in plain language.

Participants

About 463 people

The number the study aims to enrol. It can still change while the study runs.

Started

Jan 2026

Expected to finish

Dec 2026

An estimate. End dates often move.

Lead sponsor

Other sponsor

The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.

Who can take part

This study's own entry requirements. Only the study team can say for certain whether you qualify.

Who is studied

Archived slides of patients diagnosed with malignant CLPDs (e.g., mycosis fungoides, cutaneous B-cell lymphoma) and benign mimickers (e.g., pseudolymphoma, pityriasis lichenoides chronica, PLEVA) were identified from the pathology database of Kasr Al-Aini Hospitals, Cairo University. Cases were selected based on WHO-EORTC diagnostic criteria and availability of adequate quality H\&E slides plus relevant clinical data.

Ages

Children (under 18), adults (18 to 64) and older adults (65 and over)

Sex

Anyone

Show the full entry requirements

Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.

Inclusion Criteria: * Archived slides of patients with a confirmed histopathological diagnosis of malignant CLPDs (e.g., mycosis fungoides at all stages, cutaneous B-cell lymphoma, primary cutaneous anaplastic large cell lymphoma, lymphomatoid papulosis), based on WHO-EORTC criteria. * Archived slides of patients with benign CLPDs that mimic MF clinically and histologically (e.g., pseudolymphoma, pityriasis lichenoides chronica, pityriasis lichenoides et varioliformis acuta \[PLEVA\]). * Availability of adequate quality hematoxylin and eosin (H\&E) stained slides. * Availability of relevant clinical data (age, sex, disease duration, distribution of lesions, drug history). Exclusion Criteria: * Slides with significant artifacts (folding, tearing, poor staining) that prevent adequate image analysis. * Cases with insufficient clinical or pathological data for definitive diagnosis. * Cases with secondary cutaneous CLPDs

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Conditions

The condition(s) this trial relates to.

acute lichenoid pityriasis disease lymphomatoid papulosis mycosis fungoides pityriasis lichenoides primary cutaneous anaplastic large cell lymphoma primary cutaneous B-cell lymphoma pseudolymphoma

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

Cutaneous lymphoproliferative diseases Mycosis fungoides of skin (diagnosis) Pleva-PLC spectrum Primary cutaneous B-cell lymphoma (CBCL) Pseudolymphoma T cell dyscrasia

Contacts and locations

Locations

  • Kasr Al-Aini Hospitals, Cairo University

    Cairo, Egypt

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