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Dentists' new AI sidekick: X-Ray reader predicts tricky root canals

NCT ID NCT07611279

Diagnosis Sponsor: Cairo University Source: ClinicalTrials.gov ↗

What the study statuses mean

This study's is highlighted.

Recruitment status, easiest to join first

Recruiting now
This trial is taking on new participants right now.
Not yet recruiting This study
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
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 Results may not be published yet.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This status has not been confirmed recently, so it may be out of date.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 Jun 26, 2026 · Last updated Jun 27, 2026 · Updated 1 time

Summary

This study will develop and test an artificial intelligence model that reads dental X-rays to predict how difficult a root canal retreatment will be. Researchers will use 123 X-rays of back teeth that need retreatment, and experts will grade the difficulty. The goal is to help dentists decide whether to treat or refer the case.

What this could mean

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

Active substance
Deep learning model (AI software)
What this could lead to
If it works, this could give dentists a reliable tool to quickly assess retreatment difficulty from a simple X-ray, improving treatment planning and referrals.
What could go wrong
This is an early-stage study using existing X-rays, not a live test. The AI may not perform well on all types of X-rays or in real-world clinics.

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.

Phase

Not a phased trial

Phase numbers describe drug development. The registry uses this when they do not apply, as it does for trials of devices, procedures or behaviour changes, and for observational studies.

Participants

About 123 people

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

Expected to start

Jul 2026

An estimate. Start dates often move.

Expected to finish

Jan 2027

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.

Ages

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

Sex

Anyone

Healthy volunteers

Not accepted

This study is not open to healthy volunteers. The entry requirements below say who it is open to.

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: Periapical radiographs of maxillary and mandibular molars requiring non-surgical endodontic retreatment will be included. Radiographs should exhibit satisfactory image quality, characterized by adequate sharpness, contrast, and minimal distortion or noise to allow accurate assessment of relevant anatomical and treatment-related features. Images should clearly display the tooth of interest, surrounding periapical structures, and any existing root canal filling materials or restorations. Exclusion Criteria: Deciduous teeth, non-restorable, non-treated teeth

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As listed by the trial registrant

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

Ai (artificial intelligence) Deep learning model Difficulty assessment Endodontic retreatment Endodontics Missed canals Non-surgical retreatment Obturation quality Perforation Poor obturation Separated instrument

How to take part

Only the study team decides who joins. These are the ways to reach them.

  1. The official record

    ClinicalTrials.gov lists the study team's own contact details, including names and phone numbers. We don't republish those.

    Open the record ↗

  2. A doctor treating you

    A doctor who knows your case can contact a study site on your behalf, and can tell you whether this study is worth pursuing at all.

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