Can AI make lung cancer scans easier to read?

NCT ID NCT07829640

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 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 Results may not be published yet.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This status has not been confirmed recently, so it may be out of date.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 Sep 21, 2026 · Last updated Sep 21, 2026

Summary

Researchers are building an artificial intelligence system that analyzes chest CT images and offers decision support to doctors reading those scans for lung cancer. They use deidentified CT exams from routine care to develop and lock the AI models. In the prospective stage, about 12 to 15 physicians each complete two reading sessions in random order: one without AI help and one with AI help, separated by at least four weeks. The study compares diagnostic accuracy, reading time, confidence, and agreement between readers. All readings happen offline, and the AI is not used for actual patient care.

What this could mean

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

Active substance
an artificial intelligence decision-support system that analyzes chest CT images
What this could lead to
If it works, this could point toward AI-assisted chest CT reading that helps doctors spot lung cancer more accurately and possibly faster.
What could go wrong
This is a small, single-center reader study with 12 to 15 physicians, and the AI is tested offline, not in real patient care. The AI may not improve accuracy, and incorrect AI suggestions could mislead readers.

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 15 people

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

Expected to start

Sep 2026

An estimate. Start dates often move.

Expected to finish

Aug 2028

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

18 years and older

Sex

Anyone

Healthy volunteers

Accepted

You do not need to have the condition being studied to take part.

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: * Physicians with education or training relevant to medical imaging * Experience in interpreting chest CT examinations * Ability to complete the required study training and both reading sessions * Willingness to provide written informed consent and comply with study procedures Exclusion Criteria: * Failure to complete the required study training * Inability or unwillingness to complete both reading sessions as required * Any protocol deviation likely to compromise the validity of the reader-study data

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Conditions

The condition(s) this trial relates to.

As listed by the trial registrant

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

How to take part

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

  1. The places running it

    1 site. The list below names each one and where it is.

  2. The official record

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

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  3. 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.

Contacts and locations

Locations

  • Union Hospital, Tongji Medical College, Huazhong University of Science and Technology

    Wuhan, Hubei, 430022, China

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