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AI trained on 144,000 scans to help doctors spot disease

NCT ID NCT04579237

Knowledge-focused Sponsor: National Institutes of Health Clinical Center (CC) 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
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 Results may not be published yet.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This status has not been confirmed recently, so it may be out of date.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 Jun 27, 2026 · Last updated Jun 27, 2026

Summary

This study uses over 144,000 existing medical images (like CT and MRI scans) to develop computer programs that can help detect and diagnose diseases. Researchers aim to create algorithms that find lesions, model anatomy, and track disease over time. The study includes people of all ages whose scans are stored in the hospital's database.

What this could mean

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

What this could lead to
If successful, this could lead to better computer tools that help doctors spot diseases on scans more quickly and accurately.
What could go wrong
This is an early-stage data analysis study, not a treatment trial. The algorithms may not work well in real-world settings or on different types of images.

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

144,625 people

The number who actually took part.

Started

Oct 2020

Expected to finish

Jun 2030

An estimate. End dates often move.

Lead sponsor

A government research agency

The lead sponsor is the US National Institutes of Health.

Who can take part

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

Who is studied

Special classes of subjects, such as pregnant women, children, cognitively impaired individuals, or others likely to be vulnerable will be included since the data has already been obtained under an IRB-approved protocol and there are no anticipated additional risks from this research

Ages

1 year to 100 years

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: * All radiologic exams available in the clinical PACS (picture archiving system) of the Clinical Center taken from July, 6, 1953 with no end date. * Males and Females of all ages. * Patients with target lesions of any kind will be included * Patients without the target lesion will be included to determine the specificity of the computer aided detection or diagnosis algorithm EXCLUSION CRITERIA: None

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Conditions

The condition(s) this trial relates to.

Lymphadenopathy

As listed by the trial registrant

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

Radiology information systems

Contacts and locations

Locations

  • National Institutes of Health Clinical Center

    Bethesda, Maryland, 20892, United States