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AI eye on lungs: can computers help find hidden cancer?

NCT ID NCT06746324

Knowledge-focused Sponsor: University of Florida 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
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 Results may not be published yet.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 This study
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This status has not been confirmed recently, so it may be out of date.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 26, 2026

Summary

This study planned to see if an artificial intelligence (AI) program called qXR-LN could help radiologists find more lung nodules and cancers on chest X-rays. Researchers would compare how often nodules were detected before and after the AI was put into use. The study was withdrawn before any patients were enrolled, so no results are available.

What this could mean

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

Active substance
qXR-LN (an artificial intelligence tool for analyzing chest X-rays)
What this could lead to
If successful, this could show that AI helps radiologists catch lung nodules and cancers earlier, potentially improving outcomes.
What could go wrong
The study was withdrawn before any participants enrolled, so no results are available. AI tools can also miss findings or create false alarms.

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.

Expected to start

May 2025

An estimate. Start dates often move.

Expected to finish

Jun 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

The study population consists of patients aged 35 years and older who have undergone chest X-rays as part of routine clinical care. These patients are evaluated for the presence of lung nodules and potential lung cancer. The study includes two cohorts: a pre-deployment cohort, where chest X-rays are interpreted using standard clinical methods, and a post-deployment cohort, where chest X-rays are interpreted with the assistance of the FDA-cleared AI tool qXR-LN. Patients with a known history of lung cancer or those undergoing lateral chest X-ray views are excluded. The population includes individuals from diverse clinical settings, such as outpatient clinics, emergency departments, and inpatient hospital units, to ensure a representative sample of real-world patients with respiratory conditions. The primary goal is to assess the impact of AI assistance on lung nodule detection and early-stage lung cancer diagnosis.

Ages

35 years and older

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: * Age ≥35 years at the time of chest X-ray acquisition * Chest X-ray must be obtained as part of routine care (e.g., ordered for respiratory complaints, screening, or other clinical indications) * Chest X-ray performed using CR/DR/DX imaging modality * Examination described as "Chest" * View: PA or AP * Patient positioned as Erect or Supine * Image available in valid DICOM format with proper DICOM prefix values (including "DICM" in the header) Exclusion Criteria: * Patients aged \<35 years at the time of chest X-ray * Patients with known lung cancer at the time of chest X-ray acquisition * Lateral views or any imaging modality other than CR/DR/DX * Imaging or anatomy not specified as Chest (e.g., different body parts or modalities)

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Conditions

The condition(s) this trial relates to.

lung cancer lung neoplasm

As listed by the trial registrant

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

Artificial intelligence in radiology Computer-aided detection Early stage lung cancer Lung cancers Lung nodules

More trials for these conditions

Other studies related to the condition(s) this trial covers.