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AI reads lung cancer scans to predict survival

NCT ID NCT07068139

Knowledge-focused Sponsor: Hilkat Fatih Elverdi 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
Running, but no longer taking on new participants.
Completed This study
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 Results may not be published yet.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This status has not been confirmed recently, so it may be out of date.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 explores whether artificial intelligence can predict the stage and survival of non-small cell lung cancer by analyzing CT and PET scans. Researchers will train a deep learning model using existing medical records from 156 patients who had lung cancer surgery. The goal is to create a tool that helps doctors make faster, more accurate predictions without any new treatments or procedures.

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 AI model could help doctors predict lung cancer stage and survival more quickly and accurately from routine scans.
What could go wrong
This is a small, retrospective study using data from a single hospital. The AI may not work as well in other settings or on different patient groups.

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

156 people

The number who actually took part.

Started

Jan 2010

Finished

Jun 2026

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

This study includes patients who underwent surgical treatment for non-small cell lung cancer (NSCLC) at Ondokuz Mayis University Hospital in Samsun, Türkiye. Eligible patients are selected from the hospital's electronic medical records and radiologic imaging archive between January 2010 and March 2025. The population reflects a clinical sample from a tertiary referral center serving a diverse adult patient population in the Black Sea region of Türkiye.

Ages

18 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 ≥ 18 years * Diagnosed with non-small cell lung cancer (NSCLC) * Underwent surgical treatment for NSCLC at Ondokuz Mayis University Hospital * Available preoperative PET-CT and chest CT imaging * Available postoperative histopathological diagnosis and staging * Signed informed consent form for data use in research Exclusion Criteria: * Age \< 18 years * No available PET-CT or chest CT imaging in hospital records * No available histopathological diagnosis in hospital records * Diagnosed with a type of lung cancer other than NSCLC * Patients who did not undergo surgery * Patients who did not provide informed consent for retrospective data use

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Conditions

The condition(s) this trial relates to.

non-small cell lung carcinoma

As listed by the trial registrant

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

Artificial intelligence (AI) in diagnosis Non small cell lung cancer

More trials for these conditions

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