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AI showdown: three computer models battle to predict lung cancer from CT scans

NCT ID NCT07727122

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 Results may not be published yet.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This status has not been confirmed recently, so it may be out of date.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 Jul 27, 2026 · Last updated Jul 28, 2026 · Updated 1 time

Summary

This study will compare three different artificial intelligence (AI) models that analyze chest CT scans to predict whether a lung nodule is cancerous. The trial will enroll 3,000 adults with small lung nodules (≤3 cm) who have a definitive diagnosis from biopsy or surgery. Each AI model will generate a cancer-risk score based only on the CT images, and the results will be checked against the actual pathology report to see which model is most accurate.

What this could mean

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

Active substance
three artificial intelligence models (MVCS, LungDoc, and a United Imaging AI model) that analyze chest CT images to predict malignancy risk
What this could lead to
If one AI model proves clearly more accurate, it could become a standard tool to help doctors decide which lung nodules need biopsy or surgery, reducing unnecessary procedures.
What could go wrong
The AI models are tested only on nodules that already have a pathology result, which may not reflect real-world screening populations. Also, the best model may still have limited accuracy for certain nodule types.

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

About 3,000 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

Dec 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.

Who is studied

Adults (≥18 years) undergoing routine clinical care at five tertiary hospitals in China who have at least one pulmonary nodule (≤3 cm) detected on chest CT and receive surgical or biopsy pathology with a definitive benign or malignant diagnosis. All participants have adequate CT image quality and complete clinicopathologic information for AI model validation

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, any sex. * At least one pulmonary nodule detected on chest CT, with initial nodule diameter ≤ 3 cm. * The nodule undergoes surgical resection or biopsy with a definitive benign or malignant pathological diagnosis. * Time interval between CT examination and pathological examination ≤ 6 months. * Availability of complete CT imaging data in DICOM format with adequate image quality (no severe artifacts), meeting input requirements of all three AI models. Availability of complete clinicopathologic information including histologic type and grade, with clear pathological diagnosis suitable as gold standard labels for AI validation. -The patient (or legally authorized representative) is willing and able to sign written informed consent. Exclusion Criteria: * Pathological results are unclear, inconclusive, or disputed; nodule nature or grade cannot be reliably determined. * The patient receives treatments between CT and pathology that may significantly alter nodule appearance (e.g., chemotherapy, radiotherapy, targeted therapy). * CT imaging data are incomplete (missing essential series) or have severe motion, metal, or other artifacts preventing accurate AI analysis. * Required metadata for any AI model are missing and cannot be imputed. History of other malignant tumors (malignancies other than the index non-small cell lung cancer). * Severe psychiatric illness, cognitive impairment, or other conditions that prevent cooperation with study-related procedures and follow-up. Participation in another clinical study that may interfere with the results of this research. -The patient or legal representative refuses participation. Exclusion (Post-Enrollment / Removal from Analysis) Participants already enrolled may be excluded from the analysis set if: * They are later found not to meet inclusion criteria or to meet exclusion criteria. * No usable data are available after enrollment. * Required AI model assessments are not completed (e.g., technical failure to generate outputs). * Critical data are missing, preventing contribution to primary analysis. * The interval between CT and pathology exceeds 6 months.

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Conditions

The condition(s) this trial relates to.

Multiple Pulmonary Nodules

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

    5 sites. 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.

    Open the record ↗

  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

  • Affiliated Hospital of Xuzhou Medical University

    Xuzhou, Jiangsu, 221006, China

  • Guangdong Provincial People's Hospital

    Guangzhou, Guangdong, 510000, China

  • Second Affiliated Hospital of Army Medical University (Xinqiao Hospital)

    Chongqing, Chongqing Municipality, 400037, China

  • Zhejiang University

    Hangzhou, Zhejiang, 310003, China

  • Zhujiang Hospital, Southern Medical University

    Guangzhou, Guangdong, 510000, China

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