AI boosts Radiologists' accuracy in stomach cancer staging
NCT ID NCT07651644
First seen Jun 27, 2026 · Last updated Jun 27, 2026
Summary
This study tests whether an artificial intelligence (AI) tool can help radiologists more accurately determine the stage of stomach cancer from CT scans. Fifty-four radiologists will review 60 scans each, first without AI help and then with AI assistance, to see if the AI improves their accuracy. The goal is to improve cancer diagnosis and guide better treatment decisions.
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Study facts
What this study's own registry entry says, in plain language.
- Phase
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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
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About 54 people
The number the study aims to enrol. It can still change while the study runs.
- Expected to start
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Jun 2026
An estimate. Start dates often move.
- Expected to finish
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Aug 2026
An estimate. End dates often move.
- Lead sponsor
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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
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Children (under 18), adults (18 to 64) and older adults (65 and over)
- Sex
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Anyone
- Healthy volunteers
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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 Hide 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 (Imaging Data) 1. Contrast-enhanced CT (CE-CT) images of gastric cancer patients from the Liaoning Cancer Hospital; 2. Patients with a definitive postoperative pathological diagnosis of gastric cancer and a clear T-stage classification (T1-T4, including T4a and T4b); 3. Imaging data must be complete and of sufficient quality to meet diagnostic and analytical requirements, with no significant artefacts or missing key data; 4. Complete clinical and pathological information must be available to establish a diagnostic gold standard for comparison. Physician Inclusion Criteria (Image Readers) 1. Radiologists holding a valid medical licence; 2. From the radiology department of a Grade A tertiary hospital or a non-Grade A tertiary hospital; 3. Classified as senior or junior physicians based on clinical experience; 4. Voluntarily participating in this study and completing both the non-AI-assisted and AI-assisted image interpretation tasks. Case Exclusion Criteria 1. Severe missing imaging data or quality failing to meet analysis requirements (e.g., severe motion artefacts); 2. Lack of clear postoperative pathological T-staging results; 3. Cases not involving gastric cancer or with incomplete pathological information; 4. Cases of duplicate enrolment or inconsistent data recording. Physician Exclusion Criteria 1. Those unable to complete all image review tasks or demonstrating severe non-compliance; 2. Those who withdraw during the study period and are unable to provide complete data for both phases of image review; 3. Those who fail to complete the AI-assisted and non-AI-assisted interpretation processes as specified. Withdrawal Criteria 1. Physicians who voluntarily withdraw from the study for personal reasons (e.g., time, health or work commitments); 2. Physicians who fail to complete the required image review tasks or have data missing in excess of the specified threshold; 3. Cases where critical data errors are identified during subsequent verification or where pathological results cannot be traced; Data found during the study to be non-compliant with ethical or quality control requirements must be excluded.
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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.
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The places running it
1 site. The list below names each one and where it is.
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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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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
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Cancer Hospital of Dalian University of Technology (Liaoning Cancer Hospital & Institute)
RECRUITINGShenyang, Liaoning, 110024, China
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