💬In plain words
What the trial is, and whether it could suit you
This study employed a prospective, randomised crossover trial design to evaluate the clinical utility of the TRACE artificial intelligence system for gastric cancer T-staging. A total of 54 radiologists from tertiary and non-tertiary hospitals, including both senior and junior practitioners, were enrolled. The study aimed to investigate whether AI-assisted diagnosis could improve the diagnostic accuracy of gastric cancer T-staging compared with independent interpretation by radiologists.
All participants were required to interpret 60 contrast-enhanced CT cases sequentially, completing two readings for each case: one without AI assistance and one with AI assistance; The order of the two readings was randomised, and a one-month washout period was observed between readings to eliminate memory bias. All cases were pathologically confirmed gastric cancer cases (stages T1-T4b), and the study
Sign in to get the eligibility rules as simple questions to take to your doctor.
📋 Eligibility rules (as published)
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.
HealthTeky