Colorectal Cancer, Gastric Cancer, Gastrointestinal Cancer
Conditions
Keywords
Colorectal Cancer, Gastric Cancer, MDT, Artificial Intelligence
Brief summary
This prospective, single-center observational study will evaluate the concordance between a multimodal artificial intelligence system and multidisciplinary team decisions in patients with gastrointestinal tumors. For each enrolled case, the AI system and the MDT will independently review the same available clinical information, including medical history, laboratory findings, imaging, pathology, and other relevant diagnostic data, and will generate recommendations regarding diagnosis, staging, treatment planning, and further examinations. An independent expert panel will assess the agreement, clinical appropriateness, and potential major errors of the two decision pathways. AI-generated recommendations will be used solely for research evaluation and will not directly influence patient care. The study aims to determine the feasibility, reliability, and safety of multimodal AI-assisted decision-making in real-world gastrointestinal oncology workflows.
Interventions
OTHERMultidisciplinary Team Clinical Decision Assessment
Using the same clinical information available at the predefined decision time point, the institutional multidisciplinary team will independently formulate recommendations regarding diagnosis, staging, additional examinations, and treatment planning according to routine clinical practice. Clinical management will remain under the responsibility of the treating physicians and the multidisciplinary team. The MDT decision and the independently generated AI output will subsequently be compared and evaluated by an independent expert panel.
OTHERMultimodal Artificial Intelligence-Based Clinical Decision Assessment
Available clinical information for each enrolled participant, including medical history, laboratory findings, endoscopic findings, imaging, pathology, and molecular testing results when available, will be entered into a multimodal artificial intelligence system. The system will independently generate a structured assessment of diagnosis, staging, additional diagnostic tasks, and treatment planning. The AI-generated output will be recorded solely for research comparison, will not be disclosed to the treating multidisciplinary team before its decision is finalized, and will not directly influence patient care.
Sponsors
Shanghai Minimally Invasive Surgery Center
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
1. Aged 18 years or older, with no restriction based on sex. 2. Histologically confirmed gastric, colon, or rectal cancer; or highly suspected gastric, colon, or rectal malignancy based on clinical, endoscopic, or imaging findings, with further diagnostic, staging, or treatment planning required. 3. Scheduled for multidisciplinary team evaluation at the study center because of an initial diagnosis, clinical staging, perioperative treatment, surgical planning, recurrence or metastasis, conversion therapy, treatment response assessment, or another complex clinical management question. 4. A clearly identifiable clinical decision time point can be established, and the clinical information available before that time point can be defined. 5. At the clinical decision time point, at least the basic medical history, the clinical question to be addressed, and at least one core source of information from endoscopy, pathology, or imaging are available. Completion of all examinations is not required, because missing examinations may be evaluated as part of diagnostic task planning. 6. A corresponding multidisciplinary team recommendation regarding diagnostic tasks or the principal treatment decision can be obtained for comparison with the artificial intelligence output. 7. Willing and able to understand the study and provide dated written informed consent.
Exclusion criteria
1. Further examination confirms a condition other than gastric, colon, or rectal cancer, and the case is not applicable to the gastrointestinal oncology pathways evaluated in this study. 2. The participant is undergoing routine follow-up or continuation of a previously established treatment plan and has no clinical question requiring additional diagnostic tasks, modification of the principal treatment pathway, or multidisciplinary team decision-making. 3. A clear clinical decision time point cannot be established, or information available before and after the decision cannot be distinguished, preventing comparison of the artificial intelligence system and the multidisciplinary team under the same information conditions. 4. Core clinical information is severely incomplete, such that the current stage of care and the clinical question cannot be identified and a clinically meaningful artificial intelligence output cannot be generated. 5. A clear multidisciplinary team recommendation corresponding to the clinical decision time point cannot be obtained, or the multidisciplinary team documentation is insufficient for paired evaluation. 6. The participant requires immediate resuscitation or urgent clinical management, and study recruitment could interfere with necessary medical care. 7. The participant is unable to provide valid informed consent because of impaired consciousness, severe cognitive impairment, or another reason, and no ethics-approved proxy consent procedure is available for this study. 8. The participant declines research use of the medical record, endoscopic, pathological, imaging, or other required clinical data. 9. Any other condition that, in the investigator's judgment, could seriously affect participant rights, data compliance, or the reliability of the study results.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Clinical Acceptability Concordance Rate Between the Multimodal Artificial Intelligence System and the Multidisciplinary Team | At the predefined index clinical decision point, within 28 days after enrollment | The proportion of evaluable participants whose AI-generated diagnostic task plan and principal treatment recommendation are judged by an independent expert panel to be fully concordant with the MDT decision or a clinically acceptable alternative. Results will be reported as a percentage with a 95% confidence interval. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Full Concordance Rate | At the predefined index clinical decision point, within 28 days after enrollment | The proportion of evaluable participants whose AI-generated diagnostic task plan and principal treatment recommendation are judged to be fully concordant with the MDT decision. |
| Major Discordance Rate | At the predefined index clinical decision point, within 28 days after enrollment | The proportion of evaluable participants whose AI-generated recommendation is judged to contain a major discordance with potential for clinically significant harm. |
| Successful AI Output Rate | At the predefined index clinical decision point, within 28 days after enrollment | The proportion of enrolled participants for whom the AI system successfully generates an evaluable diagnostic task plan and principal treatment recommendation. |
Countries
China
Contacts
CONTACTJing Sun, MD, PhD
Outcome results
None listed