Silent Evaluation of DeepTRG for Assessing Tumor Response After Preoperative Treatment in Stomach and Gastroesophageal Junction Cancer
This is not medical advice. AI-assisted translation — inaccuracies may occur. Always verify the original and consult your oncologist before taking any steps.
About the trial
This study will evaluate whether an artificial intelligence (AI) system called DeepTRG can reliably assess cancer tissue removed during surgery after treatment given before surgery. It will include adults with stomach cancer or cancer at the junction between the stomach and the food pipe who have received treatment before surgery. Pathologists are doctors who examine tissue to diagnose disease. After cancer surgery, they assess how much living cancer remains and whether cancer is present in nearby lymph nodes. DeepTRG analyzes digital images of tissue slides to measure remaining cancer and describe tissue changes, such as scarring and inflammation. It combines information from the original tumor site and lymph nodes to produce a structured assessment. The main question is: \* How often can DeepTRG complete the required assessment and produce a clear result without a person correcting the AI analysis? The study will also examine: * How closely the system's measurements agree with assessments made by independent expert pathologists. * How accurately it detects remaining cancer, including small amounts of cancer and cancer in lymph nodes. * How long the analysis takes and how often it fails or produces an uncertain result. * Whether its performance differs across treatment types and cancer tissue types. This study will take place at the Fourth Hospital of Hebei Medical University in China. Eligible patients will be enrolled consecutively. Researchers will use tissue collected during the patients' planned surgery. No additional surgery or biopsy is required for this study. DeepTRG will run in the background in "silent mode." The doctors responsible for the patients' routine pathology reports and treatment decisions will not receive its results. Patients will continue to receive usual care. The AI model and its grading rules will be fixed before validation begins. Independent expert pathologists will assess the tissue without seeing the AI results. Researchers will then compare the expert assessments, routine pathology reports, and DeepTRG outputs. Cases with poor-quality images, failed analyses, or uncertain outputs will remain part of the assessment of how reliably the system works. Researchers will also collect information about subsequent treatment, cancer recurrence, and survival during follow-up. The initial analysis will focus on feasibility and measurement performance. A separate future study would be needed to determine whether using DeepTRG in clinical care improves doctors' decisions or patient outcomes.
Original English text from ClinicalTrials.gov
Who can (and can't) join
✓ Qualifies
- •Osoby w wieku 18 lat lub starsze.
- •Zdiagnozowany rak żołądka lub połączenia przełykowo-żołądkowego.
- •Pacjenci, którzy otrzymali leczenie przed planowaną operacją.
- •Pacjenci, którzy przejdą operację w celu wyleczenia.
✗ Disqualifies
- •Inne rodzaje raka niż rak gruczołowy.
- •Operacja z powodu nawrotu raka.
- •Tkanka pacjenta była wcześniej używana do nauki systemu DeepTRG.
Simplified criteria — AI translation
Trial details
- Minimum age
- 18 Years
- Last updated (source)
- September 30, 2026
- Sex
- No restrictions
Therapies / drugs in trial
Locations (1)
the Fourth Hospital of Hebei Medical University
Shijiazhuang, China
Trial contact
Ping'an Ding
Contact information from ClinicalTrials.gov. Contact in English.
Share this trial
Data from ClinicalTrials.gov. AI-assisted translation, last sync: 10/1/2026.
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