NCT07849608Recruiting
Silent Evaluation of DeepTRG for Assessing Tumor Response After Preoperative Treatment in Stomach and Gastroesophageal Junction Cancer
Prospective Observational Study of the Feasibility and Accuracy of DeepTRG for Automated Pathological Response Assessment After Neoadjuvant Therapy in Gastric and Gastroesophageal Junction Adenocarcinoma: A Single-Center Silent Validation Study
Source: ClinicalTrials.gov · Last updated 30 Sept 2026
Brief summary (registry, in English)
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.
- Status (registry)
- Recruiting
- Study type
- Observational
- Enrollment
- 200 (estimated)
- First submitted
- 24 Sept 2026
- Start date
- 1 Sept 2026
- Primary completion date
- 30 Dec 2026
- Lead sponsor
- Qun Zhao
- Diseases
- Gastric and esophageal cancer
- NCT number
- NCT07849608
What you commit to
- Study type: Observational
- Planned participants: 200
- From 1 Sept 2026 to the primary completion date, 30 Dec 2026
- 1 site in 1 country
- Visits and tests: ask the trial team, the registry does not list them
Built from the registry fields of ClinicalTrials.gov. It describes the study, not your situation.
Who cannot take part
Copied verbatim from ClinicalTrials.gov and grouped by topic. Only the trial team decides who can take part.
Prior treatment
- Previous inclusion of the patient's tissue or data in DeepTRG model training, grading-rule development, or parameter tuning.
- Patients will not be excluded because of a complete pathological response, positive surgical margins, poor-quality or unavailable slides, digitization failure, algorithm failure, or uncertain or unassessable DeepTRG results. Technical limitations identified after enrollment will be recorded and retained in the feasibility analysis. Patients who do not proceed to surgical resection will be documented in the study flow and will not contribute to the specimen-based primary outcome denominator.
Other illness
- Non-adenocarcinoma malignancies, including squamous cell carcinoma, lymphoma, gastrointestinal stromal tumor, or neuroendocrine carcinoma.
- Surgery for recurrent gastric or gastroesophageal junction cancer.
Who the study is looking for
- Age 18 years or older.
- Histologically confirmed adenocarcinoma of the stomach or gastroesophageal junction (Siewert type II or III), diagnosed before neoadjuvant treatment.
- Received neoadjuvant anticancer treatment before planned surgical resection.
- Scheduled to undergo surgical resection with curative intent at the Fourth Hospital of Hebei Medical University, with routine pathological examination of the primary tumor site and regional lymph nodes.
- Written informed consent obtained in accordance with the ethics-approved study protocol.
Age in the registry: 18 years to - · Sex: All
Sites (1)
Sites in registry order. Pick your city on the disease page to sort them by distance.
| Site | City | Country | Site status |
|---|---|---|---|
| The Fourth Hospital of Hebei Medical University Coordinator of this site? Confirm its status | Shijiazhuang | China | Recruiting |
This page is information, not medical advice. Discuss any trial with your doctor.