NCT06451393Recruiting
Predicting Gastric Cancer Response to Chemo With Multimodal AI Model
A Radio-Pathomic Multimodal Machine Learning Model for Predicting Pathological Complete Response to Neoadjuvant Chemotherapy in Advanced Gastric Cancer: A Retrospective Observational Study
Source: ClinicalTrials.gov · Last updated 11 Jun 2024 · Not updated for over 12 months - ask the site whether it is still open
Brief summary (registry, in English)
This study aims to develop a multimodal model combining radiomic and pathomic features to predict pathological complete response (pCR) in advanced gastric cancer patients undergoing neoadjuvant chemotherapy (NAC). The researchers intended to collected pre-intervention CT images and pathological slides from patients, extract radiomic and pathomic features, and build a prediction model using machine learning algorithms. The model will be validated using a separate cohort of patients. This research intend to build a radiomic-pathomic model that can outperform models based on either radiomic or pathomic features alone, aiming to improve the prediction of pCR in gastric cancer.
- Status (registry)
- Recruiting
- Study type
- Observational
- Enrollment
- 500 (estimated)
- First submitted
- 4 Jun 2024
- Start date
- 1 Feb 2013
- Primary completion date
- 30 Sept 2022
- Lead sponsor
- Sixth Affiliated Hospital, Sun Yat-sen University
- Diseases
- Gastric and esophageal cancer
- NCT number
- NCT06451393
What you commit to
- Study type: Observational
- Planned participants: 500
- From 1 Feb 2013 to the primary completion date, 30 Sept 2022
- 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.
Other
- Patients with indistinguishable tumor lesions on the CT images due to insufficient filling of the stomach during the CT inspection;
- patients without indistinguishable tumor cell on the pathological slides due to inadequate sampling;
- patients with insufficient data.
Who the study is looking for
- patients with histologically confirmed adenocarcinoma of the stomach or esophagogastric junction who received NAC and radical gastrectomy;
- patients who underwent abdominal multidetector computed tomography (CT) inspection, gastroscope, and tumor tissue biopsy before any intervention started;
- Lesions that are assessable according to The Response Evaluation Criteria in Solid Tumors Version 1.1
Age in the registry: 20 years to 90 years · Sex: All · Does not accept healthy volunteers
Sites (1)
Sites in registry order. Pick your city on the disease page to sort them by distance.
| Site | City | Country | Site status |
|---|---|---|---|
| The Sixth Affiliated Hospital, Sun Yat-sen University Coordinator of this site? Confirm its status | Guangzhou | China | Recruiting |
This page is information, not medical advice. Discuss any trial with your doctor.