Predicting Gastric Cancer Response to Chemo With Multimodal AI Model

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Total Enrollment

500 participants

Study Classification

OBSERVATIONAL

Study Start Date

2013-02-01

Study Completion Date

2026-12-30

Brief Summary

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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.

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Detailed Description

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Conditions

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Gastric Cancer Chemotherapy Effect

Study Design

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Observational Model Type

COHORT

Study Time Perspective

RETROSPECTIVE

Study Groups

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Neoadjuvant chemotherapy with radical tumor resection surgery

(i) Patients with indistinguishable tumor lesions on the CT images due to insufficient filling of the stomach during the CT inspection; (ii) patients without indistinguishable tumor cell on the pathological slides due to inadequate sampling; (iii) patients with insufficient data.

Neoadjuvant chemotherapy with radical tumor resection surgery

Intervention Type DRUG

All patients were pathologically diagnosed as advanced gastric cancer, all receive neoadjuvant chemotherapy, after the completion of neoadjuvant chemotherapy, all patients receive radical tumor resection surgery (partial gastrectomy or total gastrectomy, as proper).

Interventions

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Neoadjuvant chemotherapy with radical tumor resection surgery

All patients were pathologically diagnosed as advanced gastric cancer, all receive neoadjuvant chemotherapy, after the completion of neoadjuvant chemotherapy, all patients receive radical tumor resection surgery (partial gastrectomy or total gastrectomy, as proper).

Intervention Type DRUG

Eligibility Criteria

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Inclusion Criteria

* 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

Exclusion Criteria

* 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.

Minimum Eligible Age

20 Years

Maximum Eligible Age

90 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No