Research on Early Recurrence of Locally Advanced Gastric Cancer Based on CT Radiomics Prediction

Enrolling by invitation

Conditions studied: Gastric Cancer

In brief

This study aims to develop a model for predicting postoperative recurrence in patients with LAGC using artificial intelligence (AI) technology based on preoperative computed tomography (CT) images

Key facts

Study ID

NCT07683195

Run by

Liu Yang

People needed

900

Starts

2020-01-01

Expected to finish

2026-08-31

Last updated by the study team

2026-07-07

Who can join

Age: 18 and older, up to 85. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

• pathology diagnosis of LAGC (pT2NxM0-pT4NxM0);
• radical gastrectomy with D2 lymph node dissection (>15 lymph nodes);
• available clinicopathological data;
• patients underwent contrast-enhanced abdominal CT scans within 4 weeks before surgery.

You may not qualify if…

• preoperative treatment for LAGC (radiotherapy, chemotherapy, or systemic therapy);
• previous malignancies;
• unsatisfactory gastric distention or inability to identify the primary tumor;
• image artifacts.

Where it is running

• QianfoshanH — Jinan, Shandong, China

Full record on ClinicalTrials.gov

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