Combination of CT and Ultrasound Radiomics Combined With Liquid Biopsy to Predict Neoadjuvant Chemotherapy Response in Patients With Locally Advanced Gastric Cancer

Sponsor
Liu Yang
Study ID
NCT07697079
Status
Not Yet Recruiting

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Conditions

Eligibility Criteria

Sex
ALL
Age
18 Years - 80 Years
Healthy Volunteers
Not accepted

Study Details

This prospective cohort study aims to construct an artificial intelligence (AI)-derived predictive model for neoadjuvant chemotherapy response prediction in patients with locally advanced gastric cancer based on preoperative ultrasound (US), computed tomography (CT) images and liquid biopsy. Additionally, we explore the potential biological mechanisms behind this model.

Key Dates

First listed
Jul 10, 2026
Start date
Feb 1, 2027
Status verified
Jul 2026
Primary completion
Dec 31, 2029
Completion
Dec 31, 2030

Study Design

Enrollment
300 participants (estimated)

Arms

  • Arm: Good pathological response
    Patients with locally advanced gastric cancer achieved TRG grade 0-1 after the neoadjuvant chemotherapy
  • Arm: Poor pathological response
    Patients with locally advanced gastric cancer achieved TRG grade 2-3 after the neoadjuvant chemotherapy

Primary Outcome Measure

Accuracy of pathological response to neoadjuvant chemotherapyin patients with locally advanced gastric cancer models [ Time Frame: The pathological response prediction model will be assessed immediately after its development. ]

Central Contacts

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Gastric cancer trialsOncology trialsGI oncology trials

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