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

NCT07697079 | Not Yet Recruiting DMC

• 1 other identifier: YXLL-KY-2026(046)
• Study Type: observational
• Target: 300
• Locations: 1 country
• Sites: 1

Brief Summary

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.

Conditions

Gastric Cancer

Keywords

locally advanced gastric cancer; ultrasound; CT; liquid biopsies; radiomics; neoadjuvant chemotherapy; Pathological response

Outcome Measures

Primary Outcomes (1)

• Accuracy of pathological response to neoadjuvant chemotherapyin patients with locally advanced gastric cancer models

  This prospective study will collect contrast-enhanced abdominal CT and ultrasound images, as well as peripheral blood samples, from 300 patients with locally advanced gastric cancer (LAGC) prior to neoadjuvant chemotherapy. Using deep learning and machine learning algorithms, we will construct a tumor regression grade (TRG)-oriented model to predict pathological response to treatment. TRG classification is defined in accordance with the NCCN Guidelines (Version 4, 2021): TRG 0-1 indicates favorable response; TRG 2-3 poor response. The diagnostic accuracy and stability of the model will be evaluated, with performance quantified via the AUC and precision-recall curve.

  The pathological response prediction model will be assessed immediately after its development.

Study Arms (2)

Good pathological response

Patients with locally advanced gastric cancer achieved TRG grade 0-1 after the neoadjuvant chemotherapy

Poor pathological response

Patients with locally advanced gastric cancer achieved TRG grade 2-3 after the neoadjuvant chemotherapy

Eligibility Criteria

• Age: 18 Years - 80 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

patients with histologically confirmed GC at a locally advanced stage (cT2-4N0/+M0) who received NACT

You may qualify if:

• Capable of understanding the study and voluntarily signing the written informed consent form (ICF) prior to any study-specified research procedures.
• Aged ≥18 and ≤80 years old at the time of ICF signing.
• Pathologically confirmed locally advanced gastric cancer (LAGC, cT2NxM0-cT4NxM0) with clinical indications for neoadjuvant chemotherapy.
• Completion of gastrointestinal contrast-enhanced ultrasound and contrast-enhanced abdominal CT before neoadjuvant chemotherapy.
• Provision of peripheral blood samples before chemotherapy (for genetic and protein detection).
• Availability of postoperative pathological specimens for TRG grading after standardized neoadjuvant chemotherapy.
• Willing and able to comply with all study protocol requirements.

You may not qualify if:

• Diagnosis of non-primary gastric cancer.
• Incomplete imaging data, failure to collect peripheral blood samples, or substandard sample quality.
• Discontinued chemotherapy, modified treatment regimen, or lack of complete postoperative pathological assessment.
• Unavailable follow-up data precluding evaluation of chemotherapy response.
• Concurrent participation in another clinical trial; or any other conditions judged by investigators to warrant subject withdrawal, including severe comorbidities requiring simultaneous treatment (psychiatric disorders included), alcohol dependence, substance abuse, or familial/social factors that may compromise subject safety or treatment compliance.

Sponsors & Collaborators

• Liu Yang: lead

Study Sites (1)

QianfoshanH

Jinan, Shandong, 250014, China

Location

Biospecimen

Retention: SAMPLES WITH DNA

Blood samples were prospectively collected using Cell-Free DNA BCT tubes (Streck, La Vista, NE).

MeSH Terms

Conditions

Stomach Neoplasms

Condition Hierarchy (Ancestors)

Gastrointestinal Neoplasms; Digestive System Neoplasms; Neoplasms by Site; Neoplasms; Digestive System Diseases; Gastrointestinal Diseases; Stomach Diseases

Study Officials

• Guang yong Zhang

  Qianfoshan Hospital

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Liu Yang

CONTACT

+8615168862857; yangliu102625@163.com

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: Attending Physician

Study Record Dates

• First Submitted: July 5, 2026
• First Posted: July 10, 2026
• Study Start (Estimated): February 1, 2027
• Primary Completion (Estimated): December 31, 2029
• Study Completion (Estimated): December 31, 2030
• Last Updated: July 13, 2026

Record last verified: 2026-07

Data Sharing

• IPD Sharing: Will not share

Locations

CN (1)