An Artificial Intelligence Model for Aiding Claudin18.2 Expression Diagnosis in Gastric Adenocarcinoma

Development and Real-World Validation of an Intelligent Interpretation Model for Claudin18.2 Protein Expression in Digestive System Tumors

The investigators plan to develop a deep learning-based automatic interpretation model for Claudin18.2(CLDN18.2) using the institution's and multiple other centers' extensive pathological resources of digestive system adenocarcinomas. This study will not only strictly follow the latest domestic expert consensus and standards, but also aims to address current pain points in manual interpretation. It seeks to provide technical support for standardizing, objectifying, and streamlining CLDN18.2 testing, thereby advancing the application of precision medicine in the diagnosis and treatment of digestive system diseases. The project has clear clinical necessity and broad application prospects.

Study Overview

• Status: Enrolling by invitation
• Conditions: Digestive Oncology

• Study Type: Observational
• Enrollment (Estimated): 2000

Contacts and Locations

Study Locations

• China
  • Guangdong
    • Guangzhou, Guangdong, China, 510515
      • Nanfang Hospital, Southern Medical University
  • Shandong
    • Jinan, Shandong, China, 250014
      • Qianfoshan Hospital

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

Inclusion criteria comprised patients aged over 18 years with definitive pathological diagnoses.

Description

Inclusion Criteria:

1. Age over 18 years.
2. Patients who underwent CLDN18.2 immunohistochemistry and H&E staining.
3. Availability of complete pathology reports and clinical information.

Exclusion Criteria:

1.Patients with missing data or specimens not meeting quality control requirements for analysis.

Study Plan

How is the study designed?

Number of groups / cohorts

3

Cohorts and Interventions

Group / Cohort
Prospective validation dataset; We conducted a prospective validation study to compare the diagnostic performance among pathologists, our pathology foundation model, and pathologist-with-AI-assisted diagnosis. This study was initiated on October 1, 2025 at Nanfang Hospital, Southern Medical University (NFHSMU)
QFSH external validation dataset; 2000 slides from 1000 eligible individuals were obtained in the Qianfoshan Hospital (QFSH, Jinan, China) between January 2020 and February 2026, which was used to validate the model.
Randomized controlled trial; We conducted a randomized controlled trial（RCT）to compare the diagnostic performance among pathologists, the pathology foundation model, and pathologist-with-model-assisted diagnosis at Nanfang Hospital of Southern Medical University (NFHSMU).The trial commenced data collection on February 1, 2023 to establish the NFHSMU randomized controlled trial dataset. Following quality control, the slides were randomly allocated (1:1 ratio) into three groups:Pathologist-only group/Model-assisted pathologist group.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Area under ROC curve (AUC)	Area under the curve	Diagnostic evaluation will be performed within 1 week when the whole slide images(WSIs) are obtained.

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Specificity	The true negative rate (TNR) of the diagnostic platform, which is the ratio between the number of negative individuals correctly categorized by platform and the total number of actual negative individuals (%).	Diagnostic evaluation will be performed within 1 week when the WSIs are obtained
Sensitivity	The true positive rate (TPR) of the diagnostic platform, which is the ratio between the number of positive individuals correctly categorized by platform and the total number of actual positive individuals (%).	Diagnostic evaluation will be performed within 1 week when the WSIs are obtained

Collaborators and Investigators

• Sponsor: Nanfang Hospital, Southern Medical University
• Collaborators: Qianfoshan Hospital
• Investigators: Study Director: Li Liang, Nanfang Hospital, Southern Medical University

Study record dates

Study Major Dates

• Study Start (Actual): October 1, 2025
• Primary Completion (Estimated): July 1, 2028
• Study Completion (Estimated): August 1, 2028

Study Registration Dates

• First Submitted: November 27, 2025
• First Submitted That Met QC Criteria: November 27, 2025
• First Posted (Actual): December 10, 2025

Study Record Updates

• Last Update Posted (Actual): February 10, 2026
• Last Update Submitted That Met QC Criteria: February 6, 2026
• Last Verified: February 1, 2026

More Information

Terms related to this study

• Other Study ID Numbers: NFEC-2025-619

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO
• IPD Plan Description: Requests for the data collected and analyzed in this study will be considered if the application is in line with public benefits and the applicant is willing to sign a data access agreement. Contact can be through the corresponding author.