AI-Assisted Pathologist Performance Improvement: A Multicenter, Prospective, Randomized Controlled Trial

Nanfang Hospital, Southern Medical University

Status: Invitation-only

Conditions: Interdisciplinary Research; Randomized Controlled Trial; Pathology Foundation Model

Treatments: Other: AI pathology model; Other: Control

Study type: Interventional

Funder types: Other

Identifiers

NCT07291362

NFEC-2025-653

Details and patient eligibility

About

We plan to conduct a multicenter, prospective, randomized controlled trial to systematically evaluate the added value of pathology-based AI models in the gastric cancer diagnostic workflow. The study will focus on comparing AI-assisted platform interpretation with conventional independent slide reading in terms of diagnostic accuracy (e.g., AUC), reading efficiency (e.g., comparison of time to diagnosis), quality of diagnostic reports, diagnostic confidence (Likert scale), and pathologists' satisfaction with the AI models. We will also assess superiority for less-experienced (junior) pathologists and noninferiority for more-experienced (senior) pathologists. Successful completion of this project will provide high-level prospective evidence to support the standardized deployment, quality control, and broader application of pathology AI in the gastric cancer care pathway.

Enrollment: 1,000 estimated patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

1. Sex: ≥ 18 years of age;
2. Patients undergoing gastric mucosal biopsy or gastric cancer surgical resection, with available digital pathology images and clinical information.

Exclusion criteria

1.Missing data or data of insufficient quality for analysis

Trial design

Primary purpose: Other

Allocation: Randomized

Interventional model: Crossover Assignment

Masking: Single Blind

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1,000 participants in 2 patient groups, including a placebo group

AI-assisted group

Experimental group

Description:

Doctors in this group are required to use the AI pathology diagnostic model to assist their diagnoses. The AI pathology model will provide a predicted result for each case.

Treatment:

Other: AI pathology model

Independent Diagnosis Group (Control Group)

Placebo Comparator group

Description:

In this group, pathologists will independently diagnose each case based on their own clinical experience, and will record both their time to diagnosis and their diagnostic confidence.

Treatment:

Other: Control