Skip to main content
OpenTrials
Recruiting

NCT Number: NCT07157618

Prospective Pathology Foundation Models

Histopathology remains the gold standard for disease diagnosis, yet faces challenges including pathologist shortages and diagnostic model limitations. This underscores the critical need to develop deep learning-based pathology foundation models integrating prospective imaging and clinical data. Such models would enhance diagnostic accuracy and efficiency, enabling tumor grading, histo-molecular classification, and intelligent chemotherapy guidance - ultimately optimizing clinical workflows. However, a critical gap remains: the absence of prospectively validated, pan-disease pathology foundation models. Developing clinically validated models is therefore imperative.

Recruiting

Interested in participating?

Request Info

Key information

Conditions

Age range

18 year–75 year

Sex eligibility

All sexes

Study type

Observational

Primary location

Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China

Loading trial locations.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Aged 18-75 years old.
  • Patients with complete pathological slides and clinical information.

Exclusion criteria

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

Treatment and study plan

Primary outcomes

  1. Area under ROC curve (AUC)

    Time frame: Diagnostic evaluation will be performed within 1 week when the WSIs are obtained

    Area under the curve

Secondary outcomes

  1. Specificity

    Time frame: Diagnostic evaluation will be performed within 1 week when the WSIs are obtained

    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 (%).

  2. Sensitivity

    Time frame: Diagnostic evaluation will be performed within 1 week when the WSIs are obtained

    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 (%).

Study contacts

Contact information is provided by the study sponsor or research team.

Zhengyu Zhang

CONTACT

[email protected]

+8613837365993

Sponsors and collaborators

Lead sponsor

Nanfang Hospital, Southern Medical University

Other

Collaborators

  • Air Force Military Medical University, China
  • First Affiliated Hospital of Shantou University Medical College
  • Qianfoshan Hospital
  • The First Affiliated Hospital of Zhengzhou University
  • Zhejiang University
  • Zhujiang Hospital

Registry information

Official study title

Development and Clinical Application of Deep Learning-Based Prospective Pathology Foundation Models

Important dates

Study start
2025
Primary completion
2028
Study completion
2028
First posted
Sep 5, 2025
Registry last updated
Apr 23, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

Published trials that share one or more normalized conditions with this study.