The Clinical Application of Artificial Intelligence Assisted Renal Biopsy Diagnosis System.

NCT07330362 | Recruiting

• 1 other identifier: 2024BA0045_GC
• Study Type: observational
• Target: 2,900
• Locations: 1 country
• Sites: 2

Brief Summary

This research project aims to collect images from patients with chronic glomerulonephritis. For each subject, the images obtained from renal biopsy will undergo evaluation by both the diagnostic model and the 'gold standard' diagnosis by pathologists. The researchers will test the subjects using the diagnostic model and compare the results with the known 'gold standard' diagnosis, in order to evaluate the AUC, specificity, and sensitivity of the diagnostic model.

Conditions

Chronic Kidney Disease; Chronic Glomerulonephritis

Keywords

Artificial intelligence; TEM-AID; glomerulonephritis

Outcome Measures

Primary Outcomes (1)

• The area under curve (AUC) of Receiver Operating Characteristic (ROC) curves of the TEM-AID artificial intelligence model

  The area under curve (AUC) of Receiver Operating Characteristic (ROC) curves of the TEM-AID artificial intelligence model for candidates will be calculated.

  baseline

Secondary Outcomes (2)

• The specificity of the TEM-AID artificial intelligence model.

  baseline

• The sensitivity of the TEM-AID artificial intelligence model.

  baseline

Eligibility Criteria

• Age: 15 Years - 79 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

For patients with chronic kidney disease who need further diagnosis through renal biopsy.

You may qualify if:

• Voluntary signing of informed consent form;
• Patients clinically diagnosed or suspected of having chronic kidney disease according to the 2023 KDIGO Clinical Practice Guideline for the Evaluation and Management of Kidney Disease;
• Undergoing renal biopsy and pathological specimen preparation.

You may not qualify if:

• Biopsy tissue from donor kidney or transplanted kidney;
• Poor quality of pathological specimen, unable to conduct pathological diagnosis.

Sponsors & Collaborators

• Zhujiang Hospital: lead

Study Sites (2)

Nanfang Hospital

Guangzhou, Guangdong, China

RECRUITING

Zhujiang Hospital of Southern Medical University

Guangzhou, Guangdong, China

RECRUITING

MeSH Terms

Conditions

Renal Insufficiency, Chronic; Glomerulonephritis

Condition Hierarchy (Ancestors)

Renal Insufficiency; Kidney Diseases; Urologic Diseases; Female Urogenital Diseases; Female Urogenital Diseases and Pregnancy Complications; Urogenital Diseases; Male Urogenital Diseases; Chronic Disease; Disease Attributes; Pathologic Processes; Pathological Conditions, Signs and Symptoms; Nephritis

Central Study Contacts

Yangshu Zhou

CONTACT

020-61643888; 764709402@qq.com

Study Design

• Study Type: observational
• Observational Model: OTHER
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: December 28, 2025
• First Posted: January 9, 2026
• Study Start: July 1, 2024
• Primary Completion (Estimated): December 31, 2026
• Study Completion (Estimated): December 31, 2026
• Last Updated: January 27, 2026

Record last verified: 2025-12

Data Sharing

• IPD Sharing: Will not share

Locations

CN (2)