The Clinical Application of Artificial Intelligence Assisted Renal Biopsy Diagnosis System.
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- This is an observational study: the protocol does not assign a study treatment.
- Who it may be relevant to
- Registry conditions: Chronic Glomerulonephritis, Chronic Kidney Disease. Basic parameters: 15 years — 79 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- China
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official title
The Clinical Application of Artificial Intelligence Assisted Renal Biopsy Image Diagnosis System.
Overview
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.
Detailed description
Renal biopsy pathology is an essential gold standard for the diagnosis of most glomerular diseases, relying on the comprehensive evaluation of H\&E staining, special stains (such as PAS, PASM, and Masson), immunofluorescence, and the ultrastructural study under transmission electron microscopy (TEM). 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.
Primary outcome measures
- The area under curve (AUC) of Receiver Operating Characteristic (ROC) curves of the TEM-AID artificial intelligence model [Time frame: baseline]
Secondary outcome measures (2)
- The specificity of the TEM-AID artificial intelligence model. [Time frame: baseline]
- The sensitivity of the TEM-AID artificial intelligence model. [Time frame: baseline]
Eligibility criteria
Inclusion criteria
- 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.
Exclusion criteria
- Biopsy tissue from donor kidney or transplanted kidney;
- Poor quality of pathological specimen, unable to conduct pathological diagnosis.
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Observational model
- Other
Study locations
China · 2 centers
- Nanfang Hospital — Guangzhou
- Zhujiang Hospital of Southern Medical University — Guangzhou
Identifiers
NCT: NCT07330362 · 2024BA0045_GC