Model Development and Application Based on Renal Pathology Images

This single-center retrospective observational cohort study will utilize digital renal pathology images along with corresponding clinical and laboratory data from patients who underwent kidney biopsy at Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, between January 1, 2019, and March 31, 2026. Deep learning and image analysis techniques will be employed to develop and validate models for the pathological diagnosis and classification of kidney diseases. The study will also assess model performance in evaluating disease activity and chronicity, as well as investigate the association between image-derived features and long-term renal outcomes. Diagnoses will be established by consensus among three senior renal pathologists, who will serve as the reference standard. A minimum of 8,000 eligible cases are planned for inclusion, which will be divided into training, validation, and independent test sets.

Inclusion Criteria: 1. Patients with kidney disease confirmed by kidney biopsy. 2. Availability of complete digital renal pathology images, including light microscopy, immunofluorescence microscopy, and/or electron microscopy images, as required for the relevant diagnostic task. 3. Availability of the clinical and laboratory data required for the planned analyses. Exclusion Criteria: 1. Renal pathology images of insufficient quality for analysis. 2. Missing key clinical data required for the planned analyses. 3. Kidney allograft biopsy specimens.