Observational studyKidney international2025
Clinical relevance of computationally derived tubular features and their spatial relationships with the interstitial microenvironment in minimal change disease/focal segmental glomerulosclerosis.
Observational study in Kidney international, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Next-generation kidney tissue analysis - spatial omics and digital pathology.Nature reviews. Nephrology · 2026Review
- Artificial Intelligence in Kidney Transplant Pathology: Current Evidence, Limitations, and Relevance to the Banff Framework.Kidney international reports · 2026Review
- Individualised treatment effects of corticosteroids in IgA nephropathy.EBioMedicine · 2026Article
- Rapid slide-level assessment of glomerular yield using virtual staining of unstained renal biopsy sections.Diagnostic pathology · 2026Article
- Prognostic Stratification in Primary Glomerulonephritis: Integrating Histology, Biomarkers, and Risk Prediction Models.Life (Basel, Switzerland) · 2026Review
- Computational Characterization of Lymphocyte Topology on Whole Slide Images of Glomerular Diseases.Journal of the American Society of Nephrology : JASN · 2026Article
- Glomerular Segmentation, Classification, and Pathomic Feature-based Prediction of Clinical Outcomes in Minimal Change Disease and Focal Segmental Glomerulosclerosis.medRxiv : the preprint server for health sciences · 2025Article
- Can Artificial Intelligence Whole Slide Image-Based Methods Predict Kidney Function?Kidney international reports · 2025Article
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21 authors.
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Abstract
backgroundVisual scoring of tubular damage has limitations in capturing the full spectrum of structural changes and prognostic potential. Here, we investigated if computationally quantified tubular features can enhance prognostication and reveal spatial relationships with interstitial fibrosis.
methodsDeep-learning and image-analysis approaches were employed on 254/266 Periodic acid Schiff-stained whole slide image (WSI) kidney biopsies from participants in the NEPTUNE/CureGN prospective observational cohort studies (135/153 with focal segmental glomerulosclerosis (FSGS) and 119/113 with minimal change disease (MCD)) to segment cortex, tubular lumen (TL), epithelium (TE), nuclei (TN), and basement membrane (TBM). One hundred four pathomic features were extracted from these segmented tubular substructures and aggregated at the patient level using summary statistics. In the NEPTUNE dataset, tubular features were quantified at the WSI level and in manually segmented regions of mature interstitial fibrosis and tubular atrophy (IFTA), pre-IFTA, and non-IFTA. Minimum Redundancy Maximum Relevance was then used to select features most associated with disease progression and proteinuria remission. Ridge-penalized Cox models evaluated their predictive discrimination compared to clinical/demographic data and visual-assessment. Models were evaluated in the CureGN dataset.
resultsNine features were predictive of disease progression and/or proteinuria remission. Models with tubular features had high prognostic accuracy in both NEPTUNE and CureGN, and higher prognostic accuracy for both outcomes compared to conventional parameters alone in NEPTUNE. TBM thickness/area and TE flattening and/or reduced cell size progressively increased from non- to pre- and mature IFTA.
conclusionsPreviously underrecognized computationally derived and quantifiable tubular characteristics may contribute to improving prognostic accuracy and risk stratification in patients with FSGS/MCD. Future studies are needed to test their generalizability across different diseases and populations before they can be deployed in clinical practice.
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