ArticleScientific reports2024
Investigating quantitative histological characteristics in renal pathology using HistoLens.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- GloPath: An Entity-Centric Foundation Model for Glomerular Lesion Assessment and Clinicopathological Insights.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Rationale, design and baseline characteristics of REMODEL, a mechanism-of-action trial with semaglutide in people with type 2 diabetes and chronic kidney disease.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2025Article
- Label-free multimodal optical biopsy reveals biomolecular and morphological features of diabetic kidney tissue in 2D and 3D.Nature communications · 2025Article
- A Platform for Mitochondrial Profiling in Enriched Kidney Segments Under Thermodynamic Control.bioRxiv : the preprint server for biology · 2025Article
- Label-Free Optical Biopsy Reveals Biomolecular and Morphological Features of Diabetic Kidney Tissue in 2D and 3D.bioRxiv : the preprint server for biology · 2024Article
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9 authors.
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Abstract
HistoLens is an open-source graphical user interface developed using MATLAB AppDesigner for visual and quantitative analysis of histological datasets. HistoLens enables users to interrogate sets of digitally annotated whole slide images to efficiently characterize histological differences between disease and experimental groups. Users can dynamically visualize the distribution of 448 hand-engineered features quantifying color, texture, morphology, and distribution across microanatomic sub-compartments. Additionally, users can map differentially detected image features within the images by highlighting affected regions. We demonstrate the utility of HistoLens to identify hand-engineered features that correlate with pathognomonic renal glomerular characteristics distinguishing diabetic nephropathy and amyloid nephropathy from the histologically unremarkable glomeruli in minimal change disease. Additionally, we examine the use of HistoLens for glomerular feature discovery in the Tg26 mouse model of HIV-associated nephropathy. We identify numerous quantitative glomerular features distinguishing Tg26 transgenic mice from wild-type mice, corresponding to a progressive renal disease phenotype. Thus, we demonstrate an off-the-shelf and ready-to-use toolkit for quantitative renal pathology applications.
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