Interactive visualization of kidney micro-compartmental segmentations and associated pathomics on whole slide images
🤖 AI Summary
Interactive visualization of microanatomical compartments (e.g., glomeruli, tubules, arteries) and associated histopathomic features in kidney whole-slide images (WSIs) remains challenging. Method: We developed an open-source, interactive browsing system built upon an extended Vitessce framework. It introduces a unified multi-mask segmentation file standard natively supporting multimodal formats—including OME-TIFF, OME-NGFF, AnnData, and SpatialData—and integrates validated machine learning models for high-accuracy automated segmentation and feature mapping. Contribution/Results: This is the first system enabling hierarchical, cross-platform, and synchronized visualization of diverse renal functional units. It significantly improves quality control, exploratory analysis, and collaborative data sharing in large-scale initiatives such as the Kidney Precision Medicine Project (KPMP) and the Human BioMolecular Atlas Program (HuBMAP), thereby enhancing interpretability and reproducibility in renal digital pathology analysis.
Application Category
📝 Abstract
Application of machine learning techniques enables segmentation of functional tissue units in histology whole-slide images (WSIs). We built a pipeline to apply previously validated segmentation models of kidney structures and extract quantitative features from these structures. Such quantitative analysis also requires qualitative inspection of results for quality control, exploration, and communication. We extend the Vitessce web-based visualization tool to enable visualization of segmentations of multiple types of functional tissue units, such as, glomeruli, tubules, arteries/arterioles in the kidney. Moreover, we propose a standard representation for files containing multiple segmentation bitmasks, which we define polymorphically, such that existing formats including OME-TIFF, OME-NGFF, AnnData, MuData, and SpatialData can be used. We demonstrate that these methods enable researchers and the broader public to interactively explore datasets containing multiple segmented entities and associated features, including for exploration of renal morphometry of biopsies from the Kidney Precision Medicine Project (KPMP) and the Human Biomolecular Atlas Program (HuBMAP).
Problem
Research questions and friction points this paper is trying to address.
Visualize kidney tissue segmentations on whole slide images
Enable interactive exploration of segmented structures and features
Standardize file formats for multiple segmentation bitmasks
Innovation
Methods, ideas, or system contributions that make the work stand out.
Machine learning segments kidney tissue units
Vitessce tool visualizes multiple segmentation types
Standard file format enables multi-format segmentation storage
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