# Zebra bodies recognition by artificial intelligence (ZEBRA): a computational tool for Fabry nephropathy

## TL;DR

This paper introduces ZEBRA, an AI tool that helps detect kidney damage in Fabry disease by analyzing biopsy images and improving diagnostic accuracy.

## Contribution

The novel ZEBRA score and AI pipeline provide a new method for screening and quantifying Fabry nephropathy in renal biopsies.

## Key findings

- EfficientNetB2 achieved 79% accuracy in classifying foamy podocytes.
- SegFormerB4 showed best segmentation performance with Dice score of 0.46 and IoU of 0.37.
- The ZEBRA score correlated well with manual scoring (rs = 0.66–0.71) and distinguished Fabry nephropathy from controls.

## Abstract

Fabry disease (FD) is a rare lysosomal storage disorder caused by mutations in the GLA gene, resulting in globotriaosylceramide accumulation. Kidney involvement (Fabry nephropathy) significantly contributes to morbidity and mortality. Diagnosis can be difficult, especially in females or late-onset variants. Renal biopsy remains essential, but interpretation requires expert pathologists. Digital pathology and artificial intelligence (AI) offer promising solutions to support diagnosis. The study analyzed Whole-slide images from renal biopsies of Fabry nephropathy patients to develop and validate a “foamy podocytes” screening AI tool. Two computational tasks were performed: glomerular-level classification, and podocyte-level segmentation. Performance was evaluated using standard metrics. A novel ZEBRA score (fpA/tgA%) was developed to quantify disease burden, and correlations with histological scores and clinical parameters were assessed. EfficientNetB2 achieved the highest classification accuracy (79%) in identifying foamy podocytes. SegFormerB4 had the best segmentation performance (Dice = 0.46, IoU = 0.37). The ZEBRA score effectively distinguished Fabry nephropathy from controls (p < 0.001) and showed good correlation with manual scoring (rs = 0.66–0.71). The AI-assisted ZEBRA pipeline highlights high-risk Fabry nephropathy features to support nephropathologists as a screening tool.

The online version contains supplementary material available at 10.1038/s41598-026-35466-w.