Multistain multicompartment automatic segmentation in renal biopsies with thrombotic microangiopathies and other vasculopathies.
Academic Article
Overview
abstract
Automatic tissue segmentation is a necessary step for the bulk analysis of whole slide images (WSIs) from paraffin histology sections in kidney biopsies. However, existing models often fail to generalize across the main nephropathological staining methods and to capture the severe morphological distortions in arteries, arterioles, and glomeruli common in thrombotic microangiopathy (TMA) or other vasculopathies. Therefore, we developed an automatic multi-staining segmentation pipeline covering six key compartments: Artery, Arteriole, Glomerulus, Cortex, Medulla, and Capsule/Other. This framework enables downstream tasks such as counting and labeling at instance-, WSI- or biopsy-level. Biopsies (n = 158) from seven centers: Cologne, Turin, Milan, Weill-Cornell, Mainz, Maastricht, Budapest, were classified by expert nephropathologists into TMA (n = 87) or Mimickers (n = 71). Ground truth expert segmentation masks were provided for all compartments, and expert binary TMA classification labels for Glomerulus, Artery, Arteriole. The biopsies were divided into training (n = 79), validation (n = 26), and test (n = 53) subsets. We benchmarked six deep learning models for semantic segmentation (U-Net, FPN, DeepLabV3+, Mask2Former, SegFormer, SegNeXt) and five models for classification (ResNet-34, DenseNet-121, EfficientNet-v2-S, ConvNeXt-Small, Swin-v2-B). We obtained robust segmentation results across all compartments. On the test set, the best models achieved Dice coefficients of 0.903 (Cortex), 0.834 (Medulla), 0.816 (Capsule/Other), 0.922 (Glomerulus), 0.822 (Artery), and 0.553 (Arteriole). The best classification models achieved Accuracy of 0.724 and 0.841 for Glomerulus and Artery plus Arteriole compartments, respectively. Furthermore, we release NePathTK (NephroPathology Toolkit), a powerful open-source end-to-end pipeline integrated with QuPath, enabling accurate segmentation for decision support in nephropathology and large-scale analysis of kidney biopsies.
