@inproceedings{4139fa2e82344dabb2a92d834d1f1dc7,
title = "Automated detection and quantification of Wilms' Tumor 1-positive cells in murine diabetic kidney disease",
abstract = "In diabetic kidney disease (DKD), podocyte depletion, and the subsequent migration of parietal epithelial cells (PECs) to the tuft, is a precursor to progressive glomerular damage, but the limitations of brightfield microscopy currently preclude direct pathological quantitation of these cells. Here we present an automated approach to podocyte and PEC detection developed using kidney sections from mouse model emulating DKD, stained first for Wilms' Tumor 1 (WT1) (podocyte and PEC marker) by immunofluorescence, then post-stained with periodic acid-Schiff (PAS). A generative adversarial network (GAN)-based pipeline was used to translate these PAS-stained sections into WT1-labeled IF images, enabling in silico label-free podocyte and PEC identification in brightfield images. Our method detected WT1-positive cells with high sensitivity/specificity (0.87/0.92). Additionally, our algorithm performed with a higher Cohen's kappa (0.85) than the average manual identification by three renal pathologists (0.78). We propose that this pipeline will enable accurate detection of WT1- positive cells in research applications.",
author = "Darshana Govind and Santo, {Briana A.} and Brandon Ginley and Rabi Yacoub and Rosenberg, {Avi Z.} and Jen, {Kuang Yu} and Vighnesh Walavalkar and Wilding, {Gregory E.} and Worral, {Amber M.} and Imtiaz Mohammad and Pinaki Sarder",
note = "Publisher Copyright: {\textcopyright} COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.; Medical Imaging 2021: Digital Pathology ; Conference date: 15-02-2021 Through 19-02-2021",
year = "2021",
doi = "10.1117/12.2581387",
language = "English (US)",
series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",
publisher = "SPIE",
editor = "Tomaszewski, {John E.} and Ward, {Aaron D.}",
booktitle = "Medical Imaging 2021",
}