Podocytes are depleted in several renal parenchymal processes. The current gold standard to identify podocytes considers histopathological staining of nuclei using specific antibodies and manual enumeration, which is expensive and laborious. We have developed PodoSighter, a cloud-based tool for automated, label-free podocyte detection and three-dimensional quantification from periodic acid-Schiff-stained histologic sections. A diverse dataset from rodent models of glomerular diseases (diabetic kidney disease, crescentic glomerulonephritis, and dose-dependent direct podocyte toxicity and depletion), human biopsies for steroid resistant nephrotic syndrome, and human autopsy tissue, demonstrate generalizability of the tool. Samples were derived from multiple labs, supporting broad application. This tool may facilitate clinical assessment and research involving podocyte morphometry.
D. Govind, J. U. Becker, J. Miecznikowski, A. Rosenberg, J. Dang, P. L. Tharaux, R. Yacoub, F. Thaiss, P. F. Hoyer, D. Manthey, B. Lutnick, A. M. Worral, I. Mohammad, V. Walavalkar, J. E. Tomaszewski, K. Y. Jen, and P. Sarder, “PodoSighter: A cloud-based tool for label-free podocyte detection in kidney whole slide images,” Journal of the American Society of Nephrology, vol. 32, no. 11, pp. 2795-2813, Nov. 2021.