Automated detection and quantification of Wilms’ Tumor 1-positive cells in murine diabetic kidney disease

Darshana Govind; Briana A. Santo; Brandon Ginley; Rabi Yacoub; Avi Z. Rosenberg; Kuang-Yu Jen; Vighnesh Walavalkar; Gregory E. Wilding; Amber M. Worral; Imtiaz Mohammad; Pinaki Sarder

doi:10.1117/12.2581387

15 February 2021 Automated detection and quantification of Wilms’ Tumor 1-positive cells in murine diabetic kidney disease

Darshana Govind, Briana A. Santo, Brandon Ginley, Rabi Yacoub, Avi Z. Rosenberg, Kuang-Yu Jen, Vighnesh Walavalkar, Gregory E. Wilding, Amber M. Worral, Imtiaz Mohammad, Pinaki Sarder

Author Affiliations +

Proceedings Volume 11603, Medical Imaging 2021: Digital Pathology; 116030F (2021) https://doi.org/10.1117/12.2581387
Event: SPIE Medical Imaging, 2021, Online Only

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.

Conference Presentation

Citation Download Citation

Darshana Govind, Briana A. Santo, Brandon Ginley, Rabi Yacoub, Avi Z. Rosenberg, Kuang-Yu Jen, Vighnesh Walavalkar, Gregory E. Wilding, Amber M. Worral, Imtiaz Mohammad, and Pinaki Sarder "Automated detection and quantification of Wilms’ Tumor 1-positive cells in murine diabetic kidney disease", Proc. SPIE 11603, Medical Imaging 2021: Digital Pathology, 116030F (15 February 2021); https://doi.org/10.1117/12.2581387

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE