Validation of virtual trichrome stains for kidney fibrosis evaluation using dual-mode emission and transmission microscopy
Year: 2025
Type: preprint
Abstract: Assessment of interstitial fibrosis is essential in the diagnosis and prognosis of kidney diseases. However, current histologic scoring methods using trichrome-stained slides are limited by inter-observer variability and inconsistent stain reproducibility. To address these challenges, we developed DUET (DUal-mode Emission and Transmission) microscopy, a novel imaging platform that rapidly captures both brightfield and fluorescence images from H&E-stained slides to generate pixel-registered collagen images and virtual trichrome stains. In a cohort of 32 kidney transplant biopsies, four renal pathologists estimated the extent of interstitial fibrosis in real trichrome and DUET-derived virtual trichrome whole slide images, with the latter showing improved inter-pathologist agreement. A deep learning pipeline was trained to segment interstitial kidney regions from DUET-acquired images, enabling semi-automated computational fibrosis quantitation, which demonstrated a positive correlation with pathologists' estimates of interstitial fibrosis. These findings highlight DUET as a rapid, cost-effective, and scalable alternative to traditional trichrome staining, offering both visual and computational advantages.
Source: medRxiv
Authors: Willy Ju, Samuel Border, Fatemeh Afsari, Srishti Seth, Sarah Rezapourdamanab, Ruben Renteria, Shalini S. Ramachandra, Rajib Gupta, Fadi Salem, Alton B. Farris, Richard Levenson, Jarcy Zee, Pinaki Sarder, Kuang-Yu Jen, Farzad Fereidouni
Language: English
Topic: AI in cancer detection
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4416248357