Kidney fibrosis evaluation using dual-mode emission and transmission microscopy
6 affiliations
- 1Emory University, Department of Pathology and Laboratory Medicine, Atlanta, Georgia, United States
- 2University of Florida, Department of Biomedical Engineering, Gainesville, Florida, United States
- 3University of Pennsylvania Perelman School of Medicine, Department of Biostatistics, Epidemiology, and Informatics, Philadelphia, Pennsylvania, United States
- 4UC Davis Health, Department of Pathology and Laboratory Medicine, Sacramento, California, United States
- 5Mayo Clinic, Department of Pathology and Laboratory Medicine, Jacksonville, Florida, United States
- 6Children’s Hospital of Philadelphia Research Institute, Philadelphia, Pennsylvania, United States
Abstract
Purpose: Interstitial fibrosis is a critical histopathologic feature used in the diagnosis and prognosis of kidney diseases. However, conventional assessment using trichrome-stained slides is limited by interobserver variability and inconsistent stain reproducibility. This study evaluates whether dual-mode emission and transmission (DUET) microscopy, which generates virtual trichrome images from hematoxylin and eosin (H&E) slides, can provide a practical, reproducible, and quantitative alternative for assessing interstitial fibrosis in kidney transplant biopsies.
Approach: Thirty-two kidney transplant biopsies were imaged using DUET to acquire pixel-registered brightfield and fluorescence whole-slide images from H&E-stained slides. A deep learning pipeline was trained on DUET-acquired images to extract collagen-positive signal from both the brightfield and fluorescence channels, which was used to generate virtual trichrome images and to compute quantitative fibrosis scores. Virtual trichrome images were compared with corresponding conventional trichrome slides. Four renal pathologists independently estimated interstitial fibrosis on both modalities to assess interobserver agreement, and computational fibrosis scores were correlated with pathologists’ estimates.
Results: Pathologist assessments of fibrosis on DUET-derived virtual trichrome images demonstrated interobserver agreement comparable to traditional trichrome slides, trending higher for virtual trichrome (ICC 0.536 versus 0.477, p=0.376). Agreement of each pathologist with the other three readers was higher for virtual trichrome in three of the four pathologists and significantly higher in one. Fibrosis estimates were systematically lower on virtual trichrome than on real trichrome, by a mean of 7.6 percentage points. The deep learning model for collagen extraction achieved high segmentation performance (AUC 0.994, Dice 0.903). Computational fibrosis quantitation showed moderate correlation with pathologist estimates and demonstrated stronger association with virtual trichrome than real trichrome (r 0.67 versus 0.54, R2 0.44 versus 0.29).
Conclusions: DUET microscopy enables the generation of pixel-registered virtual trichrome images from standard H&E slides with interobserver agreement comparable to conventional trichrome. By extracting collagen signal from pixel-registered fluorescence data on the same tissue section, DUET supports reproducible visual assessment and quantitative fibrosis measurement. This approach provides a scalable alternative to conventional trichrome staining and a foundation for integrated digital pathology workflows.
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BibTeX
@article{ju2026kidney,
title = {{Kidney fibrosis evaluation using dual-mode emission and transmission microscopy}},
author = {Willy Ju and Samuel Border and Fatemeh Afsari and Srishti Seth and Sarah Rezapourdamanab and Ruben Renteria and Shalini Ramachandra and Rajib Gupta and Fadi Salem and Alton Farris and Richard Levenson and Jarcy Zee and Pinaki Sarder and Kuang-Yu Jen and Farzad Fereidouni},
journal = {Journal of Medical Imaging},
year = {2026},
month = nov,
doi = {10.1117/1.jmi.13.6.067501},
url = {https://doi.org/10.1117/1.jmi.13.6.067501},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Kidney fibrosis evaluation using dual-mode emission and transmission microscopy
AU - Willy Ju
AU - Samuel Border
AU - Fatemeh Afsari
AU - Srishti Seth
AU - Sarah Rezapourdamanab
AU - Ruben Renteria
AU - Shalini Ramachandra
AU - Rajib Gupta
AU - Fadi Salem
AU - Alton Farris
AU - Richard Levenson
AU - Jarcy Zee
AU - Pinaki Sarder
AU - Kuang-Yu Jen
AU - Farzad Fereidouni
PY - 2026
DA - 2026/11/05
JO - Journal of Medical Imaging
DO - 10.1117/1.jmi.13.6.067501
UR - https://doi.org/10.1117/1.jmi.13.6.067501
AB - Purpose: Interstitial fibrosis is a critical histopathologic feature used in the diagnosis and prognosis of kidney diseases. However, conventional assessment using trichrome-stained slides is limited by interobserver variability and inconsistent stain reproducibility. This study evaluates whether dual-mode emission and transmission (DUET) microscopy, which generates virtual trichrome images from hematoxylin and eosin (H&E) slides, can provide a practical, reproducible, and quantitative alternative for assessing interstitial fibrosis in kidney transplant biopsies. Approach: Thirty-two kidney transplant biopsies were imaged using DUET to acquire pixel-registered brightfield and fluorescence whole-slide images from H&E-stained slides. A deep learning pipeline was trained on DUET-acquired images to extract collagen-positive signal from both the brightfield and fluorescence channels, which was used to generate virtual trichrome images and to compute quantitative fibrosis scores. Virtual trichrome images were compared with corresponding conventional trichrome slides. Four renal pathologists independently estimated interstitial fibrosis on both modalities to assess interobserver agreement, and computational fibrosis scores were correlated with pathologists’ estimates. Results: Pathologist assessments of fibrosis on DUET-derived virtual trichrome images demonstrated interobserver agreement comparable to traditional trichrome slides, trending higher for virtual trichrome (ICC 0.536 versus 0.477, p=0.376). Agreement of each pathologist with the other three readers was higher for virtual trichrome in three of the four pathologists and significantly higher in one. Fibrosis estimates were systematically lower on virtual trichrome than on real trichrome, by a mean of 7.6 percentage points. The deep learning model for collagen extraction achieved high segmentation performance (AUC 0.994, Dice 0.903). Computational fibrosis quantitation showed moderate correlation with pathologist estimates and demonstrated stronger association with virtual trichrome than real trichrome (r 0.67 versus 0.54, R2 0.44 versus 0.29). Conclusions: DUET microscopy enables the generation of pixel-registered virtual trichrome images from standard H&E slides with interobserver agreement comparable to conventional trichrome. By extracting collagen signal from pixel-registered fluorescence data on the same tissue section, DUET supports reproducible visual assessment and quantitative fibrosis measurement. This approach provides a scalable alternative to conventional trichrome staining and a foundation for integrated digital pathology workflows.
SN - 2329-4302
SN - 2329-4310
ER -