Abstract: TH-OR061
Label-Free Imaging of Human Kidney Biopsies Guides Downstream Interrogation
Session Information
- Harnessing Molecular, Machine-Learning, and Genomic Innovations in Pathology
October 25, 2018 | Location: 24A, San Diego Convention Center
Abstract Time: 04:30 PM - 04:42 PM
Category: Pathology and Lab Medicine
- 1501 Pathology and Lab Medicine: Basic
Authors
- Ferkowicz, Michael J., Indiana University, Indianapolis, Indiana, United States
- Winfree, Seth, Indiana University School of Medicine, Indianapolis, Indiana, United States
- Barwinska, Daria, Indiana University, Indianapolis, Indiana, United States
- Dunn, Ken, Indiana University, Indianapolis, Indiana, United States
- Kelly, Katherine J., Indiana University, Indianapolis, Indiana, United States
- Sutton, Timothy A., Indiana University School of Medicine, Indianapolis, Indiana, United States
- Eadon, Michael T., Indiana University Division of Nephrology, Indianapolis, Indiana, United States
- Dagher, Pierre C., Indiana University, Indianapolis, Indiana, United States
- El-Achkar, Tarek M., Indiana University, Indianapolis, Indiana, United States
Background
Label-free (LF) imaging of human kidney biopsies is a novel and under-utilized approach to characterize kidney pathology. Unlabeled kidney biopsies have auto-fluorescence (AF) across the visible spectrum that encodes specific signatures of nephron structures and can be correlated with pathology. In addition, AF intensity can be extended using fluorescence lifetime imaging (FLIM) to resolve endogenous fluorophores in health and disease. Second harmonic generation (SHG) by collagen fibers is an LF imaging approach that can be simultaneously acquired, allowing for rapid measurement of fibrosis.
Methods
Scanning multiphoton excitation microscopy was used to rapidly collect AF, FLIM and SHG images of human kidney sections. These same sections were subsequently stained by immuno-fluorescence and imaged with spectral multi-channel three-dimensional laser scanning confocal microscopy. These volumes were then analyzed by 3D tissue cytometry (3DTC).
Results
AF provides LF imaging and identification of tubular sub-segments. Supervised machine learning approaches can automatically and accurately identify tubular sub-segments in AF images. Lifetime imaging of AF provides an additional signature. SHG provides LF imaging of collagen fibrosis. Using 3DTC, LF images can be correlatively integrated into the analysis of stained tubular and infiltrating cells from the same kidney section.
Conclusion
Thus, the label-free imaging of human kidney biopsies using AF, FLIM and SHG will complement our existing confocal spectral imaging approach. This combined multi-dimensional imaging approach will maximize the informational yield of a biopsy when combined with downstream interrogation methods.
Label-free imaging informs analysis. A. SHG imaging delineates fibrosis (b) that spatially correlates with spectrally imaged F-actin+ cells (c and d) and inflammatory cells (e, in red and f, in red and yellow).
Funding
- NIDDK Support