Deep Learning Tubulometrics to Stratify Tubular Injury in Whole-Slide Kidney Specimens
Background: Acute kidney injury is highly prevalent and most often involves tubular injury. However, studies on detailed assessment of tubular epithelial cell morphometry within tubuli are missing. To this end, we provide a deep learning-enhanced method to segment and analyze tubular epithelial cells and tubuli ("tubulometrics") in whole slide kidney specimens of wild-type mice and mice models of acute and chronic tubular injury. Methods: Kidneys were embedded in paraffin and stained with PAS and immunohistochemistry before digital scanning. More than 1200 tubuli and 6800 tubular epithelial cells of control mice, mice suffering ischemia-reperfusion injury or chronic tubular injury were manually annotated. Subsequently, a deep learning algorithm was trained to segment tubuli and tubular epithelial cells and morphometric readouts were obtained. Furthermore, tubulometrics were compared to traditional tubular injury scores. Results: Tubular area, tubular cell number and density per tubulus section were identified as morphometric readouts. These tubulometrics were able to complement a traditional tubular injury score (PAS score) and interstitial fibrosis tubular atrophy score (IFTA). In wild-type mice PAS score was 0, IFTA 0, mean tubular area 2339 [µm2], mean tubular cell count per tubulus 7.27, and mean tubular cell density 3.09 [10-3/µm2]. In mice with ischemia-reperfusion injury PAS score was 3.44, IFTA 10%, mean tubular area 1818 [µm2], mean tubular cell count per tubulus 2.02, mean tubular cell density 1.11 [10-3/µm2]. In mice with crystal-induced chronic tubular injury PAS score was 3.06, IFTA 40%, mean tubular area 2746 [µm2], mean tubular cell count per tubulus 7.71, and mean tubular cell density 2.81 [10-3/µm2]. The deep learning segmentation algorithm ensured time-efficiency and scalability by taking 5 minutes per slide. Conclusion: We propose the analysis of tubular epithelial cell morphometry in kidney specimens to better identify and stratify tubular injury. Whereas tubular epithelial cell loss was found in acute injury, tubular hypertrophy together with cell regeneration were observed in the chronic model. Integrated with existing histopathological scores a more detailed assessment of kidney biopsies might become possible. Further studies are needed to validate the findings in larger cohorts. Funding: Government Support – Non-U.S.
Authors
- Martin Klaus (ORCID: https://orcid.org/0000-0003-0880-3302)
- Louisa Ehreiser
- Peter Gaßmann
- Stefanie Steiger (ORCID: https://orcid.org/0000-0002-5990-494X)
- Julia Lichtnekert (ORCID: https://orcid.org/0000-0001-5210-4774)
- Maciej Lech (ORCID: https://orcid.org/0000-0002-4293-2733)
- Hao Long (ORCID: https://orcid.org/0000-0001-5623-9799)
- Hans‐Joachim Anders (ORCID: https://orcid.org/0000-0003-2434-2956)
- Rosch Ronny Abdullah
Institutions
- Ludwig-Maximilians-Universität München (DE)
Publication Details
- Journal
- Journal of the American Society of Nephrology
- Published
- 2024-10-01
- DOI
- https://doi.org/10.1681/asn.20247g5d1wbh
- Primary Topic
- Chronic Kidney Disease and Diabetes
- Type
- article
- Field-Weighted Citation Impact
- 0.00