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Virchows Archiv

, Volume 472, Issue 2, pp 259–269 | Cite as

Development of CD3 cell quantitation algorithms for renal allograft biopsy rejection assessment utilizing open source image analysis software

  • Andres Moon
  • Geoffrey H. Smith
  • Jun Kong
  • Thomas E. Rogers
  • Carla L. Ellis
  • Alton B. “Brad” FarrisIIIEmail author
Original Article
  • 234 Downloads

Abstract

Renal allograft rejection diagnosis depends on assessment of parameters such as interstitial inflammation; however, studies have shown interobserver variability regarding interstitial inflammation assessment. Since automated image analysis quantitation can be reproducible, we devised customized analysis methods for CD3+ T-cell staining density as a measure of rejection severity and compared them with established commercial methods along with visual assessment. Renal biopsy CD3 immunohistochemistry slides (n = 45), including renal allografts with various degrees of acute cellular rejection (ACR) were scanned for whole slide images (WSIs). Inflammation was quantitated in the WSIs using pathologist visual assessment, commercial algorithms (Aperio nuclear algorithm for CD3+ cells/mm2 and Aperio positive pixel count algorithm), and customized open source algorithms developed in ImageJ with thresholding/positive pixel counting (custom CD3+%) and identification of pixels fulfilling “maxima” criteria for CD3 expression (custom CD3+ cells/mm2). Based on visual inspections of “markup” images, CD3 quantitation algorithms produced adequate accuracy. Additionally, CD3 quantitation algorithms correlated between each other and also with visual assessment in a statistically significant manner (r = 0.44 to 0.94, p = 0.003 to < 0.0001). Methods for assessing inflammation suggested a progression through the tubulointerstitial ACR grades, with statistically different results in borderline versus other ACR types, in all but the custom methods. Assessment of CD3-stained slides using various open source image analysis algorithms presents salient correlations with established methods of CD3 quantitation. These analysis techniques are promising and highly customizable, providing a form of on-slide “flow cytometry” that can facilitate additional diagnostic accuracy in tissue-based assessments.

Keywords

Renal allograft Image analysis Immunohistochemistry Whole slide image Rejection 

Abbreviations

ACR

Acute cellular rejection

ACR1A

Acute cellular rejection, type 1A

ACR1B

Acute cellular rejection, type 1B

ACR2A

Acute cellular rejection, type 2A

ACR3

Acute cellular rejection, type 3

PPC

Positive pixel count

WSI

Whole slide image

Notes

Acknowledgements

Special thanks are given to the laboratories of the Emory University Department of Pathology. Thanks also to Dr. Mingqing Song of Emory University and Duke University for help in whole slide scanning.

Compliance with ethical standards

This study was reviewed and approved by the Emory University Institutional Review Board.

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

428_2017_2260_MOESM1_ESM.pdf (3.7 mb)
Supplemental Figure 1 (PDF 3810 kb)
428_2017_2260_MOESM2_ESM.docx (16 kb)
ESM 1 (DOCX 16 kb)

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2017

Authors and Affiliations

  • Andres Moon
    • 1
  • Geoffrey H. Smith
    • 1
  • Jun Kong
    • 2
  • Thomas E. Rogers
    • 1
  • Carla L. Ellis
    • 1
  • Alton B. “Brad” FarrisIII
    • 1
    • 3
    Email author
  1. 1.Department of PathologyEmory UniversityAtlantaUSA
  2. 2.Department of BioinformaticsEmory UniversityAtlantaUSA
  3. 3.Emory University HospitalAtlantaUSA

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