Skip to main content
Journal cover image

Assessment of a computerized quantitative quality control tool for whole slide images of kidney biopsies.

Publication ,  Journal Article
Chen, Y; Zee, J; Smith, A; Jayapandian, C; Hodgin, J; Howell, D; Palmer, M; Thomas, D; Cassol, C; Farris, AB; Perkinson, K; Madabhushi, A ...
Published in: J Pathol
March 2021

Inconsistencies in the preparation of histology slides and whole-slide images (WSIs) may lead to challenges with subsequent image analysis and machine learning approaches for interrogating the WSI. These variabilities are especially pronounced in multicenter cohorts, where batch effects (i.e. systematic technical artifacts unrelated to biological variability) may introduce biases to machine learning algorithms. To date, manual quality control (QC) has been the de facto standard for dataset curation, but remains highly subjective and is too laborious in light of the increasing scale of tissue slide digitization efforts. This study aimed to evaluate a computer-aided QC pipeline for facilitating a reproducible QC process of WSI datasets. An open source tool, HistoQC, was employed to identify image artifacts and compute quantitative metrics describing visual attributes of WSIs to the Nephrotic Syndrome Study Network (NEPTUNE) digital pathology repository. A comparison in inter-reader concordance between HistoQC aided and unaided curation was performed to quantify improvements in curation reproducibility. HistoQC metrics were additionally employed to quantify the presence of batch effects within NEPTUNE WSIs. Of the 1814 WSIs (458 H&E, 470 PAS, 438 silver, 448 trichrome) from n = 512 cases considered in this study, approximately 9% (163) were identified as unsuitable for subsequent computational analysis. The concordance in the identification of these WSIs among computational pathologists rose from moderate (Gwet's AC1 range 0.43 to 0.59 across stains) to excellent (Gwet's AC1 range 0.79 to 0.93 across stains) agreement when aided by HistoQC. Furthermore, statistically significant batch effects (p < 0.001) in the NEPTUNE WSI dataset were discovered. Taken together, our findings strongly suggest that quantitative QC is a necessary step in the curation of digital pathology cohorts. © 2020 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Duke Scholars

Altmetric Attention Stats
Dimensions Citation Stats

Published In

J Pathol

DOI

EISSN

1096-9896

Publication Date

March 2021

Volume

253

Issue

3

Start / End Page

268 / 278

Location

England

Related Subject Headings

  • Quality Control
  • Pathology, Surgical
  • Pathology
  • Kidney Diseases
  • Image Interpretation, Computer-Assisted
  • Humans
  • Biopsy
  • Algorithms
  • 3211 Oncology and carcinogenesis
  • 3202 Clinical sciences
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Chen, Y., Zee, J., Smith, A., Jayapandian, C., Hodgin, J., Howell, D., … Janowczyk, A. (2021). Assessment of a computerized quantitative quality control tool for whole slide images of kidney biopsies. J Pathol, 253(3), 268–278. https://doi.org/10.1002/path.5590
Chen, Yijiang, Jarcy Zee, Abigail Smith, Catherine Jayapandian, Jeffrey Hodgin, David Howell, Matthew Palmer, et al. “Assessment of a computerized quantitative quality control tool for whole slide images of kidney biopsies.J Pathol 253, no. 3 (March 2021): 268–78. https://doi.org/10.1002/path.5590.
Chen Y, Zee J, Smith A, Jayapandian C, Hodgin J, Howell D, et al. Assessment of a computerized quantitative quality control tool for whole slide images of kidney biopsies. J Pathol. 2021 Mar;253(3):268–78.
Chen, Yijiang, et al. “Assessment of a computerized quantitative quality control tool for whole slide images of kidney biopsies.J Pathol, vol. 253, no. 3, Mar. 2021, pp. 268–78. Pubmed, doi:10.1002/path.5590.
Chen Y, Zee J, Smith A, Jayapandian C, Hodgin J, Howell D, Palmer M, Thomas D, Cassol C, Farris AB, Perkinson K, Madabhushi A, Barisoni L, Janowczyk A. Assessment of a computerized quantitative quality control tool for whole slide images of kidney biopsies. J Pathol. 2021 Mar;253(3):268–278.
Journal cover image

Published In

J Pathol

DOI

EISSN

1096-9896

Publication Date

March 2021

Volume

253

Issue

3

Start / End Page

268 / 278

Location

England

Related Subject Headings

  • Quality Control
  • Pathology, Surgical
  • Pathology
  • Kidney Diseases
  • Image Interpretation, Computer-Assisted
  • Humans
  • Biopsy
  • Algorithms
  • 3211 Oncology and carcinogenesis
  • 3202 Clinical sciences