Diagnostic Pathology (Feb 2024)

Quantitative assessment of H&E staining for pathology: development and clinical evaluation of a novel system

  • Catriona Dunn,
  • David Brettle,
  • Martin Cockroft,
  • Elizabeth Keating,
  • Craig Revie,
  • Darren Treanor

DOI
https://doi.org/10.1186/s13000-024-01461-w
Journal volume & issue
Vol. 19, no. 1
pp. 1 – 11

Abstract

Read online

Abstract Background Staining tissue samples to visualise cellular detail and tissue structure is at the core of pathology diagnosis, but variations in staining can result in significantly different appearances of the tissue sample. While the human visual system is adept at compensating for stain variation, with the growth of digital imaging in pathology, the impact of this variation can be more profound. Despite the ubiquity of haematoxylin and eosin staining in clinical practice worldwide, objective quantification is not yet available. We propose a method for quantitative haematoxylin and eosin stain assessment to facilitate quality assurance of histopathology staining, enabling truly quantitative quality control and improved standardisation. Methods The stain quantification method comprises conventional microscope slides with a stain-responsive biopolymer film affixed to one side, called stain assessment slides. The stain assessment slides were characterised with haematoxylin and eosin, and implemented in one clinical laboratory to quantify variation levels. Results Stain assessment slide stain uptake increased linearly with duration of haematoxylin and eosin staining (r = 0.99), and demonstrated linearly comparable staining to samples of human liver tissue (r values 0.98–0.99). Laboratory implementation of this technique quantified intra- and inter-instrument variation of staining instruments at one point in time and across a five-day period. Conclusion The proposed method has been shown to reliably quantify stain uptake, providing an effective laboratory quality control method for stain variation. This is especially important for whole slide imaging and the future development of artificial intelligence in digital pathology.

Keywords