Computer-assisted pathological immunohistochemistry scoring is more time-effective than conventional scoring, but provides no analytical advantage

Histopathology. 2010 Mar;56(4):523-9. doi: 10.1111/j.1365-2559.2010.03496.x.


Aims: Interpretation of immunohistochemistry is primarily done through human visual scoring while computer-assisted scoring is relatively uncommon. This study aimed to examine (i) the level of agreement between human visual and computer-assisted pathological scoring of immunoreactivity expression in colorectal cancers, (ii) whether computer-assisted scoring affects the prognostic significance of biomarkers, and (iii) whether computer-assisted pathological scoring provides any time-saving or reproducibility advantages.

Methods and results: Tissue microarray blocks were constructed from the primary colorectal adenocarcinoma specimens of 486 patients. Scoring of the six markers [cytokeratin (CK) 7, CK20, cyclooxygenase-2, Ki67, p27 and p53] was done independently by a qualified pathologist, a trained scientist and the Ariol SL-50 (Applied Imaging). Univariate analysis showed that human visual and computer-assisted scoring were strongly correlated (all kappa values >0.8). Both human visual and computer-assisted pathological scoring identified the same set of biomarkers with significant association with survival. Computer-assisted pathological scoring was shown to be a time-effective means of scoring larger numbers of slides (for high-throughput studies).

Conclusions: Our results suggest that computer-assisted pathological scoring can be a viable alternative to pathologist scoring in a manner that is more practical and time-effective, but, interestingly, providing no analytical advantage.

Publication types

  • Comparative Study
  • Evaluation Study

MeSH terms

  • Biomarkers, Tumor / metabolism
  • Colorectal Neoplasms / metabolism*
  • Colorectal Neoplasms / mortality
  • Colorectal Neoplasms / pathology*
  • Female
  • Humans
  • Image Processing, Computer-Assisted*
  • Immunohistochemistry / methods*
  • Male
  • Prognosis
  • Survival Analysis
  • Time Factors


  • Biomarkers, Tumor