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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
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Digital pathology: elementary, rapid and reliable automated image analysis.

Caroline Bouzin1, Monika L Saini2, Kyi-Kyi Khaing2

  • 1IREC Imaging Platform (2IP), Institut de Recherche Expérimentale et Clinique (IREC), Université catholique de Louvain (UCL), Brussels, Belgium.

Histopathology
|September 20, 2015
PubMed
Summary

Automated analysis of digital pathology slides can aid prognosis. Quantifying the stained area is a reliable and efficient method for routine clinical practice.

Keywords:
automationbiological markersdigital pathologyimage analysisimmunohistochemistryprognosisreproducibility

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Area of Science:

  • Digital Pathology
  • Computational Pathology
  • Histopathology Image Analysis

Background:

  • Slide digitalization enables advanced image analysis in pathology.
  • Automated immunostaining analysis is a powerful prognostic tool but not yet standard clinical practice.

Purpose of the Study:

  • To evaluate automated quantification methods for immunostained digital pathology slides.
  • To compare stained cell counting versus stained area proportion methods.
  • To assess image preparation steps for reliable analysis.

Main Methods:

  • Digitalized biopsy sections from two patient cohorts were analyzed.
  • Two automated methods were used: stained cell counting and stained area proportion.
  • Image preparation steps including tissue detection and fold exclusion were validated.

Main Results:

  • Both automated methods showed high correlation with each other and with pathologist visual scoring.
  • Quantification of stained area was found to be highly correlated with stained cell counting.
  • Stained area quantification is faster and easier to implement in routine settings.

Conclusions:

  • Automated analysis of immunostained digital slides is feasible and reliable.
  • The stained area proportion method is recommended for routine laboratory implementation due to its efficiency.
  • This study encourages the adoption of automated immunostaining analysis in clinical practice.