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. 2013 Jul 31:4:19.
doi: 10.4103/2153-3539.115879. eCollection 2013.

Reproducibility in the automated quantitative assessment of HER2/neu for breast cancer

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Reproducibility in the automated quantitative assessment of HER2/neu for breast cancer

Tyler Keay et al. J Pathol Inform. .

Abstract

Background: With the emerging role of digital imaging in pathology and the application of automated image-based algorithms to a number of quantitative tasks, there is a need to examine factors that may affect the reproducibility of results. These factors include the imaging properties of whole slide imaging (WSI) systems and their effect on the performance of quantitative tools. This manuscript examines inter-scanner and inter-algorithm variability in the assessment of the commonly used HER2/neu tissue-based biomarker for breast cancer with emphasis on the effect of algorithm training.

Materials and methods: A total of 241 regions of interest from 64 breast cancer tissue glass slides were scanned using three different whole-slide images and were analyzed using two different automated image analysis algorithms, one with preset parameters and another incorporating a procedure for objective parameter optimization. Ground truth from a panel of seven pathologists was available from a previous study. Agreement analysis was used to compare the resulting HER2/neu scores.

Results: The results of our study showed that inter-scanner agreement in the assessment of HER2/neu for breast cancer in selected fields of view when analyzed with any of the two algorithms examined in this study was equal or better than the inter-observer agreement previously reported on the same set of data. Results also showed that discrepancies observed between algorithm results on data from different scanners were significantly reduced when the alternative algorithm that incorporated an objective re-training procedure was used, compared to the commercial algorithm with preset parameters.

Conclusion: Our study supports the use of objective procedures for algorithm training to account for differences in image properties between WSI systems.

Keywords: Quantitative immunohistochemistry; reproducibility; whole slide imaging.

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Figures

Figure 1
Figure 1
Example of a field of view stained with a HER2/neu antibody, extracted from a whole slide image, digitized using: (a) The Aperio-CS (top), (b) The Aperio-T2 (middle), and (c) The Hamamatsu Nanozoomer (bottom) whole slide imaging systems. Images were extracted at ×20
Figure 2
Figure 2
Example of two regions of interests, one where the majority of pathologists (four out of seven) scored it as 1+ whereas Algorithm 2 scored that case as 2+ (a), and another where the majority of pathologists (six out of seven) scored it as 2+ whereas Algorithm 2 scored it as a 1+ (b). Images were extracted at ×20

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