ArticleJournal of pathology informatics2013
Reproducibility in the automated quantitative assessment of HER2/neu for breast cancer.
Article in Journal of pathology informatics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
9 citing papers in PubMed, 28 citations in OpenAlex.
- Improving HER2 Diagnostics with Digital Real-Time PCR for Ultrafast, Precise Prediction of Anti-HER2 Therapy Response in Patients with Breast Cancer.Small methods · 2026Article
- Computer-Aided Assessment of Melanocytic Lesions by Means of a Mitosis Algorithm.Diagnostics (Basel, Switzerland) · 2022Article
- Precise Identification of Cell and Tissue Features Important for Histopathologic Diagnosis by a Whole Slide Imaging System.Journal of pathology informatics · 2020Article
- Comparing Deep Learning and Immunohistochemistry in Determining the Site of Origin for Well-Differentiated Neuroendocrine Tumors.Journal of pathology informatics · 2020Article
- Quantitative pixel intensity- and color-based image analysis on minimally compressed files: implications for whole-slide imaging.Histochemistry and cell biology · 2019Article
- Impact of Altering Various Image Parameters on Human Epidermal Growth Factor Receptor 2 Image Analysis Data Quality.Journal of pathology informatics · 2017Article
- Computer-based image analysis in breast pathology.Journal of pathology informatics · 2016Review
- Whole slide imaging for human epidermal growth factor receptor 2 immunohistochemistry interpretation: Accuracy, Precision, and reproducibility studies for digital manual and paired glass slide manual interpretation.Journal of pathology informatics · 2015Article
- Comparative study between quantitative digital image analysis and fluorescence in situ hybridization of breast cancer equivocal human epidermal growth factor receptors 2 score 2(+) cases.Journal of pathology informatics · 2015Article
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundWith 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
methodsA 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.
resultsThe 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.
conclusionOur study supports the use of objective procedures for algorithm training to account for differences in image properties between WSI systems.
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