Trial reportArchives of pathology & laboratory medicine2011
Observer variability in the interpretation of HER2/neu immunohistochemical expression with unaided and computer-aided digital microscopy.
Trial report in Archives of pathology & laboratory medicine, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 68 papers, 3 of them syntheses that pooled it.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
68 citing papers in PubMed, 3 syntheses or guidelines pooled it, 122 citations in OpenAlex.
- Automated scoring methods for quantitative interpretation of Tumour infiltrating lymphocytes (TILs) in breast cancer: a systematic review.BMC cancer · 2024Pooled it
- Quantitative Image Analysis of Human Epidermal Growth Factor Receptor 2 Immunohistochemistry for Breast Cancer: Guideline From the College of American Pathologists.Archives of pathology & laboratory medicine · 2019Guideline
- Artificial Intelligence for Breast Cancer Molecular Subtype Prediction From Medical Imaging: A Systematic Review of Literature.Technology in cancer research & treatmentPooled it
- AI-Assisted Scoring Improves Interobserver Agreement in Breast Cancer Biomarker Evaluation.Cancers · 2026Article
- From case-control averages to validated subgroups: Interpreting inflammatory and neuroaxonal-injury biomarkers in schizophrenia and major depression.Brain, behavior, & immunity - health · 2026Review
- Diagnostic Accuracy and Reproducibility of ChatGPT-4o for HER2 Immunohistochemistry Scoring in Equivocal Breast Cancer Cases.Asian Pacific journal of cancer prevention : APJCP · 2026Article
- Training on PD-L1 scoring in non-small cell lung cancer with high intra- and inter-reader agreement: results of a worldwide microscopic/digital image-based training of 751 pathologists.British journal of biomedical science · 2026Article
- DAXX and ATRX Expression in Canine Prostate and Bladder Cancer Identified by Immunohistochemistry-A Digital Quantitative Pilot Study.Veterinary sciences · 2025Article
- Machine learning prediction of HER2-low expression in breast cancers based on hematoxylin-eosin-stained slides.Breast cancer research : BCR · 2025Article
- A glimpse into the future: Integrating artificial intelligence for precision HER2-positive breast cancer management.iMetaOmics · 2024Review
- Use of artificial intelligence in breast surgery: a narrative review.Gland surgery · 2024Review
- Color Standardization and Stain Intensity Calibration for Whole Slide Image-Based Immunohistochemistry Assessment.Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada · 2024Article
- AI-Powered Segmentation of Invasive Carcinoma Regions in Breast Cancer Immunohistochemical Whole-Slide Images.Cancers · 2023Article
- Immunohistochemical Stain-Aided Annotation Accelerates Machine Learning and Deep Learning Model Development in the Pathologic Diagnosis of Nasopharyngeal Carcinoma.Diagnostics (Basel, Switzerland) · 2023Article
- High inter-laboratory variability in the assessment of HER2-low breast cancer: a national registry study on 50,714 Danish patients.Breast cancer research : BCR · 2023Article
- Machine Learning for Digital Scoring of PRMT6 in Immunohistochemical Labeled Lung Cancer.Cancers · 2023Article
- Artificial Intelligence in Renal Cell Carcinoma Histopathology: Current Applications and Future Perspectives.Diagnostics (Basel, Switzerland) · 2023Review
- Motivation for using data-driven algorithms in research: A review of machine learning solutions for image analysis of micrographs in neuroscience.Journal of neuropathology and experimental neurology · 2023Review
- Zonated quantification of immunohistochemistry in normal and steatotic livers.Virchows Archiv : an international journal of pathology · 2023Article
- Validation of automated positive cell and region detection of immunohistochemically stained laryngeal tumor tissue using digital image analysis.Journal of pathology informatics · 2023Article
8 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
contextObserver variability in digital microscopy and the effect of computer-aided digital microscopy are underexamined areas in need of further research, considering the increasing use and future role of digital imaging in pathology. A reduction in observer variability using computer aids could enhance the statistical power of studies designed to determine the utility of new biomarkers and accelerate their incorporation in clinical practice.
objectivesTo quantify interobserver and intraobserver variability in immunohistochemical analysis of HER2/neu with digital microscopy and computer-aided digital microscopy, and to test the hypothesis that observer agreement in the quantitative assessment of HER2/neu immunohistochemical expression is increased with the use of computer-aided microscopy.
designA set of 335 digital microscopy images extracted from 64 breast cancer tissue slides stained with a HER2 antibody, were read by 14 observers in 2 reading modes: the unaided mode and the computer-aided mode. In the unaided mode, HER2 images were displayed on a calibrated color monitor with no other information, whereas in the computer-aided mode, observers were shown a HER2 image along with a corresponding feature plot showing computer-extracted values of membrane staining intensity and membrane completeness for the particular image under examination and, at the same time, mean feature values of the different HER2 categories. In both modes, observers were asked to provide a continuous score of HER2 expression.
resultsAgreement analysis performed on the output of the study showed significant improvement in both interobserver and intraobserver agreement when the computer-aided reading mode was used to evaluate preselected image fields.
conclusionThe role of computer-aided digital microscopy in reducing observer variability in immunohistochemistry is promising.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.