ArticleJCO precision oncology2024
Fully Automated Artificial Intelligence Solution for Human Epidermal Growth Factor Receptor 2 Immunohistochemistry Scoring in Breast Cancer: A Multireader Study.
Article in JCO precision oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- Artificial Intelligence for Diagnostic and Prognostic Support in Breast Cancer: A Literature Overview.Cancers · 2026Review
- Regulatory science for AI-basedJournal of pathology informatics · 2026Article
- World Health Organization classification of tumours of the breast 6th edition 2026.Histopathology · 2026Review
- Validation, implementation, and impact of an AI model in routine practice for pathologic diagnosis of prostate cancer in an academic medical center.Journal of pathology informatics · 2026Article
- What practicing pathologists and oncologists should know about the new computational pathology-based companion diagnostic tools.The Journal of pathology · 2026Review
- Antibody-Drug Conjugates in Oncology: Principles, Clinical Development, and Future Directions.MedComm · 2026Review
- AI-enhanced precision: boosting pathologist confidence in HER2 ultra-low diagnosis through intelligent re-screening.Breast cancer research : BCR · 2026Article
- Prevalence of HER2-ultralow breast cancer in South Korea: a multicenter study by reassessment of HER2-zero cases.Journal of pathology and translational medicine · 2026Article
- How artificial intelligence applied to digital pathology could guide treatment personalization in breast cancer.ESMO real world data and digital oncology · 2026Review
- Clinical advances and challenges of antibody-mediated targeted drug delivery in breast cancer therapeutics.Discover oncology · 2026Review
- Translational AI in whole-slide image cancer histopathology: state of the art and regulatory-approved solutions.Frontiers in digital health · 2026Review
- Redefining HER2 in Breast Cancer: From Conventional Positivity to Low and Ultralow in the New Era of Antibody-Drug Conjugates.Cancer research and treatment · 2026Review
- Artificial Intelligence-Driven Quantitative HER2 Scoring and Spatial Bystander Effect Modeling for ADC Response Stratification in HER2-Low Breast Cancer.Breast cancer (Dove Medical Press) · 2026Review
- HER2-Low Breast Cancer at the Interface of Pathology and Technology: Toward Precision Management.Biomedicines · 2025Review
- Contrasting low- and high-resolution features for HER2 scoring using deep learning.Journal of pathology informatics · 2025Article
- Bibliometric analysis of global research trends in delivery systems for breast cancer immunotherapy.Discover oncology · 2025Article
- Changes in HER2low and HER2-ultralow status in 47 advanced breast carcinoma core biopsies, matching surgical specimens, and their distant metastases assessed by conventional light microscopy, digital pathology, and artificial intelligence.Breast cancer research and treatment · 2025Article
- Transformer-BasedDiagnostics (Basel, Switzerland) · 2025Article
- Accuracy of human epidermal growth factor receptor 2 (HER2) immunohistochemistry scoring by pathologists in breast cancer, including the HER2-low cutoff : HER2 IHC scoring concordance in breast cancer.Diagnostic pathology · 2025Article
- HER2-Low Breast Cancer-Current Knowledge and Future Directions.Medicina (Kaunas, Lithuania) · 2025Review
Corrections and comments
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Authors and funding
16 authors.
Funding
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Abstract
purposeThe proven efficacy of human epidermal growth factor receptor 2 (HER2) antibody-drug conjugate therapy for treating HER2-low breast cancers necessitates more accurate and reproducible HER2 immunohistochemistry (IHC) scoring. We aimed to validate performance and utility of a fully automated artificial intelligence (AI) solution for interpreting HER2 IHC in breast carcinoma. MATERIALS AND
methodsA two-arm multireader study of 120 HER2 IHC whole-slide images from four sites assessed HER2 scoring by four surgical pathologists without and with the aid of an AI HER2 solution. Both arms were compared with high-confidence ground truth (GT) established by agreement of at least four of five breast pathology subspecialists according to ASCO/College of American Pathologists (CAP) 2018/2023 guidelines.
resultsThe mean interobserver agreement among GT pathologists across all HER2 scores was 72.4% (N = 120). The AI solution demonstrated high accuracy for HER2 scoring, with 92.1% agreement on slides with high confidence GT (n = 92). The use of the AI tool led to improved performance by readers, interobserver agreement increased from 75.0% for digital manual read to 83.7% for AI-assisted review, and scoring accuracy improved from 85.3% to 88.0%. For the distinction of HER2 0 from 1+ cases (n = 58), pathologists supported by AI showed significantly higher interobserver agreement (69.8% without AI
conclusionThis study demonstrated utility of a fully automated AI solution to aid in scoring HER2 IHC accurately according to ASCO/CAP 2018/2023 guidelines. Pathologists supported by AI showed improvements in HER2 IHC scoring consistency and accuracy, especially for distinguishing HER2 0 from 1+ cases. This AI solution could be used by pathologists as a decision support tool for enhancing reproducibility and consistency of HER2 scoring and particularly for identifying HER2-low breast cancers.
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