ArticleDiagnostic pathology2022
Artificial intelligence-assisted interpretation of Ki-67 expression and repeatability in breast cancer.
Article in Diagnostic pathology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Covalent Inhibition of SHMT2 by Gambogic Acid Induces Ferroptosis Through Mitochondrial Collapse in Triple-Negative Breast Cancer.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Article
- Automated Assessment of Ki-67 Labeling Index Using Cell-Level Detection and Classification in Whole-Slide Images.Diagnostics (Basel, Switzerland) · 2026Article
- Evaluating the Impact of a Ki-67 Decision Support Algorithm on Pathology Residents' Scoring Accuracy.Journal of imaging informatics in medicine · 2026Article
- Decoding Breast Cancer: Emerging Molecular Biomarkers and Novel Therapeutic Targets for Precision Medicine.International journal of molecular sciences · 2025Review
- Development and clinical validation of deep learning-based immunohistochemistry prediction models for subtyping and staging of gastrointestinal cancers.BMC gastroenterology · 2025Article
- Review
- Evaluating an RNA-based test for proliferation assessment and recurrence prediction in early HR+/HER2- breast cancer.Pathology oncology research : POR · 2025Article
- Flow cytometric analysis for Ki67 assessment in formalin-fixed paraffin-embedded breast cancer tissue.BMC biology · 2024Article
- Article
- Revolutionizing Pathology with Artificial Intelligence: Innovations in Immunohistochemistry.Journal of personalized medicine · 2024Review
- Early Breast Cancer Risk Assessment: Integrating Histopathology with Artificial Intelligence.Cancers · 2024Review
- Association Between Ki-67 Proliferative Index and Oncotype-Dx Recurrence Score in Hormone Receptor-Positive, HER2-Negative Early Breast Cancers. A Systematic Review of the Literature.Breast cancer : basic and clinical research · 2024Review
- Breaking Barriers: AI's Influence on Pathology and Oncology in Resource-Scarce Medical Systems.Cancers · 2023Review
- Advances in Early Breast Cancer Risk Profiling: From Histopathology to Molecular Technologies.Cancers · 2023Review
- The Approach of Artificial Intelligence in Neuroendocrine Carcinomas of the Breast: A Next Step towards Precision Pathology?-A Case Report and Review of the Literature.Medicina (Kaunas, Lithuania) · 2023Review
- The Evolution of Ki-67 and Breast Carcinoma: Past Observations, Present Directions, and Future Considerations.Cancers · 2023Review
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundKi-67 standard reference card (SRC) and artificial intelligence (AI) software were used to evaluate breast cancer Ki-67LI. We established training and validation sets and studied the repeatability inter-observers.
methodsA total of 300 invasive breast cancer specimens were randomly divided into training and validation sets, with each set including 150 cases. Breast cancer Ki-67 standard reference card ranging from 5 to 90% were created. The training set was interpreted by nine pathologists of different ages through microscopic visual assessment (VA), SRC, microscopic manual counting (MC), and AI. The validation set was interpreted by three randomly selected pathologists using SRC and AI. The intra-group correlation coefficient (ICC) were used for consistency analysis.
resultsIn the homogeneous and heterogeneous groups of validation sets, the consistency among the pathologists that used SRC and AI was very good, with an ICC of>0.905. In the validation set, using SRC and AI, three pathologists obtained results that were very consistent with the gold standard, having an ICC above 0.95, and the inter-observer agreement was also very good, with an ICC of>0.9.
conclusionsAI has satisfactory inter-observer repeatability, and the true value was closer to the gold standard, which is the preferred method for Ki-67LI reproducibility; While AI software has not been popularized, SRC may be interpreted as breast cancer Ki-67LI's standard candidate method.
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