ArticleJournal of pathology informatics2019
Ki67 Quantitative Interpretation: Insights using Image Analysis.
Article in Journal of pathology informatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Ki-67 assessment of pancreatic neuroendocrine neoplasms: Systematic review and meta-analysis of manual vs. digital pathology scoring.Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · 2022Pooled it
- IASLC Update on Classification of Pulmonary Neuroendocrine Neoplasms.Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer · 2026Review
- Well-Differentiated Neuroendocrine Tumors of Lung: A Case Series Supporting the IARC/WHO Common Classification of Neuroendocrine Tumor Nomenclature and Grading.Endocrine pathology · 2026Article
- Smart Lies and Sharp Eyes: Pragmatic Artificial Intelligence for Cancer Pathology: Promise, Pitfalls, and Access Pathways.Cancers · 2026Review
- Ki67 in cytological specimens of pancreatic neuroendocrine tumors: A literature review and validation of automated quantification.Journal of pathology informatics · 2025Article
- Comparing non-machine learning vs. machine learning methods for Ki67 scoring in gastrointestinal neuroendocrine tumors.Scientific reports · 2025Article
- Immunohistochemistry for Skin Cancers: New Insights into Diagnosis and Treatment of Melanoma.Cancers · 2025Review
- Determination of Ki-67 indices in neuroendocrine tumours of the gastrointestinal tract: the past, the present, and the future.Virchows Archiv : an international journal of pathology · 2025Article
- Digitally derived Ki-67 proliferation index for GastroEnteroPancreatic neuroendocrine neoplasms.Pathology oncology research : POR · 2025Article
- Article
- [Quantification of Ki-67 in PitNET (pituitary neuroendocrine tumors)/adenomas].Pathologie (Heidelberg, Germany) · 2024Article
- Use of a Novel Deep Learning Open-Source Model for Quantification of Ki-67 in Breast Cancer Patients in Pakistan: A Comparative Study between the Manual and Automated Methods.Diagnostics (Basel, Switzerland) · 2023Article
- Exploration of Digital Image Analysis for Ki67 Quantification in the Grading of Medullary Thyroid Carcinoma: A Pilot Study with 85 Cases.Head and neck pathology · 2023Article
- Stromal tissue segmentation in Ki67 histology images based on cytokeratin-19 stain translation.Journal of medical imaging (Bellingham, Wash.) · 2023Article
- Use of Novel Open-Source Deep Learning Platform for Quantification of Ki-67 in Neuroendocrine Tumors - Analytical Validation.International journal of general medicine · 2023Article
- Visual and digital assessment of Ki-67 in breast cancer tissue - a comparison of methods.Diagnostic pathology · 2022Article
- Automated assessment of Ki-67 proliferation index in neuroendocrine tumors by deep learning.APMIS : acta pathologica, microbiologica, et immunologica Scandinavica · 2022Article
- Optimal settings and clinical validation for automated Ki67 calculation in neuroendocrine tumors with open source informatics (QuPath).Journal of pathology informatics · 2022Article
- Automated Analysis of Proliferating Cells Spatial Organisation Predicts Prognosis in Lung Neuroendocrine Neoplasms.Cancers · 2021Article
- Ki-67 Proliferation Index Assessment in Gastroenteropancreatic Neuroendocrine Tumors by Digital Image Analysis With Stringent Case and Hotspot Level Concordance Requirements.American journal of clinical pathology · 2021Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundProliferation markers, especially Ki67, are increasingly important in diagnosis and prognosis. The best method for calculating Ki67 is still the subject of debate. MATERIALS AND
methodsWe evaluated an image analysis tool for quantitative interpretation of Ki67 in neuroendocrine tumors and compared it to manual counts. We expanded a primary digital pathology platform to include the Leica Biosystems image analysis nuclear algorithm. Slides were digitized using a Leica Aperio AT2 Scanner and accessed through the Cerner CoPath LIS interfaced with Aperio eSlideManager through Aperio ImageScope. Selected regions of interest (ROIs) were manually defined and annotated to include tumor cells only; they were then analyzed with the algorithm and by four pathologists counting on printed images. After validation, the algorithm was used to examine the impact of the size and number of areas selected as ROIs.
resultsThe algorithm provided reproducible results that were obtained within seconds, compared to up to 55 min of manual counting that varied between users. Benefits of image analysis identified by users included accuracy, time savings, and ease of viewing. Access to the algorithm allowed rapid comparisons of Ki67 counts in ROIs that varied in numbers of cells and selection of fields, the outputs demonstrated that the results vary around defined cutoffs that provide tumor grade depending on the number of cells and ROIs counted.
conclusionsDigital image analysis provides accurate and reproducible quantitative data faster than manual counts. However, access to this tool allows multiple analyses of a single sample to use variable numbers of cells and selection of variable ROIs that can alter the result in clinically significant ways. This study highlights the potential risk of hard cutoffs of continuous variables and indicates that standardization of number of cells and number of regions selected for analysis should be incorporated into guidelines for Ki67 calculations.
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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.