SynthesisModern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc2022
Ki-67 assessment of pancreatic neuroendocrine neoplasms: Systematic review and meta-analysis of manual vs. digital pathology scoring.
Synthesis in Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 1 of them a synthesis 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
44 citing papers in PubMed, 1 synthesis or guideline pooled it, 71 citations in OpenAlex.
- Pooled it
- Integrating Digital Ki-67 Labeling Index and K-TIRADS for Malignancy Risk Stratification in Thyroid Core Needle Biopsies.Cancers · 2026Article
- Multi-omic profiles of neuroendocrine neoplasms of the pancreas: an integrated landscape.Molecular cancer · 2026Review
- Review
- Quantification of Ki-67 labeling index in pediatric brain tumor immunohistochemistry images.Journal of neuropathology and experimental neurology · 2026Article
- Clinical application of digital pathology in small intestinal neuroendocrine tumours: proposal of a new G0 category.Endocrine oncology (Bristol, England) · 2026Article
- Differentiating well-differentiated neuroendocrine tumors grade 3 from poorly differentiated neuroendocrine carcinomas and adenocarcinoma with neuroendocrine differentiation: a comprehensive review.Virchows Archiv : an international journal of pathology · 2026Review
- Multi scale deep learning quantifies Ki67 index in breast cancer histopathology images.Scientific reports · 2025Article
- Ki67 in cytological specimens of pancreatic neuroendocrine tumors: A literature review and validation of automated quantification.Journal of pathology informatics · 2025Article
- Comparison of Mitotic Count and Ki-67 Index in Grading Gastroenteropancreatic Neuroendocrine Tumors and Their Association with Metastases.Biomedicines · 2025Article
- Predictors of All-Cause In-Hospital Mortality in Patients With Malignant Well-Differentiated Gastroenteropancreatic Neuroendocrine Tumors.World journal of oncology · 2025Article
- A Deep Learning Framework for Classification of Neuroendocrine Neoplasm Whole Slide Images.Cancers · 2025Article
- Decoding Pancreatic Neuroendocrine Tumors: Molecular Profiles, Biomarkers, and Pathways to Personalized Therapy.International journal of molecular sciences · 2025Review
- CT-based machine learning radiomics predicts Ki-67 expression level and its relationship with overall survival in resectable pancreatic ductal adenocarcinoma.Abdominal radiology (New York) · 2025Article
- Comparing non-machine learning vs. machine learning methods for Ki67 scoring in gastrointestinal neuroendocrine tumors.Scientific reports · 2025Article
- Toward Optimizing the Impact of Digital Pathology and Augmented Intelligence on Issues of Diagnosis, Grading, Staging, and Classification.Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · 2025Review
- Prognostic Features in Surgically Resected Well-Differentiated Pancreatic Neuroendocrine Tumors: an Analysis of 904 Patients with 7882 Person-Years of Follow-Up.Endocrine pathology · 2025Article
- Article
- Management of patients with small pancreatic neuroendocrine tumors from a biomarker and surgical perspective.Endocrine-related cancer · 2025Review
- Article
Corrections and comments
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Authors and funding
21 authors at 10 institutions in 5 countries.
Funding
Abstract
Ki-67 assessment is a key step in the diagnosis of neuroendocrine neoplasms (NENs) from all anatomic locations. Several challenges exist related to quantifying the Ki-67 proliferation index due to lack of method standardization and inter-reader variability. The application of digital pathology coupled with machine learning has been shown to be highly accurate and reproducible for the evaluation of Ki-67 in NENs. We systematically reviewed all published studies on the subject of Ki-67 assessment in pancreatic NENs (PanNENs) employing digital image analysis (DIA). The most common advantages of DIA were improvement in the standardization and reliability of Ki-67 evaluation, as well as its speed and practicality, compared to the current gold standard approach of manual counts from captured images, which is cumbersome and time consuming. The main limitations were attributed to higher costs, lack of widespread availability (as of yet), operator qualification and training issues (if it is not done by pathologists), and most importantly, the drawback of image algorithms counting contaminating non-neoplastic cells and other signals like hemosiderin. However, solutions are rapidly developing for all of these challenging issues. A comparative meta-analysis for DIA versus manual counting shows very high concordance (global coefficient of concordance: 0.94, 95% CI: 0.83-0.98) between these two modalities. These findings support the widespread adoption of validated DIA methods for Ki-67 assessment in PanNENs, provided that measures are in place to ensure counting of only tumor cells either by software modifications or education of non-pathologist operators, as well as selection of standard regions of interest for analysis. NENs, being cellular and monotonous neoplasms, are naturally more amenable to Ki-67 assessment. However, lessons of this review may be applicable to other neoplasms where proliferation activity has become an integral part of theranostic evaluation including breast, brain, and hematolymphoid neoplasms.
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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.