Literature DB >> 32836178

Ki67 index and mitotic count: Correlation and variables affecting the accuracy of the quantification in endocrine/neuroendocrine tumors.

Wei Huang1, Christian Nebiolo2, Karla Esbona2, Rong Hu2, Ricardo Lloyd2.   

Abstract

Quantification of Ki67 and mitosis is time consuming and subject to inter-observer variabilities. Limited studies explored the impact of those variables on the results and the correlation between mitotic count and Ki67 index in endocrine/neuroendocrine tumors, particularly so since the advent of PHH3 antibody and digital pathology. Using Ki67 and mitosis as examples, this study is intended to reveal variables affecting accurate quantification of biomarkers, and to explore the relationship of Ki67 index and mitotic count/index in endocrine/neuroendocrine tumors. Using both manual and pathologist supervised digital image analysis (PSDIA) methods, we examined the impact of post-analytical variables on the quantification of mitosis and Ki67 index and studied the correlation between them in 41 cases of endocrine/neuroendocrine tumors of variable histological grades/proliferating rates. We found that the selection of hotspots, field size and especially threshold affected the outcome of quantification of mitosis and Ki67 index; that mitotic count/index strongly (p < 0.05) correlated with Ki67 index only in the tumors with peak Ki67 index less than 30% and the correlation was more monotonic (positive, non-linear) than linear. In the hotspots of these tumors, the ratio of mitotic count to proliferating cells defined by Ki67 detection averaged 0.04. We also found that the PHH3 antibody could markedly increase the efficiency and accuracy of mitotic quantification. A consensus among pathologists is needed for the selection of hotspots, field size and threshold for quantification of mitosis and Ki67 index.
Copyright © 2020 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Correlation; Endocrine/Neuroendocrine Tumor; Ki67 Index; Mitotic Count/Index; PHH3

Mesh:

Substances:

Year:  2020        PMID: 32836178     DOI: 10.1016/j.anndiagpath.2020.151586

Source DB:  PubMed          Journal:  Ann Diagn Pathol        ISSN: 1092-9134            Impact factor:   2.090


  3 in total

1.  Automated assessment of Ki-67 proliferation index in neuroendocrine tumors by deep learning.

Authors:  Tiina Vesterinen; Jenni Säilä; Sami Blom; Mirkka Pennanen; Helena Leijon; Johanna Arola
Journal:  APMIS       Date:  2021-11-22       Impact factor: 3.428

2.  Proposal for a New Diagnostic Histopathological Approach in the Evaluation of Ki-67 in GEP-NETs.

Authors:  Pinuccia Faviana; Laura Boldrini; Carlo Gentile; Paola Anna Erba; Enrico Sammarco; Francesco Bartoli; Enrica Esposito; Luca Galli; Piero Vincenzo Lippolis; Massimo Bardi
Journal:  Diagnostics (Basel)       Date:  2022-08-13

Review 3.  Counting mitoses: SI(ze) matters!

Authors:  Ian A Cree; Puay Hoon Tan; William D Travis; Pieter Wesseling; Yukako Yagi; Valerie A White; Dilani Lokuhetty; Richard A Scolyer
Journal:  Mod Pathol       Date:  2021-06-02       Impact factor: 7.842

  3 in total

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