Literature DB >> 33847759

Ki-67 Proliferation Index Assessment in Gastroenteropancreatic Neuroendocrine Tumors by Digital Image Analysis With Stringent Case and Hotspot Level Concordance Requirements.

Sarag A Boukhar1, Matthew D Gosse1, Andrew M Bellizzi1, Anand Rajan K D1.   

Abstract

OBJECTIVES: The Ki-67 proliferation index is integral to gastroenteropancreatic neuroendocrine tumor (GEP-NET) assessment. Automated Ki-67 measurement would aid clinical workflows, but adoption has lagged owing to concerns of nonequivalency. We sought to address this concern by comparing 2 digital image analysis (DIA) platforms to manual counting with same-case/different-hotspot and same-hotspot/different-methodology concordance assessment.
METHODS: We assembled a cohort of GEP-NETs (n = 20) from 16 patients. Two sets of Ki-67 hotspots were manually counted by three observers and by two DIA platforms, QuantCenter and HALO. Concordance between methods and observers was assessed using intraclass correlation coefficient (ICC) measures. For each comparison pair, the number of cases within ±0.2xKi-67 of its comparator was assessed.
RESULTS: DIA Ki-67 showed excellent correlation with manual counting, and ICC was excellent in both within-hotspot and case-level assessments. In expert-vs-DIA, DIA-vs-DIA, or expert-vs-expert comparisons, the best-performing was DIA Ki-67 by QuantCenter, which showed 65% cases within ±0.2xKi-67 of manual counting.
CONCLUSIONS: Ki-67 measurement by DIA is highly correlated with expert-assessed values. However, close concordance by strict criteria (>80% within ±0.2xKi-67) is not seen with DIA-vs-expert or expert-vs-expert comparisons. The results show analytic noninferiority and support widespread adoption of carefully optimized and validated DIA Ki-67. © American Society for Clinical Pathology, 2021. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  Concordance; Digital image analysis; Grading; Ki-67; Neuroendocrine; Validation immunohistochemistry; Whole-slide imaging

Mesh:

Substances:

Year:  2021        PMID: 33847759      PMCID: PMC8427716          DOI: 10.1093/ajcp/aqaa275

Source DB:  PubMed          Journal:  Am J Clin Pathol        ISSN: 0002-9173            Impact factor:   2.493


  30 in total

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Authors:  Shintaro Sugita; Hiroshi Hirano; Yutaka Hatanaka; Hiromi Fujita; Terufumi Kubo; Noriaki Kikuchi; Yumika Ito; Taro Sugawara; Keiko Segawa; Hiroyuki Hisai; Kentaro Yamashita; Takayuki Nobuoka; Yoshihiro Matsuno; Tadashi Hasegawa
Journal:  Pathol Int       Date:  2017-11-13       Impact factor: 2.534

2.  Comparison of Three Ki-67 Index Quantification Methods and Clinical Significance in Pancreatic Neuroendocrine Tumors.

Authors:  Trynda N Kroneman; Jesse S Voss; Christine M Lohse; Tsung-Teh Wu; Thomas C Smyrk; Lizhi Zhang
Journal:  Endocr Pathol       Date:  2015-09       Impact factor: 3.943

Review 3.  The assessment of Ki-67 as a prognostic marker in neuroendocrine tumours: a systematic review and meta-analysis.

Authors:  Sebastian Richards-Taylor; Sean M Ewings; Eleanor Jaynes; Charles Tilley; Sarah G Ellis; Thomas Armstrong; Neil Pearce; Judith Cave
Journal:  J Clin Pathol       Date:  2015-12-17       Impact factor: 3.411

4.  Pancreatic endocrine tumors: improved TNM staging and histopathological grading permit a clinically efficient prognostic stratification of patients.

Authors:  Aldo Scarpa; William Mantovani; Paola Capelli; Stefania Beghelli; Letizia Boninsegna; Rossella Bettini; Francesco Panzuto; Paolo Pederzoli; Gianfranco delle Fave; Massimo Falconi
Journal:  Mod Pathol       Date:  2010-03-19       Impact factor: 7.842

5.  Quantitative immunohistochemistry using the CAS 200/486 image analysis system in invasive breast carcinoma: a reproducibility study.

Authors:  S V Makkink-Nombrado; J P Baak; L Schuurmans; J W Theeuwes; T van der Aa
Journal:  Anal Cell Pathol       Date:  1995-04       Impact factor: 2.916

6.  The ENETS/WHO grading system for neuroendocrine neoplasms of the gastroenteropancreatic system: a review of the current state, limitations and proposals for modifications.

Authors:  Marcela S Cavalcanti; Mithat Gönen; David S Klimstra
Journal:  Int J Endocr Oncol       Date:  2016-07-14

7.  Comparison of Monitor-Image and Printout-Image Methods in Ki-67 Scoring of Gastroenteropancreatic Neuroendocrine Tumors.

Authors:  Fatih Mert Dogukan; Banu Yilmaz Ozguven; Rabia Dogukan; Fevziye Kabukcuoglu
Journal:  Endocr Pathol       Date:  2019-03       Impact factor: 3.943

8.  Automated quantification of Ki-67 proliferative index of excised neuroendocrine tumors of the lung.

Authors:  Sandy Z Liu; Paul N Staats; Lindsay Goicochea; Borislav A Alexiev; Nirav Shah; Renee Dixon; Allen P Burke
Journal:  Diagn Pathol       Date:  2014-10-16       Impact factor: 2.644

9.  Ki67 Quantitative Interpretation: Insights using Image Analysis.

Authors:  Zoya Volynskaya; Ozgur Mete; Sara Pakbaz; Doaa Al-Ghamdi; Sylvia L Asa
Journal:  J Pathol Inform       Date:  2019-03-08

10.  Automated quantification of Ki-67 index associates with pathologic grade of pulmonary neuroendocrine tumors.

Authors:  Hai-Yue Wang; Zhong-Wu Li; Wei Sun; Xin Yang; Li-Xin Zhou; Xiao-Zheng Huang; Ling Jia; Dong-Mei Lin
Journal:  Chin Med J (Engl)       Date:  2019-03-05       Impact factor: 2.628

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  3 in total

1.  Optimal settings and clinical validation for automated Ki67 calculation in neuroendocrine tumors with open source informatics (QuPath).

Authors:  Rima Pai; Susan Karki; Rakhee Agarwal; Steven Sieber; Samuel Barasch
Journal:  J Pathol Inform       Date:  2022-09-21

2.  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

Review 3.  Ki-67 assessment of pancreatic neuroendocrine neoplasms: Systematic review and meta-analysis of manual vs. digital pathology scoring.

Authors:  Claudio Luchini; Liron Pantanowitz; Volkan Adsay; Sylvia L Asa; Pietro Antonini; Ilaria Girolami; Nicola Veronese; Alessia Nottegar; Sara Cingarlini; Luca Landoni; Lodewijk A Brosens; Anna V Verschuur; Paola Mattiolo; Antonio Pea; Andrea Mafficini; Michele Milella; Muhammad K Niazi; Metin N Gurcan; Albino Eccher; Ian A Cree; Aldo Scarpa
Journal:  Mod Pathol       Date:  2022-03-05       Impact factor: 8.209

  3 in total

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