Journal article
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, Vol.156(4), pp.607-619
04/13/2021
DOI: 10.1093/ajcp/aqaa275
PMID: 33847759
Abstract
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.
Details
- Title: Subtitle
- Ki-67 Proliferation Index Assessment in Gastroenteropancreatic Neuroendocrine Tumors by Digital Image Analysis With Stringent Case and Hotspot Level Concordance Requirements
- Creators
- Sarag A Boukhar - University of Iowa Hospitals and ClinicsMatthew D Gosse - University of Iowa Hospitals and ClinicsAndrew M Bellizzi - University of Iowa Hospitals and ClinicsAnand Rajan K D - University of Iowa Hospitals and Clinics
- Resource Type
- Journal article
- Publication Details
- American journal of clinical pathology, Vol.156(4), pp.607-619
- DOI
- 10.1093/ajcp/aqaa275
- PMID
- 33847759
- NLM abbreviation
- Am J Clin Pathol
- ISSN
- 0002-9173
- eISSN
- 1943-7722
- Publisher
- Oxford University Press
- Grant note
- DOI: 10.13039/100000002, name: National Institutes of Health, award: P50 CA174521-01A1
- Language
- English
- Date published
- 04/13/2021
- Academic Unit
- Pathology
- Record Identifier
- 9984183995502771
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