Publication:
Ki-67 assessment of pancreatic neuroendocrine neoplasms: systematic review and meta-analysis of manual vs. digital pathology scoring

dc.contributor.coauthorLuchini, Claudio
dc.contributor.coauthorPantanowitz, Liron
dc.contributor.coauthorAsa, Sylvia L.
dc.contributor.coauthorAntonini, Pietro
dc.contributor.coauthorGirolami, Ilaria
dc.contributor.coauthorVeronese, Nicola
dc.contributor.coauthorNottegar, Alessia
dc.contributor.coauthorCingarlini, Sara
dc.contributor.coauthorLandoni, Luca
dc.contributor.coauthorBrosens, Lodewijk A.
dc.contributor.coauthorVerschuur, Anna V.
dc.contributor.coauthorMattiolo, Paola
dc.contributor.coauthorPea, Antonio
dc.contributor.coauthorMafficini, Andrea
dc.contributor.coauthorMilella, Michele
dc.contributor.coauthorNiazi, Muhammad K.
dc.contributor.coauthorGurcan, Metin N.
dc.contributor.coauthorEccher, Albino
dc.contributor.coauthorCree, Ian A.
dc.contributor.coauthorScarpa, Aldo
dc.contributor.departmentKUH (Koç University Hospital)
dc.contributor.departmentSchool of Medicine
dc.contributor.kuauthorAdsay, Nazmi Volkan
dc.contributor.schoolcollegeinstituteKUH (KOÇ UNIVERSITY HOSPITAL)
dc.contributor.schoolcollegeinstituteSCHOOL OF MEDICINE
dc.date.accessioned2024-11-09T12:25:20Z
dc.date.issued2022
dc.description.abstractKi-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.
dc.description.fulltextYES
dc.description.indexedbyWOS
dc.description.indexedbyScopus
dc.description.indexedbyPubMed
dc.description.issue6
dc.description.openaccessYES
dc.description.publisherscopeInternational
dc.description.sponsoredbyTubitakEuN/A
dc.description.sponsorshipAssociazione Italiana Ricerca sul Cancro
dc.description.sponsorshipFondazione Cariverona: Oncology Biobank Project ’Antonio Schiavi’
dc.description.sponsorshipFondazione Italiana Malattie Pancreas (FIMP)
dc.description.versionPublisher version
dc.description.volume35
dc.identifier.doi10.1038/s41379-022-01055-1
dc.identifier.eissn1530-0285
dc.identifier.embargoNO
dc.identifier.filenameinventorynoIR03540
dc.identifier.issn0893-3952
dc.identifier.quartileQ1
dc.identifier.scopus2-s2.0-85125620430
dc.identifier.urihttps://doi.org/10.1038/s41379-022-01055-1
dc.identifier.wos764914300001
dc.keywordsArtificial-intelligence
dc.keywordsProliferative index
dc.keywordsImage-analysis
dc.keywordsLabeling index
dc.keywordsTumors
dc.keywordsKi67
dc.keywordsQuality
dc.keywordsQuantification
dc.language.isoeng
dc.publisherSpringer Nature
dc.relation.grantno26343
dc.relation.grantno203885/2017
dc.relation.grantnoJ38D19000690001
dc.relation.ispartofModern Pathology
dc.relation.urihttp://cdm21054.contentdm.oclc.org/cdm/ref/collection/IR/id/10399
dc.subjectPathology
dc.titleKi-67 assessment of pancreatic neuroendocrine neoplasms: systematic review and meta-analysis of manual vs. digital pathology scoring
dc.typeReview
dspace.entity.typePublication
local.contributor.kuauthorAdsay, Nazmi Volkan
local.publication.orgunit1SCHOOL OF MEDICINE
local.publication.orgunit1KUH (KOÇ UNIVERSITY HOSPITAL)
local.publication.orgunit2KUH (Koç University Hospital)
local.publication.orgunit2School of Medicine
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