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001-es BibID:	BIBFORM099490
035-os BibID:	(WoS)000747614400001 (Scopus)85121503950 (cikkazonosító)19
Első szerző:	Bencze János (orvos)
Cím:	Comparison of Semi-Quantitative Scoring and Artificial Intelligence Aided Digital Image Analysis of Chromogenic Immunohistochemistry / János Bencze, Máté Szarka, Balázs Kóti, Woosung Seo, Tibor G. Hortobágyi, Viktor Bencs, László V. Módis, Tibor Hortobágyi
Dátum:	2021
ISSN:	2218-273X
Megjegyzések:	Semi-quantitative scoring is a method that is widely used to estimate the quantity of proteins on chromogen-labelled immunohistochemical (IHC) tissue sections. However, it suffers from several disadvantages, including its lack of objectivity and the fact that it is a time-consuming process. Our aim was to test a recently established artificial intelligence (AI)-aided digital image analysis platform, Pathronus, and to compare it to conventional scoring by five observers on chromogenic IHC-stained slides belonging to three experimental groups. Because Pathronus operates on grayscale 0-255 values, we transformed the data to a seven-point scale for use by pathologists and scientists. The accuracy of these methods was evaluated by comparing statistical significance among groups with quantitative fluorescent IHC reference data on subsequent tissue sections. The pairwise inter-rater reliability of the scoring and converted Pathronus data varied from poor to moderate with Cohen's kappa, and overall agreement was poor within every experimental group using Fleiss' kappa. Only the original and converted that were obtained from Pathronus original were able to reproduce the statistical significance among the groups that were determined by the reference method. In this study, we present an AI-aided software that can identify cells of interest, differentiate among organelles, protein specific chromogenic labelling, and nuclear counterstaining after an initial training period, providing a feasible and more accurate alternative to semi-quantitative scoring.
Tárgyszavak:	Orvostudományok Elméleti orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk
Megjelenés:	Biomolecules. - 12 : 1 (2021), p. 1-14. -
További szerzők:	Szarka Máté (1990-) Kóti Balázs Seo, Woosung Hortobágyi Tibor G. (1998-) (orvostanhallgató) Bencs Viktor (1995-) (orvos) Módis László V. (neurológus) Hortobágyi Tibor (1965-) (patológus)
Pályázati támogatás:	EFOP-3.6.2-16-2017-00009 EFOP ÚNKP-21-3 Egyéb Nemzeti Agykutatási Program KTIA_13_NAP-A-II/7 Egyéb NKFIH_SNN_132999 Egyéb
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