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Stain normalization in digital pathology: Clinical multi-center evaluation of image quality

In digital pathology, the final appearance of digitized images is affected by several factors, resulting in stain color and intensity variation. Stain normalization is an innovative solution to overcome stain variability. However, the validation of color normalization tools has been assessed only fr...

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Autores principales: Michielli, Nicola, Caputo, Alessandro, Scotto, Manuela, Mogetta, Alessandro, Pennisi, Orazio Antonino Maria, Molinari, Filippo, Balmativola, Davide, Bosco, Martino, Gambella, Alessandro, Metovic, Jasna, Tota, Daniele, Carpenito, Laura, Gasparri, Paolo, Salvi, Massimo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9577129/
https://www.ncbi.nlm.nih.gov/pubmed/36268060
http://dx.doi.org/10.1016/j.jpi.2022.100145
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author Michielli, Nicola
Caputo, Alessandro
Scotto, Manuela
Mogetta, Alessandro
Pennisi, Orazio Antonino Maria
Molinari, Filippo
Balmativola, Davide
Bosco, Martino
Gambella, Alessandro
Metovic, Jasna
Tota, Daniele
Carpenito, Laura
Gasparri, Paolo
Salvi, Massimo
author_facet Michielli, Nicola
Caputo, Alessandro
Scotto, Manuela
Mogetta, Alessandro
Pennisi, Orazio Antonino Maria
Molinari, Filippo
Balmativola, Davide
Bosco, Martino
Gambella, Alessandro
Metovic, Jasna
Tota, Daniele
Carpenito, Laura
Gasparri, Paolo
Salvi, Massimo
author_sort Michielli, Nicola
collection PubMed
description In digital pathology, the final appearance of digitized images is affected by several factors, resulting in stain color and intensity variation. Stain normalization is an innovative solution to overcome stain variability. However, the validation of color normalization tools has been assessed only from a quantitative perspective, through the computation of similarity metrics between the original and normalized images. To the best of our knowledge, no works investigate the impact of normalization on the pathologist’s evaluation. The objective of this paper is to propose a multi-tissue (i.e., breast, colon, liver, lung, and prostate) and multi-center qualitative analysis of a stain normalization tool with the involvement of pathologists with different years of experience. Two qualitative studies were carried out for this purpose: (i) a first study focused on the analysis of the perceived image quality and absence of significant image artifacts after the normalization process; (ii) a second study focused on the clinical score of the normalized image with respect to the original one. The results of the first study prove the high quality of the normalized image with a low impact artifact generation, while the second study demonstrates the superiority of the normalized image with respect to the original one in clinical practice. The normalization process can help both to reduce variability due to tissue staining procedures and facilitate the pathologist in the histological examination. The experimental results obtained in this work are encouraging and can justify the use of a stain normalization tool in clinical routine.
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spelling pubmed-95771292022-10-19 Stain normalization in digital pathology: Clinical multi-center evaluation of image quality Michielli, Nicola Caputo, Alessandro Scotto, Manuela Mogetta, Alessandro Pennisi, Orazio Antonino Maria Molinari, Filippo Balmativola, Davide Bosco, Martino Gambella, Alessandro Metovic, Jasna Tota, Daniele Carpenito, Laura Gasparri, Paolo Salvi, Massimo J Pathol Inform Original Research Article In digital pathology, the final appearance of digitized images is affected by several factors, resulting in stain color and intensity variation. Stain normalization is an innovative solution to overcome stain variability. However, the validation of color normalization tools has been assessed only from a quantitative perspective, through the computation of similarity metrics between the original and normalized images. To the best of our knowledge, no works investigate the impact of normalization on the pathologist’s evaluation. The objective of this paper is to propose a multi-tissue (i.e., breast, colon, liver, lung, and prostate) and multi-center qualitative analysis of a stain normalization tool with the involvement of pathologists with different years of experience. Two qualitative studies were carried out for this purpose: (i) a first study focused on the analysis of the perceived image quality and absence of significant image artifacts after the normalization process; (ii) a second study focused on the clinical score of the normalized image with respect to the original one. The results of the first study prove the high quality of the normalized image with a low impact artifact generation, while the second study demonstrates the superiority of the normalized image with respect to the original one in clinical practice. The normalization process can help both to reduce variability due to tissue staining procedures and facilitate the pathologist in the histological examination. The experimental results obtained in this work are encouraging and can justify the use of a stain normalization tool in clinical routine. Elsevier 2022-09-24 /pmc/articles/PMC9577129/ /pubmed/36268060 http://dx.doi.org/10.1016/j.jpi.2022.100145 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Original Research Article
Michielli, Nicola
Caputo, Alessandro
Scotto, Manuela
Mogetta, Alessandro
Pennisi, Orazio Antonino Maria
Molinari, Filippo
Balmativola, Davide
Bosco, Martino
Gambella, Alessandro
Metovic, Jasna
Tota, Daniele
Carpenito, Laura
Gasparri, Paolo
Salvi, Massimo
Stain normalization in digital pathology: Clinical multi-center evaluation of image quality
title Stain normalization in digital pathology: Clinical multi-center evaluation of image quality
title_full Stain normalization in digital pathology: Clinical multi-center evaluation of image quality
title_fullStr Stain normalization in digital pathology: Clinical multi-center evaluation of image quality
title_full_unstemmed Stain normalization in digital pathology: Clinical multi-center evaluation of image quality
title_short Stain normalization in digital pathology: Clinical multi-center evaluation of image quality
title_sort stain normalization in digital pathology: clinical multi-center evaluation of image quality
topic Original Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9577129/
https://www.ncbi.nlm.nih.gov/pubmed/36268060
http://dx.doi.org/10.1016/j.jpi.2022.100145
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