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...
| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-01-01
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| Series: | Journal of Pathology Informatics |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2153353922007398 |
| _version_ | 1828086715698380800 |
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| author | Nicola Michielli Alessandro Caputo Manuela Scotto Alessandro Mogetta Orazio Antonino Maria Pennisi Filippo Molinari Davide Balmativola Martino Bosco Alessandro Gambella Jasna Metovic Daniele Tota Laura Carpenito Paolo Gasparri Massimo Salvi |
| author_facet | Nicola Michielli Alessandro Caputo Manuela Scotto Alessandro Mogetta Orazio Antonino Maria Pennisi Filippo Molinari Davide Balmativola Martino Bosco Alessandro Gambella Jasna Metovic Daniele Tota Laura Carpenito Paolo Gasparri Massimo Salvi |
| author_sort | Nicola Michielli |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-04-11T05:00:19Z |
| format | Article |
| id | doaj.art-e1b321e3ae25476eb77b1e6b127affe8 |
| institution | Directory Open Access Journal |
| issn | 2153-3539 |
| language | English |
| last_indexed | 2024-04-11T05:00:19Z |
| publishDate | 2022-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Pathology Informatics |
| spelling | doaj.art-e1b321e3ae25476eb77b1e6b127affe82022-12-26T04:09:00ZengElsevierJournal of Pathology Informatics2153-35392022-01-0113100145Stain normalization in digital pathology: Clinical multi-center evaluation of image qualityNicola Michielli0Alessandro Caputo1Manuela Scotto2Alessandro Mogetta3Orazio Antonino Maria Pennisi4Filippo Molinari5Davide Balmativola6Martino Bosco7Alessandro Gambella8Jasna Metovic9Daniele Tota10Laura Carpenito11Paolo Gasparri12Massimo Salvi13Biolab, PolitoBIOMed Lab, Department of Electronics and Telecommunications, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, ItalyDepartment of Medicine and Surgery, University Hospital of Salerno, Salerno, ItalyBiolab, PolitoBIOMed Lab, Department of Electronics and Telecommunications, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, ItalyBiolab, PolitoBIOMed Lab, Department of Electronics and Telecommunications, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, ItalyTechnology Transfer and Industrial Liaison Department, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, ItalyBiolab, PolitoBIOMed Lab, Department of Electronics and Telecommunications, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, ItalyPathology Unit, Humanitas Gradenigo Hospital, Corso Regina Margherita 8, 10153 Turin, ItalyDepartment of Pathology, Michele and Pietro Ferrero Hospital, 12060 Verduno, ItalyPathology Unit, Department of Medical Sciences, University of Turin, Via Santena 7, 10126 Turin, ItalyPathology Unit, Department of Medical Sciences, University of Turin, Via Santena 7, 10126 Turin, ItalyPathology Unit, Department of Medical Sciences, University of Turin, Via Santena 7, 10126 Turin, ItalyDepartment of Pathology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy; University of Milan, Milan, ItalyUOC di Anatomia Patologica, ASP Catania P.O. “Gravina”, Caltagirone, ItalyBiolab, PolitoBIOMed Lab, Department of Electronics and Telecommunications, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, Italy; Corresponding author at: Biolab, Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy; Corso Duca degli Abruzzi 24, 10129 Turin, Italy.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.http://www.sciencedirect.com/science/article/pii/S2153353922007398Stain normalizationImage qualityQualitative scoreDigital pathologyH&E staining |
| spellingShingle | Nicola Michielli Alessandro Caputo Manuela Scotto Alessandro Mogetta Orazio Antonino Maria Pennisi Filippo Molinari Davide Balmativola Martino Bosco Alessandro Gambella Jasna Metovic Daniele Tota Laura Carpenito Paolo Gasparri Massimo Salvi Stain normalization in digital pathology: Clinical multi-center evaluation of image quality Journal of Pathology Informatics Stain normalization Image quality Qualitative score Digital pathology H&E staining |
| 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 | Stain normalization Image quality Qualitative score Digital pathology H&E staining |
| url | http://www.sciencedirect.com/science/article/pii/S2153353922007398 |
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