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Pathology Quality Control for Multiplex Immunofluorescence and Image Analysis Assessment in Longitudinal Studies
Immune profiling of formalin-fixed, paraffin-embedded tissues using multiplex immunofluorescence (mIF) staining and image analysis methodology allows for the study of several biomarkers on a single slide. The pathology quality control (PQC) for tumor tissue immune profiling using digital image analy...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8363080/ https://www.ncbi.nlm.nih.gov/pubmed/34395517 http://dx.doi.org/10.3389/fmolb.2021.661222 |
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author | Lazcano, Rossana Rojas, Frank Laberiano, Caddie Hernandez, Sharia Parra, Edwin Roger |
author_facet | Lazcano, Rossana Rojas, Frank Laberiano, Caddie Hernandez, Sharia Parra, Edwin Roger |
author_sort | Lazcano, Rossana |
collection | PubMed |
description | Immune profiling of formalin-fixed, paraffin-embedded tissues using multiplex immunofluorescence (mIF) staining and image analysis methodology allows for the study of several biomarkers on a single slide. The pathology quality control (PQC) for tumor tissue immune profiling using digital image analysis of core needle biopsies is an important step in any laboratory to avoid wasting time and materials. Although there are currently no established inclusion and exclusion criteria for samples used in this type of assay, a PQC is necessary to achieve accurate and reproducible data. We retrospectively reviewed PQC data from hematoxylin and eosin (H&E) slides and from mIF image analysis samples obtained during 2019. We reviewed a total of 931 reports from core needle biopsy samples; 123 (13.21%) were excluded during the mIF PQC. The most common causes of exclusion were the absence of malignant cells or fewer than 100 malignant cells in the entire section (n = 42, 34.15%), tissue size smaller than 4 × 1 mm (n = 16, 13.01%), fibrotic tissue without inflammatory cells (n = 12, 9.76%), and necrotic tissue (n = 11, 8.94%). Baseline excluded samples had more fibrosis (90 vs 10%) and less necrosis (5 vs 90%) compared with post-treatment excluded samples. The most common excluded organ site of the biopsy was the liver (n = 19, 15.45%), followed by soft tissue (n = 17, 13.82%) and the abdominal region (n = 15, 12.20%). We showed that the PQC is an important step for image analysis and that the absence of malignant cells is the most limiting sample characteristic for mIF image analysis. We also discuss other challenges that pathologists need to consider to report reliable and reproducible image analysis data. |
format | Online Article Text |
id | pubmed-8363080 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-83630802021-08-14 Pathology Quality Control for Multiplex Immunofluorescence and Image Analysis Assessment in Longitudinal Studies Lazcano, Rossana Rojas, Frank Laberiano, Caddie Hernandez, Sharia Parra, Edwin Roger Front Mol Biosci Molecular Biosciences Immune profiling of formalin-fixed, paraffin-embedded tissues using multiplex immunofluorescence (mIF) staining and image analysis methodology allows for the study of several biomarkers on a single slide. The pathology quality control (PQC) for tumor tissue immune profiling using digital image analysis of core needle biopsies is an important step in any laboratory to avoid wasting time and materials. Although there are currently no established inclusion and exclusion criteria for samples used in this type of assay, a PQC is necessary to achieve accurate and reproducible data. We retrospectively reviewed PQC data from hematoxylin and eosin (H&E) slides and from mIF image analysis samples obtained during 2019. We reviewed a total of 931 reports from core needle biopsy samples; 123 (13.21%) were excluded during the mIF PQC. The most common causes of exclusion were the absence of malignant cells or fewer than 100 malignant cells in the entire section (n = 42, 34.15%), tissue size smaller than 4 × 1 mm (n = 16, 13.01%), fibrotic tissue without inflammatory cells (n = 12, 9.76%), and necrotic tissue (n = 11, 8.94%). Baseline excluded samples had more fibrosis (90 vs 10%) and less necrosis (5 vs 90%) compared with post-treatment excluded samples. The most common excluded organ site of the biopsy was the liver (n = 19, 15.45%), followed by soft tissue (n = 17, 13.82%) and the abdominal region (n = 15, 12.20%). We showed that the PQC is an important step for image analysis and that the absence of malignant cells is the most limiting sample characteristic for mIF image analysis. We also discuss other challenges that pathologists need to consider to report reliable and reproducible image analysis data. Frontiers Media S.A. 2021-07-30 /pmc/articles/PMC8363080/ /pubmed/34395517 http://dx.doi.org/10.3389/fmolb.2021.661222 Text en Copyright © 2021 Lazcano, Rojas, Laberiano, Hernandez and Parra. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Molecular Biosciences Lazcano, Rossana Rojas, Frank Laberiano, Caddie Hernandez, Sharia Parra, Edwin Roger Pathology Quality Control for Multiplex Immunofluorescence and Image Analysis Assessment in Longitudinal Studies |
title | Pathology Quality Control for Multiplex Immunofluorescence and Image Analysis Assessment in Longitudinal Studies |
title_full | Pathology Quality Control for Multiplex Immunofluorescence and Image Analysis Assessment in Longitudinal Studies |
title_fullStr | Pathology Quality Control for Multiplex Immunofluorescence and Image Analysis Assessment in Longitudinal Studies |
title_full_unstemmed | Pathology Quality Control for Multiplex Immunofluorescence and Image Analysis Assessment in Longitudinal Studies |
title_short | Pathology Quality Control for Multiplex Immunofluorescence and Image Analysis Assessment in Longitudinal Studies |
title_sort | pathology quality control for multiplex immunofluorescence and image analysis assessment in longitudinal studies |
topic | Molecular Biosciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8363080/ https://www.ncbi.nlm.nih.gov/pubmed/34395517 http://dx.doi.org/10.3389/fmolb.2021.661222 |
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