Automated fluorescent miscroscopic image analysis of PTBP1 expression in glioma.
Multiplexed immunofluorescent testing has not entered into diagnostic neuropathology due to the presence of several technical barriers, amongst which includes autofluorescence. This study presents the implementation of a methodology capable of overcoming the visual challenges of fluorescent microsco...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2017-01-01
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| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC5345755?pdf=render |
| _version_ | 1831751737610862592 |
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| author | Behiye Kaya Evgin Goceri Aline Becker Brad Elder Vinay Puduvalli Jessica Winter Metin Gurcan José Javier Otero |
| author_facet | Behiye Kaya Evgin Goceri Aline Becker Brad Elder Vinay Puduvalli Jessica Winter Metin Gurcan José Javier Otero |
| author_sort | Behiye Kaya |
| collection | DOAJ |
| description | Multiplexed immunofluorescent testing has not entered into diagnostic neuropathology due to the presence of several technical barriers, amongst which includes autofluorescence. This study presents the implementation of a methodology capable of overcoming the visual challenges of fluorescent microscopy for diagnostic neuropathology by using automated digital image analysis, with long term goal of providing unbiased quantitative analyses of multiplexed biomarkers for solid tissue neuropathology. In this study, we validated PTBP1, a putative biomarker for glioma, and tested the extent to which immunofluorescent microscopy combined with automated and unbiased image analysis would permit the utility of PTBP1 as a biomarker to distinguish diagnostically challenging surgical biopsies. As a paradigm, we utilized second resections from patients diagnosed either with reactive brain changes (pseudoprogression) and recurrent glioblastoma (true progression). Our image analysis workflow was capable of removing background autofluorescence and permitted quantification of DAPI-PTBP1 positive cells. PTBP1-positive nuclei, and the mean intensity value of PTBP1 signal in cells. Traditional pathological interpretation was unable to distinguish between groups due to unacceptably high discordance rates amongst expert neuropathologists. Our data demonstrated that recurrent glioblastoma showed more DAPI-PTBP1 positive cells and a higher mean intensity value of PTBP1 signal compared to resections from second surgeries that showed only reactive gliosis. Our work demonstrates the potential of utilizing automated image analysis to overcome the challenges of implementing fluorescent microscopy in diagnostic neuropathology. |
| first_indexed | 2024-12-21T22:49:57Z |
| format | Article |
| id | doaj.art-e61d1a9d0043423994b92265918219bc |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-21T22:49:57Z |
| publishDate | 2017-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-e61d1a9d0043423994b92265918219bc2022-12-21T18:47:36ZengPublic Library of Science (PLoS)PLoS ONE1932-62032017-01-01123e017099110.1371/journal.pone.0170991Automated fluorescent miscroscopic image analysis of PTBP1 expression in glioma.Behiye KayaEvgin GoceriAline BeckerBrad ElderVinay PuduvalliJessica WinterMetin GurcanJosé Javier OteroMultiplexed immunofluorescent testing has not entered into diagnostic neuropathology due to the presence of several technical barriers, amongst which includes autofluorescence. This study presents the implementation of a methodology capable of overcoming the visual challenges of fluorescent microscopy for diagnostic neuropathology by using automated digital image analysis, with long term goal of providing unbiased quantitative analyses of multiplexed biomarkers for solid tissue neuropathology. In this study, we validated PTBP1, a putative biomarker for glioma, and tested the extent to which immunofluorescent microscopy combined with automated and unbiased image analysis would permit the utility of PTBP1 as a biomarker to distinguish diagnostically challenging surgical biopsies. As a paradigm, we utilized second resections from patients diagnosed either with reactive brain changes (pseudoprogression) and recurrent glioblastoma (true progression). Our image analysis workflow was capable of removing background autofluorescence and permitted quantification of DAPI-PTBP1 positive cells. PTBP1-positive nuclei, and the mean intensity value of PTBP1 signal in cells. Traditional pathological interpretation was unable to distinguish between groups due to unacceptably high discordance rates amongst expert neuropathologists. Our data demonstrated that recurrent glioblastoma showed more DAPI-PTBP1 positive cells and a higher mean intensity value of PTBP1 signal compared to resections from second surgeries that showed only reactive gliosis. Our work demonstrates the potential of utilizing automated image analysis to overcome the challenges of implementing fluorescent microscopy in diagnostic neuropathology.http://europepmc.org/articles/PMC5345755?pdf=render |
| spellingShingle | Behiye Kaya Evgin Goceri Aline Becker Brad Elder Vinay Puduvalli Jessica Winter Metin Gurcan José Javier Otero Automated fluorescent miscroscopic image analysis of PTBP1 expression in glioma. PLoS ONE |
| title | Automated fluorescent miscroscopic image analysis of PTBP1 expression in glioma. |
| title_full | Automated fluorescent miscroscopic image analysis of PTBP1 expression in glioma. |
| title_fullStr | Automated fluorescent miscroscopic image analysis of PTBP1 expression in glioma. |
| title_full_unstemmed | Automated fluorescent miscroscopic image analysis of PTBP1 expression in glioma. |
| title_short | Automated fluorescent miscroscopic image analysis of PTBP1 expression in glioma. |
| title_sort | automated fluorescent miscroscopic image analysis of ptbp1 expression in glioma |
| url | http://europepmc.org/articles/PMC5345755?pdf=render |
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