Computer-assisted tumor grading, validation of PD-L1 scoring, and quantification of CD8-positive immune cell density in urothelial carcinoma, a visual guide for pathologists using QuPath
Abstract Background Advances in digital imaging in pathology and the new capacity to scan high-quality images have change the way to practice and research in surgical pathology. QuPath is an open-source pathology software that offers a reproducible way to analyze quantified variables. We aimed to pr...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2022-06-01
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| Series: | Surgical and Experimental Pathology |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s42047-022-00112-y |
| _version_ | 1818219041802682368 |
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| author | Aline Rodrigues Cleto Nogueira Laura Cardoso Marinho Guilherme Velozo Juliana Sousa Paulo Goberlanio Silva Fabio Tavora |
| author_facet | Aline Rodrigues Cleto Nogueira Laura Cardoso Marinho Guilherme Velozo Juliana Sousa Paulo Goberlanio Silva Fabio Tavora |
| author_sort | Aline Rodrigues |
| collection | DOAJ |
| description | Abstract Background Advances in digital imaging in pathology and the new capacity to scan high-quality images have change the way to practice and research in surgical pathology. QuPath is an open-source pathology software that offers a reproducible way to analyze quantified variables. We aimed to present the functionality of biomarker scoring using QuPath and provide a guide for the validation of pathologic grading using a series of cases of urothelial carcinomas. Methods Tissue microarrays of urothelial carcinomas were constructed and scanned. The images stained with HE, CD8 and PD-L1 immunohistochemistry were imported into QuPath and dearrayed. Training images were used to build a grade classifier and applied to all cases. Quantification of CD8 and PD-L1 was undertaken for each core using cytoplasmic and membrane color segmentation and output measurement and compared with pathologists semi-quantitative assessments. Results There was a good correlation between tumor grade by the pathologist and by QuPath software (Kappa agreement 0.73). For low-grade carcinomas (by the report and pathologist), the concordance was not as high. Of the 32 low-grade tumors, 22 were correctly classified as low-grade, but 11 (34%) were diagnosed as high-grade, with the high-grade to the low-grade ratio in these misclassified cases ranging from 0.41 to 0.58. The median ratio for bona fide high-grade carcinomas was 0.59. Some of the reasons the authors list as potential mimickers for high-grade cases are fulguration artifact, nuclear hyperchromasia, folded tissues, and inconsistency in staining. The correlation analysis between the software and the pathologist showed that the CD8 marker showed a moderate (r = 0.595) and statistically significant (p < 0.001) correlation. The internal consistency of this parameter showed an index of 0.470. The correlation analysis between the software and the pathologist showed that the PDL1 marker showed a robust (r = 0.834) and significant (p < 0.001) correlation. The internal consistency of this parameter showed a CCI of 0.851. Conclusions We were able to demonstrate the utility of QuPath in identifying and scoring tumor cells and IHC quantification of two biomarkers. The protocol we present uses a free open-source platform to help researchers deal with imaging and data processing in the surgical pathology field. |
| first_indexed | 2024-12-12T07:33:21Z |
| format | Article |
| id | doaj.art-b706879fc9524b868a5d966de66e7765 |
| institution | Directory Open Access Journal |
| issn | 2520-8454 |
| language | English |
| last_indexed | 2024-12-12T07:33:21Z |
| publishDate | 2022-06-01 |
| publisher | BMC |
| record_format | Article |
| series | Surgical and Experimental Pathology |
| spelling | doaj.art-b706879fc9524b868a5d966de66e77652022-12-22T00:32:59ZengBMCSurgical and Experimental Pathology2520-84542022-06-015111110.1186/s42047-022-00112-yComputer-assisted tumor grading, validation of PD-L1 scoring, and quantification of CD8-positive immune cell density in urothelial carcinoma, a visual guide for pathologists using QuPathAline Rodrigues0Cleto Nogueira1Laura Cardoso Marinho2Guilherme Velozo3Juliana Sousa4Paulo Goberlanio Silva5Fabio Tavora6ICC, Laboratory of Molecular Biology and GeneticsArgos LaboratoryArgos LaboratoryArgos LaboratoryArgos LaboratoryICC, Laboratory of Molecular Biology and GeneticsArgos LaboratoryAbstract Background Advances in digital imaging in pathology and the new capacity to scan high-quality images have change the way to practice and research in surgical pathology. QuPath is an open-source pathology software that offers a reproducible way to analyze quantified variables. We aimed to present the functionality of biomarker scoring using QuPath and provide a guide for the validation of pathologic grading using a series of cases of urothelial carcinomas. Methods Tissue microarrays of urothelial carcinomas were constructed and scanned. The images stained with HE, CD8 and PD-L1 immunohistochemistry were imported into QuPath and dearrayed. Training images were used to build a grade classifier and applied to all cases. Quantification of CD8 and PD-L1 was undertaken for each core using cytoplasmic and membrane color segmentation and output measurement and compared with pathologists semi-quantitative assessments. Results There was a good correlation between tumor grade by the pathologist and by QuPath software (Kappa agreement 0.73). For low-grade carcinomas (by the report and pathologist), the concordance was not as high. Of the 32 low-grade tumors, 22 were correctly classified as low-grade, but 11 (34%) were diagnosed as high-grade, with the high-grade to the low-grade ratio in these misclassified cases ranging from 0.41 to 0.58. The median ratio for bona fide high-grade carcinomas was 0.59. Some of the reasons the authors list as potential mimickers for high-grade cases are fulguration artifact, nuclear hyperchromasia, folded tissues, and inconsistency in staining. The correlation analysis between the software and the pathologist showed that the CD8 marker showed a moderate (r = 0.595) and statistically significant (p < 0.001) correlation. The internal consistency of this parameter showed an index of 0.470. The correlation analysis between the software and the pathologist showed that the PDL1 marker showed a robust (r = 0.834) and significant (p < 0.001) correlation. The internal consistency of this parameter showed a CCI of 0.851. Conclusions We were able to demonstrate the utility of QuPath in identifying and scoring tumor cells and IHC quantification of two biomarkers. The protocol we present uses a free open-source platform to help researchers deal with imaging and data processing in the surgical pathology field.https://doi.org/10.1186/s42047-022-00112-yDigital pathologyQuPathCD8Tumor infiltrating lymphocytesProgrammed death-ligand 1 immunotherapyBiomarker |
| spellingShingle | Aline Rodrigues Cleto Nogueira Laura Cardoso Marinho Guilherme Velozo Juliana Sousa Paulo Goberlanio Silva Fabio Tavora Computer-assisted tumor grading, validation of PD-L1 scoring, and quantification of CD8-positive immune cell density in urothelial carcinoma, a visual guide for pathologists using QuPath Surgical and Experimental Pathology Digital pathology QuPath CD8 Tumor infiltrating lymphocytes Programmed death-ligand 1 immunotherapy Biomarker |
| title | Computer-assisted tumor grading, validation of PD-L1 scoring, and quantification of CD8-positive immune cell density in urothelial carcinoma, a visual guide for pathologists using QuPath |
| title_full | Computer-assisted tumor grading, validation of PD-L1 scoring, and quantification of CD8-positive immune cell density in urothelial carcinoma, a visual guide for pathologists using QuPath |
| title_fullStr | Computer-assisted tumor grading, validation of PD-L1 scoring, and quantification of CD8-positive immune cell density in urothelial carcinoma, a visual guide for pathologists using QuPath |
| title_full_unstemmed | Computer-assisted tumor grading, validation of PD-L1 scoring, and quantification of CD8-positive immune cell density in urothelial carcinoma, a visual guide for pathologists using QuPath |
| title_short | Computer-assisted tumor grading, validation of PD-L1 scoring, and quantification of CD8-positive immune cell density in urothelial carcinoma, a visual guide for pathologists using QuPath |
| title_sort | computer assisted tumor grading validation of pd l1 scoring and quantification of cd8 positive immune cell density in urothelial carcinoma a visual guide for pathologists using qupath |
| topic | Digital pathology QuPath CD8 Tumor infiltrating lymphocytes Programmed death-ligand 1 immunotherapy Biomarker |
| url | https://doi.org/10.1186/s42047-022-00112-y |
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