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Automated tumor proportion score analysis for PD-L1 (22C3) expression in lung squamous cell carcinoma
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Automated tumor proportion score analysis for PD-L1 (22C3) expression in lung squamous cell carcinoma
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Journal Article
Automated tumor proportion score analysis for PD-L1 (22C3) expression in lung squamous cell carcinoma
2021
Overview
Programmed cell death ligend-1 (PD-L1) expression by immunohistochemistry (IHC) assays is a predictive marker of anti-PD-1/PD-L1 therapy response. With the popularity of anti-PD-1/PD-L1 inhibitor drugs, quantitative assessment of PD-L1 expression becomes a new labor for pathologists. Manually counting the PD-L1 positive stained tumor cells is an obviously subjective and time-consuming process. In this paper, we developed a new computer aided Automated Tumor Proportion Scoring System (ATPSS) to determine the comparability of image analysis with pathologist scores. A three-stage process was performed using both image processing and deep learning techniques to mimic the actual diagnostic flow of the pathologists. We conducted a multi-reader multi-case study to evaluate the agreement between pathologists and ATPSS. Fifty-one surgically resected lung squamous cell carcinoma were prepared and stained using the Dako PD-L1 (22C3) assay, and six pathologists with different experience levels were involved in this study. The TPS predicted by the proposed model had high and statistically significant correlation with sub-specialty pathologists’ scores with Mean Absolute Error (MAE) of 8.65 (95% confidence interval (CI): 6.42–10.90) and Pearson Correlation Coefficient (PCC) of 0.9436 (
p
<
0.001
), and the performance on PD-L1 positive cases achieved by our method surpassed that of non-subspecialty and trainee pathologists. Those experimental results indicate that the proposed automated system can be a powerful tool to improve the PD-L1 TPS assessment of pathologists.
Publisher
Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
Subject
/ Adult
/ Aged
/ Automation, Laboratory - methods
/ Biomarkers, Tumor - metabolism
/ Carcinoma, Non-Small-Cell Lung - diagnosis
/ Carcinoma, Non-Small-Cell Lung - genetics
/ Carcinoma, Squamous Cell - diagnosis
/ Carcinoma, Squamous Cell - genetics
/ China
/ Female
/ Gene Expression Profiling - methods
/ Humanities and Social Sciences
/ Humans
/ Immunohistochemistry - methods
/ Male
/ Science
