Journal of Pathology Informatics (Jan 2021)
Digital image analysis for estimating stromal CD8+ tumor-infiltrating lymphocytes in lung adenocarcinoma
Abstract
Background: Stromal CD8+ tumor-infiltrating lymphocytes (TILs) are an important prognostic and predictive indicator in non-small cell lung cancer (NSCLC). In this study, we aimed to develop and test the feasibility of a digital image analysis (DIA) workflow for estimating stromal CD8+ TIL density. Methods: A DIA workflow developed in a software platform (QuPath) was applied to a specified region of interest (ROI) within the stromal compartment of dual PD-L1/CD8 immunostained slides from 50 lung adenocarcinoma patients. A random tree classifier was trained from 25 training cases and applied to 25 test cases. The DIA-estimated CD8+ TIL densities were compared to manual estimates of three pathologists, who independently quantitated the percentage of CD8+ TILs from predefined ROIs in QuPath. Results: The average estimated total stromal cell count per case was 520 (range: 282–816) by QuPath and 551 (range: 265–744) by pathologists. The DIA-estimated CD8+ TIL density (mean = 16.9%) was comparable to pathologists' manual estimates (mean = 15.9%). A paired t-test showed no statistically significant difference between DIA and pathologist estimates of CD8+ TIL density among both training (n = 25, P = 0.55) and test (n = 25, P = 0.34) cases. There was an almost perfect agreement between QuPath and each pathologist's estimates of CD8+ TIL density (κ = 0.85–0.86). Conclusions: These findings demonstrate the feasibility of applying a DIA workflow for estimating stromal CD8+ TIL density in NSCLC. DIA has the potential to provide an efficient and standardized approach for estimating stromal CD8+ TIL density.
Keywords