Abstract 4582: Evaluating benefits of PD-L1 image analysis for the clinical setting
Authors: Staci Kearney, Joshua Black, Famke Aeffner, Joshua Black, Luke Pratte, Joseph Krueger
Journal: Cancer Research (2017)

Abstract Tissue-based investigations can prove challenging due to complex tissue architecture and heterogeneous biomarker expression, visual and cognitive “traps” that affect interpretive precision, and subjective assessments that affect reproducibility. A major concern is that these challenges could increase the risk of failure for therapeutic/diagnostic co-development and clinical use, as the biomarker measurements continue to increase in complexity and require increasingly precise diagnostic cut-points. Image analysis tools have been developed to overcome some of the challenges for conventional anatomic pathology practices, capitalizing on the objectivity and computational power of a digital platform. A computer, however, lacks the cognitive ability and experience of a human to interpret tissue architecture and context. Flagship Biosciences’ computational Tissue Analysis (cTA™) platform integrates the power of our tissue Image Analysis (tIA™) technology with the contextual experience of an anatomic pathologist to produce robust, precise, quantitative results that demonstrate biomarker content in the tissue context. Flagship Biosciences envisions the integration of our cTA™ technology into a computer-aided clinical pathology workflow as a method to improve the precision of scoring for even some of the most challenging tissue-based biomarker measurements. In a proof-of-concept study, we evaluated the performance of manual versus digital scoring approaches in a cohort of non-small cell lung carcinoma (NSCLC) samples stained with the IHC protocol for the PD-L1 PharmDx 28-8 complementary diagnostic. A comparison of the 2 modalities demonstrated that in nearly all cases, the within sample standard deviation of the cTA™ digital score results was less than the manual score (median inter-pathologist %CVs were reduced from 124.9% to 7.8% and intra-pathologists from 65.4% to 7.6% for manual and digital scores, respectively). As an additional exploratory examination, the effect of heterogeneity on PD-L1 interpretation was also investigated. Pathologists evaluated the same whole tissue slides within 5 high powered fields (HPFs) using both manual and cTA™ -derived scoring. Results demonstrated that the use of cTA™ provides improves agreement between HPF and whole slide assessments (absolute difference between the manual scores from HPF to whole slide were larger than the absolute differences for the digitally derived scores, at 3.14% and 8.27%, respectively). Taken together, these studies demonstrate that the use of cTA™ can significantly reduce variability in PD-L1 scoring, as compared to a manual scoring approach. Citation Format: Staci Kearney, Joshua Black, Famke Aeffner, Joshua Black, Luke Pratte, Joseph Krueger. Evaluating benefits of PD-L1 image analysis for the clinical setting [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4582. doi:10.1158/1538-7445.AM2017-4582