The Potential of Digital Image Analysis to Determine Tumor Cell Content in Biobanked Formalin-Fixed, Paraffin-Embedded Tissue Samples.

Introduction: Best practices dictate that biobanks ensure accurate determination of tumor content before supplying formalin-fixed, paraffin-embedded (FFPE) tissue samples to researchers for nucleic acid extraction and downstream molecular testing. It is advisable that trained and competent individuals, who understand the requirements of the downstream molecular tests, perform the microscopic morphological examination. However, the special skills, time, and costs associated with these assessments can be prohibitive, especially in large case cohorts requiring extensive pathological review. Determination of tumor content reliably by digital image analysis (DIA) could represent a significant advantage if validated, utilized, and deployed by biobanks. Materials and Methods: Whole slide digital scanned images of colorectal, lung, and breast cancer specimens were created. The scanned images were imported into the DIA software QuPath and digital annotations were completed by biobank technicians, under the direction of trained histopathology senior scientists. Automated cell detection was conducted and tumor epithelial cells were classified and quantified. Results: DIA scores were highly concordant with the manual assessment for 376 of 435 samples (86%). A detailed review of discordant cases indicated digital scores had a higher accuracy than the manual estimation. Conclusion: Automated digital quantification has the potential to replace visual estimations with reduced subjectivity and increased reliability compared with manual tumor estimations. We recommend the use of DIA by biobanks involved in provision of FFPE tissue samples, especially in large research studies requiring high volumes of cases to be analyzed.

PD-L1 Multiplex and Quantitative Image Analysis for Molecular Diagnostics.

Multiplex immunofluorescence (mIF) and digital image analysis (DIA) have transformed the ability to analyse multiple biomarkers. We aimed to validate a clinical workflow for quantifying PD-L1 in non-small cell lung cancer (NSCLC). NSCLC samples were stained with a validated mIF panel. Immunohistochemistry (IHC) was conducted and mIF slides were scanned on an Akoya Vectra Polaris. Scans underwent DIA using QuPath. Single channel immunofluorescence was concordant with single-plex IHC. DIA facilitated quantification of cell types expressing single or multiple phenotypic markers. Considerations for analysis included classifier accuracy, macrophage infiltration, spurious staining, threshold sensitivity by DIA, sensitivity of cell identification in the mIF. Alternative sequential detection of biomarkers by DIA potentially impacted final score. Strong concordance was observed between 3,3'-Diaminobenzidine (DAB) IHC slides and mIF slides (R2 = 0.7323). Comparatively, DIA on DAB IHC was seen to overestimate the PD-L1 score more frequently than on mIF slides. Overall, concordance between DIA on DAB IHC slides and mIF slides was 95%. DIA of mIF slides is rapid, highly comparable to DIA on DAB IHC slides, and enables comprehensive extraction of phenotypic data and specific microenvironmental detail intrinsic to the sample. Exploration of the clinical relevance of mIF in the context of immunotherapy treated cases is warranted.

Improving the Diagnostic Accuracy of the PD-L1 Test with Image Analysis and Multiplex Hybridization.

Targeting of the programmed cell death protein (PD-1)/programmed death-ligand 1 (PD-L1) axis with checkpoint inhibitors has changed clinical practice in non-small cell lung cancer (NSCLC). However, clinical assessment remains complex and ambiguous. We aim to assess whether digital image analysis (DIA) and multiplex immunofluorescence can improve the accuracy of PD-L1 diagnostic testing. A clinical cohort of routine NSCLC patients reflex tested for PD-L1 (SP263) immunohistochemistry (IHC), was assessed using DIA. Samples of varying assessment difficulty were assessed by multiplex immunofluorescence. Sensitivity, specificity, and concordance was evaluated between manual diagnostic evaluation and DIA for chromogenic and multiplex IHC. PD-L1 expression by DIA showed significant concordance (R² = 0.8248) to manual assessment. Sensitivity and specificity was 86.8% and 91.4%, respectively. Evaluation of DIA scores revealed 96.8% concordance to manual assessment. Multiplexing enabled PD-L1+/CD68+ macrophages to be readily identified within PD-L1+/cytokeratin+ or PD-L1-/cytokeratin+ tumor nests. Assessment of multiplex vs. chromogenic IHC had a sensitivity and specificity of 97.8% and 91.8%, respectively. Deployment of DIA for PD-L1 diagnostic assessment is an accurate process of case triage. Multiplex immunofluorescence provided higher confidence in PD-L1 assessment and could be offered for challenging cases by centers with appropriate expertise and specialist equipment.