Pathologic response is an endpoint in many ongoing clinical trials for neoadjuvant regimens, including immune checkpoint blockade and chemotherapy. Whole slide scanning of glass slides generates high resolution digital images and allows for remote review and potential measurement with image analysis tools, but concordance of pathologic response assessment on digital scans compared to glass slides has yet to be evaluated. Such a validation goes beyond previous concordance studies which focused on establishing surgical pathology diagnoses, as it requires quantitative assessment of tumor, necrosis, and regression. Further, as pathologic response assessment is being used as an endpoint, such concordance studies have regulatory implications. The purpose of this study was two fold: firstly, to determine the concordance between pathologic response assessed on glass slides and on digital scans; and secondly, to determine if pathologists benefited from using measurement tools when determining pathologic response. To that end, H&E-stained glass slides from 64 non-small cell lung carcinoma specimens were visually assessed for percent residual viable tumor (%RVT). The sensitivity and specificity for digital vs. glass reads of complete pathologic response (pCR, 0% RVT) and major pathologic response (MPR, ≤10% RVT) were all >95%. When %RVT was considered as a continuous variable, intraclass correlation coefficient of digital vs. glass reads was 0.94. The visual assessments of pathologic response were supported by pathologist annotations of residual tumor and tumor bed areas. In a separate subset of H&E-stained glass slides, several measurement approaches to quantifying %RVT were performed. Pathologist estimates strongly reflected measured %RVT. This study demonstrates the high level of concordance between glass slides evaluated using light microscopy and digital whole slide images for pathologic response assessments. Pathologists did not require measurement tools to generate robust %RVT values from slide annotations. These findings have broad implications for improving clinical workflows and multisite clinical trials.
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