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Detection of DNA mutations in tumor tissue can be a critical companion diagnostic test before prescription of a targeted therapy. Each method for detection of these mutations is associated with an analytic sensitivity that is a function of the percentage of tumor cells present in the specimen. Currently, tumor cell percentage is visually estimated resulting in an ordinal and highly variant result for a biologically continuous variable. We proposed that this aspect of DNA mutation testing could be standardized by developing a computer algorithm capable of accurately determining the percentage of malignant nuclei in an image of a hematoxylin and eosin-stained tissue. Using inForm software, we developed an algorithm, to calculate the percentage of malignant cells in histologic specimens of colon adenocarcinoma. A criterion standard was established by manually counting malignant and benign nuclei. Three pathologists also estimated the percentage of malignant nuclei in each image. Algorithm #9 had a median deviation from the criterion standard of 5.4% on the training set and 6.2% on the validation set. Compared with pathologist estimation, Algorithm #9 showed a similar ability to determine percentage of malignant nuclei. This method represents a potential future tool to assist in determining the percent of malignant nuclei present in a tissue section. Further validation of this algorithm or an improved algorithm may have value to more accurately assess percentage of malignant cells for companion diagnostic mutation testing.
Viray et al. (Thu,) studied this question.