Automated Objective Determination of Percentage of Malignant Nuclei for Mutation Testing

作者：Viray Hollis; Coulter Madeline; Li Kevin; Lane Kristin; Madan Aruna; Mitchell Kisha; Schalper Kurt; Hoyt Clifford; Rimm David L^*

来源：Applied Immunohistochemistry & Molecular Morphology, 2014, 22(5): 363-371.

DOI：10.1097/PAI.0b013e318299a1f6

• morphology
• nuclei
• automated analysis
• molecular diagnostics

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.

• 出版日期2014-6