title: Automated objective determination of percentage of malignant nuclei for mutation testing.
abstract: 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.
authors.affiliation: *Department of Pathology, Yale School of Medicine, New Haven, CT †Caliper Life Sciences (a division of Perkin Elmer), Hopkinton, MA.
authors.forename: Hollis
authors.initials: H
authors.lastname: Viray
authors.forename: Madeline
authors.initials: M
authors.lastname: Coulter
authors.forename: Kevin
authors.initials: K
authors.lastname: Li
authors.forename: Kristin
authors.initials: K
authors.lastname: Lane
authors.forename: Aruna
authors.initials: A
authors.lastname: Madan
authors.forename: Kisha
authors.initials: K
authors.lastname: Mitchell
authors.forename: Kurt
authors.initials: K
authors.lastname: Schalper
authors.forename: Clifford
authors.initials: C
authors.lastname: Hoyt
authors.forename: David L
authors.initials: DL
authors.lastname: Rimm
mesh_terms: D000230:Adenocarcinoma / Q000175:diagnosis* / Q000235:genetics / Q000473:pathology; D000465:Algorithms; D057205:Automation, Laboratory; D063646:Carcinogenesis / Q000235:genetics; D002452:Cell Count / Q000379:methods* / Q000592:standards; D002454:Cell Differentiation / Q000235:genetics; D003110:Colonic Neoplasms / Q000175:diagnosis* / Q000235:genetics / Q000473:pathology; D004247:DNA / Q000032:analysis*; D003951:Diagnostic Errors / Q000517:prevention & control; D006801:Humans; D009154:Mutation / Q000235:genetics*; D015588:Observer Variation; D012015:Reference Standards; D012984:Software
chemical_list: D004247:DNA