Quantitative tumor heterogeneity assessment on a nuclear population basis.

Immunohistochemistry Ki-67 stain is widely used for visualizing cell proliferation. The common method for scoring the proliferation is to manually select and score a hot spot. This method is time-consuming and will often not give reproducible results due to subjective selection of the hotspots and subjective scoring. An automatic hotspot detection and proliferative index scoring would be time-saving, make the determination of the Ki-67 score easier and minimize the uncertainty of the score by introducing a more objective and standardized score. Tissue Micro Array cores stained for Ki-67 and their neighbor slide stained for Pan Cytokeratin were aligned and Ki-67 positive and negative nuclei were identified inside tumor regions. A heatmap was calculated based on these and illustrates the distribution of the heterogenous response of Ki-67 positive nuclei in the tumor tissue. An automatic hot spot detection was developed and the Ki-67 score was calculated. All scores were compared with scores provided by a pathologist using linear regression models. No significant difference was found between the Ki-67 scores guided by the developed heatmap and the scores provided by a pathologist. For comparison, scores were also calculated at a random place outside the hot spot and these scores were found to be significantly different from the pathologist scores. A heatmap visualizing the heterogeneity in tumor tissue expressed by Ki-67 was developed and used for an automatic identification of hot spots in which a Ki-67 score was calculated. The Ki-67 scores did not differ significantly from scores provided by a pathologist. © 2017 International Society for Advancement of Cytometry.

Virtual Double Staining: A Digital Approach to Immunohistochemical Quantification of Estrogen Receptor Protein in Breast Carcinoma Specimens.

Visual assessment of immunohistochemically detected estrogen receptor protein is prone to interobserver and intraobserver variation due to its subjective evaluation. The aim of this study was to validate a new image analysis system based on virtual double staining (VDS) by comparing visual and automated scorings of ER in tissue microarrays of breast carcinomas. Tissue microarrays were constructed of 112 consecutive resection specimens of breast carcinomas. Immunohistochemistry assays for ER and pancytokeratin was applied on separate serial sections. ER scoring was visually performed by 5 observers using the histoscore (H-score) method. The Visiopharm ER image analysis protocol (APP) software application using VDS technique was applied separating stromal cells from carcinoma and other epithelial cells based on the pancytokeratin reaction. Using color deconvolution, polynomial filters, and nuclear segmentation the APP determined the percentage of positive cells and their intensity, and calculated the resulting H-score. On the basis of 1% cutoff VDS was perfectly correlated with visual assessment (κ=1). Using H-score, a very high agreement between VDS and visual ER assessment was seen (R=0.950). Image analysis has the attributes to eliminate the shortcomings of visual ER evaluation by generating automated, reproducible, and objective results of ER assessment.