Quantitative tumor heterogeneity assessment on a nuclear population basis. Issue 6 (31st January 2017)

• Record Type: Journal Article
• Authors: Wessel Lindberg, Anne‐Sofie; Conradsen, Knut; Larsen, Rasmus; Friis Lippert, Michael; Røge, Rasmus; Vyberg, Mogens
• Other Names: Bengtsson Ewert guestEditor.; Danielsen Håvard guestEditor.; Treanor Darren guestEditor.; Gurcan Metin N. guestEditor.; MacAulay Calum guestEditor.; Molnár Béla guestEditor.
• Is Part Of: Cytometry. Volume 91:Issue 6(2017)
• Page Start: 574
• Page End: 584
• Publication Date: 2017-01-31
• Subjects: Ki‐67 antigen -- breast cancer -- heterogeneity -- computer‐assisted image analysis -- hot spot detection -- heatmap -- hot spot; Flow cytometry -- Periodicals; Imaging systems in biology -- Periodicals; Imaging systems in medicine -- Periodicals; Diagnostic imaging -- Periodicals; 571.605
• DOI: 10.1002/cyto.a.23047
• Languages: English
• ISSNs: 1552-4922

Abstract

Abstract: 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