| Autor: |
Vranes V; Department of Basic and Environmental Science, Instituto Tecnológico de Santo Domingo (INTEC), Santo Domingo 10602, Dominican Republic. velicko.vranes@intec.edu.do., Rajković N; Department of Biophysics, School of Medicine, University of Belgrade, 11000 Belgrade, Serbia. nemanja.rajkovic@med.bg.ac.rs., Li X; Multimedia Laboratory, The Edward S. Rogers Sr. Department of Electrical & Computer Engineering, University of Toronto, Toronto, ON M5S 3G4, Canada. xingyu.li@mail.utoronto.ca., Plataniotis KN; Multimedia Laboratory, The Edward S. Rogers Sr. Department of Electrical & Computer Engineering, University of Toronto, Toronto, ON M5S 3G4, Canada. kostas@ece.utoronto.ca., Todorović Raković N; Department of Experimental Oncology, Institute for Oncology and Radiology, 11000 Belgrade, Serbia. todorovicn@ncrc.ac.rs., Milovanović J; Department of Experimental Oncology, Institute for Oncology and Radiology, 11000 Belgrade, Serbia. jelena.mil10@gmail.com., Kanjer K; Department of Experimental Oncology, Institute for Oncology and Radiology, 11000 Belgrade, Serbia. ksenijakanjer@gmail.com., Radulovic M; Department of Experimental Oncology, Institute for Oncology and Radiology, 11000 Belgrade, Serbia. marko@radulovic.net., Milošević NT; Department of Basic and Environmental Science, Instituto Tecnológico de Santo Domingo (INTEC), Santo Domingo 10602, Dominican Republic. nebojsa.milosevic@med.bg.ac.rs.; Department of Biophysics, School of Medicine, University of Belgrade, 11000 Belgrade, Serbia. nebojsa.milosevic@med.bg.ac.rs. |
| Abstrakt: |
Survival and life quality of breast cancer patients could be improved by more aggressive chemotherapy for those at high metastasis risk and less intense treatments for low-risk patients. Such personalized treatment cannot be currently achieved due to the insufficient reliability of metastasis risk prognosis. The purpose of this study was therefore, to identify novel histopathological prognostic markers of metastasis risk through exhaustive computational image analysis of 80 size and shape subsets of epithelial clusters in breast tumors. The group of 102 patients had a follow-up median of 12.3 years, without lymph node spread and systemic treatments. Epithelial cells were stained by the AE1/AE3 pan-cytokeratin antibody cocktail. The size and shape subsets of the stained epithelial cell clusters were defined in each image by use of the circularity and size filters and analyzed for prognostic performance. Epithelial areas with the optimal prognostic performance were uniformly small and round and could be recognized as individual epithelial cells scattered in tumor stroma. Their count achieved an area under the receiver operating characteristic curve (AUC) of 0.82, total area (AUC = 0.77), average size (AUC = 0.63), and circularity (AUC = 0.62). In conclusion, by use of computational image analysis as a hypothesis-free discovery tool, this study reveals the histomorphological marker with a high prognostic value that is simple and therefore easy to quantify by visual microscopy. |
