title: Gray-Level Co-Occurrence Matrix Texture Analysis of Breast Tumor Images in Prognosis of Distant Metastasis Risk.
abstract: Owing to exceptional heterogeneity in the outcome of invasive breast cancer it is essential to develop highly accurate prognostic tools for effective therapeutic management. Based on this pressing need, we aimed to improve breast cancer prognosis by exploring the prognostic value of tumor histology image analysis. Patient group (n=78) selection was based on invasive breast cancer diagnosis without systemic treatment with a median follow-up of 147 months. Gray-level co-occurrence matrix texture analysis was performed retrospectively on primary tumor tissue section digital images stained either nonspecifically with hematoxylin and eosin or specifically with a pan-cytokeratin antibody cocktail for epithelial malignant cells. Univariate analysis revealed stronger association with metastasis risk by texture analysis when compared with clinicopathological parameters. The combination of individual clinicopathological and texture variables into composite scores resulted in further powerful enhancement of prognostic performance, with an accuracy of up to 90%, discrimination efficiency by the area under the curve [95% confidence interval (CI)] of 0.94 (0.87-0.99) and hazard ratio (95% CI) of 20.1 (7.5-109.4). Internal validation was successfully performed by bootstrap and split-sample cross-validation, suggesting that the models are generalizable. Whereas further validation is needed on an external set of patients, this preliminary study indicates the potential use of primary breast tumor histology texture as a highly accurate, simple, and cost-effective prognostic indicator of distant metastasis risk.
authors: 1Department of Experimental Oncology,Institute for Oncology and Radiology,11000 Belgrade,Serbia.
authors: Tijana
authors: T
authors: Vujasinovic
authors: 1Department of Experimental Oncology,Institute for Oncology and Radiology,11000 Belgrade,Serbia.
authors: Jelena
authors: J
authors: Pribic
authors: 1Department of Experimental Oncology,Institute for Oncology and Radiology,11000 Belgrade,Serbia.
authors: Ksenija
authors: K
authors: Kanjer
authors: 2Department of Biophysics,School of Medicine,University of Belgrade,Višegradska 26/2,11000 Belgrade,Serbia.
authors: Nebojsa T
authors: NT
authors: Milosevic
authors: 3Daily Chemotherapy Hospital,Institute for Oncology and Radiology,11000 Belgrade,Serbia.
authors: Zorica
authors: Z
authors: Tomasevic
authors: 4Department of Pathology and Cytology,Institute for Oncology and Radiology,11000 Belgrade,Serbia.
authors: Zorka
authors: Z
authors: Milovanovic
authors: 1Department of Experimental Oncology,Institute for Oncology and Radiology,11000 Belgrade,Serbia.
authors: Dragica
authors: D
authors: Nikolic-Vukosavljevic
authors: 1Department of Experimental Oncology,Institute for Oncology and Radiology,11000 Belgrade,Serbia.
authors: Marko
authors: M
authors: Radulovic
mesh_terms: D001943:Breast Neoplasms / Q000150:complications* / Q000175:diagnosis / Q000473:pathology*; D006651:Histocytochemistry / Q000379:methods; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D007150:Immunohistochemistry / Q000379:methods; D008853:Microscopy / Q000379:methods*; D009362:Neoplasm Metastasis / Q000175:diagnosis*; D011379:Prognosis; D012189:Retrospective Studies; D018570:Risk Assessment
keywords: breast cancer; gray-level co-occurrence matrix; metastasis; pan-cytokeratin; tumor