NDLI: Early prognosis of metastasis risk in inflammatory breast cancer by texture analysis of tumour microscopic images

Content Provider	Springer Nature Link
Author	Kolarevic, Daniela Tomasevic, Zorica Dzodic, Radan Kanjer, Ksenija Vukosavljevic, Dragica Nikolic Radulovic, Marko
Copyright Year	2015
Abstract	Inflammatory breast cancer (IBC) is a rare and aggressive type of locally advanced breast cancer. The purpose of this study was to determine the value of microscopic tumour histomorphology texture for prognosis of local and systemic recurrence at the time of initial IBC diagnosis. This retrospective study included a group of 52 patients selected on the basis of non-metastatic IBC diagnosis, stage IIIB. Gray-Level-Co-Occurrence-Matrix (GLCM) texture analysis was performed on digital images of primary tumour tissue sections stained with haematoxylin/eosin. Obtained values were categorized by use of both data- and outcome-based methods. All five acquired GLCM texture features significantly associated with metastasis outcome. By accuracies of 69–81 % and AUCs of 0.71–0.81, prognostic performance of GLCM parameters exceeded that of standard major IBC clinical prognosticators such as tumour grade and response to induction chemotherapy. Furthermore, a composite score consisting of tumour grade, contrast and correlation as independent features resulted in further enhancement of prognostic performance by accuracy of 89 %, discrimination efficiency by AUC of 0.93 and an outstanding hazard ratio of 71.6 (95 %CI, 41.7–148.4). Internal validation was successfully performed by bootstrap and split-sample cross-validation, suggesting that the model is generalizable. This study indicates for the first time the potential use of primary breast tumour histology texture as a highly accurate, simple and cost-effective prognostic indicator of metastasis risk in IBC. Clinical relevance of the obtained results rests on the role of prognosis in decisions on induction chemotherapy and the resulting impact on quality of life and survival.
Starting Page	1
Ending Page	8
Page Count	8
File Format	PDF
ISSN	13872176
Journal	Biomedical Microdevices
Volume Number	17
Issue Number	5
e-ISSN	15728781
Language	English
Publisher	Springer US
Publisher Date	2015-08-19
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Inflammatory breast cancer Image analysis Prognosis Prognostic factor Metastasis Histology texture GLCM Biomedical Engineering Biophysics and Biological Physics Nanotechnology Engineering Fluid Dynamics
Content Type	Text
Resource Type	Article
Subject	Nanoscience and Nanotechnology Molecular Biology Biomedical Engineering

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