Classification of breast cancer stroma as a tool for prognosis
| Autor: | Patrycja Gazinska, John H. Hipwell, Sarah E Pinder, David J. Hawkes, Kalnisha Naidoo, Thomy Mertzanidou, Sara Reis |
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| Rok vydání: | 2016 |
| Předmět: |
Stromal cell
business.industry Tumor biology H&E stain 02 engineering and technology medicine.disease Bioinformatics 03 medical and health sciences 0302 clinical medicine Breast cancer Stroma Collagen fibres 030220 oncology & carcinogenesis 0202 electrical engineering electronic engineering information engineering Cancer research Medicine 020201 artificial intelligence & image processing business Radiological imaging |
| Zdroj: | Medical Imaging: Digital Pathology |
| ISSN: | 0277-786X |
| DOI: | 10.1117/12.2216520 |
| Popis: | It has been shown that the tumour microenvironment plays a crucial role in regulating tumour progression by a number of different mechanisms, including the remodeling of collagen fibres in tumour-associated stroma. It is still unclear, however, if these stromal changes are of benefit to the host or the tumour. We hypothesise that stromal maturity is an important reflection of tumour biology, and thus can be used to predict prognosis. The aim of this study is to develop a texture analysis methodology which will automatically classify stromal regions from images of hematoxylin and eosin-stained (H and E) sections into two categories: mature and immature. Subsequently we will investigate whether stromal maturity could be used as a predictor of survival and also as a means to better understand the relationship between the radiological imaging signal and the underlying tissue microstructure. We present initial results for 118 regions-of-interest from a dataset of 39 patients diagnosed with invasive breast cancer. |
| Databáze: | OpenAIRE |
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