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Proceedings Paper

A model of tumor architecture and spatial interactions with tumor microenvironment in breast carcinoma
Author(s): Bassem Ben Cheikh; Catherine Bor-Angelier; Daniel Racoceanu
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Paper Abstract

Breast carcinomas are cancers that arise from the epithelial cells of the breast, which are the cells that line the lobules and the lactiferous ducts. Breast carcinoma is the most common type of breast cancer and can be divided into different subtypes based on architectural features and growth patterns, recognized during a histopathological examination. Tumor microenvironment (TME) is the cellular environment in which tumor cells develop. Being composed of various cell types having different biological roles, TME is recognized as playing an important role in the progression of the disease. The architectural heterogeneity in breast carcinomas and the spatial interactions with TME are, to date, not well understood. Developing a spatial model of tumor architecture and spatial interactions with TME can advance our understanding of tumor heterogeneity. Furthermore, generating histological synthetic datasets can contribute to validating, and comparing analytical methods that are used in digital pathology. In this work, we propose a modeling method that applies to different breast carcinoma subtypes and TME spatial distributions based on mathematical morphology. The model is based on a few morphological parameters that give access to a large spectrum of breast tumor architectures and are able to differentiate in-situ ductal carcinomas (DCIS) and histological subtypes of invasive carcinomas such as ductal (IDC) and lobular carcinoma (ILC). In addition, a part of the parameters of the model controls the spatial distribution of TME relative to the tumor. The validation of the model has been performed by comparing morphological features between real and simulated images.

Paper Details

Date Published: 1 March 2017
PDF: 8 pages
Proc. SPIE 10140, Medical Imaging 2017: Digital Pathology, 101400C (1 March 2017); doi: 10.1117/12.2254452
Show Author Affiliations
Bassem Ben Cheikh, Sorbonne Univ., UPMC Univ Paris 06, INSERM, CNRS (France)
Catherine Bor-Angelier, UNICANCER (France)
Daniel Racoceanu, Sorbonne Univ., UPMC Univ Paris 06, INSERM, CNRS (France)
Pontifical Catholic Univ. of Peru (Peru)

Published in SPIE Proceedings Vol. 10140:
Medical Imaging 2017: Digital Pathology
Metin N. Gurcan; John E. Tomaszewski, Editor(s)

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