1
|
Zhan M, Li F, Zhu Y, Ma J, Landua J, Wei W, Vadakkan T, Zhang M, Dickinson M, Lewis M, Rosen J, Wong S. Abstract P4-02-08: Quantitative Characterization of 3D Vasculature Spatial Patterns Within Tumor Microenvironment of Breast Cancer Stem Cells. Cancer Res 2012. [DOI: 10.1158/0008-5472.sabcs12-p4-02-08] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
The sustainment characters of cancer stem cells (CSCs) such as self-renew and differentiation to other tumor cells greatly depend on the tumor microenvironment, which is composed of many components, e.g. vasculature, extracellular matrix, epithelial cells, stromal cells, as well as nutrients and oxygen. As vasculature is an important factor for the CSC and tumor development, the understanding of their spatial patterns is essential for calibrating the CSC-microenvironment interactions in mathematical modeling. In this study, we acquired the vasculature in side tumors and normal breast tissues by using two-photon fluorescence microscopy, which enables 3D in vivo imaging. We developed an advanced vasculature segmentation approach for an objective and accurate quantification of the vasculature in 3D image volumes. The approach integrates supervoxel analysis and the orientation guided hidden Markov random field (ori-HMRF) modeling together to compensate for low quality images, e.g., low signal-to-noise ratio (SNR) and uneven background. By constructing a new feature space that combines the CIELAB color space and the coordinates space, the supervoxel analysis divides an image volume into subregions with local similar intensity and restricted regular shape, boundaries of which can delineate the vasculature boundaries accurately even in low intensity contrast regions. We further designed a set of features for the separation of blood vessel regions from the background. To make use of the context information, i.e. the continuity of vasculature, the ori-HMRF model is used to incorporate the consistency of vasculatures' orientation in order to reduce the false positives and negatives. Experimental results on image volumes from both breast cancer and normal breast tissues show that the proposed method can effectively reconstruct the vasculature structure with the CSC embedded tumor microenvironment.
Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr P4-02-08.
Collapse
Affiliation(s)
- M Zhan
- NCI Center for Modeling Cancer Development, The Methodist Hospital, Houston, TX; Baylor College of Medicine, Houston, TX
| | - F Li
- NCI Center for Modeling Cancer Development, The Methodist Hospital, Houston, TX; Baylor College of Medicine, Houston, TX
| | - Y Zhu
- NCI Center for Modeling Cancer Development, The Methodist Hospital, Houston, TX; Baylor College of Medicine, Houston, TX
| | - J Ma
- NCI Center for Modeling Cancer Development, The Methodist Hospital, Houston, TX; Baylor College of Medicine, Houston, TX
| | - J Landua
- NCI Center for Modeling Cancer Development, The Methodist Hospital, Houston, TX; Baylor College of Medicine, Houston, TX
| | - W Wei
- NCI Center for Modeling Cancer Development, The Methodist Hospital, Houston, TX; Baylor College of Medicine, Houston, TX
| | - T Vadakkan
- NCI Center for Modeling Cancer Development, The Methodist Hospital, Houston, TX; Baylor College of Medicine, Houston, TX
| | - M Zhang
- NCI Center for Modeling Cancer Development, The Methodist Hospital, Houston, TX; Baylor College of Medicine, Houston, TX
| | - M Dickinson
- NCI Center for Modeling Cancer Development, The Methodist Hospital, Houston, TX; Baylor College of Medicine, Houston, TX
| | - M Lewis
- NCI Center for Modeling Cancer Development, The Methodist Hospital, Houston, TX; Baylor College of Medicine, Houston, TX
| | - J Rosen
- NCI Center for Modeling Cancer Development, The Methodist Hospital, Houston, TX; Baylor College of Medicine, Houston, TX
| | - S Wong
- NCI Center for Modeling Cancer Development, The Methodist Hospital, Houston, TX; Baylor College of Medicine, Houston, TX
| |
Collapse
|