Publication: Stochastic modeling of tissue microstructure for high-frequency ultrasound imaging simulations
All || By Area || By Year| Title | Stochastic modeling of tissue microstructure for high-frequency ultrasound imaging simulations | Authors/Editors* | M.I. Daoud, J.C. Lacefield |
|---|---|
| Where published* | Proc. SPIE |
| How published* | Proceedings |
| Year* | 2009 |
| Volume | 7262 |
| Number | |
| Pages | 72620P-1 - 72620P-9 |
| Publisher | SPIE |
| Keywords | High-frequency ultrasound, tissue microstructure, cancer imaging, small animal imaging, Gibbs- Markov point process, stereology |
| Link | http://dx.doi.org/10.1117/12.812938 |
| Abstract |
High-frequency (> 20 MHz) ultrasound images of preclinical tumor models are sensitive to changes in tissue microstructure that accompany tumor progression and treatment responses, but the relationships between tumor microanatomy and high-frequency ultrasound backscattering are incompletely understood. Computational models of tissue microstructure can be employed with ultrasound propagation simulators to investigate these relationships. This paper introduces a three-dimensional microanatomical model in which tissue is treated as a population of stochastically positioned spherical cells embedded in a homogeneous extracellular matrix, where each cell consists of a spherical nucleus surrounded by homogeneous cytoplasm. The model is used to represent the microstructure of both healthy mouse liver and experimental liver metastasis. Normal and cancerous tissue specimens stained with DAPI and H&E are digitized at 20Ã magnification and analyzed to specify values of the model parameters. Simulated healthy and tumor tissues are initialized based on the ratio of cell to nucleus diameter and the nuclear volume fraction and size distribution estimated by stereological analysis of the normal and cancerous liver specimens, respectively. For each simulated tissue, the spatial organization of cells is controlled by a Gibbs-Markov point process. The parameters of the Gibbs-Markov process are tuned to accurately reproduce the number density and distribution of center-to-center spacing of nuclei in the DAPI-stained slides of the corresponding experimental tissue specimen. The morphological variations that can be produced by changing the model parameters are expected to be sufficient to represent the microstructural changes during tumor progression that are the most significant determinants of high-frequency ultrasound backscattering. |
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