PROCEEDINGS ARTICLE | March 22, 2016
Proc. SPIE. 9783, Medical Imaging 2016: Physics of Medical Imaging
KEYWORDS: Breast, Modeling, Breast cancer, Pathology, Particles, Feature extraction, Monte Carlo methods, Solids, Fractal analysis, Reconstruction algorithms, Simulation of CCA and DLA aggregates, Digital breast tomosynthesis, Breast imaging, Clinical trials
Virtual clinical trials are a promising new approach increasingly used for the evaluation and comparison of breast
imaging modalities. A key component in such an assessment paradigm is the use of simulated pathology, in particular,
simulation of lesions. Breast mass lesions can be generally classified into two categories based on their appearance; nonspiculated
masses and spiculated masses. In our previous work, we have successfully simulated non-spiculated masses
using a fractal growth process known as diffusion limited aggregation. In this new work, we have extended the DLA
model to simulate spiculated lesions by using features extracted from patient DBT images containing spiculated lesions.
The features extracted included spicule length, width, curvature and distribution. This information was used to simulate
realistic looking spicules which were attached to the surface of a DLA mass to produce a spiculated mass. A batch of
simulated spiculated masses was inserted into normal patient images and presented to an experienced radiologist for
review. The study yielded promising results with the radiologist rating 60% of simulated lesions in 2D and 50% of
simulated lesions in DBT as realistic.
