Anders Tingberg

Steadily increasing use of computer-generated models sets high demands on the realistic representation of breast tissue and abnormalities. Previously, we demonstrated the use of Perlin noise to simulate breast lesions. Now, we expand the previous model by simulating heterogeneous lesion composition. We demonstrate a new approach to simulating 3D soft tissue lesions, with additional benefits of Perlin noise in the context of virtual clinical trials. Three simulation methods have been developed: Method I represents a homogeneous lesion made up of glandular tissue (our previous model). Method II utilizes an Euclidian distance transformation to provide a layered shell construction. In Method III we assign a range of weighting functions to achieve several progressively smaller lesion volumes (“shells”). For Methods II and III, details of the background tissue were preserved within the lesion, and higher attenuation was assigned, compared to the background tissue. In a preliminary evaluation, three radiologists gave their expert opinions on the reconstructed DBT slices of the three lesions generated with Method I-III. Methods II and III proved capable of generating lesions with complex composition. For Method II the lesion appeared blended with the background tissue, whilst the lesion generated from Method III had new internal structures resembling neoplastic regions within the lesion. There was a consensus among the radiologists that the lesion in Method III looked most realistic, due to its slightly more spiculated and heterogeneous appearance, compared to Methods I and II. Optimization of the simulation methods is ongoing.