Development of a 3D model of clinically relevant microcalcifications

A realistic 3D anthropomorphic software model of microcalcifications may serve as a useful tool to assess the performance of breast imaging applications through simulations. We present a method allowing to simulate visually realistic microcalcifications with large morphological variability. Principal component analysis (PCA) was used to analyze the shape of 281 biopsied microcalcifications imaged with a micro-CT. The PCA analysis requires the same number of shape components for each input microcalcification. Therefore, the voxel-based microcalcifications were converted to a surface mesh with same number of vertices using a marching cube algorithm. The vertices were registered using an iterative closest point algorithm and a simulated annealing algorithm. To evaluate the approach, input microcalcifications were reconstructed by progressively adding principal components. Input and reconstructed microcalcifications were visually and quantitatively compared. New microcalcifications were simulated using randomly sampled principal components determined from the PCA applied to the input microcalcifications, and their realism was appreciated through visual assessment. Preliminary results have shown that input microcalcifications can be reconstructed with high visual fidelity when using 62 principal components, representing 99.5% variance. For that condition, the average L2 norm and dice coefficient were respectively 10.5 $\mu$m and 0.93. Newly generated microcalcifications with 62 principal components were found to be visually similar, while not identical, to input microcalcifications. The proposed PCA model of microcalcification shapes allows to successfully reconstruct input microcalcifications and to generate new visually realistic microcalcifications with various morphologies.

Breast shape estimation and correction in CESM biopsy

Description of purpose: Contrast-enhanced spectral mammography can be used to guide needle biopsies. However, in vertical approach the compressed breast is deformed generating a so-called bump in the paddle aperture, which may interfere with the visibility of contrast-uptakes. Local thickness estimation would provide an enhanced image quality of the recombined image, increasing the visibility of the contrast-uptakes to be targeted during the biopsy procedure. In this work we propose a method to estimate the shape of the breast bump in biopsy vertical approach. Materials and Methods: Our method consists on two steps: first, we compute a raw thickness which does not take into account the presence of contrast-uptakes; second, we use a physical model to separate the sparse iodine texture from the breast shape. This physical model is composed by a sum of Fourier components, describing the main shape of the bump, a series of low-order polynomials, describing the main compressed thickness, paddle tilt and deflection, and non-linear components describing the translation and rotation of the paddle aperture. A 3D object mimicking a bump was fabricated to test the pertinence of our shape model. Also, clinical images of 21 patients which followed CESM-guided biopsy were visually assessed. Results: Comparison between raw and final estimated thickness of our 3D test object shows an error standard deviation of 0.37 mm similar to the noise standard deviation equals to 0.32 mm. The visual assessment of clinical cases showed that the thickness correction removes the superimposed low-frequency pattern due to non-uniform thickness of the bump, improving the identification of the lesion to be targeted. Conclusion: The proposed method for thickness estimation is adapted to CESM-guided biopsies in vertical approach and it improves the identification of the contrast-uptakes that need to be targeted during the procedure.