Methodology based on genetic heuristics for in-vivo characterizing the patient-specific biomechanical behavior of the breast tissues.

This paper presents a novel methodology to in-vivo estimate the elastic constants of a constitutive model proposed to characterize the mechanical behavior of the breast tissues. An iterative search algorithm based on genetic heuristics was constructed to in-vivo estimate these parameters using only medical images, thus avoiding invasive measurements of the mechanical response of the breast tissues. For the first time, a combination of overlap and distance coefficients were used for the evaluation of the similarity between a deformed MRI of the breast and a simulation of that deformation. The methodology was validated using breast software phantoms for virtual clinical trials, compressed to mimic MRI-guided biopsies. The biomechanical model chosen to characterize the breast tissues was an anisotropic neo-Hookean hyperelastic model. Results from this analysis showed that the algorithm is able to find the elastic constants of the constitutive equations of the proposed model with a mean relative error of about 10%. Furthermore, the overlap between the reference deformation and the simulated deformation was of around 95% showing the good performance of the proposed methodology. This methodology can be easily extended to characterize the real biomechanical behavior of the breast tissues, which means a great novelty in the field of the simulation of the breast behavior for applications such as surgical planing, surgical guidance or cancer diagnosis. This reveals the impact and relevance of the presented work.

Breast dosimetry using high-resolution voxel phantoms.

A computer model of X-ray mammography has been developed, which uses quasi-realistic high-resolution voxel phantoms to simulate the breast. The phantoms have 400 microm voxels and simulate the three-dimensional distributions of adipose and fibro-glandular tissues, Cooper's ligaments, ducts and skin and allow the estimation of dose to individual tissues. Calculations of the incident air kerma to mean glandular dose conversion factor, g, were made using a Mo/Mo spectrum at 28 kV for eight phantoms in the thickness range 40-80 mm and of varying glandularity. The values differed from standard tabulations used for breast dosimetry by up to 43%, because of the different spatial distribution of glandular tissue within the breast. To study this further, additional voxel phantoms were constructed, which gave variations of between 9 and 59% compared with standard values. For accurate breast dosimetry, it is therefore very important to take the distribution of glandular tissues into account.

Calculation of the properties of digital mammograms using a computer simulation.

A Monte Carlo computer model of mammography has been developed to study and optimise the performance of digital mammographic systems. The program uses high-resolution voxel phantoms to model the breast, which simulate the adipose and fibroglandular tissues, Cooper's ligaments, ducts and skin in three dimensions. The model calculates the dose to each tissue, and also the quantities such as energy imparted to image pixels, noise per image pixel and scatter-to-primary (S/P) ratios. It allows studies of the dependence of image properties on breast structure and on position within the image. The program has been calibrated by calculating and measuring the pixel values and noise for a digital mammographic system. The thicknesses of two components of this system were unknown, and were adjusted to obtain a good agreement between measurement and calculation. The utility of the program is demonstrated with the calculations of the variation of the S/P ratio with and without a grid, and of the image contrast across the image of a 50-mm-thick breast phantom.

Estimation of scattered radiation in digital breast tomosynthesis.

Digital breast tomosynthesis (DBT) is a promising technique to overcome the tissue superposition limitations found in planar 2D x-ray mammography. However, as most DBT systems do not employ an anti-scatter grid, the levels of scattered radiation recorded within the image receptor are significantly higher than that observed in planar 2D x-ray mammography. Knowledge of this field is necessary as part of any correction scheme and for computer modelling and optimisation of this examination. Monte Carlo (MC) simulations are often used for this purpose, however they are computationally expensive and a more rapid method of calculation is desirable. This issue is addressed in this work by the development of a fast kernel-based methodology for scatter field estimation using a detailed realistic DBT geometry. Thickness-dependent scatter kernels, which were validated against the literature with a maximum discrepancy of 4% for an idealised geometry, have been calculated and a new physical parameter (air gap distance) was used to estimate more accurately the distribution of scattered radiation for a series of anthropomorphic breast phantom models. The proposed methodology considers, for the first time, the effects of scattered radiation from the compression paddle and breast support plate, which can represent more than 30% of the total scattered radiation recorded within the image receptor. The results show that the scatter field estimator can calculate scattered radiation images in an average of 80 min for projection angles up to 25° with equal to or less than a 10% error across most of the breast area when compared with direct MC simulations.