Oliver Diaz

Image simulation and a model of noise power spectra across a range of mammographic beam qualities.

PURPOSE The aim of this work is to create a model to predict the noise power spectra (NPS) for a range of mammographic radiographic factors. The noise model was necessary to degrade images acquired on one system to match the image quality of different systems for a range of beam qualities. METHODS Five detectors and x-ray systems [Hologic Selenia (ASEh), Carestream computed radiography CR900 (CRc), GE Essential (CSI), Carestream NIP (NIPc), and Siemens Inspiration (ASEs)] were characterized for this study. The signal transfer property was measured as the pixel value against absorbed energy per unit area (E) at a reference beam quality of 28 kV, Mo/Mo or 29 kV, W/Rh with 45 mm polymethyl methacrylate (PMMA) at the tube head. The contributions of the three noise sources (electronic, quantum, and structure) to the NPS were calculated by fitting a quadratic at each spatial frequency of the NPS against E. A quantum noise correction factor which was dependent on beam quality was quantified using a set of images acquired over a range of radiographic factors with different thicknesses of PMMA. The noise model was tested for images acquired at 26 kV, Mo/Mo with 20 mm PMMA and 34 kV, Mo/Rh with 70 mm PMMA for three detectors (ASEh, CRc, and CSI) over a range of exposures. The NPS were modeled with and without the noise correction factor and compared with the measured NPS. A previous method for adapting an image to appear as if acquired on a different system was modified to allow the reference beam quality to be different from the beam quality of the image. The method was validated by adapting the ASEh flat field images with two thicknesses of PMMA (20 and 70 mm) to appear with the imaging characteristics of the CSI and CRc systems. RESULTS The quantum noise correction factor rises with higher beam qualities, except for CR systems at high spatial frequencies, where a flat response was found against mean photon energy. This is due to the dominance of secondary quantum noise in CR. The use of the quantum noise correction factor reduced the difference from the model to the real NPS to generally within 4%. The use of the quantum noise correction improved the conversion of ASEh image to CRc image but had no difference for the conversion to CSI images. CONCLUSIONS A practical method for estimating the NPS at any dose and over a range of beam qualities for mammography has been demonstrated. The noise model was incorporated into a methodology for converting an image to appear as if acquired on a different detector. The method can now be extended to work for a wide range of beam qualities and can be applied to the conversion of mammograms.

Simulation and assessment of realistic breast lesions using fractal growth models

A new method of generating realistic three dimensional simulated breast lesions known as diffusion limited aggregation (DLA) is presented, and compared with the random walk (RW) method. Both methods of lesion simulation utilize a physics-based method for inserting these simulated lesions into 2D clinical mammogram images that takes into account the polychromatic x-ray spectrum, local glandularity and scatter. DLA and RW masses were assessed for realism via a receiver operating characteristic (ROC) study with nine observers. The study comprised 150 images of which 50 were real pathology proven mammograms, 50 were normal mammograms with RW inserted masses and 50 were normal mammograms with DLA inserted masses. The average area under the ROC curve for the DLA method was 0.55 (95% confidence interval 0.51-0.59) compared to 0.60 (95% confidence interval 0.56-0.63) for the RW method. The observer study results suggest that the DLA method produced more realistic masses with more variability in shape compared to the RW method. DLA generated lesions can overcome the lack of complexity in structure and shape in many current methods of mass simulation.

A fast scatter field estimator for digital breast tomosynthesis

Digital breast tomosynthesis (DBT) is a promising alternative approach to overcome the limitations of tissue superposition found in full-field 2D digital mammography. However, due to the absence of anti-scatter grids in DBT, accurate scatter estimation for each projection is necessary for modelling the image reconstruction stage. In this work we identify the limitations associated with scatter estimation using spatial invariant scatter kernels, in particular at the edge region where such methods result in scatter overestimation. Such approaches show an overestimation of scatter-to-primary ratio of over 50% at the edges when compared with results from direct Monte Carlo simulation. This problem was found to increase with projection angle. Simulation work presented here shows that this overestimation in scatter is largely due to air gap between the lower curved breast edge and the detector. We propose a new fast, accurate scatter field estimator for use in DBT which not only considers the breast thickness and primary incidence angle, but also accounts for scatter exiting the breast edge region and traversing an air gap prior to absorption in the detector. The new proposed scatter estimator represents an alternative approach to this problem which reduces discrepancies at the edge of a breast phantom. Moreover, the time required for generating scatter has dropped from approximately 12 hours using Monte Carlo simulations for 1010 photons to just a few minutes per projection. The insertion of scatter from the compression paddle to aforementioned methodologies is also discussed.

Radiation hardness of a large area CMOS active pixel sensor for bio-medical applications

A wafer scale CMOS Active Pixel Sensor has been designed employing design techniques of transistor enclosed geometry and P+ doped guard rings to offer ionizing radiation tolerance. The detector was irradiated with 160 kVp X-rays up to a total dose of 94 kGy(Si) and remained functional. The radiation damage produced in the device has been studied, resulting in a dark current density increase per decade of 96±S pA/cm2/decade and a damage threshold of 204 Gy(Si). The damage produced in the detector has been compared with a commercially available CMOS APS, showing a radiation tolerance about 100 times higher. Moreover Monte Carlo simulations have been performed to evaluate primary and secondary energy deposition in each of the detector stages.

Monte carlo simulation of scatter field for calculation of contrast of discs in synthetic CDMAM images

This paper reports on a further development of an image simulation chain, and in particular, the inclusion of contrast degradation across an image using scatter to primary ratios calculated using Monte Carlo simulation The Monte Carlo technique, using the Geant4 toolkit, has been implemented to model the scatter conditions when imaging the CDMAM phantom with commercial digital mammography Observed differences between linear and cellular anti scatter grid are presented and discussed These results support previous assumptions taken by Yip et al.[1].

Realistic simulation of breast mass appearance using random walk

The aim of the present work was to develop a method for simulating breast lesions in digital mammographic images. Based on the visual appearance of real masses, three dimensional masses were created using a 3D random walk method where the choice of parameters (number of walks and number of steps) enables one to control the appearance of the simulated structure. This work is the first occasion that the random walk results have been combined with a model of digital mammographic imaging systems. This model takes into account appropriate physical image acquisition processes representing a particular digital X-ray mammography system. The X-ray spectrum, local glandularity above the insertion site and scatter were all taken account during the insertion procedure. A preliminary observer study was used to validate the realism of the masses. Seven expert readers each viewed 60 full field mammograms and rated the realism of the masses they contained. Half of the images contained real, histologically-confirmed masses, and half contained simulated lesions. The ROC analysis of the study (average AUC of 0.58±0.06) suggests that, on the average, there is evidence that the radiologists could distinguish, somewhat, between real and simulated masses.

Simulation of 3D DLA masses in digital breast tomosynthesis

Digital breast tomosynthesis (DBT) is suggested to have superior performance compared to 2D mammography in terms of cancer visibility, especially in the case of dense breasts. However, the overall performance of tomosynthesis for screening applications, and the manner in which tomosynthesis should be optimally used for screening remains unclear. This motivates the development of software tools that can insert user-defined synthetic pathology of realistic appearance into clinical tomosynthesis images for subsequent use in virtual clinical trials. We present a method for inserting lesions grown using Diffusion Limited Aggregation, previously validated in 2D mammograms, into clinical DBT images. A preliminary pilot study was used to validate the realism of the masses, wherein three readers each viewed 19 cases and rated the realism of the inserted masses. Each case included a simulated mass inserted in the tomosynthesis projections and the counterpart digital 2D mammogram. These results show that masses can be successfully embedded in the tomosynthesis projections and can produce visually authentic DBT images containing synthetic pathology. These results will be used to further optimize the appearance of these masses in DBT for an upcoming validation.

A modelling framework for evaluation of 2d-mammography and breast tomosynthesis systems

Planar 2D X-ray mammography is the most common screening technique used for breast cancer detection. Digital breast tomosynthesis (DBT) is a new and emerging technology that overcomes some of the limitations of conventional planar imaging. However, it is important to understand the impact of these two modalities on cancer detection rates and patient recall. Since it is difficult to adequately evaluate different modalities clinically, a collection of modeling tools is introduced in this paper that can be used to emulate the image acquisition process for both modalities. In this paper, we discuss image simulation chains that can be used for the evaluation of 2D-mammography and DBT systems in terms of both technical factors and observer studies.

Local breast density assessment using reacquired mammographic images

PURPOSE The aim of this paper is to evaluate the spatial glandular volumetric tissue distribution as well as the density measures provided by Volpara™ using a dataset composed of repeated pairs of mammograms, where each pair was acquired in a short time frame and in a slightly changed position of the breast. MATERIALS AND METHODS We conducted a retrospective analysis of 99 pairs of repeatedly acquired full-field digital mammograms from 99 different patients. The commercial software Volpara™ Density Maps (Volpara Solutions, Wellington, New Zealand) is used to estimate both the global and the local glandular tissue distribution in each image. The global measures provided by Volpara™, such as breast volume, volume of glandular tissue, and volumetric breast density are compared between the two acquisitions. The evaluation of the local glandular information is performed using histogram similarity metrics, such as intersection and correlation, and local measures, such as statistics from the difference image and local gradient correlation measures. RESULTS Global measures showed a high correlation (breast volume R=0.99, volume of glandular tissue R=0.94, and volumetric breast density R=0.96) regardless the anode/filter material. Similarly, histogram intersection and correlation metric showed that, for each pair, the images share a high degree of information. Regarding the local distribution of glandular tissue, small changes in the angle of view do not yield significant differences in the glandular pattern, whilst changes in the breast thickness between both acquisition affect the spatial parenchymal distribution. CONCLUSIONS This study indicates that Volpara™ Density Maps is reliable in estimating the local glandular tissue distribution and can be used for its assessment and follow-up. Volpara™ Density Maps is robust to small variations of the acquisition angle and to the beam energy, although divergences arise due to different breast compression conditions.

Modeling realistic breast lesions using diffusion limited aggregation

Synthesizing the appearance of malignant masses and inserting these into digital mammograms can be used as part of a wider framework for investigating the radiological detection task in X-ray mammography. However, the randomness associated with cell division within cancerous masses and the associated complex morphology challenges the realism of the modeling process. In this paper, Diffusion Limited Aggregation (DLA), a type of fractal growth process is proposed and utilized for modeling breast lesions. Masses of different sizes, shapes and densities were grown by controlling DLA growth parameters either prior to growth, or dynamically updating these during growth. A validation study was conducted by presenting 30 real and 30 simulated masses in a random order to a team of radiologists. The results from the validation study suggest that the observers found it difficult to differentiate between the real and simulated lesions.