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Digital breast tomosynthesis is an extension of digital mammography that produces quasi three-dimensional reconstructed images from a set of low-dose x-ray projections acquired over a limited angular range. The quality of the reconstructed image and the dose to the breast are dependent on the angular range and number of projections, the dose used per projection, and detector resolution and noise characteristics. This article discusses various aspects of tomosynthesis optimization., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Purpose: Power spectral analysis in radiographic images is conventionally performed using a windowed overlapping averaging periodogram. This study describes an alternative approach using a multitaper technique and compares its performance with that of the standard method. This tool will be valuable in power spectrum estimation of images, whose content deviates significantly from uniform white noise. The performance of the multitaper approach will be evaluated in terms of spectral stability, variance reduction, bias, and frequency precision. The ultimate goal is the development of a useful tool for image quality assurance., Methods: A multitaper approach uses successive data windows of increasing order. This mitigates spectral leakage allowing one to calculate a reduced-variance power spectrum. The multitaper approach will be compared with the conventional power spectrum method in several typical situations, including the noise power spectra (NPS) measurements of simulated projection images of a uniform phantom, NPS measurement of real detector images of a uniform phantom for two clinical digital mammography systems, and the estimation of the anatomic noise in mammographic images (simulated images and clinical mammograms)., Results: Examination of spectrum variance versus frequency resolution and bias indicates that the multitaper approach is superior to the conventional single taper methods in the prevention of spectrum leakage and variance reduction. More than four times finer frequency precision can be achieved with equivalent or less variance and bias., Conclusions: Without any shortening of the image data length, the bias is smaller and the frequency resolution is higher with the multitaper method, and the need to compromise in the choice of regions of interest size to balance between the reduction of variance and the loss of frequency resolution is largely eliminated.

Digital breast tomosynthesis uses a limited number (typically 10-20) of low-dose x-ray projections to produce a pseudo-three-dimensional volume tomographic reconstruction of the breast. The purpose of this investigation was to characterize and evaluate the effect of scattered radiation on the image quality for breast tomosynthesis. In a simulation, scatter point spread functions generated by a Monte Carlo simulation method were convolved over the breast projection to estimate the distribution of scatter for each angle of tomosynthesis projection. The results demonstrate that in the absence of scatter reduction techniques, images will be affected by cupping artifacts, and there will be reduced accuracy of attenuation values inferred from the reconstructed images. The effect of x-ray scatter on the contrast, noise, and lesion signal-difference-to-noise ratio (SDNR) in tomosynthesis reconstruction was measured as a function of the tumor size. When a with-scatter reconstruction was compared to one without scatter for a 5 cm compressed breast, the following results were observed. The contrast in the reconstructed central slice image of a tumorlike mass (14 mm in diameter) was reduced by 30%, the voxel value (inferred attenuation coefficient) was reduced by 28%, and the SDNR fell by 60%. The authors have quantified the degree to which scatter degrades the image quality over a wide range of parameters relevant to breast tomosynthesis, including x-ray beam energy, breast thickness, breast diameter, and breast composition. They also demonstrate, though, that even without a scatter rejection device, the contrast and SDNR in the reconstructed tomosynthesis slice are higher than those of conventional mammographic projection images acquired with a grid at an equivalent total exposure.

Blocking layers are used to reduce leakage current in amorphous selenium detectors. The effect of the thickness of the blocking layer on the presampling modulation transfer function (MTF) and on dark current was experimentally determined in prototype single-line CCD-based amorphous selenium (a-Se) x-ray detectors. The sampling pitch of the detectors evaluated was 25 microm and the blocking layer thicknesses varied from 1 to 51 microm. The blocking layers resided on the signal collection electrodes which, in this configuration, were used to collect electrons. The combined thickness of the blocking layer and a-Se bulk in each detector was approximately 200 microm. As expected, the dark current increased monotonically as the thickness of the blocking layer was decreased. It was found that if the blocking layer thickness was small compared to the sampling pitch, it caused a negligible reduction in MTF. However, the MTF was observed to decrease dramatically at spatial frequencies near the Nyquist frequency as the blocking layer thickness approached or exceeded the electrode sampling pitch. This observed reduction in MTF is shown to be consistent with predictions of an electrostatic model wherein the image charge from the a-Se is trapped at a characteristic depth within the blocking layer, generally near the interface between the blocking layer and the a-Se bulk.

Oblique incidence of x rays on an imaging detector causes blurring that reduces spatial resolution. For simple projection imaging this effect is small and often ignored. However, for breast tomosynthesis, the incidence angle can be larger (>20 degrees), leading to increased blur for some of the projections. The modulation transfer function (MTF) is measured for a typical phosphor-coupled flat-panel detector versus angular incidence of the x-ray beam for two x-ray spectra: 26 kV Mo/Mo and 40 kV Rh/Al. At an incidence angle of 40 degrees the MTF at 5 mm(-1) falls by 35% and 40% for each spectrum, respectively (and 65%/80% at 8 mm(-1)). Increasing the detector absorber thickness to achieve improved quantum efficiency will cause the blurring effect due to beam obliquity to become greater. The impact of this blur is likely to cause misregistration and increased relative noise in tomosynthesis reconstructed images.

This paper on digital mammography image acquisition is 1 of 3 papers written as part of an intersociety effort to establish image quality standards for digital mammography. The information included in this paper is intended to support the development of an ACR guideline on image quality for digital mammography. The topics of the other 2 papers are digital mammography image display and digital mammography image storage, transmission, and retrieval. The societies represented in compiling this document were the Radiological Society of North America, the ACR, the American Association of Physicists in Medicine, and the Society for Computer Applications in Radiology. These papers describe in detail what is known to improve image quality for digital mammography and make recommendations about how digital mammography should be performed to optimize the visualization of breast cancers. Through the publication of these papers, the ACR is seeking input from industry, radiologists, and other interested parties on their contents so that the final ACR guideline for digital mammography will represent the consensus of the broader community interested in these topics.

A pulse-height spectroscopic technique is used to measure the linear attenuation coefficients of commercially available composite phantom materials designed to simulate the attenuation characteristics of breast fat and breast glandular tissue. The manufacturers have specified the composition of these materials with the goal of matching the linear attenuation coefficients of breast tissues, calculated using the mixture rule. Over the energy range 18 to 100 keV, measurements from these materials are in close agreement with manufacturers' predictions and with previously measured linear attenuation coefficients of breast tissue samples.

Mammographic parenchymal patterns are among the strongest indicators of the risk of developing breast cancer. Risk evaluation through breast patterns may have an important role in studies of the aetiology of breast cancer and for monitoring changes in the breast in evaluating potential risk-modifying interventions. Typically, patterns are assessed by an experienced radiologist according to Wolfe grade, or on a coarse quantitative scale according to percent density. Parenchymal characterization methods, to overcome variability of classification by human observer, are under investigation. These include image segmentation using semi-automatic thresholding and automatic classification through textural and density measures. An important practical question relates to the extent to which information about mammographic pattern is carried by any one of the four views obtained in a typical examination. Specifically, variations of right-left breast symmetry and variations between the two standard views of each breast were tested. The mammograms of 30 premenopausal women, comprising 90 images [30 each of the right cranial-caudal (RCC), left cranial-caudal (LCC) and right medial-lateral oblique (RMLO)] were evaluated. Parameters included both subjective (radiologist classification and interactive image thresholding) and objective (fractal and skewness indices) quantitative measurements of parenchymal pattern. For the parameters tested, a high degree of correlations was observed for measurements on the RCC, LCC and RMLO views. Pearson correlation coefficients between 0.86-0.96 were found for the comparisons of quantitative parameters. The strong correlations suggest that, in the study and application of mammographic density classification, representative information is provided in a single view.

Information derived from mammographic parenchymal patterns provides one of the strongest indicators of the risk of developing breast cancer. To address several limitations of subjective classification of mammographic parenchyma into coarse density categories, we have been investigating more quantitative, objective methods of analysing the film-screen mammogram. These include measures of the skewness of the image brightness histogram, and of image texture characterized by the fractal dimension. Both measures were found to be strongly correlated with radiologists' subjective classifications of mammographic parenchyma (Spearman correlation coefficients, Rs = -0.88 and -0.76 for skewness and fractal dimension measurements, respectively). Further, neither measure was strongly dependent on simulated changes in mammographic technique. Correlation with subjective classification of mammographic density was better when both the skewness and fractal measures were used in combination than when either was used alone. This suggests that each feature provides some independent information.

Film-screen x-ray mammography is an effective tool for the detection and diagnosis of breast cancer. Several limitations of current mammographic technology have been identified, and there is now good evidence that improved image quality and possibly reduced radiation dose could be achieved if mammograms are acquired directly in digital form. In this article, the rationale for digital mammography is presented and various approaches to the design of a digital mammography system are described. Current challenges in developing a practical, clinically acceptable digital mammography system are discussed and applications of digital mammography to computer-aided diagnosis, telemammography, and quantitative imaging are suggested.

Quantitative classification of mammographic parenchyma based on radiological assessment has been shown to provide one of the strongest estimates of the risk of developing breast cancer. Existing classification schemes, however, are limited by coarse category scales. In addition, subjectivity can lead to sizeable interobserver and intraobserver variations. Here, we propose an interactive thresholding technique applied to digitized film-screen mammograms, which assesses the proportion of the mammographic image representing radiographically dense tissue. Observers viewed images on a CRT display and selected grey-level thresholds from which the breast and regions of dense tissue in the breast were identified. The proportion of radiographic density was then calculated from the image histogram. The technique was evaluated for the mammograms of 30 women and is well correlated (R > 0.91, Spearman coefficient) with a six-category subjective classification of radiographic density by radiologists. The technique was found to be very reliable with an intraclass correlation coefficient between observers typically R > 0.9. This technique may have a role in routine mammographic analysis for the purpose of assessing risk categories and as a tool in studies of the etiology of breast cancer, in particular for monitoring changes in breast parenchyma during potential preventive interventions.