X-ray characterisation of normal and neoplastic breast tissues

A method to estimate the fractional fat volume within a ROI of a breast biopsy for WAXS applications: animal tissue evaluation

PURPOSE

To develop a method to estimate the mean fractional volume of fat (ν¯fat) within a region of interest (ROI) of a tissue sample for wide-angle x-ray scatter (WAXS) applications. A scatter signal from the ROI was obtained and use of ν¯fat in a WAXS fat subtraction model provided a way to estimate the differential linear scattering coefficient μs of the remaining fatless tissue.

METHODS

The efficacy of the method was tested using animal tissue from a local butcher shop. Formalin fixed samples, 5 mm in diameter 4 mm thick, were prepared. The two main tissue types were fat and meat (fibrous). Pure as well as composite samples consisting of a mixture of the two tissue types were analyzed. For the latter samples, νfat for the tissue columns of interest were extracted from corresponding pixels in CCD digital x-ray images using a calibration curve. The means ν¯fat were then calculated for use in a WAXS fat subtraction model. For the WAXS measurements, the samples were interrogated with a 2.7 mm diameter 50 kV beam and the 6° scattered photons were detected with a CdTe detector subtending a solid angle of 7.75 × 10(-5) sr. Using the scatter spectrum, an estimate of the incident spectrum, and a scatter model, μs was determined for the tissue in the ROI. For the composite samples, a WAXS fat subtraction model was used to estimate the μs of the fibrous tissue in the ROI. This signal was compared to μs of fibrous tissue obtained using a pure fibrous sample.

RESULTS

For chicken and beef composites, ν¯fat=0.33±0.05 and 0.32 ± 0.05, respectively. The subtractions of these fat components from the WAXS composite signals provided estimates of μs for chicken and beef fibrous tissue. The differences between the estimates and μs of fibrous obtained with a pure sample were calculated as a function of the momentum transfer x. A t-test showed that the mean of the differences did not vary from zero in a statistically significant way thereby validating the methods.

CONCLUSIONS

The methodology to estimate ν¯fat in a ROI of a tissue sample via CCD x-ray imaging was quantitatively accurate. The WAXS fat subtraction model allowed μs of fibrous tissue to be obtained from a ROI which had some fat. The fat estimation method coupled with the WAXS models can be used to compare μs coefficients of fibroglandular and cancerous breast tissue.

Research in digital mammography and tomosynthesis at the University of Toronto

There have been major advances in the field of breast cancer imaging since the early 1970s, both in technological improvements and in the use of the methods of medical physics and image analysis to optimize image quality. The introduction of digital mammography in 2000 provided a marked improvement in imaging of dense breasts. In addition, it became possible to produce tomographic and functional images on modified digital mammography systems. Digital imaging also greatly facilitated the extraction of quantitative information from images. My laboratory has been fortunate in being able to participate in some of these exciting developments. I will highlight some of the areas of our research interest which include modeling of the image formation process, development of high-resolution X-ray detectors for digital mammography and investigating new methods for analyzing image quality. I will also describe our more recent work on developing new applications of digital mammography including tomosynthesis, contrast-enhanced mammography, and measurement of breast density. Finally, I will point to a new area for our research--the application of the techniques of medical imaging to making pathology more quantitative to contribute to use of biomarkers for better characterizing breast cancer and directing therapeutic decisions.

Breast tissue characterization with photon-counting spectral CT imaging: a postmortem breast study

PURPOSE

To investigate the feasibility of breast tissue characterization in terms of water, lipid, and protein contents with a spectral computed tomographic (CT) system based on a cadmium zinc telluride (CZT) photon-counting detector by using postmortem breasts.

MATERIALS AND METHODS

Nineteen pairs of postmortem breasts were imaged with a CZT-based photon-counting spectral CT system with beam energy of 100 kVp. The mean glandular dose was estimated to be in the range of 1.8-2.2 mGy. The images were corrected for pulse pile-up and other artifacts by using spectral distortion corrections. Dual-energy decomposition was then applied to characterize each breast into water, lipid, and protein contents. The precision of the three-compartment characterization was evaluated by comparing the composition of right and left breasts, where the standard error of the estimations was determined. The results of dual-energy decomposition were compared by using averaged root mean square to chemical analysis, which was used as the reference standard.

RESULTS

The standard errors of the estimations of the right-left correlations obtained from spectral CT were 7.4%, 6.7%, and 3.2% for water, lipid, and protein contents, respectively. Compared with the reference standard, the average root mean square error in breast tissue composition was 2.8%.

CONCLUSION

Spectral CT can be used to accurately quantify the water, lipid, and protein contents in breast tissue in a laboratory study by using postmortem specimens.

WAXS fat subtraction model to estimate differential linear scattering coefficients of fatless breast tissue: phantom materials evaluation

PURPOSE

Develop a method to subtract fat tissue contributions to wide-angle x-ray scatter (WAXS) signals of breast biopsies in order to estimate the differential linear scattering coefficients μ(s) of fatless tissue. Cancerous and fibroglandular tissue can then be compared independent of fat content. In this work phantom materials with known compositions were used to test the efficacy of the WAXS subtraction model.

METHODS

Each sample 5 mm in diameter and 5 mm thick was interrogated by a 50 kV 2.7 mm diameter beam for 3 min. A 25 mm(2) by 1 mm thick CdTe detector allowed measurements of a portion of the θ = 6° scattered field. A scatter technique provided means to estimate the incident spectrum N(0)(E) needed in the calculations of μ(s)[x(E, θ)] where x is the momentum transfer argument. Values of [Formula: see text] for composite phantoms consisting of three plastic layers were estimated and compared to the values obtained via the sum [Formula: see text], where ν(i) is the fractional volume of the ith plastic component. Water, polystyrene, and a volume mixture of 0.6 water + 0.4 polystyrene labelled as fibphan were chosen to mimic cancer, fat, and fibroglandular tissue, respectively. A WAXS subtraction model was used to remove the polystyrene signal from tissue composite phantoms so that the μ(s) of water and fibphan could be estimated. Although the composite samples were layered, simulations were performed to test the models under nonlayered conditions.

RESULTS

The well known μ(s) signal of water was reproduced effectively between 0.5 < x < 1.6 nm(-1). The [Formula: see text] obtained for the heterogeneous samples agreed with [Formula: see text]. Polystyrene signals were subtracted successfully from composite phantoms. The simulations validated the usefulness of the WAXS models for nonlayered biopsies.

CONCLUSIONS

The methodology to measure μ(s) of homogeneous samples was quantitatively accurate. Simple WAXS models predicted the probabilities for specific x-ray scattering to occur from heterogeneous biopsies. The fat subtraction model can allow μ(s) signals of breast cancer and fibroglandular tissue to be compared without the effects of fat provided there is an independent measurement of the fat volume fraction ν(f). Future work will consist of devising a quantitative x-ray digital imaging method to estimate ν(f) in ex vivo breast samples.

Diffusion-weighted imaging of the high-risk breast: Apparent diffusion coefficient values and their relationship to breast density

PURPOSE

To document the apparent diffusion coefficient (ADC) of fibroglandular breast tissue in women at high-risk of developing breast cancer and investigate the relationship between ADC and breast density.

MATERIALS AND METHODS

Local research ethics approval was obtained. A total of 33 high-risk women including 17 BRCA1/2 mutation carriers (mean age, 43 years) and 16 women postmantle irradiation (mean age 40 years) underwent diffusion-weighted MRI between days 6 and 16 of their menstrual cycle. ADC histograms from a region of interest in fibroglandular tissue and mammographic breast density measurements were obtained. Mean, percentile ADC values (10th, 25th, 50th, 75th, 90th) and skew were compared for the two groups; ADC and mammographic breast density were correlated.

RESULTS

Mean ADC values (×10(-6) mm(2) /s) were 2017 ± 197 in postmantle irradiated women and 1827 ± 289 in BRCA1/2 mutation carriers (P = 0.035) with significant differences at all percentiles (P < 0.0001) but not skew (P = 0.44). ADC values showed weak positive correlation with mammographic breast density in BRCA1/2 mutation carriers (r = 0.51, P = 0.043) but not in postmantle radiotherapy patients (r = 0.49, P = 0.13).

CONCLUSION

Higher ADC values seen in fibroglandular tissue postmantle irradiation compared with BRCA1/2 mutation carriers has potential to improve tumor detection in these patients. Lack of correlation between ADC and breast density postmantle irradiation may be a result of microstructural changes.

Quantitative breast tissue characterization using grating-based x-ray phase-contrast imaging

X-ray phase-contrast imaging has received growing interest in recent years due to its high capability in visualizing soft tissue. Breast imaging became the focus of particular attention as it is considered the most promising candidate for a first clinical application of this contrast modality. In this study, we investigate quantitative breast tissue characterization using grating-based phase-contrast computed tomography (CT) at conventional polychromatic x-ray sources. Different breast specimens have been scanned at a laboratory phase-contrast imaging setup and were correlated to histopathology. Ascertained tumor types include phylloides tumor, fibroadenoma and infiltrating lobular carcinoma. Identified tissue types comprising adipose, fibroglandular and tumor tissue have been analyzed in terms of phase-contrast Hounsfield units and are compared to high-quality, high-resolution data obtained with monochromatic synchrotron radiation, as well as calculated values based on tabulated tissue properties. The results give a good impression of the method's prospects and limitations for potential tumor detection and the associated demands on such a phase-contrast breast CT system. Furthermore, the evaluated quantitative tissue values serve as a reference for simulations and the design of dedicated phantoms for phase-contrast mammography.

Radiological assessment of breast density by visual classification (BI-RADS) compared to automated volumetric digital software (Quantra): implications for clinical practice

OBJECTIVE

This study was done to assess breast density on digital mammography and digital breast tomosynthesis according to the visual Breast Imaging Reporting and Data System (BI-RADS) classification, to compare visual assessment with Quantra software for automated density measurement, and to establish the role of the software in clinical practice.

MATERIALS AND METHODS

We analysed 200 digital mammograms performed in 2D and 3D modality, 100 of which positive for breast cancer and 100 negative. Radiological density was assessed with the BI-RADS classification; a Quantra density cut-off value was sought on the 2D images only to discriminate between BI-RADS categories 1-2 and BI-RADS 3-4. Breast density was correlated with age, use of hormone therapy, and increased risk of disease.

RESULTS

The agreement between the 2D and 3D assessments of BI-RADS density was high (K 0.96). A cut-off value of 21% is that which allows us to best discriminate between BI-RADS categories 1-2 and 3-4. Breast density was negatively correlated to age (r = -0.44) and positively to use of hormone therapy (p = 0.0004). Quantra density was higher in breasts with cancer than in healthy breasts.

CONCLUSIONS

There is no clear difference between the visual assessments of density on 2D and 3D images. Use of the automated system requires the adoption of a cut-off value (set at 21%) to effectively discriminate BI-RADS 1-2 and 3-4, and could be useful in clinical practice.

Comparative power law analysis of structured breast phantom and patient images in digital mammography and breast tomosynthesis

PURPOSE

This work characterizes three candidate mammography phantoms with structured background in terms of power law analysis in the low frequency region of the power spectrum for 2D (planar) mammography and digital breast tomosynthesis (DBT).

METHODS

The study was performed using three phantoms (spheres in water, Voxmam, and BR3D CIRS phantoms) on two DBT systems from two different vendors (Siemens Inspiration and Hologic Selenia Dimensions). Power spectra (PS) were calculated for planar projection, DBT projection, and reconstructed images and curve fitted in the low frequency region from 0.2 to 0.7 mm(-1) with a power law function characterized by an exponent β and magnitude κ. The influence of acquisition dose and tube voltage on the power law parameters was first explored. Then power law parameters were calculated from images acquired with the same anode∕filter combination and tube voltage for the three test objects, and compared with each other. Finally, PS curves for automatic exposure controlled acquisitions (anode∕filter combination and tube voltages selected by the systems based on the breast equivalent thickness of the test objects) were compared against PS analysis performed on patient data (for Siemens 80 and for Hologic 48 mammograms and DBT series). Dosimetric aspects of the three test objects were also examined.

RESULTS

The power law exponent (β) was found to be independent of acquisition dose for planar mammography but varied more for DBT projections of the sphere-phantom. Systematic increase of tube voltage did not affect β but decreased κ, both in planar and DBT projection phantom images. Power spectra of the BR3D phantom were closer to those of the patients than these of the Voxmam phantom; the Voxmam phantom gave high values of κ compared to the other phantoms and the patient series. The magnitude of the PS curves of the BR3D phantom was within the patient range but β was lower than the average patient value. Finally, PS magnitude for the sphere-phantom coincided with the patient curves for Siemens but was lower for the Hologic system. Close agreement of doses for all three phantoms with patient doses was found.

CONCLUSIONS

Power law parameters of the phantoms were close to those of the patients but no single phantom matched in terms of both magnitude (κ) and texture (β) for the x-ray systems in this work. PS analysis of structured phantoms is feasible and this methodology can be used to suggest improvements in phantom design.

Investigation of energy weighting using an energy discriminating photon counting detector for breast CT

PURPOSE

Breast CT is an emerging imaging technique that can portray the breast in 3D and improve visualization of important diagnostic features. Early clinical studies have suggested that breast CT has sufficient spatial and contrast resolution for accurate detection of masses and microcalcifications in the breast, reducing structural overlap that is often a limiting factor in reading mammographic images. For a number of reasons, image quality in breast CT may be improved by use of an energy resolving photon counting detector. In this study, the authors investigate the improvements in image quality obtained when using energy weighting with an energy resolving photon counting detector as compared to that with a conventional energy integrating detector.

METHODS

Using computer simulation, realistic CT images of multiple breast phantoms were generated. The simulation modeled a prototype breast CT system using an amorphous silicon (a-Si), CsI based energy integrating detector with different x-ray spectra, and a hypothetical, ideal CZT based photon counting detector with capability of energy discrimination. Three biological signals of interest were modeled as spherical lesions and inserted into breast phantoms; hydroxyapatite (HA) to represent microcalcification, infiltrating ductal carcinoma (IDC), and iodine enhanced infiltrating ductal carcinoma (IIDC). Signal-to-noise ratio (SNR) of these three lesions was measured from the CT reconstructions. In addition, a psychophysical study was conducted to evaluate observer performance in detecting microcalcifications embedded into a realistic anthropomorphic breast phantom.

RESULTS

In the energy range tested, improvements in SNR with a photon counting detector using energy weighting was higher (than the energy integrating detector method) by 30%-63% and 4%-34%, for HA and IDC lesions and 12%-30% (with Al filtration) and 32%-38% (with Ce filtration) for the IIDC lesion, respectively. The average area under the receiver operating characteristic curve (AUC) for detection of microcalcifications was higher by greater than 19% (for the different energy weighting methods tested) as compared to the AUC obtained with an energy integrating detector.

CONCLUSIONS

This study showed that breast CT with a CZT photon counting detector using energy weighting can provide improvements in pixel SNR, and detectability of microcalcifications as compared to that with a conventional energy integrating detector. Since a number of degrading physical factors were not modeled into the photon counting detector, this improvement should be considered as an upper bound on achievable performance.

Contrast-enhanced digital mammography

Mammography is the only technology documented to reduce breast cancer mortality. Its sensitivity, however, is 75% to 80% at best and reduced to 30% to 50% in women with dense breasts. MR imaging is a sensitive modality for the detection of breast cancer but cannot be used in all patients. Its sensitivity is due in large part to its ability to detect enhancement of tumor vascularity so cancers can be detected before a mass is present. Contrast-enhanced dual-energy mammography uses the same capability of vascular enhancement and has been demonstrated to be more sensitive than routine mammography.

What effect does mammographic breast density have on lesion detection in digital mammography?

Effective detection of breast cancer using mammography is an important public health issue worldwide. Breasts that contain higher levels of fibroglandular compared with fatty tissue increase breast radio-opacity making it more difficult to differentiate between normal and abnormal findings. The higher prevalence of breast cancer amongst women with denser breasts demands the origination of effective solutions to manage this common radiographic appearance. This brief review considers the impact of higher levels of density on cancer detection and the importance of digital technology in possibly reducing the negative effects of increased density.

Measurement of breast-tissue x-ray attenuation by spectral mammography: first results on cyst fluid

Knowledge of x-ray attenuation is essential for developing and evaluating x-ray imaging technologies. For instance, techniques to better characterize cysts at mammography screening would be highly desirable to reduce recalls, but the development is hampered by the lack of attenuation data for cysts. We have developed a method to measure x-ray attenuation of tissue samples using a prototype photon-counting spectral mammography unit. The method was applied to measure the attenuation of 50 samples of breast cyst fluid and 50 samples of water. Spectral (energy-resolved) images of the samples were acquired and the image signal was mapped to equivalent thicknesses of two known reference materials, which can be used to derive the x-ray attenuation as a function of energy. The attenuation of cyst fluid was found to be significantly different from water. There was a relatively large natural spread between different samples of cyst fluid, whereas the homogeneity of each individual sample was found to be good; the variation within samples did not reach above the quantum noise floor. The spectral method proved stable between several measurements on the same sample. Further, chemical analysis and elemental attenuation calculation were used to validate the spectral measurement on a subset of the samples. The two methods agreed within the precision of the elemental attenuation calculation over the mammographic energy range.

Investigation of mammographic breast density as a risk factor for ovarian cancer

BACKGROUND

Endogenous hormones and growth factors that increase mammographic breast density could increase ovarian cancer risk. We examined whether high breast density is associated with ovarian cancer risk.

METHODS

We conducted a cohort study of 724,603 women aged 40 to 79 years with 2,506,732 mammograms participating in the Breast Cancer Surveillance Consortium from 1995 to 2009. Incident epithelial ovarian cancer was diagnosed in 1373 women. We used partly conditional Cox regression to estimate the association between breast density and 5-year risk of incident epithelial ovarian cancer overall and stratified by 10-year age group. All statistical tests were two-sided.

RESULTS

Compared with women with scattered fibroglandular densities, women with heterogeneously dense and extremely dense breast tissue had 20% and 18% increased 5-year risk of incident epithelial ovarian cancer (hazard ratio [HR] = 1.20, 95% confidence interval [CI] = 1.06 to 1.36; HR = 1.18, 95% CI = 0.93 to 1.50, respectively; P(trend) = .01). Among women aged 50 to 59 years, we observed a trend in elevated risk associated with increased breast density (P(trend) = .02); women with heterogeneously and extremely dense breast tissue had 30% (HR = 1.30; 95% CI = 1.03 to 1.64) and 65% (HR = 1.65; 95% CI = 1.12 to 2.44) increased risk, respectively, compared with women with scattered fibroglandular densities. The pattern was similar but not statistically significant at age 40 to 49 years. There were no consistent patterns of breast density and ovarian cancer risk at age 60 to 79 years.

CONCLUSIONS

Dense breast tissue was associated with a modest increase in 5-year ovarian cancer risk in women aged 50 to 59 years but was not associated with ovarian cancer at ages 40 to 49 or 60 to 79 years.

A virtual trial framework for quantifying the detectability of masses in breast tomosynthesis projection data

PURPOSE

Digital breast tomosynthesis (DBT) is a promising breast cancer screening tool that has already begun making inroads into clinical practice. However, there is ongoing debate over how to quantitatively evaluate and optimize these systems, because different definitions of image quality can lead to different optimal design strategies. Powerful and accurate tools are desired to extend our understanding of DBT system optimization and validate published design principles.

METHODS

The authors developed a virtual trial framework for task-specific DBT assessment that uses digital phantoms, open-source x-ray transport codes, and a projection-space, spatial-domain observer model for quantitative system evaluation. The authors considered evaluation of reconstruction algorithms as a separate problem and focused on the information content in the raw, unfiltered projection images. Specifically, the authors investigated the effects of scan angle and number of angular projections on detectability of a small (3 mm diameter) signal embedded in randomly-varying anatomical backgrounds. Detectability was measured by the area under the receiver-operating characteristic curve (AUC). Experiments were repeated for three test cases where the detectability-limiting factor was anatomical variability, quantum noise, or electronic noise. The authors also juxtaposed the virtual trial framework with other published studies to illustrate its advantages and disadvantages.

RESULTS

The large number of variables in a virtual DBT study make it difficult to directly compare different authors' results, so each result must be interpreted within the context of the specific virtual trial framework. The following results apply to 25% density phantoms with 5.15 cm compressed thickness and 500 μm(3) voxels (larger 500 μm(2) detector pixels were used to avoid voxel-edge artifacts): 1. For raw, unfiltered projection images in the anatomical-variability-limited regime, AUC appeared to remain constant or increase slightly with scan angle. 2. In the same regime, when the authors fixed the scan angle, AUC increased asymptotically with the number of projections. The threshold number of projections for asymptotic AUC performance depended on the scan angle. In the quantum- and electronic-noise dominant regimes, AUC behaviors as a function of scan angle and number of projections sometimes differed from the anatomy-limited regime. For example, with a fixed scan angle, AUC generally decreased with the number of projections in the electronic-noise dominant regime. These results are intended to demonstrate the capabilities of the virtual trial framework, not to be used as optimization rules for DBT.

CONCLUSIONS

The authors have demonstrated a novel simulation framework and tools for evaluating DBT systems in an objective, task-specific manner. This framework facilitates further investigation of image quality tradeoffs in DBT.

Investigating the effect of characteristic x-rays in cadmium zinc telluride detectors under breast computerized tomography operating conditions

A number of research groups have been investigating the use of dedicated breast computerized tomography (CT). Preliminary results have been encouraging, suggesting an improved visualization of masses on breast CT as compared to conventional mammography. Nonetheless, there are many challenges to overcome before breast CT can become a routine clinical reality. One potential improvement over current breast CT prototypes would be the use of photon counting detectors with cadmium zinc telluride (CZT) (or CdTe) semiconductor material. These detectors can operate at room temperature and provide high detection efficiency and the capability of multi-energy imaging; however, one factor in particular that limits image quality is the emission of characteristic x-rays. In this study, the degradative effects of characteristic x-rays are examined when using a CZT detector under breast CT operating conditions. Monte Carlo simulation software was used to evaluate the effect of characteristic x-rays and the detector element size on spatial and spectral resolution for a CZT detector used under breast CT operating conditions. In particular, lower kVp spectra and thinner CZT thicknesses were studied than that typically used with CZT based conventional CT detectors. In addition, the effect of characteristic x-rays on the accuracy of material decomposition in spectral CT imaging was explored. It was observed that when imaging with 50-60 kVp spectra, the x-ray transmission through CZT was very low for all detector thicknesses studied (0.5-3.0 mm), thus retaining dose efficiency. As expected, characteristic x-ray escape from the detector element of x-ray interaction increased with decreasing detector element size, approaching a 50% escape fraction for a 100 μm size detector element. The detector point spread function was observed to have only minor degradation with detector element size greater than 200 μm and lower kV settings. Characteristic x-rays produced increasing distortion in the spectral response with decreasing detector element size. If not corrected for, this caused a large bias in estimating tissue density parameters for material decomposition. It was also observed that degradation of the spectral response due to characteristic x-rays caused worsening precision in the estimation of tissue density parameters. It was observed that characteristic x-rays do cause some degradation in the spatial and spectral resolution of thin CZT detectors operating under breast CT conditions. These degradations should be manageable with careful selection of the detector element size. Even with the observed spectral distortion from characteristic x-rays, it is still possible to correctly estimate tissue parameters for material decomposition using spectral CT if accurate modeling is used.

Characterization of a constrained paired-view technique in iterative reconstruction for breast tomosynthesis

PURPOSE

The order in which the projection views are employed in the reconstruction of tomosynthesis by iterative algorithms, such as simultaneous algebraic reconstruction technique and maximum likelihood, has a strong effect on the rate of convergence, accuracy, and the edge-blurring artifacts in the reconstructed image. The purpose of this investigation was to characterize and evaluate the effects of ordering schemes on image quality for breast tomosynthesis reconstruction and to explore a new constrained paired-view technique that could provide reduction of reconstruction artifacts. In this work, the authors compared several different ordering schemes and characterized the image quality and the formation of out-of-plane artifacts. Furthermore, a new normalization method is presented. It produces more accurate reconstructions with reduced artifacts comparing to the standard method of sequential ordering.

METHODS

In addition to visual assessment of image quality, several indices such as the signal-difference-to-noise ratio, the artifact-spread function, and the lesion detectability (d(')) were computed to quantitatively evaluate the effect of ordering scheme. The sets of breast tomosynthesis projection images were simulated for reconstruction; one set had uniform background (white noise only) and the other two contained both anatomic background and quantum noise. Clinical breast images were also studied for comparison.

RESULTS

The authors have quantified the image quality in reconstructed slices for a range of tumor sizes. The authors' proposed method provides better performance for all of the metrics tested (contrast, d('), and the level of artifacts) both for the uniform phantom case and in the presence of anatomical structure.

CONCLUSIONS

The paired projection normalization provides better performance in the image quality of the reconstructed slices, and results in a lower level of artifacts in the Z direction. This implies that even a relatively simple method like the "side-to-side" sequence, which pairs two symmetrical projections with equal angular distance from the central projection, would achieve better reconstructed image quality than the conventional "step-by-step" method, which uses sequential projections one after another.

Breast density measurements with ultrasound tomography: a comparison with film and digital mammography

PURPOSE

To investigate the use of the whole-breast sound speed measurement as a marker of breast density (BD), a known risk factor for breast cancer.

METHODS

As part of an ongoing study of breast cancer detection, 249 patients were scanned with a clinical prototype that operates on the principles of ultrasound tomography. Typically, 40-100 sound speed tomograms were reconstructed from the scan data, corresponding to the entire volume of the breast of each patient. The data were used to estimate the volume averaged sound speed (VASS) of the breast for each patient. The corresponding mammograms were used to calculate mammographic percent density (MPD) using CUMULUS software. Film mammograms were available for 164 patients while 85 digital mammograms were available for the remaining patients. Standard statistical techniques were used to determine associations of breast sound speed with a variety of mammographic measures such as percent density, area of dense tissue, and area of nondense tissue. Furthermore, associations of breast sound speed with continuous variables such as age and weight and dichotomous variables such as parity and menopausal status were also assessed.

RESULTS

VASS was found to be significantly associated with MPD. The Spearman correlation coefficient (r(s)) between VASS and MPD was found to be 0.77 and 0.71 for film and digital mammography, respectively. VASS was positively correlated with dense areas by mammography, both digital (r(s) = 0.46) and film (r(s) = 0.56). VASS was negatively associated with nondense area by mammography, both digital (r(s) = -0.58) and film (r(s) = -0.63). BD by all methods was less in postmenopausal than in premenopausal women. The MPD was lower in the postmenopausal group (by 6.6%, p < 0.08, for the digital group and 7.73%, p < 0.007, for the film group). The VASS was also lower in the postmenopausal group (by 15 m∕s, p < 0.001 for the digital group and 8 m∕s, p < 0.08, for the film group). The association of MPD with age was characterized with r(s) = -0.06 (p < 0.6) for digital mammography and r(s) = -0.53 (p < 0.002) for film mammography. For weight, the MPD associations were characterized by r(s) = -0.53 (p < 0.0001) for digital mammography and -0.38 (p < 0.0001) for film mammography. The association of VASS with age was r(s) = -0.33 (p < 0.002) for the digital group and -0.17 (p < 0.03) for the film group. For weight, the relationship was characterized with r(s) = -0.45 (p < 0.001) for the digital group and -0.37 (p < 0.0001) for the film group.

CONCLUSIONS

The association between VASS and MPD is strong for both film and digital mammography, suggesting that VASS is a viable measure of breast density. This result sets the stage for future work that will focus on directly testing the association of VASS with breast cancer risk.

Validation of a power-law noise model for simulating small-scale breast tissue

We have validated a small-scale breast tissue model based on power-law noise. A set of 110 patient images served as truth. The statistical model parameters were determined by matching the radially averaged power-spectrum of the projected simulated tissue with that of the central tomosynthesis patient breast projections. Observer performance in a signal-known exactly detection task in simulated and actual breast backgrounds was compared. Observers included human readers, a pre-whitening observer model and a channelized Hotelling observer model. For all observers, good agreement between performance in the simulated and actual backgrounds was found, both in the tomosynthesis central projections and the reconstructed images. This tissue model can be used for breast x-ray imaging system optimization. The complete statistical description of the model is provided.

Towards a nanoscale mammographic contrast agent: development of a modular pre-clinical dual optical/x-ray agent

Contrast-enhanced digital mammography (CEDM) can provide improved breast cancer detection and characterization compared to conventional mammography by imaging the effects of tumour angiogenesis. Current small-molecule contrast agents used for CEDM are limited by a short plasma half-life and rapid extravasation into tissue interstitial space. To address these limitations, nanoscale agents that can remain intravascular except at sites of tumour angiogenesis can be used. For CEDM, this agent must be both biocompatible and strongly attenuate mammographic energy x-rays. Nanoscale perfluorooctylbromide (PFOB) droplets have good x-ray attenuation and have been used in patients for other applications. However, the macroscopic scale of x-ray imaging (50-100 µm) is inadequate for direct verification that PFOB droplets localize at sites of breast tumour angiogenesis. For efficient pre-clinical optimization for CEDM, we integrated an optical marker into PFOB droplets for microscopic assessment (≪50 µm). To develop PFOB droplets as a new nanoscale mammographic contrast agent, PFOB droplets were labelled with fluorescent quantum dots (QDs). The droplets had mean diameters of 160 nm, fluoresced at 635 nm and attenuated x-ray spectra at 30.5 keV mean energy with a relative attenuation of 5.6 ± 0.3 Hounsfield units (HU) mg(-1) mL(-1) QD-PFOB. With the agent loaded into tissue phantoms, good correlation between x-ray attenuation and optical fluorescence was found (R(2) = 0.96), confirming co-localization of the QDs with PFOB for quantitative assessment using x-ray or optical methods. Furthermore, the QDs can be removed from the PFOB agent without affecting its x-ray attenuation or structural properties for expedited translation of optimized PFOB droplet formulations into patients.

Background ¹⁸F-FDG uptake in positron emission mammography (PEM): correlation with mammographic density and background parenchymal enhancement in breast MRI

We aimed to determine whether background (18)F-FDG uptake in positron emission mammography (PEM) was related to mammographic density or background parenchymal enhancement in breast MRI.

METHODS

We studied a total of 52 patients (mean age, 50.9 years, 26 premenopausal, 26 postmenopausal) with newly diagnosed breast cancer who underwent (18)F-FDG PEM (positron emission mammography), conventional mammography and breast MRI. The background mean (18)F-FDG uptake value on PEM was obtained by drawing a user-defined region of interest (ROI) in a normal area of the contralateral breast. We reviewed the mammography retrospectively for overall breast density of contralateral breast according to the four-point scale (grade 1-4) of the Breast Imaging Reporting and Data System (BI-RADS) classification. The background parenchymal enhancement of breast MRI was classified as minimal, mild, moderate, or marked. All imaging findings were interpreted by two readers in consensus without knowledge of image findings of other modalities.

RESULTS

Multiple linear regression analysis revealed a significant correlation between background (18)F-FDG uptake on PEM and mammographic density after adjustment for age and menopausal status (P<0.01), but not between background (18)F-FDG uptake on PEM and background parenchymal enhancement on MRI.

CONCLUSION

Background (18)F-FDG uptake on PEM significantly increases as mammographic density increases. Background parenchymal enhancement in breast MRI was not an independent predictor of the background (18)F-FDG uptake on PEM unlike mammographic density.

Mammographic density and breast cancer: a comparison of related and unrelated controls in the Breast Cancer Family Registry

Introduction

Percent mammographic density (PMD) is a strong and highly heritable risk factor for breast cancer. Studies of the role of PMD in familial breast cancer may require controls, such as the sisters of cases, selected from the same 'risk set' as the cases. The use of sister controls would allow control for factors that have been shown to influence risk of breast cancer such as race/ethnicity, socioeconomic status and a family history of breast cancer, but may introduce 'overmatching' and attenuate case-control differences in PMD.

Methods

To examine the potential effects of using sister controls rather than unrelated controls in a case-control study, we examined PMD in triplets, each comprised of a case with invasive breast cancer, an unaffected full sister control, and an unaffected unrelated control. Both controls were matched to cases on age at mammogram. Total breast area and dense area in the mammogram were measured in the unaffected breast of cases and a randomly selected breast in controls, and the non-dense area and PMD calculated from these measurements.

Results

The mean difference in PMD between cases and controls, and the standard deviation (SD) of the difference, were slightly less for sister controls (4.2% (SD = 20.0)) than for unrelated controls (4.9% (SD = 25.7)). We found statistically significant correlations in PMD between cases (n = 228) and sister controls (n = 228) (r = 0.39 (95% CI: 0.28, 0.50; P <0.0001)), but not between cases and unrelated controls (n = 228) (r = 0.04 (95% CI: -0.09, 0.17; P = 0.51)). After adjusting for other risk factors, square root transformed PMD was associated with an increased risk of breast cancer when comparing cases to sister controls (adjusted odds ratio (inter-quintile odds ratio (IQOR) = 2.19, 95% CI = 1.20, 4.00) or to unrelated controls (adjusted IQOR = 2.62, 95% CI = 1.62, 4.25).

Conclusions

The use of sister controls in case-control studies of PMD resulted in a modest attenuation of case-control differences and risk estimates, but showed a statistically significant association with risk and allowed control for race/ethnicity, socioeconomic status and family history.

Generation of voxelized breast phantoms from surgical mastectomy specimens

PURPOSE

In the research and development of dedicated tomographic breast imaging systems, digital breast object models, also known as digital phantoms, are useful tools. While various digital breast phantoms do exist, the purpose of this study was to develop a realistic high-resolution model suitable for simulating three-dimensional (3D) breast imaging modalities. The primary goal was to design a model capable of producing simulations with realistic breast tissue structure.

METHODS

The methodology for generating an ensemble of digital breast phantoms was based on imaging surgical mastectomy specimens using a benchtop, cone-beam computed tomography system. This approach allowed low-noise, high-resolution projection views of the mastectomy specimens at each angular position. Reconstructions of these projection sets were processed using correction techniques and diffusion filtering prior to segmentation into breast tissue types in order to generate phantoms.

RESULTS

Eight compressed digital phantoms and 20 uncompressed phantoms from which an additional 96 pseudocompressed digital phantoms with voxel dimensions of 0.2 mm(3) were generated. Two distinct tissue classification models were used in forming breast phantoms. The binary model classified each tissue voxel as either adipose or fibroglandular. A multivalue scaled model classified each tissue voxel as percentage of adipose tissue (range 1%-99%). Power spectral analysis was performed to compare simulated reconstructions using the breast phantoms to the original breast specimen reconstruction, and fits were observed to be similar.

CONCLUSIONS

The digital breast phantoms developed herein provide a high-resolution anthropomorphic model of the 3D uncompressed and compressed breast that are suitable for use in evaluating and optimizing tomographic breast imaging modalities. The authors believe that other research groups might find the phantoms useful, and therefore they offer to make them available for wider use.

Towards Visual-Search Model Observers for Mass Detection in Breast Tomosynthesis

We are investigating human-observer models that perform clinically realistic detection and localization tasks as a means of making reliable assessments of digital breast tomosynthesis images. The channelized non-prewhitening (CNPW) observer uses the background known exactly task for localization and detection. Visual-search observer models attempt to replicate the search patterns of trained radiologists. The visual-search observer described in this paper utilizes a two-phase approach, with an initial holistic search followed by directed analysis and decision making. Gradient template matching is used for the holistic search, and the CNPW observer is used for analysis and decision making. Spherical masses were embedded into anthropomorphic breast phantoms, and simulated projections were made using ray-tracing and a serial cascade model. A localization ROC study was performed on these images using the visual-search model observer and the CNPW observer. Observer performance from the two computer observers was compared to human observer performance. The visual-search observer was able to produce area under the LROC curve values similar to those from human observers; however, more research is needed to increase the robustness of the algorithm.

Observation of super-resolution in digital breast tomosynthesis

PURPOSE

Digital breast tomosynthesis (DBT) is a 3D x-ray imaging modality in which tomographic sections of the breast are generated from a limited range of tube angles. Because oblique x-ray incidence shifts the image of an object in subpixel detector element increments with each increasing projection angle, it is demonstrated that DBT is capable of super-resolution (i.e., subpixel resolution).

METHODS

By convention, DBT reconstructions are performed on planes parallel to the breast support at various depths of the breast volume. In order for resolution in each reconstructed slice to be comparable to the detector, the pixel size should match that of the detector elements; hence, the highest frequency that can be resolved in the plane of reconstruction is the alias frequency of the detector. This study considers reconstruction grids with much smaller pixelation to visualize higher frequencies. For analytical proof of super-resolution, a theoretical framework is developed in which the reconstruction of a high frequency sinusoidal input is calculated using both simple backprojection (SBP) and filtered backprojection. To study the frequency spectrum of the reconstruction, its Fourier transform is also determined. The experimental feasibility of super-resolution was investigated by acquiring images of a bar pattern phantom with frequencies higher than the detector alias frequency.

RESULTS

Using analytical modeling, it is shown that the central projection cannot resolve frequencies exceeding the detector alias frequency. The Fourier transform of the central projection is maximized at a lower frequency than the input as evidence of aliasing. By contrast, SBP reconstruction can resolve the input, and its Fourier transform is correctly maximized at the input frequency. Incorporating filters into the reconstruction smoothens pixelation artifacts in the spatial domain and reduces spectral leakage in the Fourier domain. It is also demonstrated that the existence of super-resolution is dependent on position in the reconstruction and on the directionality of the input frequency. Consistent with the analytical results, experimental reconstructions of bar patterns showed visibility of frequencies greater than the detector alias frequency. Super-resolution was present at positions predicted from analytical modeling.

CONCLUSIONS

This work demonstrates the existence of super-resolution in DBT. Super-resolution has the potential to impact the visualization of fine structural details in the breast, such as microcalcifications and other subtle signs of cancer.

Mammographic density and risk of breast cancer

The radiographic appearance of the breast on mammography varies among women, and reflects variations in breast tissue composition and the different X-ray attenuation characteristics of these tissues. Fat is radiologically lucent and appears dark on a mammogram. Connective and epithelial tissues are radiologically dense and appear light. These variations in appearance are commonly described as the percentage of the breast image that is radiologically dense, or as percent mammographic density (PMD). There is now extensive evidence that PMD is a risk factor for breast cancer, with a 4- to 6-fold gradient in risk between women with 75% or more PMD compared with those with 10% or less. However, the accuracy of risk prediction in individual women is modest. The extent of PMD is associated inversely with greater age, parity, and weight, and is reduced by the menopause and by tamoxifen. PMD is positively associated with greater height, a family history of breast cancer, and is increased by combined hormone therapy. The relative risk associated with density is substantially larger than the relative risk of breast cancer associated with a family history of the disease or any of the menstrual and reproductive risk factors. It is estimated that the risks of breast cancer attributable to density of 50% or more may be 16% for all breast cancers. Although combined hormone therapy and tamoxifen respectively increase a decrease both PMD and breast cancer risk, there is as yet insufficient evidence to use PMD as a surrogate marker for breast cancer.

The potential of iodine for improving breast cancer diagnosis and treatment

Early detection through modalities such as mammography remains pivotal in the fight against breast cancer. The detectability of breast cancer through mammography is rooted in the differential X-ray attenuation properties of cancerous and normal breast tissue. An unexplored component of the X-ray contrast between fibrous breast tissue and similarly composed tumor tissue is the presence of naturally localized iodine in the cancer but not healthy breast tissue. It is hypothesized that differing amounts of iodine are present in tumor versus normal breast tissue that leads to more easily detectable cancer due to an increased Z value of the tumor tissue relative to the healthy tissue, which results in enhanced differences in X-ray attenuation properties between the two tissues and thus greater radiographic contrast. The hypothesis is supported by experimental observations explaining how iodine could localize in the tumor tissue but not surrounding healthy tissue. Breast cancer cells express the sodium-iodide symporter (NIS), an ion pump which sequesters iodine in tumor cells. Healthy non-lactating breast tissue, in contrast, does not express NIS. Further evidence for the differential expression of NIS resulting in X-ray contrast enhancement in breast cancer is the established correlation between expression of insulin growth factor (IGF) and enhanced X-ray contrast, and the evidence that IGF is a promoter for NIS. Ultimately, if the expression of iodine can be shown to be a component of radiographic contrast between healthy and tumor breast tissue, this could be used to drive the development of new technology and techniques for use in the detection and treatment of breast cancer. The proof of this hypothesis could thus have a substantial impact in the fight against breast cancer.

Advances in functional X-ray imaging techniques and contrast agents

X-rays have been used for non-invasive high-resolution imaging of thick biological specimens since their discovery in 1895. They are widely used for structural imaging of bone, metal implants, and cavities in soft tissue. Recently, a number of new contrast methodologies have emerged which are expanding X-ray's biomedical applications to functional as well as structural imaging. These techniques are promising to dramatically improve our ability to study in situ biochemistry and disease pathology. In this review, we discuss how X-ray absorption, X-ray fluorescence, and X-ray excited optical luminescence can be used for physiological, elemental, and molecular imaging of vasculature, tumors, pharmaceutical distribution, and the surface of implants. Imaging of endogenous elements, exogenous labels, and analytes detected with optical indicators will be discussed.

Cascaded systems analysis of noise and detectability in dual-energy cone-beam CT

PURPOSE

Dual-energy computed tomography and dual-energy cone-beam computed tomography (DE-CBCT) are promising modalities for applications ranging from vascular to breast, renal, hepatic, and musculoskeletal imaging. Accordingly, the optimization of imaging techniques for such applications would benefit significantly from a general theoretical description of image quality that properly incorporates factors of acquisition, reconstruction, and tissue decomposition in DE tomography. This work reports a cascaded systems analysis model that includes the Poisson statistics of x rays (quantum noise), detector model (flat-panel detectors), anatomical background, image reconstruction (filtered backprojection), DE decomposition (weighted subtraction), and simple observer models to yield a task-based framework for DE technique optimization.

METHODS

The theoretical framework extends previous modeling of DE projection radiography and CBCT. Signal and noise transfer characteristics are propagated through physical and mathematical stages of image formation and reconstruction. Dual-energy decomposition was modeled according to weighted subtraction of low- and high-energy images to yield the 3D DE noise-power spectrum (NPS) and noise-equivalent quanta (NEQ), which, in combination with observer models and the imaging task, yields the dual-energy detectability index (d(')). Model calculations were validated with NPS and NEQ measurements from an experimental imaging bench simulating the geometry of a dedicated musculoskeletal extremities scanner. Imaging techniques, including kVp pair and dose allocation, were optimized using d(') as an objective function for three example imaging tasks: (1) kidney stone discrimination; (2) iodine vs bone in a uniform, soft-tissue background; and (3) soft tissue tumor detection on power-law anatomical background.

RESULTS

Theoretical calculations of DE NPS and NEQ demonstrated good agreement with experimental measurements over a broad range of imaging conditions. Optimization results suggest a lower fraction of total dose imparted by the low-energy acquisition, a finding consistent with previous literature. The selection of optimal kVp pair reveals the combined effect of both quantum noise and contrast in the kidney stone discrimination and soft-tissue tumor detection tasks, whereas the K-edge effect of iodine was the dominant factor in determining kVp pairs in the iodine vs bone task. The soft-tissue tumor task illustrated the benefit of dual-energy imaging in eliminating anatomical background noise and improving detectability beyond that achievable by single-energy scans.

CONCLUSIONS

This work established a task-based theoretical framework that is predictive of DE image quality. The model can be utilized in optimizing a broad range of parameters in image acquisition, reconstruction, and decomposition, providing a useful tool for maximizing DE-CBCT image quality and reducing dose.

A novel wavelet-statistics based feature detection system for detecting microcalcifications

This paper describes a wavelet-statistics based feature detection system as applied to microcalcification detection. While a number of researches have been conducted towards microcalcification detection using wavelet analysis and auxiliary information, most of this auxiliary information was obtained from within the spatial domain. In this research, a continuous wavelet transform was used to segment features and compute energy maps of these segmented features. The kurtoses of these features were computed in the wavelet domain. This statistical information together with the energy maps forms the inputs to a rule-based classifier. Physiological information from the spatial domain was used to exclude false-positives. The system was tested using a ROI from the LLNL database. The result is one false-positive within the cluster as classified by the radiologist.

A statistically defined anthropomorphic software breast phantom

PURPOSE

Digital anthropomorphic breast phantoms have emerged in the past decade because of recent advances in 3D breast x-ray imaging techniques. Computer phantoms in the literature have incorporated power-law noise to represent glandular tissue and branching structures to represent linear components such as ducts. When power-law noise is added to those phantoms in one piece, the simulated fibroglandular tissue is distributed randomly throughout the breast, resulting in dense tissue placement that may not be observed in a real breast. The authors describe a method for enhancing an existing digital anthropomorphic breast phantom by adding binarized power-law noise to a limited area of the breast.

METHODS

Phantoms with (0.5 mm)(3) voxel size were generated using software developed by Bakic et al. Between 0% and 40% of adipose compartments in each phantom were replaced with binarized power-law noise (β = 3.0) ranging from 0.1 to 0.6 volumetric glandular fraction. The phantoms were compressed to 7.5 cm thickness, then blurred using a 3 × 3 boxcar kernel and up-sampled to (0.1 mm)(3) voxel size using trilinear interpolation. Following interpolation, the phantoms were adjusted for volumetric glandular fraction using global thresholding. Monoenergetic phantom projections were created, including quantum noise and simulated detector blur. Texture was quantified in the simulated projections using power-spectrum analysis to estimate the power-law exponent β from 25.6 × 25.6 mm(2) regions of interest.

RESULTS

Phantoms were generated with total volumetric glandular fraction ranging from 3% to 24%. Values for β (averaged per projection view) were found to be between 2.67 and 3.73. Thus, the range of textures of the simulated breasts covers the textures observed in clinical images.

CONCLUSIONS

Using these new techniques, digital anthropomorphic breast phantoms can be generated with a variety of glandular fractions and patterns. β values for this new phantom are comparable with published values for breast tissue in x-ray projection modalities. The combination of conspicuous linear structures and binarized power-law noise added to a limited area of the phantom qualitatively improves its realism.

Adult weight gain, fat distribution and mammographic density in Spanish pre- and post-menopausal women (DDM-Spain)

High mammographic density (MD) is a phenotype risk marker for breast cancer. Body mass index (BMI) is inversely associated with MD, with the breast being a fat storage site. We investigated the influence of abdominal fat distribution and adult weight gain on MD, taking age, BMI and other confounders into account. Because visceral adiposity and BMI are associated with breast cancer only after menopause, differences in pre- and post-menopausal women were also explored. We recruited 3,584 women aged 45–68 years within the Spanish breast cancer screening network. Demographic, reproductive, family and personal history data were collected by purpose-trained staff, who measured current weight, height, waist and hip circumferences under the same protocol and with the same tools. MD was assessed in the left craniocaudal view using Boyd’s Semiquantitative Scale. Association between waist-to-hip ratio, adult weight gain (difference between current weight and self-reported weight at 18 years) and MD was quantified by ordinal logistic regression, with random center-specific intercepts. Models were adjusted for age, BMI, breast size, time since menopause, parity, family history of breast cancer and hormonal replacement therapy use. Natural splines were used to describe the shape of the relationship between these two variables and MD. Waist-to-hip ratio was inversely associated with MD, and the effect was more pronounced in pre-menopausal (OR = 0.53 per 0.1 units; 95 % CI = 0.42–0.66) than in post-menopausal women (OR = 0.73; 95 % CI = 0.65–0.82) (P of heterogeneity = 0.010). In contrast, adult weight gain displayed a positive association with MD, which was similar in both groups (OR = 1.17 per 6 kg; 95 % CI = 1.11–1.23). Women who had gained more than 24 kg displayed higher MD (OR = 2.05; 95 % CI = 1.53–2.73). MD was also evaluated using Wolfe’s and Tabár’s classifications, with similar results being obtained. Once BMI, fat distribution and other confounders were considered, our results showed a clear dose–response gradient between the number of kg gained during adulthood and the proportion of dense tissue in the breast.

Adaptation of a clustered lumpy background model for task-based image quality assessment in x-ray phase-contrast mammography

PURPOSE

Since the introduction of clinical x-ray phase-contrast mammography (PCM), a technique that exploits refractive-index variations to create edge enhancement at tissue boundaries, a number of optimization studies employing physical image-quality metrics have been performed. Ideally, task-based assessment of PCM would have been conducted with human readers. These studies have been limited, however, in part due to the large parameter-space of PCM system configurations and the difficulty of employing expert readers for large-scale studies. It has been proposed that numerical observers can be used to approximate the statistical performance of human readers, thus enabling the study of task-based performance over a large parameter-space.

METHODS

Methods are presented for task-based image quality assessment of PCM images with a numerical observer, the most significant of which is an adapted lumpy background from the conventional mammography literature that accounts for the unique wavefield propagation physics of PCM image formation and will be used with a numerical observer to assess image quality. These methods are demonstrated by performing a PCM task-based image quality study using a numerical observer. This study employs a signal-known-exactly, background-known-statistically Bayesian ideal observer method to assess the detectability of a calcification object in PCM images when the anode spot size and calcification diameter are varied.

RESULTS

The first realistic model for the structured background in PCM images has been introduced. A numerical study demonstrating the use of this background model has compared PCM and conventional mammography detection of calcification objects. The study data confirm the strong PCM calcification detectability dependence on anode spot size. These data can be used to balance the trade-off between enhanced image quality and the potential for motion artifacts that comes with use of a reduced spot size and increased exposure time.

CONCLUSIONS

A method has been presented for the incorporation of structured breast background data into task-based numerical observer assessment of PCM images. The method adapts conventional background simulation techniques to the wavefield propagation physics necessary for PCM imaging. This method is demonstrated with a simple detection task.

A first evaluation of breast radiological density assessment by QUANTRA software as compared to visual classification

Breast radiological density is a determinant of breast cancer risk and of mammography sensitivity and may be used to personalize screening approach. We first analyzed the reproducibility of visual density assessment by eleven experienced radiologists classifying a set of 418 digital mammograms: reproducibility was satisfactory on a four (BI-RADS D1-2-3-4: weighted kappa = 0.694-0.844) and on a two grade (D1-2 vs D3-4: kappa = 0.620-0.851), but subjects classified as with dense breast would range between 25.1 and 50.5% depending on the classifying reader. Breast density was then assessed by computer using the QUANTRA software which provided systematically lower density percentage values as compared to visual classification. In order to predict visual classification results in discriminating dense and non-dense breast subjects on a two grade scale (D3-4 vs, D1-2) the best fitting cut off value observed for QUANTRA was ≤22.0%, which correctly predicted 88.6% of D1-2, 89.8% of D3-4, and 89.0% of total cases. Computer assessed breast density is absolutely reproducible, and thus to be preferred to visual classification. Thus far few studies have addressed the issue of adjusting computer assessed density to reproduce visual classification, and more similar comparative studies are needed.

Optimization of phosphor-based detector design for oblique x-ray incidence in digital breast tomosynthesis

PURPOSE

In digital breast tomosynthesis (DBT), a volumetric reconstruction of the breast is generated from a limited range of x-ray projections. One trade-off of DBT is resolution loss in the projections due to non-normal (i.e., oblique) x-ray incidence. Although degradation in image quality due to oblique incidence has been studied using empirical data and Monte Carlo simulations, a theoretical treatment has been lacking. The purpose of this work is to extend Swank's calculations of the transfer functions of turbid granular phosphors to oblique incidence. The model is ultimately used as a tool for optimizing the design of DBT detectors.

METHODS

A quantum-limited system and 20 keV x-rays are considered. Under these assumptions, the modulation transfer function (MTF) and noise power spectra (NPS) are derived using the diffusion approximation to the Boltzmann equation to model optical scatter within the phosphor. This approach is applicable to a nonstructured scintillator such as gadolinium oxysulfide doped with terbium (Gd(2)O(2)S:Tb), which is commonly used in breast imaging and which can reasonably approximate other detector materials. The detective quantum efficiency (DQE) is then determined from the Nishikawa formulation, where it is written as the product of the x-ray quantum detection efficiency, the Swank factor, and the Lubberts fraction. Transfer functions are calculated for both front- and back-screen configurations, which differ by positioning the photocathode at the exit or entrance point of the x-ray beam, respectively.

RESULTS

In the front-screen configuration, MTF and DQE are found to have considerable angular dependence, while NPS is shown to vary minimally with projection angle. As expected, the high frequency MTF and DQE are degraded substantially at large angles. By contrast, all transfer functions for the back-screen configuration have the advantage of significantly less angular dependence. Using these models, we investigated the possibility for optimizing the design of DBT detectors. As an example optimization strategy, the phosphor thickness which maximizes the DQE at a fixed frequency is analyzed. This work demonstrates that the optimal phosphor thickness for the front-screen is angularly dependent, shifting to lower thickness at higher angles. Conversely, the back-screen is not optimized by a single thickness but instead attains reasonably high DQE values over a large range of thicknesses. Although the back-screen configuration is not suited for current detectors using a glass substrate, it may prove to be preferred in future detectors using newly proposed plastic thin-film transistor (TFT) substrates.

CONCLUSIONS

Using the diffusion approximation to the Boltzmann equation to model the spread of light in a scintillator, this paper develops an analytical model of MTF, NPS, and DQE for a phosphor irradiated obliquely. The model is set apart from other studies on oblique incidence in being derived from first principles. This work has applications in the optimization of DBT detector design.