Breast composition measurement with a cadmium-zinc-telluride based spectral computed tomography system

Monte-Carlo study of contrast-enhanced spectral mammography with cadmium telluride photon-counting x-ray detectors

BACKGROUND

Contrast-enhanced spectral mammography (CESM) with photon-counting x-ray detectors (PCDs) can be used to improve the classification of breast cancers as benign or malignant. Commercially-available PCD-based mammography systems use silicon-based PCDs. Cadmium-telluride (CdTe) PCDs may provide a practical advantage over silicon-based PCDs because they can be implemented as large-area detectors that are more easily adaptable to existing mammography systems.

PURPOSE

The purpose of this work is to optimize CESM implemented with CdTe PCDs and to investigate the influence of the number of energy bins, electronic noise level, pixel size, and anode material on image quality.

METHODS

We developed a Monte Carlo model of the energy-bin-dependent modulation transfer functions (MTFs) and noise power spectra, including spatioenergetic noise correlations. We validated model predictions using a CdTe PCD with analog charge summing for charge-sharing suppression. Using the ideal-observer detectability, we optimized CESM for the task of detecting a 7-mm-diameter iodine nodule embedded in a breast with 50% glandularity. We optimized the tube voltage, beam filtration, and the location of energy thresholds for 50 and 100- μ $\mu$ m pixels, tungsten and molybdenum anodes, and two electronic noise levels. One of the electronic noise levels was that of the experimental system; the other was half that of the experimental system. Optimization was performed for CdTe PCDs with two or three energy bins. We also estimated the impact of anatomic noise due to background parenchymal enhancement and computed the minimum detectable iodine area density in the presence of quantum and anatomic noise.

RESULTS

Model predictions of the MTFs and noise power spectra agreed well with experiment. For optimized systems, adding a third energy bin increased quantum noise levels and reduced detectability by ∼55% compared to two-bin approaches that simply suppress contrast between fibroglandular and adipose tissue. Decreasing the electronic noise standard deviation from 3.4 to 1.7 keV increased iodine detectability by ∼5% and ∼30% for two-bin imaging and three-bin imaging, respectively. After optimizing for tube voltage, beam filtration, and the location of energy thresholds, there was ∼a 3% difference in iodine detectability between molybdenum and tungsten anodes for two-bin imaging, but for three-bin imaging, molybdenum anodes provided up to 14% increase in detectability relative to tungsten anodes. Anatomic noise decreased iodine detectability by 15% to 40%, with greater impact for lower electronic noise settings and larger pixel sizes.

CONCLUSIONS

For CESM implemented with CdTe PCDs, (1) quantitatively-accurate three-material decompositions using three energy bins are associated with substantial increases in quantum noise relative to two-energy-bin approaches that simply suppress contrast between fibroglandular and adipose tissues; (2) tungsten and molybdenum anodes can provide nearly equal iodine detectability for two-bin imaging, but molybdenum provides a modest detectability advantage for three-bin imaging provided that all other technique parameters are optimized; (3) reducing pixel sizes from 100 to 50  μ $\mu$ m can reduce detectability by up to 20% due to charge sharing; (4) anatomic noise due to background parenchymal enhancement is estimated to have a substantial impact on lesion visibility, reducing detectability by approximately 30%.

Dedicated breast CT: state of the art-Part I. Historical evolution and technical aspects

Dedicated breast CT is an emerging 3D isotropic imaging technology for breast, which overcomes the limitations of 2D compression mammography and limited angle tomosynthesis while providing some of the advantages of magnetic resonance imaging. This first installment in a 2-part review describes the evolution of dedicated breast CT beginning with a historical perspective and progressing to the present day. Moreover, it provides an overview of state-of-the-art technology. Particular emphasis is placed on technical limitations in scan protocol, radiation dose, breast coverage, patient comfort, and image artifact. Proposed methods of how to address these technical challenges are also discussed. KEY POINTS: • Advantages of breast CT include no tissue overlap, improved patient comfort, rapid acquisition, and concurrent assessment of microcalcifications and contrast enhancement. • Current clinical and prototype dedicated breast CT systems differ in acquisition modes, imaging techniques, and detector types. • There are still details to be decided regarding breast CT techniques, such as scan protocol, radiation dose, breast coverage, patient comfort, and image artifact.

Characterization of arterial plaque composition with dual energy computed tomography: a simulation study

To investigate the feasibility of quantifying the chemical composition of coronary artery plaque in terms of water, lipid, protein, and calcium contents using dual-energy computed tomography (CT) in a simulation study. A CT simulation package was developed based on physical parameters of a clinical CT scanner. A digital thorax phantom was designed to simulate coronary arterial plaques in the range of 2-5 mm in diameter. Both non-calcified and calcified plaques were studied. The non-calcified plaques were simulated as a mixture of water, lipid, and protein, while the calcified plaques also contained calcium. The water, lipid, protein, and calcium compositions of the plaques were selected to be within the expected clinical range. A total of 95 plaques for each lesion size were simulated using the CT simulation package at 80 and 135 kVp. Half-value layer measurements were made to make sure the simulated dose was within the range of clinical dual energy scanning protocols. Dual-energy material decomposition using a previously developed technique was performed to determine the volumetric fraction of water, lipid, protein, and calcium contents in each plaque. For non-calcified plaque, the total volume conservation provides the third constrain for three-material decomposition with dual energy CT. For calcified plaque, a fourth criterion was introduced from a previous report suggesting a linear correlation between water and protein contents in soft tissue. For non-calcified plaque, the root mean-squared error (RMSE) of the image-based decomposition was estimated to be 0.7%, 1.5%, and 0.3% for water, lipid, and protein contents, respectively. As for the calcified plaques, the RMSE of the 5 mm plaques were estimated to be 5.6%, 5.7%, 0.2%, and 3.1%, for water, lipid, calcium, and protein contents, respectively. The RMSE increases as the plaque size reduces. The simulation results indicate that chemical composition of coronary arterial plaques can be quantified using dual-energy CT. By accurately quantifying the content of a coronary plaque lesion, our decomposition method may provide valuable insight for the assessment and stratification of coronary artery disease.

Quantification of water and lipid density with dual-energy mammography: validation in postmortem breasts

OBJECTIVES

Breast cancer is the most common cancer in women and the second leading cause of cancer death. It is well known that breast density is an important risk factor for breast cancer and also can be used to personalize screening and for assessment of treatment response. Breast density has previously been correlated to volumetric water density. The purpose of this study is to validate the accuracy and precision of dual-energy mammography in measuring water density in postmortem breasts.

METHODS

Twenty pairs of postmortem breasts were imaged using dual-energy mammography with energy-sensitive photon-counting detectors. Chemical analysis was used as the reference standard to assess the accuracy of dual-energy mammography in measuring volumetric water and lipid density. Images from different views and contralateral breasts were used to assess estimate of precision for water and lipid volumetric density measurements.

RESULTS

The measured volumetric water and lipid density from dual-energy mammography and chemical analysis were in good agreement, where the standard errors of estimates (SEE) of both were calculated to be 2.1%. Volumetric water and lipid density measurements from different views were also in good agreement, with a SEE of 1.3% and 1.1%, respectively.

CONCLUSIONS

The results indicate that dual-energy mammography can be used to accurately measure volumetric water and lipid density in breast tissue. Accurate quantification of volumetric water density is expected to enhance its utility as a risk factor for breast cancer and for assessment of response to therapy.

KEY POINTS

• Dual-energy mammography can be used to accurately measure water and lipid volumetric density in breast tissue. • Improved quantification of volumetric water density is expected to enhance its utility for assessment of response to therapy and as a risk factor for breast cancer.

Objective assessment of task performance: a comparison of two FFDM detectors using an anthropomorphic breast phantom

Current digital mammography systems primarily employ one of two types of detectors: indirect conversion, typically using a cesium-iodine scintillator integrated with an amorphous silicon photodiode matrix, or direct conversion, using a photoconductive layer of amorphous selenium (a-Se) combined with thin-film transistor array. The goal of this study was to evaluate a methodology for objectively assessing image quality to compare human observer task performance in detecting microcalcification clusters and extended mass-like lesions achieved with different detector types. The proposed assessment methodology uses a novel anthropomorphic breast phantom fabricated with ink-jet printing. In addition to human observer detection performance, standard linear metrics such as modulation transfer function, noise power spectrum, and detective quantum efficiency (DQE) were also measured to assess image quality. An Analogic Anrad AXS-2430 a-Se detector used in a commercial FFDM/DBT system and a Teledyne Dalsa Xineos-2329 with CMOS pixel readout were evaluated and compared. The DQE of each detector was similar over a range of exposures. Similar task performance in detecting microcalcifications and masses was observed between the two detectors over a range of clinically applicable dose levels, with some perplexing differences in the detection of microcalcifications at the lowest dose measurement. The evaluation approach presented seems promising as a new technique for objective assessment of breast imaging technology.

Feasibility of estimating volumetric breast density from mammographic x-ray spectra using a cadmium telluride photon-counting detector

PURPOSE

Mammographic density of glandular breast tissue has a masking effect that can reduce lesion detection accuracy and is also a strong risk factor for breast cancer. Therefore, accurate quantitative estimation of breast density is clinically important. In this study, we investigate experimentally the feasibility of quantifying volumetric breast density with spectral mammography using a CdTe-based photon-counting detector.

METHODS

To demonstrate proof-of-principle, this study was carried out using the single pixel Amptek XR-100T-CdTe detector. The total number of x rays recorded by the detector from a single pencil-beam projection through 50%/50% of adipose/glandular mass fraction-equivalent phantoms was measured. Material decomposition assuming two, four, and eight energy bins was then applied to characterize the inspected phantom into adipose and glandular using log-likelihood estimation, taking into account the polychromatic source, the detector response function, and the energy-dependent attenuation.

RESULTS

Measurement tests were carried out for different doses, kVp settings, and different breast sizes. For dose of 1 mGy and above, the percent relative root mean square (RMS) errors of the estimated breast density was measured below 7% for all three phantom studies. It was also observed that some decrease in RMS errors was achieved using eight energy bins. For 3 and 4 cm thick phantoms, performance at 40 and 45 kVp showed similar performance. However, it was observed that 45 kVp showed better performance for a phantom thickness of 6 cm at low dose levels due to increased statistical variation at lower photon count levels with 40 kVp.

CONCLUSION

The results of the current study suggest that photon-counting spectral mammography systems using CdTe detectors have the potential to be used for accurate quantification of volumetric breast density on a pixel-to-pixel basis, with an RMS error of less than 7%.

Quantitative contrast-enhanced spectral mammography based on photon-counting detectors: A feasibility study

PURPOSE

To investigate the feasibility of accurate quantification of iodine mass thickness in contrast-enhanced spectral mammography.

MATERIALS AND METHODS

A computer simulation model was developed to evaluate the performance of a photon-counting spectral mammography system in the application of contrast-enhanced spectral mammography. A figure-of-merit (FOM), which was defined as the decomposed iodine signal-to-noise ratio (SNR) with respect to the square root of the mean glandular dose (MGD), was chosen to optimize the imaging parameters, in terms of beam energy, splitting energy, and prefiltrations for breasts of various thicknesses and densities. Experimental phantom studies were also performed using a beam energy of 40 kVp and a splitting energy of 34 keV with 3 mm Al prefiltration. A two-step calibration method was investigated to quantify the iodine mass thickness, and was validated using phantoms composed of a mixture of glandular and adipose materials, for various breast thicknesses and densities. Finally, the traditional dual-energy log-weighted subtraction method was also studied as a comparison. The measured iodine signal from both methods was compared to the known value to characterize the quantification accuracy and precision.

RESULTS

The optimal imaging parameters, which lead to the highest FOM, were found at a beam energy between 42 and 46 kVp with a splitting energy at 34 keV. The optimal tube voltage decreased as the breast thickness or the Al prefiltration increased. The proposed quantification method was able to measure iodine mass thickness on phantoms of various thicknesses and densities with high accuracy. The root-mean-square (RMS) error for cm-scale lesion phantoms was estimated to be 0.20 mg/cm² . The precision of the technique, characterized by the standard deviation of the measurements, was estimated to be 0.18 mg/cm² . The traditional weighted subtraction method also predicted a linear correlation between the measured signal and the known iodine mass thickness. However, the correlation slope and offset values were strongly dependent on the total breast thickness and density.

CONCLUSION

The results of this study suggest that iodine mass thickness for cm-scale lesions can be accurately quantified with contrast-enhanced spectral mammography. The quantitative information can potentially improve the differential power for malignancy.

Microcalcification detectability using a bench-top prototype photon-counting breast CT based on a Si strip detector

PURPOSE

To investigate the feasibility of detecting breast microcalcification (μCa) with a dedicated breast computed tomography (CT) system based on energy-resolved photon-counting silicon (Si) strip detectors.

METHODS

The proposed photon-counting breast CT system and a bench-top prototype photon-counting breast CT system were simulated using a simulation package written in matlab to determine the smallest detectable μCa. A 14 cm diameter cylindrical phantom made of breast tissue with 20% glandularity was used to simulate an average-sized breast. Five different size groups of calcium carbonate grains, from 100 to 180 μm in diameter, were simulated inside of the cylindrical phantom. The images were acquired with a mean glandular dose (MGD) in the range of 0.7-8 mGy. A total of 400 images was used to perform a reader study. Another simulation study was performed using a 1.6 cm diameter cylindrical phantom to validate the experimental results from a bench-top prototype breast CT system. In the experimental study, a bench-top prototype CT system was constructed using a tungsten anode x-ray source and a single line 256-pixels Si strip photon-counting detector with a pixel pitch of 100 μm. Calcium carbonate grains, with diameter in the range of 105-215 μm, were embedded in a cylindrical plastic resin phantom to simulate μCas. The physical phantoms were imaged at 65 kVp with an entrance exposure in the range of 0.6-8 mGy. A total of 500 images was used to perform another reader study. The images were displayed in random order to three blinded observers, who were asked to give a 4-point confidence rating on each image regarding the presence of μCa. The μCa detectability for each image was evaluated by using the average area under the receiver operating characteristic curve (AUC) across the readers.

RESULTS

The simulation results using a 14 cm diameter breast phantom showed that the proposed photon-counting breast CT system can achieve high detection accuracy with an average AUC greater than 0.89 ± 0.07 for μCas larger than 120 μm in diameter at a MGD of 3 mGy. The experimental results using a 1.6 cm diameter breast phantom showed that the prototype system can achieve an average AUC greater than 0.98 ± 0.01 for μCas larger than 140 μm in diameter using an entrance exposure of 1.2 mGy.

CONCLUSIONS

The proposed photon-counting breast CT system based on a Si strip detector can potentially offer superior image quality to detect μCa with a lower dose level than a standard two-view mammography.

Characterization of energy response for photon-counting detectors using x-ray fluorescence

PURPOSE

To investigate the feasibility of characterizing a Si strip photon-counting detector using x-ray fluorescence.

METHODS

X-ray fluorescence was generated by using a pencil beam from a tungsten anode x-ray tube with 2 mm Al filtration. Spectra were acquired at 90° from the primary beam direction with an energy-resolved photon-counting detector based on an edge illuminated Si strip detector. The distances from the source to target and the target to detector were approximately 19 and 11 cm, respectively. Four different materials, containing silver (Ag), iodine (I), barium (Ba), and gadolinium (Gd), were placed in small plastic containers with a diameter of approximately 0.7 cm for x-ray fluorescence measurements. Linear regression analysis was performed to derive the gain and offset values for the correlation between the measured fluorescence peak center and the known fluorescence energies. The energy resolutions and charge-sharing fractions were also obtained from analytical fittings of the recorded fluorescence spectra. An analytical model, which employed four parameters that can be determined from the fluorescence calibration, was used to estimate the detector response function.

RESULTS

Strong fluorescence signals of all four target materials were recorded with the investigated geometry for the Si strip detector. The average gain and offset of all pixels for detector energy calibration were determined to be 6.95 mV/keV and -66.33 mV, respectively. The detector's energy resolution remained at approximately 2.7 keV for low energies, and increased slightly at 45 keV. The average charge-sharing fraction was estimated to be 36% within the investigated energy range of 20-45 keV. The simulated detector output based on the proposed response function agreed well with the experimental measurement.

CONCLUSIONS

The performance of a spectral imaging system using energy-resolved photon-counting detectors is very dependent on the energy calibration of the detector. The proposed x-ray fluorescence technique offers an accurate and efficient way to calibrate the energy response of a photon-counting detector.

Breast tissue decomposition with spectral distortion correction: a postmortem study

PURPOSE

To investigate the feasibility of an accurate measurement of water, lipid, and protein composition of breast tissue using a photon-counting spectral computed tomography (CT) with spectral distortion corrections.

METHODS

Thirty-eight postmortem breasts were imaged with a cadmium-zinc-telluride-based photon-counting spectral CT system at 100 kV. The energy-resolving capability of the photon-counting detector was used to separate photons into low and high energy bins with a splitting energy of 42 keV. The estimated mean glandular dose for each breast ranged from 1.8 to 2.2 mGy. Two spectral distortion correction techniques were implemented, respectively, on the raw images to correct the nonlinear detector response due to pulse pileup and charge-sharing artifacts. Dual energy decomposition was then used to characterize each breast in terms of water, lipid, and protein content. In the meantime, the breasts were chemically decomposed into their respective water, lipid, and protein components to provide a gold standard for comparison with dual energy decomposition results.

RESULTS

The accuracy of the tissue compositional measurement with spectral CT was determined by comparing to the reference standard from chemical analysis. The averaged root-mean-square error in percentage composition was reduced from 15.5% to 2.8% after spectral distortion corrections.

CONCLUSIONS

The results indicate that spectral CT can be used to quantify the water, lipid, and protein content in breast tissue. The accuracy of the compositional analysis depends on the applied spectral distortion correction technique.

Sparse-view spectral CT reconstruction using spectral patch-based low-rank penalty

Spectral computed tomography (CT) is a promising technique with the potential for improving lesion detection, tissue characterization, and material decomposition. In this paper, we are interested in kVp switching-based spectral CT that alternates distinct kVp X-ray transmissions during gantry rotation. This system can acquire multiple X-ray energy transmissions without additional radiation dose. However, only sparse views are generated for each spectral measurement; and the spectra themselves are limited in number. To address these limitations, we propose a penalized maximum likelihood method using spectral patch-based low-rank penalty, which exploits the self-similarity of patches that are collected at the same position in spectral images. The main advantage is that the relatively small number of materials within each patch allows us to employ the low-rank penalty that is less sensitive to intensity changes while preserving edge directions. In our optimization formulation, the cost function consists of the Poisson log-likelihood for X-ray transmission and the nonconvex patch-based low-rank penalty. Since the original cost function is difficult to minimize directly, we propose an optimization method using separable quadratic surrogate and concave convex procedure algorithms for the log-likelihood and penalty terms, which results in an alternating minimization that provides a computational advantage because each subproblem can be solved independently. We performed computer simulations and a real experiment using a kVp switching-based spectral CT with sparse-view measurements, and compared the proposed method with conventional algorithms. We confirmed that the proposed method improves spectral images both qualitatively and quantitatively. Furthermore, our GPU implementation significantly reduces the computational cost.

Nanoparticle contrast agents for computed tomography: a focus on micelles

Computed tomography (CT) is an X-ray-based whole-body imaging technique that is widely used in medicine. Clinically approved contrast agents for CT are iodinated small molecules or barium suspensions. Over the past seven years there has been a great increase in the development of nanoparticles as CT contrast agents. Nanoparticles have several advantages over small molecule CT contrast agents, such as long blood-pool residence times and the potential for cell tracking and targeted imaging applications. Furthermore, there is a need for novel CT contrast agents, owing to the growing population of renally impaired patients and patients hypersensitive to iodinated contrast. Micelles and lipoproteins, a micelle-related class of nanoparticle, have notably been adapted as CT contrast agents. In this review we discuss the principles of CT image formation and the generation of CT contrast. We discuss the progress in developing nontargeted, targeted and cell tracking nanoparticle CT contrast agents. We feature agents based on micelles and used in conjunction with spectral CT. The large contrast agent doses needed will necessitate careful toxicology studies prior to clinical translation. However, the field has seen tremendous advances in the past decade and we expect many more advances to come in the next decade.

Breast density quantification using magnetic resonance imaging (MRI) with bias field correction: a postmortem study

PURPOSE

Quantification of breast density based on three-dimensional breast MRI may provide useful information for the early detection of breast cancer. However, the field inhomogeneity can severely challenge the computerized image segmentation process. In this work, the effect of the bias field in breast density quantification has been investigated with a postmortem study.

METHODS

T1-weighted images of 20 pairs of postmortem breasts were acquired on a 1.5 T breast MRI scanner. Two computer-assisted algorithms were used to quantify the volumetric breast density. First, standard fuzzy c-means (FCM) clustering was used on raw images with the bias field present. Then, the coherent local intensity clustering (CLIC) method estimated and corrected the bias field during the iterative tissue segmentation process. Finally, FCM clustering was performed on the bias-field-corrected images produced by CLIC method. The left-right correlation for breasts in the same pair was studied for both segmentation algorithms to evaluate the precision of the tissue classification. Finally, the breast densities measured with the three methods were compared to the gold standard tissue compositions obtained from chemical analysis. The linear correlation coefficient, Pearson's r, was used to evaluate the two image segmentation algorithms and the effect of bias field.

RESULTS

The CLIC method successfully corrected the intensity inhomogeneity induced by the bias field. In left-right comparisons, the CLIC method significantly improved the slope and the correlation coefficient of the linear fitting for the glandular volume estimation. The left-right breast density correlation was also increased from 0.93 to 0.98. When compared with the percent fibroglandular volume (%FGV) from chemical analysis, results after bias field correction from both the CLIC the FCM algorithms showed improved linear correlation. As a result, the Pearson's r increased from 0.86 to 0.92 with the bias field correction.

CONCLUSIONS

The investigated CLIC method significantly increased the precision and accuracy of breast density quantification using breast MRI images by effectively correcting the bias field. It is expected that a fully automated computerized algorithm for breast density quantification may have great potential in clinical MRI applications.

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.

Measurement of breast tissue composition with dual energy cone-beam computed tomography: a postmortem study

PURPOSE

To investigate the feasibility of a three-material compositional measurement of water, lipid, and protein content of breast tissue with dual kVp cone-beam computed tomography (CT) for diagnostic purposes.

METHODS

Simulations were performed on a flat panel-based computed tomography system with a dual kVp technique in order to guide the selection of experimental acquisition parameters. The expected errors induced by using the proposed calibration materials were also estimated by simulation. Twenty pairs of postmortem breast samples were imaged with a flat-panel based dual kVp cone-beam CT system, followed by image-based material decomposition using calibration data obtained from a three-material phantom consisting of water, vegetable oil, and polyoxymethylene plastic. The tissue samples were then chemically decomposed into their respective water, lipid, and protein contents after imaging to allow direct comparison with data from dual energy decomposition.

RESULTS

Guided by results from simulation, the beam energies for the dual kVp cone-beam CT system were selected to be 50 and 120 kVp with the mean glandular dose divided equally between each exposure. The simulation also suggested that the use of polyoxymethylene as the calibration material for the measurement of pure protein may introduce an error of -11.0%. However, the tissue decomposition experiments, which employed a calibration phantom made out of water, oil, and polyoxymethylene, exhibited strong correlation with data from the chemical analysis. The average root-mean-square percentage error for water, lipid, and protein contents was 3.58% as compared with chemical analysis.

CONCLUSIONS

The results of this study suggest that the water, lipid, and protein contents can be accurately measured using dual kVp cone-beam CT. The tissue compositional information may improve the sensitivity and specificity for breast cancer diagnosis.

Breast density quantification with cone-beam CT: a post-mortem study

Forty post-mortem breasts were imaged with a flat-panel based cone-beam x-ray CT system at 50 kVp. The feasibility of breast density quantification has been investigated using standard histogram thresholding and an automatic segmentation method based on the fuzzy c-means algorithm (FCM). The breasts were chemically decomposed into water, lipid, and protein immediately after image acquisition was completed. The per cent fibroglandular volume (%FGV) from chemical analysis was used as the gold standard for breast density comparison. Both image-based segmentation techniques showed good precision in breast density quantification with high linear coefficients between the right and left breast of each pair. When comparing with the gold standard using %FGV from chemical analysis, Pearson's r-values were estimated to be 0.983 and 0.968 for the FCM clustering and the histogram thresholding techniques, respectively. The standard error of the estimate was also reduced from 3.92% to 2.45% by applying the automatic clustering technique. The results of the postmortem study suggested that breast tissue can be characterized in terms of water, lipid and protein contents with high accuracy by using chemical analysis, which offers a gold standard for breast density studies comparing different techniques. In the investigated image segmentation techniques, the FCM algorithm had high precision and accuracy in breast density quantification. In comparison to conventional histogram thresholding, it was more efficient and reduced inter-observer variation.

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.

K-edge ratio method for identification of multiple nanoparticulate contrast agents by spectral CT imaging

OBJECTIVE

Recently introduced energy-sensitive X-ray CT makes it feasible to discriminate different nanoparticulate contrast materials. The purpose of this work is to present a K-edge ratio method for differentiating multiple simultaneous contrast agents using spectral CT.

METHODS

The ratio of two images relevant to energy bins straddling the K-edge of the materials is calculated using an analytic CT simulator. In the resulting parametric map, the selected contrast agent regions can be identified using a thresholding algorithm. The K-edge ratio algorithm is applied to spectral images of simulated phantoms to identify and differentiate up to four simultaneous and targeted CT contrast agents.

RESULTS

We show that different combinations of simultaneous CT contrast agents can be identified by the proposed K-edge ratio method when energy-sensitive CT is used. In the K-edge parametric maps, the pixel values for biological tissues and contrast agents reach a maximum of 0.95, whereas for the selected contrast agents, the pixel values are larger than 1.10. The number of contrast agents that can be discriminated is limited owing to photon starvation. For reliable material discrimination, minimum photon counts corresponding to 140 kVp, 100 mAs and 5-mm slice thickness must be used.

CONCLUSION

The proposed K-edge ratio method is a straightforward and fast method for identification and discrimination of multiple simultaneous CT contrast agents.

ADVANCES IN KNOWLEDGE

A new spectral CT-based algorithm is proposed which provides a new concept of molecular CT imaging by non-iteratively identifying multiple contrast agents when they are simultaneously targeting different organs.

Tight-frame based iterative image reconstruction for spectral breast CT

PURPOSE

To investigate tight-frame based iterative reconstruction (TFIR) technique for spectral breast computed tomography (CT) using fewer projections while achieving greater image quality.

METHODS

The experimental data were acquired with a fan-beam breast CT system based on a cadmium zinc telluride photon-counting detector. The images were reconstructed with a varying number of projections using the TFIR and filtered backprojection (FBP) techniques. The image quality between these two techniques was evaluated. The image's spatial resolution was evaluated using a high-resolution phantom, and the contrast to noise ratio (CNR) was evaluated using a postmortem breast sample. The postmortem breast samples were decomposed into water, lipid, and protein contents based on images reconstructed from TFIR with 204 projections and FBP with 614 projections. The volumetric fractions of water, lipid, and protein from the image-based measurements in both TFIR and FBP were compared to the chemical analysis.

RESULTS

The spatial resolution and CNR were comparable for the images reconstructed by TFIR with 204 projections and FBP with 614 projections. Both reconstruction techniques provided accurate quantification of water, lipid, and protein composition of the breast tissue when compared with data from the reference standard chemical analysis.

CONCLUSIONS

Accurate breast tissue decomposition can be done with three fold fewer projection images by the TFIR technique without any reduction in image spatial resolution and CNR. This can result in a two-third reduction of the patient dose in a multislit and multislice spiral CT system in addition to the reduced scanning time in this system.

Quantification of breast density with spectral mammography based on a scanned multi-slit photon-counting detector: a feasibility study

A simple and accurate measurement of breast density is crucial for the understanding of its impact in breast cancer risk models. The feasibility to quantify volumetric breast density with a photon-counting spectral mammography system has been investigated using both computer simulations and physical phantom studies. A computer simulation model involved polyenergetic spectra from a tungsten anode x-ray tube and a Si-based photon-counting detector has been evaluated for breast density quantification. The figure-of-merit (FOM), which was defined as the signal-to-noise ratio of the dual energy image with respect to the square root of mean glandular dose, was chosen to optimize the imaging protocols, in terms of tube voltage and splitting energy. A scanning multi-slit photon-counting spectral mammography system has been employed in the experimental study to quantitatively measure breast density using dual energy decomposition with glandular and adipose equivalent phantoms of uniform thickness. Four different phantom studies were designed to evaluate the accuracy of the technique, each of which addressed one specific variable in the phantom configurations, including thickness, density, area and shape. In addition to the standard calibration fitting function used for dual energy decomposition, a modified fitting function has been proposed, which brought the tube voltages used in the imaging tasks as the third variable in dual energy decomposition. For an average sized 4.5 cm thick breast, the FOM was maximized with a tube voltage of 46 kVp and a splitting energy of 24 keV. To be consistent with the tube voltage used in current clinical screening exam (∼32 kVp), the optimal splitting energy was proposed to be 22 keV, which offered a FOM greater than 90% of the optimal value. In the experimental investigation, the root-mean-square (RMS) error in breast density quantification for all four phantom studies was estimated to be approximately 1.54% using standard calibration function. The results from the modified fitting function, which integrated the tube voltage as a variable in the calibration, indicated a RMS error of approximately 1.35% for all four studies. The results of the current study suggest that photon-counting spectral mammography systems may potentially be implemented for an accurate quantification of volumetric breast density, with an RMS error of less than 2%, using the proposed dual energy imaging technique.

Image-based spectral distortion correction for photon-counting x-ray detectors

PURPOSE

To investigate the feasibility of using an image-based method to correct for distortions induced by various artifacts in the x-ray spectrum recorded with photon-counting detectors for their application in breast computed tomography (CT).

METHODS

The polyenergetic incident spectrum was simulated with the tungsten anode spectral model using the interpolating polynomials (TASMIP) code and carefully calibrated to match the x-ray tube in this study. Experiments were performed on a Cadmium-Zinc-Telluride (CZT) photon-counting detector with five energy thresholds. Energy bins were adjusted to evenly distribute the recorded counts above the noise floor. BR12 phantoms of various thicknesses were used for calibration. A nonlinear function was selected to fit the count correlation between the simulated and the measured spectra in the calibration process. To evaluate the proposed spectral distortion correction method, an empirical fitting derived from the calibration process was applied on the raw images recorded for polymethyl methacrylate (PMMA) phantoms of 8.7, 48.8, and 100.0 mm. Both the corrected counts and the effective attenuation coefficient were compared to the simulated values for each of the five energy bins. The feasibility of applying the proposed method to quantitative material decomposition was tested using a dual-energy imaging technique with a three-material phantom that consisted of water, lipid, and protein. The performance of the spectral distortion correction method was quantified using the relative root-mean-square (RMS) error with respect to the expected values from simulations or areal analysis of the decomposition phantom.

RESULTS

The implementation of the proposed method reduced the relative RMS error of the output counts in the five energy bins with respect to the simulated incident counts from 23.0%, 33.0%, and 54.0% to 1.2%, 1.8%, and 7.7% for 8.7, 48.8, and 100.0 mm PMMA phantoms, respectively. The accuracy of the effective attenuation coefficient of PMMA estimate was also improved with the proposed spectral distortion correction. Finally, the relative RMS error of water, lipid, and protein decompositions in dual-energy imaging was significantly reduced from 53.4% to 6.8% after correction was applied.

CONCLUSIONS

The study demonstrated that dramatic distortions in the recorded raw image yielded from a photon-counting detector could be expected, which presents great challenges for applying the quantitative material decomposition method in spectral CT. The proposed semi-empirical correction method can effectively reduce these errors caused by various artifacts, including pulse pileup and charge sharing effects. Furthermore, rather than detector-specific simulation packages, the method requires a relatively simple calibration process and knowledge about the incident spectrum. Therefore, it may be used as a generalized procedure for the spectral distortion correction of different photon-counting detectors in clinical breast CT systems.

A SPECT Camera for Combined MRI and SPECT for Small Animals

We describe an MR-compatible SPECT camera for small animals. The SPECT camera system can be inserted into the bore of a state-of-the-art MRI system and allows researchers to acquire tomographic images from a mouse in-vivo with the MRI and the SPECT acquiring simultaneously. The SPECT system provides functional information, while MRI provides anatomical information. Until today it was impossible to operate conventional SPECT inside the MRI because of mutual interference. The new SPECT technology is based on semiconductor radiation sensors (CZT, ASICs), and it fits into conventional high field MRI systems with a minimum 12-cm bore size. The SPECT camera has an MR-compatible multi-pinhole collimator for mice with a ø25-mm field-of-view. For the work reported here we assembled a prototype SPECT camera system and acquired SPECT and MRI data from radioactive sources and resolution phantoms using the camera outside and inside the MRI.