Justin L. Ducote

Radiation dose reduction using a CdZnTe-based computed tomography system: Comparison to flat-panel detectors

PURPOSE Although x-ray projection mammography has been very effective in early detection of breast cancer, its utility is reduced in the detection of small lesions that are occult or in dense breasts. One drawback is that the inherent superposition of parenchymal structures makes visualization of small lesions difficult. Breast computed tomography using flat-panel detectors has been developed to address this limitation by producing three-dimensional data while at the same time providing more comfort to the patients by eliminating breast compression. Flat panels are charge integrating detectors and therefore lack energy resolution capability. Recent advances in solid state semiconductor x-ray detector materials and associated electronics allow the investigation of x-ray imaging systems that use a photon counting and energy discriminating detector, which is the subject of this article. METHODS A small field-of-view computed tomography (CT) system that uses CdZnTe (CZT) photon counting detector was compared to one that uses a flat-panel detector for different imaging tasks in breast imaging. The benefits afforded by the CZT detector in the energy weighting modes were investigated. Two types of energy weighting methods were studied: Projection based and image based. Simulation and phantom studies were performed with a 2.5 cm polymethyl methacrylate (PMMA) cylinder filled with iodine and calcium contrast objects. Simulation was also performed on a 10 cm breast specimen. RESULTS The contrast-to-noise ratio improvements as compared to flat-panel detectors were 1.30 and 1.28 (projection based) and 1.35 and 1.25 (image based) for iodine over PMMA and hydroxylapatite over PMMA, respectively. Corresponding simulation values were 1.81 and 1.48 (projection based) and 1.85 and 1.48 (image based). Dose reductions using the CZT detector were 52.05% and 49.45% for iodine and hydroxyapatite imaging, respectively. Image-based weighting was also found to have the least beam hardening effect. CONCLUSIONS The results showed that a CT system using an energy resolving detector reduces the dose to the patient while maintaining image quality for various breast imaging tasks.

Quantification of breast density with dual energy mammography: an experimental feasibility study.

PURPOSE Breast density, the percentage of glandular breast tissue, has been shown to be a strong indicator of breast cancer risk. A quantitative method to measure breast density with dual energy mammography was investigated using physical phantoms. METHODS The dual energy mammography system used a tungsten anode x-ray tube with a 50 microm rhodium beam filter for low energy images and a 300 microm copper beam filter for high energy images. Glandular and adipose equivalent phantoms of uniform thickness were used to calibrate a dual energy basis decomposition algorithm. Four different phantom studies were used to evaluate the technique. The first study consisted of phantoms with thicknesses of 2.5-8.5 cm in 0.5 cm steps with variable densities centered at a mean of 28%. The second study consisted of phantoms at a fixed thickness of 4.0 cm, which ranged in densities from 0% to 100% in increments of 12.5%. The third study consisted of 4.0 cm thick phantoms at densities of 25%, 50% and 75% each imaged at three areal sizes, approximately 62.5, 125, and 250 cm2, in order to assess the effect of breast size on density measurement. The fourth study consisted of step phantoms designed to more closely mimic the shape of a female breast with maximal thicknesses from 3.0 to 7.0 cm at a fixed density of 50%. All images were corrected for x-ray scatter. RESULTS The RMS errors in breast density measurements were 0.44% for the variable thickness phantoms, 0.64% for the variable density phantoms, 2.87% for the phantoms of different areal sizes, and 4.63% for step phantoms designed to closely resemble the shape of a breast. CONCLUSIONS The results of the phantom studies indicate that dual energy mammography can be used to measure breast density with an RMS error of approximately 5%.

Scatter correction in digital mammography based on image deconvolution

X-ray scatter is a major cause of nonlinearity in densitometry measurements using digital mammography. Previous scatter correction techniques have primarily used a single scatter point spread function to estimate x-ray scatter. In this study, a new algorithm to correct x-ray scatter based on image convolution was implemented using a spatially variant scatter point spread function which is energy and thickness dependent. The scatter kernel was characterized in terms of its scattering fraction (SF) and scatter radial extent (k) on uniform Lucite phantoms with thickness of 0.8-8.0 cm. The algorithm operates on a pixel-by-pixel basis by grouping pixels of similar thicknesses into a series of mask images that are individually deconvolved using Fourier image analysis with a distinct kernel for each image. The algorithm was evaluated with three Lucite step phantoms and one anthropomorphic breast phantom using a full-field digital mammography system at energies of 24, 28, 31 and 49 kVp. The true primary signal was measured with a multi-hole collimator. The effect on image quality was also evaluated. For all 16 studies, the average mean percentage error in estimating the true primary signal was found to be -2.13% and the average rms percentage error was 2.60%. The image quality was seen to improve at every energy up to 25% at 49 kVp. The results indicate that a technique based on a spatially variant scatter point spread function can accurately estimate x-ray scatter.

Real-time tumor tracking using implanted positron emission markers: Concept and simulation study

The delivery accuracy of radiation therapy for pulmonary and abdominal tumors suffers from tumor motion due to respiration. Respiratory gating should be applied to avoid the use of a large target volume margin that results in a substantial dose to the surrounding normal tissue. Precise respiratory gating requires the exact spatial position of the tumor to be determined in real time during treatment. Usually, fiducial markers are implanted inside or next to the tumor to provide both accurate patient setup and real-time tumor tracking. However, current tumor tracking systems require either substantial x-ray exposure to the patient or large fiducial markers that limit the value of their application for pulmonary tumors. We propose a real-time tumor tracking system using implanted positron emission markers (PeTrack). Each marker will be labeled with low activity positron emitting isotopes, such as 124I, 74As, or 84Rb. These isotopes have half-lives comparable to the duration of radiation therapy (from a few days to a few weeks). The size of the proposed PeTrack marker will be 0.5-0.8 mm, which is approximately one-half the size of markers currently employed in other techniques. By detecting annihilation gammas using position-sensitive detectors, multiple positron emission markers can be tracked in real time. A multimarker localization algorithm was developed using an Expectation-Maximization clustering technique. A Monte Carlo simulation model was developed for the PeTrack system. Patient dose, detector sensitivity, and scatter fraction were evaluated. Depending on the isotope, the lifetime dose from a 3.7 MBq PeTrack marker was determined to be 0.7-5.0 Gy at 10 mm from the marker. At the center of the field of view (FOV), the sensitivity of the PeTrack system was 240-320 counts/s per 1 MBq marker activity within a 30 cm thick patient. The sensitivity was reduced by 45% when the marker was near the edge of the FOV. The scatter fraction ranged from 12% (124I, 74As) to 16% (84Rb). In addition, four markers (labeled with 124I) inside a 30 cm diameter water phantom were simulated to evaluate the feasibility of the multimarker localization algorithm. Localization was considered successful if a marker was localized to within 2 mm from its true location. The success rate of marker localization was found to depend on the number of annihilation events used and the error in the initial estimate of the marker position. By detecting 250 positron annihilation events from 4 markers (average of 62 events per marker), the marker success rates for initial errors of +/-5, +/-10, and +/-15 mm were 99.9%, 99.6%, and 92.4%, respectively. Moreover, the average localization error was 0.55 (+/-0.27) mm, which was independent of initial error. The computing time for localizing four markers was less than 20 ms (Pentium 4, 2.8 GHz processor, 512 MB memory). In conclusion, preliminary results demonstrate that the PeTrack technique can potentially provide real-time tumor tracking with low doses associated with the markers activity. Furthermore, the small size of PeTrack markers is expected to facilitate implantation and reduce patient risk.

Feasibility of real time dual‐energy imaging based on a flat panel detector for coronary artery calcium quantification

The feasibility of a real-time dual-energy imaging technique with dynamic filtration using a flat panel detector for quantifying coronary arterial calcium was evaluated. In this technique, the x-ray beam was switched at 15 Hz between 60 kVp and 120 kVp with the 120 kVp beam having an additional 0.8 mm silver filter. The performance of the dynamic filtration technique was compared with a static filtration technique (4 mm Al+0.2 mm Cu for both beams). The ability to quantify calcium mass was evaluated using calcified arterial vessel phantoms with 20-230 mg of hydroxylapatite. The vessel phantoms were imaged over a Lucite phantom and then an anthropomorphic chest phantom. The total thickness of Lucite phantom ranges from 13.5-26.5 cm to simulate patient thickness of 16-32 cm. The calcium mass was measured using a densitometric technique. The effective dose to patient was estimated from the measured entrance exposure. The effects of patient thickness on contrast-to-noise ratio (CNR), effective dose, and the precision of calcium mass quantification (i.e., the frame to frame variability) were studied. The effects of misregistration artifacts were also measured by shifting the vessel phantoms manually between low- and high-energy images. The results show that, with the same detector signal level, the dynamic filtration technique produced 70% higher calcium contrast-to-noise ratio with only 4% increase in patient dose as compared to the static filtration technique. At the same time, x-ray tube loading increased by 30% with dynamic filtration. The minimum detectability of calcium with anatomical background was measured to be 34 mg of hydroxyapatite. The precision in calcium mass measurement, determined from 16 repeated dual-energy images, ranges from 13 mg to 41 mg when the patient thickness increased from 16 to 32 cm. The CNR was found to decrease with the patient thickness linearly at a rate of (-7%/cm). The anatomic background produced measurement root-mean-square (RMS) errors of 13 mg and 18 mg when the vessel phantoms were imaged over a uniform (over the rib) and nonuniform (across the edge of rib) bone background, respectively. Misregistration artifacts due to motions of up to 1.0 mm between the low- and high-energy images introduce RMS error of less than 4.3 mg, which is much smaller than the frame to frame variability and the measurement error due to anatomic background. The effective dose ranged from 1.1 to 6.6 microSv for each dual-energy image, depending on patient thickness. The study shows that real-time dual-energy imaging can potentially be used as a low dose technique for quantifying coronary arterial calcium.

Quantification of breast density with dual energy mammography: A simulation study

Breast density, the percentage of glandular breast tissue, has been identified as an important yet underutilized risk factor in the development of breast cancer. A quantitative method to measure breast density with dual energy imaging was investigated using a computer simulation model. Two configurations to measure breast density were evaluated: the usage of monoenergetic beams and an ideal detector, and the usage of polyenergetic beams with spectra from a tungsten anode x-ray tube with a detector modeled after a digital mammography system. The simulation model calculated the mean glandular dose necessary to quantify the variability of breast density to within 1/3%. The breast was modeled as a semicircle 10 cm in radius with equal homogenous thicknesses of adipose and glandular tissues. Breast thicknesses were considered in the range of 2-10 cm and energies in the range of 10-150 keV for the two monoenergetic beams, and 20-150 kVp for spectra with a tungsten anode x-ray tube. For a 4.2 cm breast thickness, the required mean glandular doses were 0.183 microGy for two monoenergetic beams at 19 and 71 keV, and 9.85 microGy for two polyenergetic spectra from a tungsten anode at 32 and 96 kVp with beam filtrations of 50 microm Rh and 300 microm Cu for the low and high energy beams, respectively. The results suggest that for either configuration, breast density can be precisely measured with dual energy imaging requiring only a small amount of additional dose to the breast. The possibility of using a standard screening mammogram as the low energy image is also discussed.

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

PURPOSE To investigate the feasibility of breast tissue composition in terms of water, lipid, and protein with a cadmium-zinc-telluride (CZT) based computed tomography (CT) system to help better characterize suspicious lesions. METHODS Simulations and experimental studies were performed using a spectral CT system equipped with a CZT-based photon-counting detector with energy resolution. Simulations of the figure-of-merit (FOM), the signal-to-noise ratio (SNR) of the dual energy image with respect to the square root of mean glandular dose (MGD), were performed to find the optimal configuration of the experimental acquisition parameters. A calibration phantom 3.175 cm in diameter was constructed from polyoxymethylene plastic with cylindrical holes that were filled with water and oil. Similarly, sized samples of pure adipose and pure lean bovine tissues were used for the three-material decomposition. Tissue composition results computed from the images were compared to the chemical analysis data of the tissue samples. RESULTS The beam energy was selected to be 100 kVp with a splitting energy of 40 keV. The tissue samples were successfully decomposed into water, lipid, and protein contents. The RMS error of the volumetric percentage for the three-material decomposition, as compared to data from the chemical analysis, was estimated to be approximately 5.7%. CONCLUSIONS The results of this study suggest that the CZT-based photon-counting detector may be employed in the CT system to quantify the water, lipid, and protein mass densities in tissue with a relatively good agreement.

Volumetric lean percentage measurement using dual energy mammography.

PURPOSE Currently, there is no accepted standard for measuring breast density. Dual energy mammography, which has demonstrated accurate measurement in phantoms, has been proposed as one possible method. To examine the use of chemical analysis as a possible means to validate breast density measurements from dual energy mammography, a bovine tissue model was investigated. Known quantities of lean and adipose tissue were compared with composition values measured from dual energy images and chemical analysis. METHODS Theoretical simulations were performed to assess the impact variations in breast composition would have on measurement of breast density from a single calibration. Fourteen ex-vivo tissue samples composed of varying amounts of pure lean tissue and pure adipose tissue (lean percentage) from 0 to 100%, in increments of 10%, were imaged using dual energy mammography. This was followed by chemical analysis based on desiccation, trituration, and fat extraction with petroleum ether to determine water, lipid, and protein content. The volumetric lean percentage (VLP) as measured from images (VLP(I)) and as derived from chemical analysis data (VLP(CA)) were compared with the VLP calculated from measurements of sample mass with a scale (VLP(M)). Finally, data from the bovine tissue model in this study were compared to compositional data from a previous report of human tissue composition. RESULTS The results from simulation suggest a substantial impact on measuring breast density is likely due to changes in anatomical breast composition. VLP(I) was related to the VLP(M) by VLP(I) = 1.53 VLP(M) + 10.0 (r2 > 0.99). VLP(CA) was related to VLP(M) by VLP(CA) = 0.76 VLP(M) + 22.8 (r2 > 0.99). VLP(I) was related to VLP(CA) by VLP(I) = 2.00 VLP(CA) - 35.6 (r2 > 0.99). Bovine adipose tissue was shown to be very similar to human adipose tissue in terms of water, lipid, and protein content with RMS differences of 1.2%. Bovine lean tissue was shown to be very similar to human skeletal muscle tissue and somewhat similar to human mammary gland tissue with RMS differences of 0.4 and 22.2%, respectively. CONCLUSIONS The results of this study show strong linear relationships between volumetric lean percentage measurements using dual energy mammography, chemical analysis and the actual mass. Determining the existence of a relationship between VLP(I) and VLP(CA) was necessary before comparing density results from the dual energy technique to composition data from chemical analysis for samples of unknown composition.

Optimization of a flat‐panel based real time dual‐energy system for cardiac imaging

A simulation study was conducted to evaluate the effects of high-energy beam filtration, dual-gain operation and noise reduction on dual-energy images using a digital flat-panel detector. High-energy beam filtration increases image contrast through greater beam separation and tends to reduce total radiation exposure and dose per image pair. It is also possible to reduce dual-energy image noise by acquiring low and high-energy images at two different detector gains. In addition, dual-energy noise reduction algorithms can further reduce image noise. The cumulative effect of these techniques applied in series was investigated in this study. The contrast from a small thickness of calcium was simulated over a step phantom of tissue equivalent material with a CsI phosphor as the image detector. The dual-energy contrast-to-noise ratio was calculated using values of energy absorption and energy variance. A figure-of-merit (FOM) was calculated from dual-energy contrast-to-noise ratio (CNR) and patient effective dose estimated from values of entrance exposure. Filter atomic numbers in the range of 1-100 were considered with thicknesses ranging from 0-2500 mg/cm2. The simulation examined combinations of the above techniques which maximized the FOM. The application of a filter increased image contrast by as much as 45%. Near maximal increases were seen for filter atomic numbers in the range of 40-60 and 85-100 with masses above 750 mg/cm2. Increasing filter thickness beyond 1000 mg/cm2 increased tube loading without further significant contrast enhancement. No additional FOM improvements were seen with dual gain before or after the application of any noise reduction algorithm. Narrow beam experiments were carried out to verify predictions. The measured FOM increased by more than a factor of 3.5 for a silver filter thickness of 800 microm, equal energy weighting and application of a noise clipping algorithm. The main limitation of dynamic high-energy filtration is increased tube loading. The results of this study can be used to help develop an optimal dual-energy imaging system.

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.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.