Huy Le

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.

Least squares parameter estimation methods for material decomposition with energy discriminating detectors.

PURPOSE Energy resolving detectors provide more than one spectral measurement in one image acquisition. The purpose of this study is to investigate, with simulation, the ability to decompose four materials using energy discriminating detectors and least squares minimization techniques. METHODS Three least squares parameter estimation decomposition techniques were investigated for four-material breast imaging tasks in the image domain. The first technique treats the voxel as if it consisted of fractions of all the materials. The second method assumes that a voxel primarily contains one material and divides the decomposition process into segmentation and quantification tasks. The third is similar to the second method but a calibration was used. The simulated computed tomography (CT) system consisted of an 80 kVp spectrum and a CdZnTe (CZT) detector that could resolve the x-ray spectrum into five energy bins. A postmortem breast specimen was imaged with flat panel CT to provide a model for the digital phantoms. Hydroxyapatite (HA) (50, 150, 250, 350, 450, and 550 mg/ml) and iodine (4, 12, 20, 28, 36, and 44 mg/ml) contrast elements were embedded into the glandular region of the phantoms. Calibration phantoms consisted of a 30/70 glandular-to-adipose tissue ratio with embedded HA (100, 200, 300, 400, and 500 mg/ml) and iodine (5, 15, 25, 35, and 45 mg/ml). The x-ray transport process was simulated where the Beer-Lambert law, Poisson process, and CZT absorption efficiency were applied. Qualitative and quantitative evaluations of the decomposition techniques were performed and compared. The effect of breast size was also investigated. RESULTS The first technique decomposed iodine adequately but failed for other materials. The second method separated the materials but was unable to quantify the materials. With the addition of a calibration, the third technique provided good separation and quantification of hydroxyapatite, iodine, glandular, and adipose tissues. Quantification with this technique was accurate with errors of 9.83% and 6.61% for HA and iodine, respectively. Calibration at one point (one breast size) showed increased errors as the mismatch in breast diameters between calibration and measurement increased. A four-point calibration successfully decomposed breast diameter spanning the entire range from 8 to 20 cm. For a 14 cm breast, errors were reduced from 5.44% to 1.75% and from 6.17% to 3.27% with the multipoint calibration for HA and iodine, respectively. CONCLUSIONS The results of the simulation study showed that a CT system based on CZT detectors in conjunction with least squares minimization technique can be used to decompose four materials. The calibrated least squares parameter estimation decomposition technique performed the best, separating and accurately quantifying the concentrations of hydroxyapatite and iodine.

Segmentation and quantification of materials with energy discriminating computed tomography: A phantom study

PURPOSE To experimentally investigate whether a computed tomography (CT) system based on CdZnTe (CZT) detectors in conjunction with a least-squares parameter estimation technique can be used to decompose four different materials. METHODS The material decomposition process was divided into a segmentation task and a quantification task. A least-squares minimization algorithm was used to decompose materials with five measurements of the energy dependent linear attenuation coefficients. A small field-of-view energy discriminating CT system was built. The CT system consisted of an x-ray tube, a rotational stage, and an array of CZT detectors. The CZT array was composed of 64 pixels, each of which is 0.8 x 0.8 x 3 mm. Images were acquired at 80 kVp in fluoroscopic mode at 50 ms per frame. The detector resolved the x-ray spectrum into energy bins of 22-32, 33-39, 40-46, 47-56, and 57-80 keV. Four phantoms were constructed from polymethylmethacrylate (PMMA), polyethylene, polyoxymethylene, hydroxyapatite, and iodine. Three phantoms were composed of three materials with embedded hydroxyapatite (50, 150, 250, and 350 mg/ml) and iodine (4, 8, 12, and 16 mg/ml) contrast elements. One phantom was composed of four materials with embedded hydroxyapatite (150 and 350 mg/ml) and iodine (8 and 16 mg/ml). Calibrations consisted of PMMA phantoms with either hydroxyapatite (100, 200, 300, 400, and 500 mg/ml) or iodine (5, 15, 25, 35, and 45 mg/ml) embedded. Filtered backprojection and a ramp filter were used to reconstruct images from each energy bin. Material segmentation and quantification were performed and compared between different phantoms. RESULTS All phantoms were decomposed accurately, but some voxels in the base material regions were incorrectly identified. Average quantification errors of hydroxyapatite/iodine were 9.26/7.13%, 7.73/5.58%, and 12.93/8.23% for the three-material PMMA, polyethylene, and polyoxymethylene phantoms, respectively. The average errors for the four-material phantom were 15.62% and 2.76% for hydroxyapatite and iodine, respectively. CONCLUSIONS The calibrated least-squares minimization technique of decomposition performed well in breast imaging tasks with an energy resolving detector. This method can provide material basis images containing concentrations of the relevant materials that can potentially be valuable in the diagnostic process.

Estimation of regional myocardial mass at risk based on distal arterial lumen volume and length using 3D micro-CT images ☆

The determination of regional myocardial mass at risk distal to a coronary occlusion provides valuable prognostic information for a patient with coronary artery disease. The coronary arterial system follows a design rule which allows for the use of arterial branch length and lumen volume to estimate regional myocardial mass at risk. Image processing techniques, such as segmentation, skeletonization and arterial network tracking, are presented for extracting anatomical details of the coronary arterial system using micro-computed tomography (micro-CT). Moreover, a method of assigning tissue voxels to their corresponding arterial branches is presented to determine the dependent myocardial region. The proposed micro-CT technique was utilized to investigate the relationship between the sum of the distal coronary arterial branch lengths and volumes to the dependent regional myocardial mass using a polymer cast of a porcine heart. The correlations of the logarithm of the total distal arterial lengths (L) to the logarithm of the regional myocardial mass (M) for the left anterior descending (LAD), left circumflex (LCX) and right coronary (RCA) arteries were log(L)=0.73log(M)+0.09 (R=0.78), log(L)=0.82log(M)+0.05 (R=0.77) and log(L)=0.85log(M)+0.05 (R=0.87), respectively. The correlation of the logarithm of the total distal arterial lumen volumes (V) to the logarithm of the regional myocardial mass for the LAD, LCX and RCA were log(V)=0.93log(M)-1.65 (R=0.81), log(V)=1.02log(M)-1.79 (R=0.78) and log(V)=1.17log(M)-2.10 (R=0.82), respectively. These morphological relations did not change appreciably for diameter truncations of 600-1400microm. The results indicate that the image processing procedures successfully extracted information from a large 3D dataset of the coronary arterial tree to provide prognostic indications in the form of arterial tree parameters and anatomical area at risk.

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, Pearsons 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.

Effect of area x-ray beam equalization on image quality and dose in digital mammography

In mammography, thick or dense breast regions persistently suffer from reduced contrast-to-noise ratio (CNR) because of degraded contrast from large scatter intensities and relatively high noise. Area x-ray beam equalization can improve image quality by increasing the x-ray exposure to under-penetrated regions without increasing the exposure to other breast regions. Optimal equalization parameters with respect to image quality and patient dose were determined through computer simulations and validated with experimental observations on a step phantom and an anthropomorphic breast phantom. Three parameters important in equalization digital mammography were considered: attenuator material (Z = 13-92), beam energy (22-34 kVp) and equalization level. A Mo/Mo digital mammography system was used for image acquisition. A prototype 16 x 16 piston driven equalization system was used for preparing patient-specific equalization masks. Simulation studies showed that a molybdenum attenuator and an equalization level of 20 were optimal for improving contrast, CNR and figure of merit (FOM = CNR2/dose). Experimental measurements using these parameters showed significant improvements in contrast, CNR and FOM. Moreover, equalized images of a breast phantom showed improved image quality. These results indicate that area beam equalization can improve image quality in digital mammography.

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, Pearsons 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 Pearsons 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.

WE‐A‐201B‐06: Quantification of Breast Density Using Dual Energy Mammography: A Post Mortem Study

Purpose: To investigate the feasibility of measuring breast density in post mortem breast samples with dual energy mammography.Method and Materials: Twenty pairs of post mortem breast samples (n=40) were imaged with a dual energy mammography system. The system was equipped with a tungstenanode x‐ray tube. Low energy images of each sample were acquired at a tube voltage of 28 kVp with a 50 μm rhodium beam filter at 60 mAs. High energy images of each sample were acquired at a tube voltage of 49 kVp with a 300 μm copper filter also at 60 mAs. Each sample was imaged at two different orientations. Half the samples were rotated about their horizontal axis and half the samples were manually reconfigured to simulate CC (craniocaudal) and MLO (mediolateral oblique) views. Scatter correction was performed on all images. Glandular and adipose material thickness maps were generated from each pair of dual energy images. The volume and breast density (glandular fraction) of each breast was calculated from the images of material thickness. Results: The measurements of breast volume for the first (V1) and second (V2) orientation were related by V2 = 1.03 V1 − 6.2 (r2 > 0.99). The measurements of breast density for the first (D1) and second (D2) orientation were related by D2 = 0.97 D1 − 0.03 (r2 > 0.97). The correspondence of breast mass as calculated from dual energy mammograms (MDE) to the mass of the sample as measured from a scale (MS) was related by MDE = 1.01 MS − 8.10 (r2 > 0.99). Conclusion: The results of post mortem studies were highly correlated and indicate that dual energy mammography is a repeatable measure of breast volume and breast density and a reliable measure of breast mass.

SU‐GG‐I‐33: Quantitative Imaging of a Gold Nanoparticle Contrast Agent with Dual Energy CT

Purpose: To investigate the feasibility of imaging a goldnanoparticlecontrast agent with dual‐energy CT for the detection of vulnerable plaques.Method and Materials: A chest phantom of the thorax was simulated with mixtures of either calcium hydroxyaptatite and water, elemental gold and water, or calcium hydroxyaptatite, elemental gold and water. The range of calcium and gold concentrations were 50 mg/mL to 1000 mg/mL and 0.5 mg/mL to 3.0 mg/mL, respectively. Two cases were considered. The first case was ideal and assumed the volume of the mixture was conserved and there was no interaction between any of the constituent materials. The assumption of volume conservation was relaxed for the second case and the materials were allowed to mix as occurs physically. CTimages were generated at monoenergetic beam energies of 50 keV and 80 keV. A non‐linear dual energy decomposition algorithm was adapted from projection imaging for use in CT. The known densities of calcium hydroxyaptatite and gold were related to the measured low and high energy signals from CT with a nine parameter fit. Measured densities were then calculated from the resultant fit. Results: For the ideal case, the mean percentage error in measuredgold density was −0.25% and the mean percentage error in measuredcalcium hydroxyapatite density was −0.11%. For the physical case, the mean percentage error in measuredgold density was −8.76% and the mean percentage error in measuredcalcium hydroxyapatite density was −3.82%. Conclusion: The results of simulation studies suggest that the density of a goldcontrast agent can be measured in both two material and three material mixtures. The use of a nonlinear decomposition algorithm allowed the density of a goldcontrast agent in a physical mixture to be measured with a mean error of less than 10%.

TU‐E‐201B‐08: K‐Edge Imaging Using a Gold Nanoparticle Contrast Agent and a CT System with Photon Counting Detectors

Purpose: To investigate the feasibility of imaging a goldnanoparticle (GNP) contrast agent for detection of vulnerable plaque using a CT with photon countingdetectors and energy resolution. Materials and Methods: Simulation was performed for material decomposition based on the likelihood maximization method. The simulations were based on single‐slice parallel beam geometry. The beam energy was set to 120 kVp in order to provide high enough photon flux for energies above the k‐edge of the gold (80.7 keV). A CdZnTe detector with 5 different energy bins was used. Both ideal and more realistic detectors were used in the simulation. The phantom used for the simulation contained polymethyl‐methacrylate (PMMA), calcium, and GNP. The concentration of calcium in plaque was adjusted in such a way that the linear attenuation coefficients of GNP and calcium were approximately equal. It is expected in patients with an unstable plaque that goldnanoparticles would occupy portions of calcified tissue. Thus, the simulation of these three materials allows the simulation of the situations which are clinically relevant. Results: In reconstructed images after decomposition only gold was visualized without any traces of PMMA or calcium. The minimum detectablegold density for ideal detector was found to be ∼300 μg/cm3. The minimum detectable density increased by a factor of two as imperfections were added to the detector during simulation. However, the minimum detectable GNP density was far less than the amount of GNP that is accumulated in the plaque. The effect of dose, beam energy, and gold concentration on the image quality was also studied. Conclusions: These studies show the feasibility of using GNP as a contrast agent to detect vulnerable plaque.