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Cone-beam CT breast imaging with a flat panel detector - A simulation study

This paper investigates the feasibility of using a flat panel based cone-beam computer tomography (CT) system for 3-D breast imaging with computer simulation and imaging experiments. In our simulation study, 3-D phantoms were analytically modeled to simulate a breast loosely compressed into cylindrical shape with embedded soft tissue masses and calcifications. Attenuation coefficients were estimated to represent various types of breast tissue, soft tissue masses and calcifications to generate realistic image signal and contrast. Projection images were computed to incorporate x-ray attenuation, geometric magnification, x-ray detection, detector blurring, image pixelization and digitization. Based on the two-views mammography comparable dose level on the central axis of the phantom (also the rotation axis), x-ray kVp/filtration, transmittance through the phantom, detected quantum efficiency (DQE), exposure level, and imaging geometry, the photon fluence was estimated and used to estimate the phantom noise level on a pixel-by-pixel basis. This estimated noise level was then used with the random number generator to produce and add a fluctuation component to the noiseless transmitted image signal. The noise carrying projection images were then convolved with a Gaussian-like kernel, computed from measured 1-D line spread function (LSF) to simulated detector blurring. Additional 2-D Gaussian-like kernel is designed to suppress the noise fluctuation that inherently originates from projection images so that the reconstructed image detectability of low contrast masses phantom can be improved. Image reconstruction was performed using the Feldkamp algorithm. All simulations were performed on a 24 PC (2.4 GHz Dual-Xeon CPU) cluster with MPI parallel programming. With 600 mrads mean glandular dose (MGD) at the phantom center, soft tissue masses as small as 1 mm in diameter can be detected in a 10 cm diameter 50% glandular 50% adipose or fatter breast tissue, and 2 mm or larger masses are visible in a 100% glandular 0% adipose breast tissue. We also found that the 0.15 mm calcification can be detected for 100μm detector while only 0.2 μm or above are visible for 200 μm detector. Our simulation study has shown that the cone-beam CT breast imaging can provide reasonable good quality and detectability at a dose level similar to that of two views\mammography. For imaging experiments, a stationary x-ray source and detector, a step motor driven rotating phantom system was constructed to demonstrate cone beam breast CT image. A breast specimen from mastectomy and animal tissue embedded with calcifications were imaged. The resulting images show that 355-425 μm calcifications were visible in images obtained at 77 kVp with a voxel size of 316 μm and a center dose of 600 mrads. 300-315 μm calcifications were visible in images obtained at 60 kVp with a voxel size of 158 μm and a center dose of 3.6 rads.

Cone Beam Breast CT with a Flat Panel Detector- Simulation, Implementation and Demonstration

This paper describes our experiences in the simulation, implementation and application of a flat panel detector based cone beam computed tomography (CT) imaging system for dedicated 3-D breast imaging. In our simulation study, the breast was analytically modeled as a cylinder of breast tissue loosely molded into cylindrical shape with embedded soft tissue masses and calcifications. Attenuation coefficients for various types of breast tissue, soft tissue masses and calcifications were estimated for various kVps to generate simulated image signals. Projection images were computed to incorporate X-ray attenuation, geometric magnification, X-ray detection, detector blurring, image pixelization and digitization. Based on the X-ray kVp/filtration used, transmittance through the phantom, detective quantum efficiency (DQE), exposure level, and imaging geometry, the photon fluence was estimated and used to compute the quantum noise level on a pixel-by-pixel basis for various dose levels at the isocenter. This estimated noise level was then used with a random number generator to generate and add a fluctuation component to the noiseless transmitted image signal. The noise carrying projection images were then convolved with a Gaussian-like kernel, computed from measured 1-D line spread function (LSF) to simulate detector blurring. Additional 2-D Gaussian filtering was applied to the projection images and tested for improving the detection of soft tissue masses and calcifications in the reconstructed images. Reconstruction was performed using the Feldkamp filtered backprojection algorithm. All simulations were performed on a 24 PC (2.4 GHz Dual-Xeon CPU) cluster with MPI parallel programming. With 600 mrads mean glandular dose (MGD) at the phantom center, soft tissue masses as small as 1 mm in diameter could be visualized in a 10 cm diameter 50% glandular 50% adipose or fatter breast tissue, and 2 mm or larger masses were visible in a 100% glandular 0% adipose breast tissue. We have also demonstrated that 0.15 mm or larger calcification could be detected with a 100 mum detector pixel size while 0.2 mm or larger calcifications were visible with a pixel size of 200 mum. Our simulation study has shown that the cone-beam CT breast imaging can provide reasonable good quality and detectability at a dose level similar to that of two views mammography. For imaging experiments, a stationary x-ray source and detector, a stationary gantry, rotating phantom system was constructed to demonstrate cone beam breast CT imaging. Breast specimens from mastectomy were imaged to demonstrate the superior tissue contrast that can be achieved with the cone beam CT technique. Various phantoms were imaged to demonstrate that calcifications as small as 280 mum could be imaged at 80 RVp with a voxel size of 140 mum with an estimated isocenter dose of 1.8 rad

Effects of scattered radiation and beam quality on low contrast performance in cone beam breast CT

In this work, we investigated the effects of scattered radiation and beam quality on the low contrast performance relevant to cone beam breast CT imaging. For experiments, we used our benchtop conebeam CT system and constructed a phantom consisting of simulated fat and soft tissues. We varied the field of view (FOV) along the z direction to observe its effect on scattered radiation. The beam quality was altered by varying the tube voltage from 50 to 100 kV. We computed the contrast-to-noise ratio (CNR) from reconstructed images and normalized it to the square root of dose measured at the center of the phantom. The results were used as the figure of merit (FOM). The effect of the beam quality on the scatter to primary ratio (SPR) had minimal impact and the SPR was primarily dominated by the FOV. In the central section of the phantom, increasing the FOV from 4 to 16 cm resulted in drop of CNR in the order of 15-20% at any given kVp setting. For a given FOV, the beam quality had insignificant effect on the FOM in the central section of the phantom. In the peripheral section, a 10 % drop in FOM was observed when the kVp setting was increased from 50 to 100. At lower kVp values, the primary x-ray transmission through the thicker parts of the phantom was severely reduced. Under such circumstances, ring artifacts were observed due to imperfect flat field correction at very low signal intensities. Higher kVp settings and higher SPRs helped to increase the signal intensity in highly attenuating regions and suppressed the ring artifacts.

SU‐FF‐I‐15: Effects, Detection and Removal of Zingers From Scattered X‐Rays in CCD Based Cone Beam CT

Purpose: Zingers are tiny spurious white dots that appear randomly in CCDimages. In order to improve the quality of CCD based cone beam CT technique, a new technique for the detection and removal of zingers is described and evaluated. Method and Materials: A bench top CCD based cone beam CT system was used to measure and investigate the presence of zingers. The cause and effects of zingers were studied. A new technique was developed to detect and correct the zingers. With this technique, the statistical behavior of pixel values in a projection image was first analyzed to identify candidates for zingers. Pixel values at the detected zinger locations were then compared in two consecutive projection views to eliminate false detections. To investigate and evaluate this technique, zingers were simulated by increasing the pixel values at randomly selected locations in projection data computed for a modified Shepp‐Logan phantom. The simulated data were then detected and corrected for zingers and used for reconstruction. The resulting reconstructed image was compared with the imagereconstructed from zinger free data and with imagesreconstructed from data corrected using three other zinger removal techniques. Results: Our measurement indicated that zingers may have resulted from scattered x‐rays. They were found to generate visible artifacts and degrade the quality of reconstructed images. It was shown that zingers detection by comparing two identically acquired projections could be highly effective but impractical in CTimaging. Detection by comparing two consecutive projection views was equally effective but may be subject image blurring. Detection by analyzingsignal fluctuations could result in a large number of faulty detections. The proposed new detection technique was found to be practical and effective without resulting in image blurring or faulty detections. This work was supported in part by a research grant CA104759 from NIHNCI.

MO-E-I-609-02: Imaging Properties of Cone Beam Breast CT- Effects of Detector Properties and Imaging Conditions

Purpose: To investigates the effects of detector properties and imaging conditions on the imaging properties of cone‐beam breast CT with both computer simulations and imaging experiments. Method and Materials: Cone beam breast CT was simulated with the breast analytically modeled as cylinder embedded spherical shape soft tissue masses and calcifications. X‐ray spectrum, breast attenuation, geometric magnification, focal spot blurring, x‐ray detection,detector blurring, image pixelization and digitization were all incorporated in computing the projection images.Quantum noise, system noise,detector blurring were also simulated and incorporated in the model. Image filtering and reconstruction were then performed using the Feldkamp algorithm. Simulation was performed for two flat‐panel detectors, one CsI based and the other a‐Se based. Images of phantoms and breast specimens were also obtained to demonstrate the ability of our experimental cone beam breast CT system to image the 3‐D structures of the breast with embedded cancers and calcifications. Results: Our simulation results shows that the a‐Se detector performs slightly better at 30 and 40 kVps while the CsI detector performs better at 50 or higher kVps. ImageSNRs are optimized at 50 and 60 kVp for the s‐Se and CsI detector, respectively. Phantom images obtained with our experimental system show that with higher dose and smaller pixel size, calcifications as small as could be resolved. Images of breast specimens show excellent separation between glandular and adipose tissues. The speculated nature of the tumor masses can be clearly seen in selected projection while ambiguous in other projections or in regular mammograms. It was also found that inclusion of surgical clips (used to indicate tumor location) had caused detrimental reconstruction artifacts. Acknowledgment: This work was supported in part by a research grant EB000117 from the NIBIB and a research grant CA104759 from the NCI.

SU‐FF‐I‐16: Volume‐Of‐Interest (VOI) Cone Beam CTwith Dual Resolution Image Acquisition

In this study, we investigate the feasibility of using VOI projection data acquired at high resolution in conjunction with full width projection data acquired at low resolution to reconstruct cone beam CTimages for the VOI. To simulate cone beam CT with dual resolution image acquisition, flat panel images of a mastectomy specimen, acquired in the non‐binning mode, were converted into low resolution full width projection data. High resolution VOI projection data were directly extracted from the original data. To prepare for reconstruction, the low resolution projection data were first interpolated, re‐sampled to fill in the truncated space outside the VOI. The dual resolution full width projection data, consisting of true high resolution data in the VOI and interpolated data outside the VOI, were then used to reconstruct the 3‐D image for the VOI. Reconstructed images obtained with dual resolution projection data were compared with those obtained with low resolution data and those obtained with high resolution data for the visibility of small calcifications. We have successfully demonstrated the use of dual resolution projection data for VOI cone beam CTimaging. While the low resolution full width projection data did not allow smaller calcifications to be seen in the reconstructed images, addition of high resolution projection data for the VOI only could make them visible. The use of interpolated low resolution projection data to pad the truncated space outside the VOI did not affect the spatial resolution of reconstructed images inside the VOI. With the dual resolution technique, it would be possible to selectively image a VOI at very high resolution without requiring excessively long acquisition and reconstruction or unnecessarily overexposing the patient outside the VOI. (This work was supported in part by a research grant CA104759 from the NCI and a research grant EB‐00117 from the NIBIB).

TU-FF-A4-04: Intensity Modulation Patterns for Regional Exposure Control with Multiple Angle Slot Scan Imaging: Simulated Annealing Optimization Technique Approach

Purpose: To study the feasibility of using simulated annealing algorithm to determine the intensity modulation patterns for regional exposure control with multiple angle slot scan imaging. Method and Materials: We acquired a digital image from the chest radiography and then processed with a 2‐D Gaussian filter as an exposure equalization mask. Slot scanning exposures at evenly spaced angle between 0 and 180 degrees were used to achieve the ideal exposure distribution. An optimization technique, simulated annealing, was used to search the best intensity modulation patterns. This method is based on the theory of statistical physics and uses Boltzmannprobability distribution to locate the minimum energy state. An objective function was mathematically constructed and Metropolis scheme was incorporated into the numerical computation. Various tuning parameters such as the control temperature setting for the annealing schedule were explored and the best combination was empirically chosen. We also calculated the percent root mean square error to quantify the results. Results: A wide range of scanning angles was tested in the study. For 8 projection angles, it took 10 minutes to complete the intensity modulation patterns search in a single processor computer and the percent root mean square error was 12.0%. The percent root mean square error can be further reduced by adding the number of scanning angles. Conclusion: Our study indicated that simulated annealing technique has the potential to determine the optimized intensity modulation patterns. Current work is focused on the reduction of both the computing time and percent root mean square error. Other optimization techniques such as the conjugate gradient method and the applications of parallel computing methods to accelerate the search algorithms are to be investigated. Supported in part by a research grant EB00117 by the National Institute of Biomedical Imaging and Bioengineering.

TH‐C‐330A‐06: Effects of KVp Setting and Radiation Dose On Calcification Visibility in Cone Beam CT

Purpose: To investigate how the kVp setting and radiation dose affects the detection of microcalcifications in cone beam CT(CBCT).Materials and Methods:Calciumcarbonate grains, ranging from 200–212 to 355–425 micron, were used to simulate microcalcifications. The simulated microcalcifications from the same size were arranged to form a 5×5 microcalcification cluster. Each cluster was embedded between two slices of a stacked lunch meat and positioned at the center of each slice of the lunch meat. The lunch meat was then imaged with an experimental CBCTsystem, which employs a 30 × 40 cm2 a‐Si/CsI based flat panel detector with a pixel size of 194 microns. 300 projection images over 360 degrees were acquired in the non‐binning mode at two kVp setting (60 and 80 kVp) and various doses (4.2, 6, 12, 18, and 24 mGy). The projection images were reconstructed with the Feldkamp algorithm. After that, 767×767×9 volume data were extracted from the CBCTreconstructed images for each MC size group and each dose level as well as each kVp. The images were sequentially displayed on a review workstation with a 1600×1200 CRT monitor and reviewed by six readers independently. The order of the images was randomized for each reader. The readers were asked to count the number of visible microcalcifications. The ratios of the visible microcalcifications were averaged over all readers. Student t‐test was used to compute the p values. Result: For 80 kVp, the images acquired with 4.2 mGy performed similarly to those acquired with 6 mGy (p > 0.05) for each MC size. Additionally, the images acquired with 18 mGy performed similarly to those with 24 mGy (p > 0.05) for most MC sizes. This work was supported in part by a research grant EB000117 from the NIBIB and a research grant CA104759 from the NCI.

TH‐C‐330A‐07: Noise and Nodule Detectability in Simulated Cone Beam CT Imaging

Purpose: To evaluate and quantify the impact of various types of noise(quantum noise,photonscatter, flat panel detector blurring, and systemnoise) on the nodule detectability in simulated cone beam CT(CBCT)images by conducting the eight‐alternative forced choice (8‐AFC) observer performance experiment. Method and Materials: We used Radon transform formalism to mathematically model a 3D chest phantom with spherical nodules of various sizes. Quantum noise,photonscatter,detector blurring, and systemnoise were then simulated and added to the projection images individually. The projection images were reconstructed by using the Feldkamp algorithm and the final images were then used for the observer performance study. Other impact factors for the image quality (e.g., contrast variation, x‐ray dose, nodule size, number of projection images, cone beam angle etc.) were also incorporated into the reading study. Detection curves were then determined statistically from the 8‐AFC experimental data by using a maximum‐likelihood method. Nodule detectability was then quantified directly from the reading performance participated by 6 observers in the 8‐AFC tests. Results: Our preliminary data indicated that at the high x‐ray dose level, photonscatter had the highest impact on the simulated CBCTimages; while at the low dose level, systemnoise had the biggest impact. At all tested dose levels, detector blurring had the lowest impact on the detectability. In consistent with the previous theoretical study, the nodule detectability can be improved by increasing the number of projection images.Conclusion: Our work indicated that using photonscatter correction techniques and reducing the systemnoise had the biggest potential to improve the CBCTimage quality. We are currently investigating the impact of various scatter reduction algorithms and reconstruction methods on the CBCTimage quality. Supported in part by a research grant EB00117 by the National Institute of Biomedical Imaging and Bioengineering.

TU-EE-A3-04: Cone Beam CT Imaging Versus Digital Tomosynthesis: A Computer Simulation Study for Comparisons

Purpose: We used a general-purpose PC cluster to develop a parallel computer simulation model for comparisons between the cone beam CT imaging and digital tomosynthesis with the same image acquisition geometry. Method and Materials: Our model incorporates quantum noise, detector blurring, and additive system noise into the computer simulation. Radon transforms formalism was applied to analytically calculate the phantom image projection data which were then used to reconstruct the volumetric images for low contrast performance and image quality studies. Feldkamp algorithm was used in the cone beam CT imaging, while the shift-and-add, filtered backprojection, and optimization based algorithms were used in digital tomosynthesis. We implemented a parallel random number generator based on the Weyl sequence to simulate both quantum and system noise. For digital tomosynthesis, we used blurring profiles and the artifact spread function (ASF) to quantify the magnitude of the out-of-plane artifacts. We also calculated the noise power spectra to characterize the image quality for cone beam CT imaging and digital tomosynthesis. Some artifacts removal methods and programming optimization techniques were also investigated in this study. Results: The test results showed that our parallel random number generator had good randomness quality and can be used in the noise study. The images reconstructed from using the digital tomosynthesis algorithms were worse than the Feldkamp algorithm in the cone beam CT imaging. However, it was possible to remove the out-of-plane blurring in digital tomosynthesis by using some special techniques. Conclusion: We had successfully developed a parallel computing technique to simulate quantum noise, detector blurring, and system noise for both cone beam CT imaging and digital tomosynthesis. Several quantification methodologies were used to compare these two 3D imaging techniques. Supported in part by a research grant EB000117 from the NIBIB and a research grant CA104759 from the NCI.