PROCEEDINGS ARTICLE | April 20, 2005
Proc. SPIE. 5745, Medical Imaging 2005: Physics of Medical Imaging
KEYWORDS: Breast, X-ray computed tomography, Tissues, Imaging systems, Sensors, X-rays, Image filtering, X-ray imaging, X-ray detectors, Breast imaging
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.
