Gao Juan

Preliminary simulation studies on a cylindrical PEM scanner using GATE

In this paper, we investigate the performance of a cylindrical positron emission mammography (PEM) by simulation, in order to estimate its feasibility before implementation. A well-developed simulation package, Geant4 Application for Tomographic Emission (GATE), is used to simulate the scanner geometry and physical processes. The simulated PEM scanner is composed of 64 blocks axially arranged in 4 rings with an axial field-of-view (AFOV) of 12.8 cm and 16.6 cm in diameter. For each block, there is a 16×16 array of 2 mm×2 mm×15 mm lutetium yttrium oxyorthosilicate (LYSO) crystals. In the simulated measurements, the spatial resolution is at the center of the FOV of 1.73±0.07 mm (radial) and 1.81±0.08 mm (tangential), but of 4.83±0.09 mm (radial) and 4.37±0.07 mm (tangential) while 5 cm off the center. The central point source sensitivity (ACS) is 4.04% (1.50 Mcps/mCi) at an energy window of 350–650 keV. Moreover, the capillary and cylindrical sources are simulated coupled to breast phantoms for the scatter fraction (SF) and Noise Equivalent Count Rate (NECR) test. For a breast phantom with a 350–650 keV energy window, SF may reach the highest 32.95%, while NECR is degraded down to the lowest 255.71 kcps/mCi. Finally, we model a breast phantom embedded with two spheres of different activities. The reconstructed image gives good results despite a bit of difference in image contrast. Further, the image quality will be improved by scatter and random correction. All these test results indicate the feasibility of this PEM system for breast cancer detection.

Respiratory motion correction with an improved demons algorithm for PET images

Respiratory motion is a major factor that affects the quality of PET images of the thoracic area. The diaphragm moves about 15–20 mm due to respiratory motion, which substantially degrades the effective spatial resolution of PET. In this paper, a gated acquisition method is used to correct the motion effects. In this method, an improved demons algorithm is proposed to align the gated images. The experimental results show that the quality of PET images is significantly improved when using our improved method and the proposed method has a faster convergence rate than the original demons algorithm.

Investigation of scatter from out of the field of view and multiple scatter in PET using Monte Carlo simulations

In fully three-dimensional (3D) positron emission tomography (PET) imaging, the scatter fraction (SF) is about 40%-60%, which may degrade the imaging quality severely. Scatter correction is important for high quality image reconstruction. Model-based scatter correction has been proved to be accurate and available in clinical PET. However, it does not correct the scatter from out of the field of view (OFOV) and multiple scatters. In this study, we demonstrate the radial and axial distribution of scatters from OFOV when the source is located in different radial positions. In order to apply the above conclusions to different PET systems, we characterize the scatters from OFOV as a function of the ratio of the scanner diameter to the length of the axial field of view (AFOV) by modeling several typical whole-body and micro PET systems. The proportions of true events (S0–0), single scatter of one photon (S1–0), single scatter of both photons (S1–1), double scatter of one photon (S2–0) and multiple scatter (Sm) are also calculated and compared. Here the 3D-PET Monte Carlo simulations are performed with the Geant4 Application for Tomography Emission (GATE). In summary, the scatters from OFOV tend to be recorded on the lines of response (LOR) far away from the source. They have a much more serious impact on whole-body PET than micro PET depending on the ratio of scanner diameter to the length of AFOV. In whole-body PET, twice scatters including single scatter of both photons (S1–1) and double scatter of one photon (S2–0) add up to about 12% so that twice scatter correction must be taken into account to acquire a high quality reconstruction image.