Abstract
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Objectives: uEXPLORER, the world’s 1st total-body positron emission tomography (PETCT) scanner,which has a 194-cm axial field of view and more than half million crystals,can provide new possibilities in biomedical research and clinical imaging with its 40-fold higher sensitivity than current commercial scanners. The huge number of lines of response (LORs) brings new challenges to physics correction and image reconstruction. Scatter correction, which influences both the quality and quantification of reconstructed image, is traditionally handled by the single scatter simulation algorithm. However, due to the increase of multi-scatter events in LORs with large ring differences in a long-axial PET, a more accurate scatter correction method is required. Theoretically, scatter correction based on Monte Carlo simulation is regard as the gold standard and most time consuming. A Monte Carlo simulation (MCS) scatter correction algorithm is developed for uEXPLORER, which applies a series of deep optimizations to achieve the speed requirement of a clinical PET system while ensuring the reliability of the scattering simulation. In the present work, the MCS algorithm is validated with GATE simulations and scanning data.
Methods: uEXPLORER consists of 8 units, each of which has a length close to a conventional commercial PET system. The coincidence pairing between five adjacent units is available. Single and multiple scattering events in a uniform phantom with a length of 200 cm and a diameter of 20 cm are simulated by the GATE toolkit and our MCS algorithm separately. Sinogram profiles of different unit pairings are extracted for the comparison between GATE simulation and our MCS algorithm. Furthermore, a similar comparison is performed for TOF sinogram profiles of a standard NEMA-IQ phantom. Further, a uniform phantom with a length of 200 cm and a diameter of 15 cm is used for the validation of MCS algorithm in uEXPLORER.
Results: Figure 1 depicts the single and multiple scatter sinogram profiles of the uniform phantom from GATE simulation and our MCS algorithm, where (a) is the data from maximum unit difference =0, and (b) is from maximum unit difference =4. Results of TOF sinogram profiles of a standard NEMA-IQ phantom is presented in figure 2. The good agreement between profiles form GATE and the MCS algorithm in both Fig. 1 and Fig. 2 demonstrates the reliability of our MCS algorithm for both long-axial PET system and TOF simulation. Figure 3 presents the reconstruction image of the measured 2-meter uniform phantom, the transverse and axial profiles further verify the accuracy of our MCS algorithm.
Conclusions: The new MCS based scatter correction algorithm is validated by both the GATE simulation data and a 200-cm long uniform phantom scanned in uEXPLORER
