A Hybrid Scatter Correction Method Combining the SSS Algorithm and Beam Stopper Method for 3D PET

Scattered events represent a major cause of inaccurate quantification and image degradation in three-dimensional (3D) positron emission tomography (3D PET) scanners. The single scatter simulation (SSS) method is the most widely used scatter correction method. However, this method relies on tail data to scale the estimated scatter to the measured data. Consequently, this method might fail when tail data are insufficient; for example, when scanning obese patients. Unfortunately, the global prevalence of obesity has increased substantially in recent decades; hence, developing alternative solutions to this problem is necessary. The beam stopper (BS) method is used to measure the actual scatter at locations blocked by the BS device. This method can then be applied to estimate the entire scatter sinogram by using an interpolation. However, this interpolation might not reflect the true condition if the BS device has been set up inappropriately. This study presents a hybrid scatter correction method (SSS-BS) based on the SSS and BS methods. In the SSS-BS method, the scatters measured by applying the BS method are used to adjust the scatter distribution calculated by employing the SSS method, thereby obtaining a more accurate scatter distribution. The performance of this hybrid method was investigated by using Monte Carlo simulations. A thorax Zubal phantom (55.8 cm in width and 37.8 cm in height) and a Jaszczak-like phantom (55.2 cm in diameter and 22.75 cm in length) were used to investigate cases involving obese patients. In contrast to the SSS method, the hybrid method does not suffer from the scatter-distribution inaccuracies caused by insufficient tails. The results from the Zubal phantom show that the SSS-BS, SSS, and BS methods yield similar scatter-fraction (SF) estimates, whereas the SSS-BS and SSS methods have a slightly smaller root mean square error (RMSE) of reconstructed images than that of the BS method. For the Jaszczak-like phantom, the SSS-BS method generates a more accurate estimate of SF than both the SSS and BS methods do, reducing the RMSE by nearly half. This study demonstrates that the hybrid method enables the accurate scatter-distribution estimation of 3D PET in cases involving obese patients.