Correction for scatter and septal penetration using convolution subtraction methods and model-based compensation in 123I brain SPECT imaging—a Monte Carlo study

Abstract

Scatter and septal penetration deteriorate contrast and quantitative accuracy in single photon emission computed tomography (SPECT). In this study four different correction techniques for scatter and septal penetration are evaluated for 123I brain SPECT. One of the methods is a form of model-based compensation which uses the effective source scatter estimation (ESSE) for modelling scatter, and collimator–detector response (CDR) including both geometric and penetration components. The other methods, which operate on the 2D projection images, are convolution scatter subtraction (CSS) and two versions of transmission dependent convolution subtraction (TDCS), one of them proposed by us. This method uses CSS for correction for septal penetration, with a separate kernel, and TDCS for scatter correction. The corrections are evaluated for a dopamine transporter (DAT) study and a study of the regional cerebral blood flow (rCBF), performed with 123I. The images are produced using a recently developed Monte Carlo collimator routine added to the program SIMIND which can include interactions in the collimator. The results show that the method included in the iterative reconstruction is preferable to the other methods and that the new TDCS version gives better results compared with the other 2D methods.