Preliminary investigation of a Monte Carlo-based system matrix approach for quantitative clinical brain 123I SPECT imaging

A next-generation, adaptive, dynamic multi-pinhole system, AdaptiSPECT-C, dedicated to clinical brain SPECT imaging, is currently under development as part of a collaboration between the universities of Arizona and Massachusetts. It has been shown that accurate modeling of the system matrix is a key aspect of SPECT image reconstruction as it has the potential to improve the imaging performance of any system. A straight-forward approach to modeling is based on the use of Monte Carlo simulation to pre-compute and store the system matrix. Generally, in clinical imaging, given the large sizes of detectors and volume of interests this approach faces critical memory storage issues despite the use of sparse structures to store the system matrix. The aim of this work was to investigate the feasibility of a Monte Carlo simulation pre-computed system matrix approach for
¹²³
I clinical brain SPECT imaging with the AdaptiSPECT-C system. Our efficient method was evaluated using an XCAT brain perfusion phantom. The present approach's feasibility was fully demonstrated in case of clinical
¹²³
I brain imaging.