Simulation study comparing the helmet-chin PET with a cylindrical PET of the same number of detectors.

ABSTRACT

There is a growing interest in developing brain PET scanners with high sensitivity and high spatial resolution for early diagnosis of neurodegenerative diseases and studies of brain functions. Sensitivity of the PET scanner can be improved by increasing the solid angle. However, conventional PET scanners are designed based on a cylindrical geometry, which may not be the most efficient design for brain imaging in terms of the balance between sensitivity and cost. We proposed a dedicated brain PET scanner based on a hemispheric shape detector and a chin detector (referred to as the helmet-chin PET), which is designed to maximize the solid angle by increasing the number of lines-of-response in the hemisphere. The parallax error, which PET scanners with a large solid angle tend to have, can be suppressed by the use of depth-of-interaction detectors. In this study, we carry out a realistic evaluation of the helmet-chin PET using Monte Carlo simulation based on the 4-layer GSO detector which consists of a 16 × 16 × 4 array of crystals with dimensions of 2.8 × 2.8 × 7.5 mm3. The purpose of this simulation is to show the gain in imaging performance of the helmet-chin PET compared with the cylindrical PET using the same number of detectors in each configuration. The sensitivity of the helmet-chin PET evaluated with a cylindrical phantom has a significant increase, especially at the top of the (field-of-view) FOV. The peak-NECR of the helmet-chin PET is 1.4 times higher compared to the cylindrical PET. The helmet-chin PET provides relatively low noise images throughout the FOV compared to the cylindrical PET which exhibits enhanced noise at the peripheral regions. The results show the helmet-chin PET can significantly improve the sensitivity and reduce the noise in the reconstructed images.