Development and assessment of statistical iterative image reconstruction for CT on a small animal SPECT/CT dual-modality system

Abstract

We developed a statistical iterative CT image reconstruction software for a newly constructed high-resolution small animal SPECT/CT dual-modality system, and assessed its performance at different radiation exposure levels. The objective of this work was to preserve or improve reconstructed image quality at either the same or reduced animal x-ray radiation exposure. The SPECT/CT system used a single detector for both the CT and SPECT modalities that consists of a micro-columnar CsI(TI) phosphor, a light image intensifier (LII) and a CCD sensor. The CT reconstruction software was based on the ordered-subset-convex (OSC) algorithm, and the system matrix was calculated through a ray-driven approach. A self-calibration method was implemented to calculate the offset of the axis of rotation (AOR), an important geometry parameter of the system. An endovascular stent was imaged to evaluate the high resolution performance of the statistical reconstructed image. A sacrificed mouse was scanned at different exposure levels to assess the effect of statistical noise on the image. The mouse studies were reconstructed with both the statistical reconstruction software and a filtered back-projection (FBP) program. The images were assessed and compared by contrast to noise ratio (CNR) in the region of interest. The images yielded by the statistical reconstruction software were artifact free and show superior noise performance to those from FBP reconstruction at different radiation exposure levels. The statistical reconstructed images with reduced exposure showed obviously higher image quality than those from FBP reconstruction at full exposure.