Image-Based Spatially Variant and Count Rate Dependent Point Spread Function on the HRRT

Abstract

Spatial resolution on the High Resolution Research Tomograph (HRRT) is of high importance, due to the need for accurate quantification of small brain structures. Thus accurate characterization of the scanner’s resolution properties and subsequent inclusion of such information within image reconstruction, requires measuring its point spread function (PSF). In this study we measured in detail the spatial variation of the image space PSF and assessed the impact of the scanner’s depth of interaction (DOI) capability on the spatial resolution. Furthermore, we characterized the dependency of the PSF on progressively increasing count rate statistics. An array of 15 × 11 printed point sources was scanned twice, initially on its own to measure the PSF spatial dependency, and subsequently with an extension line containing $\sim $ 300 MBq of carbon-11, to assess the count rate dependency. PSF data were reconstructed with the scanner’s default OP-OSEM and invariant PSF OP-OSEM algorithms, followed by image space model fitting. The axial, radial and tangential components of the PSF were found to vary under radial and angular transformations, but being radially symmetric and almost axially independent. The FWHM improves by $\sim $ 1.3 mm using the PSF-OP-OSEM but is still radially variable with $\sim $ 1 mm degradation within the FOV boundaries. When DOI was not taken into account, an additional degradation up to 0.7 mm was seen in the radial FWHM using OP-OSEM. Using the invariant PSF OP-OSEM, this degradation was less notable ( $\sim $ 0.5 mm), despite the fact an invariant kernel is used. In terms of count rate dependency, a clear resolution degradation was seen for mean count rates above 5–10 kcps. However, this degradation was found to vary within the FOV. The spatially variant PSF at low count rates could be incorporated within a resolution modelling image reconstruction. However, including a count rate dependent PSF model is less straightforward.