Abstract

A PET/CT system's imaging capabilities are best described by its point spread function (PSF) in the spatial domain or equivalently by its modulation transfer function (MTF) in the spatial frequency domain. Knowing PSFs or MTFs is a prerequisite for many numerical methods attempting to improve resolution and to reduce the partial volume effect. In PET/CT, the observed PSF is a convolution of the system's intrinsic imaging capabilities including image reconstruction (PSF0) and the positron range function (PRF) of the imaged β+ emitting isotope. A PRF describes the non-Gaussian distribution of β+ annihilation events around a hypothetical point source. The main aim was to introduce a new method for determining a PET/CT system's intrinsic MTF (MTF0) from phantom measurements of hot spheres independently of the β+ emitting isotope used for image acquisition. Secondary aim was to examine non-Gaussian and nonlinear MTFs of a modern iterative reconstruction algorithm. PET/CT images of seven phantom spheres with volumes ranging from 0.25 to 16 ml and filled either with 18F or with 68Ga were acquired and reconstructed using filtered back projection (FBP). MTFs were modeled with linear splines. The spline fit iteratively minimized the mean squared error between the acquired PET/CT image and a convolution of the thereof derived PSF with a numerical representation of the imaged hot phantom sphere. For determining MTF0, the numerical sphere representations were convolved with a PRF, simulating a fill with either 18F or 68Ga. The MTFs determined by this so-called MTF fit method were compared with MTFs derived from point source measurements and also compared with MTFs derived with a previously published PSF fit method. The MTF fit method was additionally applied to images reconstructed by a vendor iterative algorithm with PSF recovery (Siemens TrueX). The MTF fit method was able to determine 18F and 68Ga dependent MTFs and MTF0 from FBP reconstructed images. Root-mean-square deviation between fit determined MTFs and point source determined MTFs ranged from 0.023 to 0.039. MTFs from Siemens TrueX reconstructions varied with size of the imaged sphere. MTF0 can be determined regardless of the imaged isotope, when using existing PRF models for the MTF fit method presented. The method proves that modern iterative PET/CT reconstruction algorithms have nonlinear imaging properties. This behaviour is not accessible by point source measurements. MTFs resulting from these clinically applied algorithms need to be estimated from objects of similar geometry to those intended for clinical imaging.

Highlights

  • In previous work,[1] we had introduced the transconvolution (TC) method for PET/CT image normalization and to improve comparability of quantitative PET measurements performed on different PET/CT systems

  • Any difference seen in the corresponding point spread function (PSF) between point source measurements and spherical measurements was below the resolution capabilities of our PET/CT system, i.e., 4.5 mm (NEMA 2007) and 2 mm (Siemens True X + Time of Flight).[24]

  • The 0.25 sphere is excluded from the average trace in red. (b) Averaged modulation transfer function (MTF) from TrueX point source measurements compared with the average trace from (a) and with the averaged filtered back projection (FBP) 18F MTF taken from (a). (See color online version.)

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Summary

Introduction

In previous work,[1] we had introduced the transconvolution (TC) method for PET/CT image normalization and to improve comparability of quantitative PET measurements performed on different PET/CT systems. TC offers a comprehensive way of mathematically transforming images acquired on different PET/CT systems to images with uniform imaging characteristics, as if they had been acquired by one single virtual PET/CT system (vPET). After measuring system-specific PSFs or MTFs, a standardized vPET-PSF and/or vPET-MTF is deconvolved with these PSFs, resulting in specific transconvolution functions (TCFs) for every participating PET/CT system. The TCFs itself are used to recast (transconvolve) images acquired on these systems into vPET images, allowing for comparable quantification of PET/CT measurements performed on multiple PET/CT systems. One process giving rise to non-Gaussian PSFs lies in the very foundations of how positron ( β+) decay

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