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. 2014 Dec;1(1):12.
doi: 10.1186/2197-7364-1-12. Epub 2014 Sep 19.

The influence of different signal-to-background ratios on spatial resolution and F18-FDG-PET quantification using point spread function and time-of-flight reconstruction

Julian Mm Rogasch  1 , Frank Hofheinz  2 , Alexandr Lougovski  3 , Christian Furth  4 , Juri Ruf  5   6 , Oliver S Großer  7 , Konrad Mohnike  8 , Peter Hass  9 , Mathias Walke  10 , Holger Amthauer  11 , Ingo G Steffen  12
Affiliations

The influence of different signal-to-background ratios on spatial resolution and F18-FDG-PET quantification using point spread function and time-of-flight reconstruction

Julian Mm Rogasch et al. EJNMMI Phys. 2014 Dec.

Abstract

Background: F18-fluorodeoxyglucose positron-emission tomography (FDG-PET) reconstruction algorithms can have substantial influence on quantitative image data used, e.g., for therapy planning or monitoring in oncology. We analyzed radial activity concentration profiles of differently reconstructed FDG-PET images to determine the influence of varying signal-to-background ratios (SBRs) on the respective spatial resolution, activity concentration distribution, and quantification (standardized uptake value [SUV], metabolic tumor volume [MTV]).

Methods: Measurements were performed on a Siemens Biograph mCT 64 using a cylindrical phantom containing four spheres (diameter, 30 to 70 mm) filled with F18-FDG applying three SBRs (SBR1, 16:1; SBR2, 6:1; SBR3, 2:1). Images were reconstructed employing six algorithms (filtered backprojection [FBP], FBP + time-of-flight analysis [FBP + TOF], 3D-ordered subset expectation maximization [3D-OSEM], 3D-OSEM + TOF, point spread function [PSF], PSF + TOF). Spatial resolution was determined by fitting the convolution of the object geometry with a Gaussian point spread function to radial activity concentration profiles. MTV delineation was performed using fixed thresholds and semiautomatic background-adapted thresholding (ROVER, ABX, Radeberg, Germany).

Results: The pairwise Wilcoxon test revealed significantly higher spatial resolutions for PSF + TOF (up to 4.0 mm) compared to PSF, FBP, FBP + TOF, 3D-OSEM, and 3D-OSEM + TOF at all SBRs (each P < 0.05) with the highest differences for SBR1 decreasing to the lowest for SBR3. Edge elevations in radial activity profiles (Gibbs artifacts) were highest for PSF and PSF + TOF declining with decreasing SBR (PSF + TOF largest sphere; SBR1, 6.3%; SBR3, 2.7%). These artifacts induce substantial SUVmax overestimation compared to the reference SUV for PSF algorithms at SBR1 and SBR2 leading to substantial MTV underestimation in threshold-based segmentation. In contrast, both PSF algorithms provided the lowest deviation of SUVmean from reference SUV at SBR1 and SBR2.

Conclusions: At high contrast, the PSF algorithms provided the highest spatial resolution and lowest SUVmean deviation from the reference SUV. In contrast, both algorithms showed the highest deviations in SUVmax and threshold-based MTV definition. At low contrast, all investigated reconstruction algorithms performed approximately equally. The use of PSF algorithms for quantitative PET data, e.g., for target volume definition or in serial PET studies, should be performed with caution - especially if comparing SUV of lesions with high and low contrasts.

Keywords: FDG-PET/CT reconstruction; Gibbs artifact; Gibbs phenomenon; Metabolic tumor volume delineation; PSF; Radial activity concentration profile; Ringing artifact; Signal-to-background ratio; Spatial resolution; TOF.

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Figures

Figure 1
Figure 1
Determination of Gibbs artifacts (GA). The black circles represent the radial profile and the gray line depicts the smoothing spline. The black horizontal lines show A+ and A- determined from the smoothing spline.
Figure 2
Figure 2
Spatial resolution displayed as a function of reconstruction algorithm, sphere diameter, and SBR. (A) SBR1. (B) SBR2. (C) SBR3.
Figure 3
Figure 3
Radial activity profiles of the largest sphere (70 mm) depending on reconstruction algorithm and SBR. Edge elevations (Gibbs artifacts) can be observed after reconstruction with PSF + TOF and PSF (not displayed) at SBR1 (A, D, G) and SBR2 (B, E, H). SBR3 (C, F, I) shows no considerable artifacts. The gray lines indicate the respective smoothing spline.
Figure 4
Figure 4
Radial activity profiles of the smallest sphere (30 mm) depending on reconstruction algorithm and SBR. Edge elevations (Gibbs artifacts) can be observed after reconstruction with PSF + TOF and PSF (not displayed) at SBR1 (A, D, G) and SBR2 (B, E, H). SBR3 (C, F, I) shows no considerable artifacts. The gray lines indicate the respective smoothing spline.
Figure 5
Figure 5
SUVmax/SUVmean displayed as a function of reconstruction algorithm, sphere diameter, and SBR. SUVmean based on segmentation with tBC or with t50, respectively. (A, D, G) SBR1. (B, E, H) SBR2. (C, F, I) SBR3.
Figure 6
Figure 6
Relative MTV deviations displayed as a function of reconstruction algorithm, sphere diameter, and SBR. (A, D, G, J) SBR1. (B, E, H, K) SBR2. (C, F, I, L) SBR3.
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