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• W2162235342 abstract "The high-resolution research tomograph (HRRT) is a dedicated human brain PET scanner. At present, iterative reconstruction methods are preferred for reconstructing HRRT studies. However, these iterative reconstruction algorithms show bias in short-duration frames. New algorithms such as the shifted Poisson ordered-subsets expectation maximization (SP-OSEM) and ordered-subsets weighted least squares (OSWLS) showed promising results in bias reduction, compared with the recommended ordinary Poisson OSEM (OP-OSEM). The goal of this study was to evaluate quantitative accuracy of these iterative reconstruction algorithms, compared with 3-dimensional filtered backprojection (3D-FBP).The 3 above-mentioned 3D iterative reconstruction methods were implemented for the HRRT. To evaluate the various 3D iterative reconstruction techniques quantitatively, several phantom studies and a human brain study (n=5) were performed.OSWLS showed a low and almost linearly increasing coefficient of variation (SD over average activity concentration), with decreasing noise-equivalent count rates. In decay studies, OSWLS showed good agreement with the 3D-FBP gray matter (GM)-to-white matter (WM) contrast ratio (<4%), and OP-OSEM and SP-OSEM showed agreement within 6% and 7%, respectively. For various frame durations, both SP-OSEM and OP-OSEM showed the fewest errors in GM-to-WM contrast ratios, varying 75% between different noise-equivalent count rates; this variability was much higher for other iterative methods (>92%). 3D-FBP showed the least variability (34%). Visually, OSWLS hardly showed any artifacts in parametric images and showed good agreement with 3D-FBP data for parametric images, especially in the case of reference-tissue kinetic methods (slope, 1.02; Pearson correlation coefficient, 0.99).OP-OSEM, SP-OSEM, and OSWLS showed good performance for phantom studies. In addition, OSWLS showed better results for parametric analysis of clinical studies and is therefore recommended for quantitative HRRT brain PET studies." @default.
• W2162235342 created "2016-06-24" @default.
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• W2162235342 date "2008-12-17" @default.
• W2162235342 modified "2023-09-23" @default.
• W2162235342 title "Accuracy of 3-Dimensional Reconstruction Algorithms for the High-Resolution Research Tomograph" @default.
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• W2162235342 doi "https://doi.org/10.2967/jnumed.108.052985" @default.
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