Clinical validation of high-resolution image reconstruction algorithms in brain 18F-FDG-PET: effect of incorporating Gaussian filter, point spread function, and time-of-flight
Clinical validation of high-resolution image reconstruction algorithms in brain 18F-FDG-PET: effect of incorporating Gaussian filter, point spread function, and time-of-flight
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DOI:
10.1097/mnm.0000000000000187
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发表时间:
2014-12-01
影响因子:
1.5
通讯作者:
Matsutomo, Norikazu
中科院分区:
文献类型:
--
作者:
Nagaki, Akio;Onoguchi, Masahisa;Matsutomo, Norikazu
ObjectivesAccurate estimation of radiopharmaceutical uptake in the brain is difficult because of count statistics, low spatial resolution, and smoothing filter. The aim of this study was to assess the counting rate performance of PET scanners and the image quality with different combinations of high-resolution image reconstruction algorithms in brain F-18-2-fluorodeoxy-d-glucose (F-18-FDG)-PET.Materials and methodsUsing 23 patient studies, we analyzed the coincidence rates of true and random, random fraction, and the noise equivalent counts per axial length (NECpatient) in brain and liver bed positions. The reconstruction algorithms were combined with baseline ordered subsets expectation maximization, Gaussian filter (GF), point spread function (PSF), and time-of-flight (TOF). The image quality of the brain cortex was quantitatively evaluated with respect to spatial resolution, contrast, and signal-to-noise ratio (SNR).ResultsThe true coincidence rate in the brain was higher by 1.86 times and the random coincidence rate was lower by 0.61 times compared with that in the liver. In the brain, random fraction was lower and NECpatient was higher than that of the liver. Although GF improved the SNR, spatial resolution and contrast were reduced by 12 and 11%, respectively (P