Norikazu Matsutomo
   Department   Kawasaki University of Medical Welfare  ,
   Position   Associate Professor with Special Assignment
Article types 原著
Language English
Peer review Peer reviewed
Title 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.
Journal Formal name：Nuclear medicine communications
Abbreviation：Nucl Med Commun
ISSN code：14735628/01433636
Domestic / ForeginDomestic
Volume, Issue, Page 35(12),pp.1224-32
Author and coauthor Akio Nagaki, Masahisa Onoguchi, Norikazu Matsutomo
Publication date 2014/12
Summary OBJECTIVES:Accurate 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-2-fluorodeoxy-D-glucose (F-FDG)-PET.MATERIALS AND METHODS:Using 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).RESULTS:The 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<0.01). PSF improved spatial resolution and SNR by 11 and 53%, respectively (P<0.01), and TOF improved SNR by ∼23% (P<0.01).CONCLUSION:We have demonstrated that a high-resolution image reconstruction algorithm for brain F-FDG-PET is promising without the use of a GF because of high true coincidence counts and that combined with PSF and TOF is optimal for obtaining a better SNR of the image.
DOI 10.1097/MNM.0000000000000187
PMID 25203246