Advancement in PET quantification using 3D-OP-OSEM point spread function reconstruction with the HRRT
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Image reconstruction including the modelling of the point spread function (PSF) is an approach improving the resolution of the PET images. This study assessed the quantitative improvements provided by the implementation of the PSF modelling in the reconstruction of the PET data using the High Resolution Research Tomograph (HRRT).
Measurements were performed on the NEMA-IEC/2001 (Image Quality) phantom for image quality and on an anthropomorphic brain phantom (STEPBRAIN). PSF reconstruction was also applied to PET measurements in two cynomolgus monkeys examined with [18F]FE-PE2I (dopamine transporter) and with [11C]MNPA (D2 receptor), and in one human subject examined with [11C]raclopride (D2 receptor).
PSF reconstruction increased the recovery coefficient (RC) in the NEMA phantom by 11–40% and the grey to white matter ratio in the STEPBRAIN phantom by 17%. PSF reconstruction increased binding potential (BP ND) in the striatum and midbrain by 14 and 18% in the [18F]FE-PE2I study, and striatal BP ND by 6 and 10% in the [11C]MNPA and [11C]raclopride studies.
PSF reconstruction improved quantification by increasing the RC and thus reducing the partial volume effect. This method provides improved conditions for PET quantification in clinical studies with the HRRT system, particularly when targeting receptor populations in small brain structures.
KeywordsResolution Modelling Small brain nuclei Partial volume effect
The authors would like to thank members of the Karolinska Institutet PET Centre for assistance in the PET experiments. The authors also thank Drs. Inki Hong and Merence Sibomana for implementation of the PSF modelling in the fast reconstruction software, and Dr. Bruno Alfano for providing the STEPBRAIN phantom.
This study was presented in abstract form at the Neuroreceptor Mapping 2008 Meeting, Pittsburgh, PA, USA, and at the European Association of Nuclear Medicine 2008 Congress, Munich, Germany. This study was funded in part by the EC - FP6-project DiMI, LSHB-CT-2005-512146 and by VR Swedish Science Council 48105.
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