[en] ¹⁸F-Florbetapir positron emission tomography (PET) can be used to image amyloid burden in the human brain. A previously developed research method has been shown to have a high test-retest reliability and good correlation between standardized uptake value ratio (SUVR) and amyloid burden at autopsy. The goal of this study was to determine how well SUVRs computed using the research method could be reproduced using an automatic quantification method, developed for clinical use. Two methods for the quantitative analysis of ¹⁸F-florbetapir PET were compared in a diverse clinical population of 604 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and in a group of 74 younger healthy controls (YHC). Cortex to cerebellum SUVRs were calculated using the research method, which is based on SPM, yielding 'research SUVRs', and using syngo.PET Amyloid Plaque, yielding 'sPAP SUVRs'. Mean cortical SUVRs calculated using the two methods for the 678 subjects were correlated (r = 0.99). Linear regression of sPAP SUVRs on research SUVRs was used to convert the research method SUVR threshold for florbetapir positivity of 1.10 to a corresponding threshold of 1.12 for sPAP. Using the corresponding thresholds, categorization of SUVR values were in agreement between research and sPAP SUVRs for 96.3 % of the ADNI images. SUVRs for all YHC were below the corresponding thresholds. Automatic florbetapir PET quantification using sPAP yielded cortex to cerebellum SUVRs which were correlated and in good agreement with the well-established research method. The research SUVR threshold for florbetapir positivity was reliably converted to a corresponding threshold for sPAP SUVRs. (orig.)

[en] Calculating attenuation correction for brain PET imaging rather than using CT presents opportunities for low radiation dose applications such as pediatric imaging and serial scans to monitor disease progression. Our goal is to evaluate the iterative time-of-flight based maximum-likelihood activity and attenuation correction factors estimation (MLACF) method for clinical FDG brain PET imaging. FDG PET/CT brain studies were performed in 57 patients using the Biograph mCT (Siemens) four-ring scanner. The time-of-flight PET sinograms were acquired using the standard clinical protocol consisting of a CT scan followed by 10 min of single-bed PET acquisition. Images were reconstructed using CT-based attenuation correction (CTAC) and used as a gold standard for comparison. Two methods were compared with respect to CTAC: a calculated brain attenuation correction (CBAC) and MLACF based PET reconstruction. Plane-by-plane scaling was performed for MLACF images in order to fix the variable axial scaling observed. The noise structure of the MLACF images was different compared to those obtained using CTAC and the reconstruction required a higher number of iterations to obtain comparable image quality. To analyze the pooled data, each dataset was registered to a standard template and standard regions of interest were extracted. An SUVr analysis of the brain regions of interest showed that CBAC and MLACF were each well correlated with CTAC SUVrs. A plane-by-plane error analysis indicated that there were local differences for both CBAC and MLACF images with respect to CTAC. Mean relative error in the standard regions of interest was less than 5% for both methods and the mean absolute relative errors for both methods were similar (3.4%  ±  3.1% for CBAC and 3.5%  ±  3.1% for MLACF). However, the MLACF method recovered activity adjoining the frontal sinus regions more accurately than CBAC method. The use of plane-by-plane scaling of MLACF images was found to be a crucial step in order to obtain improved activity estimates. Presence of local errors in both MLACF and CBAC based reconstructions would require the use of a normal database for clinical assessment. However, further work is required in order to assess the clinical advantage of MLACF over CBAC based method. (paper)