[en] Florbetaben is a β-amyloid-targeted PET tracer with significant potential for augmenting the toolbox in the clinical diagnosis of Alzheimer's disease (AD). In dementia imaging, shortening of scan duration may simplify future clinical use. The aim of this retrospective study was to investigate the effect of scan duration on diagnostic accuracy. PET scans obtained from 25 AD patients and 25 healthy volunteers (HVs) were analysed. In each subject, scans of three different durations (5, 10 and 20 min; all starting 90 min after injection) were obtained, randomized, and visually assessed by three experts blinded to the subject's identity and group affiliation. Presence/absence of β-amyloid and diagnostic confidence (0-100 %) were scored, and 10 % of the scans were re-read. Further, randomly selected datasets of ten AD patients and ten HVs were quantified using an established VOI-based approach and using a voxel-based approach. The sensitivity and specificity of the blinded read were 80 % and 96 %, respectively, for all scan durations. Diagnostic confidence was high (97 ± 6 %, 97 ± 6 % and 95 ± 8 % for the 20-min, 10-min and 5-min scans, respectively; n.s.), as was interreader agreement (kappa_20min = 0.94, kappa_10min = 0.94, kappa_5min = 0.89; n.s.). Intrareader agreement was highest for the 20-min scan (kappa = 1.00) and lower for the 10-min scan (kappa = 0.71) and 5-min scan (kappa = 0.80; p = 0.002 and 0.003 vs. the 20-min scan). For all scan durations, composite SUVRs (Cohen's d effect size 4.5, 3.9 and 4.8 for the 5-min, 10-min and 20-min scans; p < 0.0001 each) and individual brain volumes affected by β-amyloid (Cohen's d effect size 1.6, 1.8 and 2.0 for the 5-min, 10-min and 20-min scans; p < 0.005 each) were significantly higher in AD patients than in HVs. Reduction in scan duration did not relevantly affect the accuracy of florbetaben PET scans in discriminating between AD patients and HVs. Thus, a reduction in scan duration seems conceivable for the future clinical use of florbetaben. (orig.)

[en] For regional quantification of nuclear brain imaging data, defining volumes of interest (VOIs) by hand is still the gold standard. As this procedure is time-consuming and operator-dependent, a variety of software tools for automated identification of neuroanatomical structures were developed. As the quality and performance of those tools are poorly investigated so far in analyzing amyloid PET data, we compared in this project four algorithms for automated VOI definition (HERMES Brass, two PMOD approaches, and FreeSurfer) against the conventional method. We systematically analyzed florbetaben brain PET and MRI data of ten patients with probable Alzheimer's dementia (AD) and ten age-matched healthy controls (HCs) collected in a previous clinical study. VOIs were manually defined on the data as well as through the four automated workflows. Standardized uptake value ratios (SUVRs) with the cerebellar cortex as a reference region were obtained for each VOI. SUVR comparisons between ADs and HCs were carried out using Mann-Whitney-U tests, and effect sizes (Cohen's d) were calculated. SUVRs of automatically generated VOIs were correlated with SUVRs of conventionally derived VOIs (Pearson's tests). The composite neocortex SUVRs obtained by manually defined VOIs were significantly higher for ADs vs. HCs (p=0.010, d=1.53). This was also the case for the four tested automated approaches which achieved effect sizes of d=1.38 to d=1.62. SUVRs of automatically generated VOIs correlated significantly with those of the hand-drawn VOIs in a number of brain regions, with regional differences in the degree of these correlations. Best overall correlation was observed in the lateral temporal VOI for all tested software tools (r=0.82 to r=0.95, p<0.001). Automated VOI definition by the software tools tested has a great potential to substitute for the current standard procedure to manually define VOIs in β-amyloid PET data analysis. (orig.)