Feasibility of @entity9241 kinetic modeling in XXXX using shortened acquisition times.

@entity1 @entity135 @entity419 @entity9241 @entity5 @entity957 @entity15757 @entity27915 @entity519 @entity14 @entity19488 @entity35
UNASSIGNED: @entity9241 dynamic positron emission tomography (dPET) is used to identify @entity5 @entity519 non-invasively. Its routine clinical implementation, however, has been hampered by the long acquisition times required. We investigated the feasibility of kinetic modeling using shortened acquisition times in @entity9241 dPET, with the goal of expediting the clinical implementation of @entity9241 dPET protocols. METHODS: Six @entity1 with @entity957 of the @entity135 and ten HT29 @entity14 -bearing nude @entity35 were studied. In addition to an @entity419 PET scan, each @entity1 underwent a 45-min @entity9241 dPET scan, followed by 10 min acquisitions at 96  4 and 163  17 min post-injection. Ninety-minute @entity9241 dPET acquisitions were performed in animals. Intra- @entity5 voxels were classified into 4 clusters based on their kinetic behavior using k-means clustering. Kinetic modeling was carried out using the foregoing @entity27915 ( @entity27915 ) and repeated for each of two shortened datasets corresponding to the first ~100 min ( @entity15757 ; @entity1 only) or the first 45 min (SD2) of dPET data. The kinetic rate constants (KRCs) as calculated with a 2-compartment model for both @entity15757 and SD2 were compared to those derived from @entity27915 by correlation (Pearson), regression (Passing-Bablok), deviation (Bland-Altman) and classification (area under receiver operating characteristic curve; AUC) analyses. Simulations were performed to assess uncertainties due to statistical noise. RESULTS: Strong correlation (r>= 0.75, p<0.001) existed between all KRCs deduced from both @entity15757 and SD2, and from @entity27915 . Significant differences between KRCs were only found for @entity27915 -SD2 correlations in @entity1 studies. @entity19488 were reproducible to within ~6% and ~30% ( @entity27915 - @entity15757 ; @entity1 ) and ~4% and ~75% ( @entity27915 -SD2; animals). AUC values for classification of @entity1 clusters as @entity519 , using a @entity5 -to-blood ratio>1.2, were 0.91 ( @entity15757 ) and 0.86 (SD2). The percentage standard deviation in estimating @entity19488 from 45-min shortened datasets due to noise was <1% and between 2-12% respectively. CONCLUSION: Using single-session 45-min shortened @entity9241 dynamic PET datasets appears to be adequate for the identification of intra- @entity5 regions of @entity519 . However, k3 was significantly overestimated in the clinical cohort. Further studies are necessary to evaluate the clinical significance of differences between the results as calculated from full and shortened datasets.
