To date, no full kinetic analysis of [18 F]FDG data based on arterial sampling and a dynamic HRRT scanning protocol in humans has been reported. In the present study, average CMRglu values of 0.33 and 0.11 μmol/cm3 per minute were obtained for manually drawn gray and white matter regions, respectively. Automatically delineated regions yielded values of 0.29 and 0.19 μmol/cm3 per minute for gray matter and white matter, respectively, averaged over nine patients with a CoV of less than 15%. However, especially the white matter estimate based on the latter method was contaminated with some gray matter spill in.
Previously, Heiss and co-workers have acquired CMRglu data on an HRRT scanner . Using fixed rate constants from the literature, they found similar gray and white matter CMRglu values with a GM/WM ratio of 2.7, which is only slightly lower than the present ratio for manually drawn regions. Therefore, it seems that a static scanning protocol, together with fixed rate constants, is a valid approximation of full kinetic modeling in the case of healthy volunteers. Nevertheless, it should be noted that the assumption of fixed rate constants may not be valid in certain clinically relevant patient populations, such as those having diabetes , characterized by a.o. hyperglycemia and hyperinsulinemia which both affect the blood vessel wall and the permeability surface area product , and decreased glucose metabolism . Furthermore, normal fixed rate constants are not automatically applicable to flow-limited states .
The good correlation between Patlak and NLR results (slope 0.96, r2 0.98) implies that this linearization is a valid approach, as shown previously . The underestimation of 4% is likely due to the blood volume (5%) that is taken into account in the NLR analysis, but not in the Patlak linearization. Parametric K
i images without smoothing showed good correlation with regional K
i values (r2 of 0.99) with a slope of 1.04, probably induced by differences in noise and tissue heterogeneity present in regional- versus voxel-based TACs. Smoothing the dynamic 18 F]FDG images resulted in a lower slope and poorer correlation, and this is therefore not recommended.
Average CBF values of 0.43 and 0.13 mL/cm3 per minute were obtained for manually drawn gray and white matter regions, respectively. These values are in line with the recent data acquired on an HRRT by Walker and co-workers , who found values of 0.44 and 0.15 mL/cm3 per minute (Table 3). The good correlation between BFM and NLR results implies that this linearization is a valid approach.
We found an FDG extraction fraction of 18%, which is in line with earlier reported values of approximately 20% , determined using the double-indicator method . To our knowledge, this has not been derived from a combined CBF and CMRglu (K
1) measurement before.
The use of a noninvasive input function, derived from the carotid arteries, allowed for quantitatively correct estimates of regional CMRglu when Patlak linearization was used. In the case of NLR, however, the more stringent requirements placed on the input function (i.e., in addition to the area under the curve, the detailed shape of the peak is needed) resulted in good CMRglu estimates for only seven out of nine subjects and incorrect (with an average slope of 0.76) estimates in the other two. Nevertheless, clinical dynamic [18 F]FDG studies without the need for an arterial line can be performed (on a voxel-by-voxel basis) by analyzing data using the Patlak linearization.
Unfortunately, the IDIF approach was not applicable to the analysis of CBF scans. Scaling to the manual samples yielded a similar factor as for CMRglu scans, but an underestimation of the peak was observed (by a factor of 3). Although 15O has a higher positron energy (leading to an effective spatial resolution of 3.4 in the case of 15O, if it were 3.0 for 18 F), this is not likely to be the main reason for the underestimation of the peak. Possible explanations will probably include the implementation of scatter correction as well as the performance of the reconstruction algorithm for highly localized activity distributions, as prevailing in the blood just after the [15O]H2O bolus. Therefore, optimization of the frame definition and the use of a point spread function reconstruction may lead to a better match between BSIF and IDIF.
It is of importance to note that, although the images used were smoothed 6 mm at FWHM, the IDIF applicability cannot be automatically used for data generated at other PET scanners. This still needs a validation for every single tracer, every single scanner, and each acquisition and data analysis protocol separately. The success of the use of an IDIF depends on the intrinsic spatial resolution of the scanner, which is often lower than that of the scanner used in our study, and on the iterative reconstruction algorithm used (e.g., whether or not priors are included and whether the partial volume effect is implemented in the reconstruction algorithm), determining the signal-to-noise ratio as well as the minimum frame duration that can be applied. Furthermore, the duration of tracer injection needs to be optimized since the number of frames that can be acquired during the bolus should not be too low. The exact effect of these different options cannot be predicted and needs to be tested in the way as was described in this paper.