Purpose: This study aimed to investigate the results of compartmental modeling (CM) and spectral analysis (SA) generated with dynamic 18F-FMISO tumor images. Besides, the regular tissue-to-blood ratio (TBR) images were derived and compared with the dynamic models.
Methods: Nine subjects with glioblastoma underwent PET/CT imaging with the 18F-FMISO tracer. The protocol for PET imaging began with 15 min in dynamic mode and two 10-min duration static images at 120 min and 180 min post-injection. We used the two-tissue compartmental model for CM at the voxel basis, and we conducted SA to estimate the 18F-FMISO accumulation within each voxel. We also investigated the usual tumor-to-blood ratio (TBR) for comparison.
Results: The images of the tumor showed different patterns of hypoxia and necrosis as a function of PET scanning times, while CM and SA methods based on dynamic PET imaging equally located tumor hypoxia. The mean correlation of K images of all subjects between CM and SA was 0.63 ± 0.19 (0.24-0.86). CM produced less noisy images than SA, and, in the contrary, SA produced accumulation component images more clear than with CM. CM- and SA-K images were correlated with TBR images ( = 0.72 ± 0.20 and 0.56 ± 0.26, respectively). In the only subject having a continuously increasing tumor time-activity curve, the image showed a high uptake in the necrosis region which was not apparent in TBR or images.
Conclusion: Based on these results, the combination of CM and SA approaches was found more appropriate in generating voxel-based hypoxia images.
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| http://dx.doi.org/10.1007/s13139-021-00693-8 | DOI Listing |
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