Nucl Med Mol Imaging.  2021 Jun;55(3):107-115. 10.1007/s13139-021-00693-8.

Quantification of Hypoxia in Human Glioblastoma using PET with 18F-FMISO

• Abdo Ra
• Lamare F
• Fernandez P
• Bentourkia M

• KMID: 2516688
• DOI: http://doi.org/10.1007/s13139-021-00693-8

Abstract

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_i images of all subjects between CM and SA was 0.63 ± 0.19 (0.24-0.86). CM produced less noisy K_i images than SA, and, in the contrary, SA produced accumulation component images more clear than with CM. CM-K_i and SA-K_i images were correlated with TBR images (r = 0.72 ± 0.20 and 0.56 ± 0.26, respectively). In the only subject having a continuously increasing tumor time-activity curve, the K₃ image showed a high uptake in the necrosis region which was not apparent in TBR or K_i images.
Conclusion
Based on these results, the combination of CM and SA approaches was found more appropriate in generating voxelbased hypoxia images.

Keyword

FMISO; Hypoxia; Compartmental modeling; Spectral analysis