Dual tracer brain PET simulation from two separate exams
2021
1528 Objectives: There are potential applications for dual tracer PET studies1,2. The advantages of doing simultaneous studies could vary from reducing cost and patient comfort to studying an identical physiological state. In most cases, the first step of designing such studies is simulations to predict the outcome or to optimize the dose or injection times. In order to do that, we have developed a tool to combine two separate PET exams of the same subject and the same radionuclide but different tracers to simulate the dual tracer imaging.
Theory: The first step of combining two brain PET exams is co-registration of the two studies. We have used the recently developed tool for rigid motion correction3`to co-register two brain exams. We used the Lava-Water MRI images of the two studies which are used for MR attenuation correction, to estimate the transform matrix between the two studies. We under-sampled both studies by a factor of 2 before combining them together and since the total random events of the two studies were very close (only 8% difference), we simply added the random estimates of the two exams for the combined study image reconstruction. We used the average scatter correction and the average sensitivity map for the combined study.
Methods: One subject was injected with 8 mCi of 18F-FBB and underwent a 30-minute brain scan after 60 min of uptake time on a SIGNA PET/MR (GE Healthcare, Waukesha, WI). Same subject on another date was injected with 9.5 mCi of 18F-PI-2620 and underwent a 30-minute brain scan after 60 min uptake time. Both studies were approved by Stanford9s Institutional Review Board and the subject provided written consent. 3D T1 IR FSPGR and 3D T2 FLAIR CUBE images were acquired simultaneously with PET. Head motion was estimated using 1 min frame PET frames for both studies. The motion transformation between the two studies’ Lava-Flex Water images was calculated and applied to 18F-PI-2620 study for co-registration. Both studies were reconstructed with full-dose and also with half-dose under-sampling. After half-dose under-sampling, all events from both studies were combined and reconstructed together to form the combined image.Two set of image reconstruction methods was used for full-dose, half-dose and combined study reconstruction. One was conventional TOF-OSEM with 1.17×1.17×2.78 mm3 image resolution using 28 subsets, 3 iterations, in-plane Gaussian filter with 4 mm spatial cut-off frequency and standard filtering in z-direction. The other one was MRgTOF-BSREM4 with 1 mm isotropic resolution with β =15 and βm=150.
Results: Figure 1 shows the full dose reconstructions of both 18F-FBB and 18F-PI2620 studies after motion correction and co-registration. It shows a good co-registration between the two studies. Figure 2 shows the half dose reconstructions along with the combined image. The combined image shows a good registration between the two studies. Figure 3 shows the full dose reconstructions of the two studies using MR priors. Figure 4 shows the half dose reconstructions along with the combined image using MR priors where it also shows a good registration between the two studies.
Conclusions and Discussion: We have presented a tool for combining two separate brain PET exams on the same subject with the same radionuclide but different tracers. This tool can be potentially used for designing and optimizing a simultaneous dual tracer brain PET exam.
References: 1. Moradi F., Iagaru, A. “Dual-tracer imaging of malignant bone involvement using PET”. Clin Transl Imaging3, 123-131 (2015)
2. El Fakhri G., et al., “Dual-Tracer PET Using Generalized Factor Analysis of Dynamic Sequences”, Mol Imaging Biol., 2013 Dec; 15(6).
3. Spangler-Bickell M. et al., "Rigid Motion Correction for Brain PET/MR Imaging using Optical Tracking", IEEE Transactions on Radiation and Plasma Medical Sciences, Oct 2018.
4. Khalighi MM, Deller T., et Al. High Quality Isotropic Whole-body PET Imaging Using MR Priors. J Nucl Med May 1, 2020 vol. 61 no. supplement 1 1477
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