Abstract
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Objectives SPECT has the ability to image multiple isotopes simultaneously by discriminating emission energies, which has the benefits of increasing throughput and imaging multiple functional parameters. However, multi-isotope imaging has not been widely used, due to down-scatter and the inability of conventional gamma cameras to discriminate closely separated energy emissions. Small scatter fraction in pre-clinical small animal imaging and the availability of high energy resolution CZT detector SPECT systems makes multi-isotope imaging practical, and phantom studies to evaluate the quantitative accuracy in multi-isotope imaging are presented in this paper.
Methods A phantom consisting of three 1.5-ml plastic test tubes, one containing 180 μCi In-111, one with 150 μCi Tc-99m, and one with a mixture of 50 μCi Tc-99m and 90 μCi In-111, was constructed. It was scanned using a Triumph pre-clinical PET/SPECT/CT system (GE Healthcare), which has a CZT based SPECT sub-system with 4.5% energy resolution. Quantitative accuracy was evaluated with different acquisition times in the range of 5 to 60 minutes, and energy windows of 5, 10, and 20%.
Results The energy spectrum from the phantom clearly distinguishes photo-peaks of all emissions. A visual inspection of the Tc-99m image with the 20% energy window shows contribution of counts from In-111, while In-111 contribution diminishes in the 5% energy window. Quantitative analysis indicates that the down-scattered counts in Tc-99m increase by 2.0 times and 3.8 times in 10% and 20% energy windows, respectively, compared to 5% energy window counts. Images in In-111 windows did not show any visible contribution from Tc-99m. Quantitatively, they were less than 5% of Tc-99m photo-peak counts.
Conclusions Quantitative accuracy of dual-isotope imaging was evaluated in a mouse-sized phantom. The high-energy resolution of the CZT detector enables minimal down scatter from higher energy isotopes into lower energy isotope windows, making multi-isotope SPECT imaging practical in pre-clinical settings