Abstract
This paper addresses 123I and 125I dual isotope SPECT imaging, which can be challenging because of spectrum overlap in the low energy spectrums of these isotopes. We first quantify the contribution of low-energy photons from each isotope using GATE-based Monte Carlo simulations for the MOBY mouse phantom. We then describe and analyze a simple, but effective method that uses the ratio of detected low and high energy 123I activity to separate the mixed low energy 123I and 125I activities. Performance is compared with correction methods used in conventional tissue biodistribution techniques. The results indicate that the spectrum overlap effects can be significantly reduced, if not entirely eliminated, when attenuation and scatter is either absent or corrected for using standard methods. In particular, we show that relative activity levels of the two isotopes can be accurately estimated for a wide range of organs and provide quantitative validation that standard methods for spectrum overlap correction provide reasonable estimates for reasonable corrections in small-animal SPECT/CT imaging.
Highlights
Dual isotope SPECT imaging using radioiodide is a useful technique for performing preclinical comparative effectiveness studies of biological agents, such as antibodies and peptides in individual animals
Quantitatively validate with Monte Carlo techniques, that spectrum stripping methods used in gamma counters for separating the contributions from each isotope provides a sufficient estimation of the degree of spectrum overlap and can confidently be applied accurately to SPECT/ CT imaging [7]
The 125I data from gamma counting of samples of liver, spleen, kidneys, and heart were corrected for spectral overlap by subtracting 43% of the counts measured in the 123I window
Summary
Dual isotope SPECT imaging using radioiodide is a useful technique for performing preclinical comparative effectiveness studies of biological agents, such as antibodies and peptides in individual animals. Quantitatively validate with Monte Carlo techniques, that spectrum stripping methods used in gamma counters for separating the contributions from each isotope provides a sufficient estimation of the degree of spectrum overlap and can confidently be applied accurately to SPECT/ CT imaging [7]. The 125I data from gamma counting of samples of liver, spleen, kidneys, and heart were corrected for spectral overlap (spillover) by subtracting 43% of the counts measured in the 123I (high energy) window.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
