99m Tc/ 123 I Dual-Radionuclide Correction for Self-Scatter, Down-Scatter, and Tailing Effect for a CZT SPECT with Varying Tracer Distributions.
Alexandre F VeloPeng FanHuidong XieXiongchao ChenNabil BoutagyAttila FeherAlbert J SinusasMichael LjungbergChi LiuPublished in: IEEE transactions on radiation and plasma medical sciences (2023)
SPECT systems distinguish radionuclides by using multiple energy windows. For CZT detectors, the energy spectrum has a low energy tail leading to additional crosstalk between the radionuclides. Previous work developed models to correct the scatter and crosstalk for CZT-based dedicated cardiac systems with similar 99m Tc/ 123 I tracer distributions. These models estimate the primary and scatter components by solving a set of equations employing the MLEM approach. A penalty term is applied to ensure convergence. The present work estimates the penalty term for any 99m Tc/ 123 I activity level. An iterative approach incorporating Monte Carlo into the iterative image reconstruction loops was developed to estimate the penalty terms. We used SIMIND and XCAT phantoms in this study. Distribution of tracers in the myocardial tissue and blood pool were varied to simulate a dynamic acquisition. Evaluations of the estimated and the real penalty terms were performed using simulations and large animal data. The myocardium to blood pool ratio was calculated using ROIs in the myocardial tissue and the blood pool for quantitative analysis. All corrected images yielded a good agreement with the gold standard images. In conclusion, we developed a CZT crosstalk correction method for quantitative imaging of 99m Tc/ 123 I activity levels by dynamically estimating the penalty terms.
Keyphrases
- monte carlo
- deep learning
- left ventricular
- high resolution
- preterm infants
- convolutional neural network
- pet ct
- optical coherence tomography
- pet imaging
- image quality
- positron emission tomography
- gestational age
- heart failure
- computed tomography
- electronic health record
- magnetic resonance
- artificial intelligence
- atrial fibrillation
- mass spectrometry
- fluorescence imaging