DocumentCode :
3330481
Title :
Simultaneous 99mTc/111In SPECT image reconstruction using convolution based forced detection
Author :
Karamat, Muhammad I. ; Farncombe, Troy H.
Author_Institution :
Dept. of Med. Phys. & Appl. Radiat. Sci., McMaster Univ., Hamilton, ON, Canada
fYear :
2011
fDate :
23-29 Oct. 2011
Firstpage :
2625
Lastpage :
2631
Abstract :
Simultaneous multi-isotope SPECT imaging has a number of applications, for example, cardiac, brain and cancer imaging. The major concern in simultaneous multi-isotope is the significant crosstalk contamination between the different isotopes used. The current study focuses on a method of crosstalk compensation between two isotopes in simultaneous dual isotope SPECT acquisition applied to cancer imaging using 99mTc/111In. Monte Carlo (MC), which is thought to offer the most realistic crosstalk and scatter compensation modeling, in typical implementations, has inherent long calculation times (often several hours or days) associated with it. This makes MC unsuitable for clinical applications. We have previously incorporated convolution based forced detection into SIMIND Monte Carlo program which have made MC feasible to use in clinical time frames. In order to evaluate the accuracy of our accelerated MC program a number of point source simulation results were compared to experimentally acquired data in terms of spatial resolution and detector sensitivity. We have developed an iterative MC-based image reconstruction technique that simulates the photon downscatter from one isotope into the acquisition window of a second isotope. The MC based estimation of scatter contamination contained in projection views is then used to compensate for the photon contamination during iterative reconstruction. We use a modified ordered subset-expectation maximization (OS-EM), named as simultaneous ordered subset-expectation maximization (Sim-OSEM), to perform this step. We have undertaken a number of simulation tests and phantom studies to verify this approach. The proposed reconstruction technique also evaluated by reconstruction of experimentally acquired projection phantom data. Reconstruction using Sim-OSEM showed very promising results in terms of crosstalk and scatter compensation and uniformity of background compared to analytical attenuation based reconstruc- ion after triple energy window (TEW) based scatter correction of projection data. In our case images obtained using Sim-OSEM showed better scatter compensation and more uniform background when compared to the images reconstructed for separately acquired projection data using analytical attenuation based reconstruction.
Keywords :
Monte Carlo methods; brain; cancer; convolution; crosstalk; data acquisition; image reconstruction; image resolution; medical image processing; optimisation; phantoms; single photon emission computed tomography; Monte Carlo based estimation; SIMIND Monte Carlo program; analytical attenuation method; brain imaging; cancer imaging; cardiac imaging; clinical time frames; convolution based forced detection method; crosstalk compensation method; crosstalk contamination analysis; detector sensitivity analysis; iterative MC-based image reconstruction technique; modified ordered subset-expectation maximization; photon contamination analysis; photon downscatter simulation; point source simulation; projection phantom data analysis; scatter compensation model; scatter contamination estimation; simultaneous 111In SPECT image reconstruction; simultaneous 99mTc SPECT image reconstruction; simultaneous dual isotope SPECT acquisition; simultaneous multiisotope SPECT imaging method; simultaneous ordered subset-expectation maximization; spatial resolution; triple energy window; Educational institutions; Isotopes; USA Councils; Monte Carlo; OS-EM; SPECT; crosstalk;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), 2011 IEEE
Conference_Location :
Valencia
ISSN :
1082-3654
Print_ISBN :
978-1-4673-0118-3
Type :
conf
DOI :
10.1109/NSSMIC.2011.6152704
Filename :
6152704
Link To Document :
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