new approach to scatter correction in SPECT images based on Klein_Nishina equation

Scattered photon is one of the main defects that degrade the quality and quantitative accuracy of nuclear medicine images. Accurate estimation of scatter in projection data of SPECT is computationally extremely demanding for activity distribution in uniform and non-uniform dense media. The objective of this paper is to develop and validate a scatter correction technique that use an accurate analytical model based on Klein_Nishina scatter equation and compare Klein_Nishina scatter estimation with triple energy window. In order to verify the proposed scattering model several cylindrical phantoms were simulated. The linear source in the cylindrical Phantoms was a hot rod filled with 99mTc. K factor defines as the ratio of scatter resulting from MC simulation to scatter estimated from Klein_Nishina formula. Also a SPECT/CT scan of the image quality phantom was acquired. Row data were transferred to a PC computer for scatter estimation and processing of the images using MLEM iterative algorithm in MATLAB software. The scatter and attenuation compensated images by the proposed model had better contrast than uncorrected and only attenuation corrected images. The K-factors that used in proposed model doesn't vary with different activities and diameters of linear source and they're just a function of depth and composition of pixels. Based on Mont Carlo simulation data, the K_N formula that used in this study demonstrates better estimation of scattered photons than TEW. Proposed scattered correction algorithm will improve 52.3% in the contrast of the attenuated corrected images of image quality phantom

Evaluation of the role of system matrix in SPECT images reconstructed by OSEM technique

Ordered subset expectation maximization [OSEM], is an effective iterative method for SPECT image reconstruction. The aim of this study is the evaluation of the role of system matrix in OSEM image reconstruction method using four different physical beam radiation models with three detection configurations. SPECT was done with an arc of 180 degree in 32 projections after injection of 2 mCi of [99m]Tc-pertechnetate in a heart phantom by a Siemens E.Cam gamma camera equipped with LEHR collimator and data were transferred to a PC computer for reconstruction of the images with Mathlab software. The system or probability matrixes were firstly calculated using radiation fraction of pixels for three different detection models with linear, rectangular and divergent FOV, and reduction coefficient of photons from pixels to detectors in four different radiation models of distance independent [DID], inverse distance dependence [IDD] [= 1/R], inverse square distance dependence [ISDD],[= 1/R[2]] and inverse exponential distance dependence[IEDD], [= exp-R]. In these calculations the detector was assumed at a distance of 842 mm from the phantom center and pixel size was 6.638 mm. The divergent angle in divergent field of view was 2.08 degree. 12 Images of the phantom were reconstructed using system matrixes of 4 different radiation and 3 detection models. Qualities of the images were compared using universal image quality index, UIQI. The results shows negligible although statistically significant difference between contrast and brightness of the images, but it is possible in the organs with constant absorption coefficients such as brain, to use the system matrix with mathematical IEDD radiation model for attenuation correction in SPECT images. It is shown that variation in distance weighting factors in mathematical IEDD radiation model changes the system matrix so that the weights of deeper data decrease in image reconstruction process. Therefore, by this method contrast of the image at different depth can be controlled. Applying different beam radiation models and detection configurations in system matrix has no significant improvements on the image quality. However image contrast at different depth can be controlled by using system matrix derived from different distance weighting factor in mathematical IEDD radiation model

Evaluation of attenuation correction process in cardiac SPECT images

Attenuation correction is a useful process for improving myocardial perfusion SPECT and is dependent on activity and distribution of attenuation coefficients in the body [attenuation map]. Attenuation artifacts are a common problem in myocardial perfusion SPECT. The aim of this study was to compare the effect of attenuation correction using different attenuation maps and different activities in a specially designed heart phantom. The SPECT imaging for different activities and different body contours were performed by a phantom using tissue-equivalent boluses for making different thicknesses. The activity was ranged from 0.3-2mCi and the images were acquired in 180 degree, 32 steps. The images were reconstructed by OSEM method in a PC computer using Matlab software. Attenuation map were derived from CT images of the phantom. Two quality and quantity indices, derived from universal image quality index have been used to investigate the effect of attenuation correction in each SPECT image. The result of our measurements showed that the quantity index of corrected image was in the range of 3.5 to 5.2 for minimum and maximum tissue thickness and was independent of activity. Comparing attenuation corrected and uncorrected images, the quality index of corrected image improved by increasing body thickness and decreasing activity of the voxels. Attenuation correction was more effective for images with low activity or phantoms with more thickness. In our study, the location of the pixel relative to the associated attenuator tissues was another important factor in attenuation correction. The more accurate the registration process [attenuation map and SPECT] the better the result of attenuation correction