Introduction: In this study, we aimed to evaluate the possibility of assessing cardiac abnormality using the left ventricular anatomical axis (LVAA) obtained from short-axis views of myocardial perfusion imaging (MPI).Methods: To obtain LVAA, an ellipse was drawn around the outer wall of SPECT images from XCAT phantoms and patients. The best line was then drawn from the center of all the ellipses in the short-axis views called LVAA. Then, we defined two angles based on LVAA including Ɵ which is the angle created by LVAA with the x-axis, and Φ which is the angle created by LVAA with the z-axis.Results: In this study, 94 cases were enrolled including 48 males (51%) and 46 females (49%) with a mean age of 65.65±10.04. According to the results, there was a significant difference between the two obtained angles and the result of the scan (p<0.05). The ideal cut-off of Ɵ for an abnormal scan was 91.79 (AUC, 0.93; p=0.001) with the sensitivity of 98% and specificity of 80%.Conclusion: It can be concluded that LVAA as a quantitative factor is significantly different between normal and abnormal MPS and can be used for the evaluation of MPI.

Purpose: Noise in brain Single Photon Emission Computed Tomography (SPECT) images limits an early diagnosis of Parkinson's Disease (PD). To overcome the limitation, as an image processing approach, wavelet transformation was used to denoising the images also with a segmentation method to differentiate the basal ganglia in brain SPECT. Materials and Methods: The brain scans of the human XCAT phantom through the Simulating Medical Imaging Nuclear Detectors (SIMIND) simulated SPECT system were imported to the MATLAB toolkit for image processing. The reconstructed brain images by iterative reconstruction were de-noised through 9 methods of wavelet transformation at different levels, and then six segmentation methods were applied to differentiate the caudate and putamen. The Dice coefficient, Specificity, and Sensitivity evaluation criteria were calculated based on the adaptive thresholding of the selected images from segmentation. A ground truth image was manually marked by a clinical nuclear medicine specialist. Results: The dice coefficient was obtained in a range from 0. 3979 to 0. 6299, as well as the specificity criterion from 0. 7682 to 0. 8168 and the sensitivity from 0. 9049 to 0. 9871. The results from adaptive threshold segmentation and the evaluation criteria showed that the best levels of the nucleuses detectability were provided by level 7 of Biorthogonal, levels 4 and 7 of Coiflet, level 6 of Daubechies, level 5 of Haar, level 6 of Morlet and level 6 of Symlet methods. Conclusion: Parkinson’s disease may be diagnosed in the early stage by an image processing approach to improve the quality of brain SPECT images.

Introduction: Use of SPECT/CT data is the most accurate method for patient-specific internal dosimetry when isotopes emit single gamma rays. The manual or semi-automatic segmentation of organs is a major obstacle that slows down and limits the patient-specific dosimetry. Using digital phantoms that mimic patient’s anatomy can bypass the segmentation step and facilitate the dosimetry process. In this study, the results of a patient-specific dosimetry based on CT data and XCAT phantom, a flexible phantom with predefined organs, are compared.Methods: The dosimetry results (S-value and SAF) were calculated for a patient with breast cancer who received Samarium- 153 ethylenediamine-N, N, N′, N′-tetrakis (methylenephosphonic acid (153 Sm-EDTMP). Biodistribution of activity was obtained from the SPECT scan. The anatomical data and attenuation map were extracted from CT as well as the XCAT phantom with different BMIs. GATE Monte-Carlo simulator was used to calculate the dose to different organs based on the activity distribution and segmented anatomy.Results: The whole body dosimetry results are the same for both calculations based on the CT and XCAT with different BMIs; however for target organs, the differences between SAFs and S-values are high. In the spine, the clinically important target organ for Samarium therapy, the dosimetry results obtained from phantoms with unmatched BMIs between XCAT phantom and CT are substantially different.Conclusion: We showed that atlas-based dosimetry using XCAT phantom even with matched BMI may lead to considerable errors as compared to calculations based on patient’s own CT. For accurate dosimetry results, calculations should be done using CT data.

For specific clinical diagnoses, positron emission tomography (PET) can detect more sites of disease than conventional anatomical imaging such as x-ray computed tomography (CT) or magnetic resonance imaging (MRI). Interpretation of PET can be difficult; however, PET images have few anatomical landmarks for determining the location of abnormal findings. Combining PET and CT images acquired sequentially on their separate devices provides a partial solution to this problem. In earlier years PET/CT has an important role in detecting tumors, planning radiation treatment and evaluating response to therapy. Differences in PET and CT imaging time, especially in the lung region, cause artifacts and errors in estimating tumor uptake and volume determination. The purpose of this paper was to investigate qualitative and quantitative errors due to respiratory artifacts on tumors of the lung. For this purpose, the XCAT phantom was used to simulate respiratory motion and also, STIR was used to apply attenuation maps on reconstruction of PET images. The evaluation of results was performed by ROI and SULmax parameters. The images from various methods of attenuation correction, indicated that respiratory motion on regions above the lungs is poorly. The best method is the Initial review of PET images to obtain the size and location of the tumor and then make a decision about the appropriate respiratory phase based on the size and location of the tumor for attenuation correction of PET images.

Background & Aims: Nowadays, imaging of the blood supply of the heart muscle by single photon emission computed tomography (SPECT: Single Photon Emission Computed Tomography) due to its non-invasive nature and providing information with physiological value and low cost compared to the valuable angiography method. It is highly diagnostic. But these images undergo changes and artifacts under the influence of factors, the result of which is the reduction of the diagnostic accuracy of the images and false positive cases. During the detection process, several physical effects such as attenuation, scattering, and collimator response function affect the frequency of emitted photons,this leads to the destruction of the contrast and as a result of reducing the quantitative and qualitative accuracy of the images. Attenuation, as the most destructive factor of SPECT images, reduces the quality of SPECT images of heart blood supply and reduces the sensitivity of tests related to the diagnosis of coronary artery diseases, and for non-uniform environments, especially in nuclear imaging of chest areas. And the heart is necessary to produce a map of patient attenuation coefficients. The existence of scattered photons is also one of the main factors of error in quantization,the detection of scattered events affects the contrast of the lesions and causes the lack of image resolution and signal-to-noise ratio. Therefore, to correct the attenuation and scattering of the rays in the heart images quantitatively and qualitatively, patterns are needed in SPECT systems. Due to the importance of the topic, various research groups around the world have presented their research and results on correcting the effect of scattering of rays and also correcting the effect of weakening the rays. If there was no limitation of energy resolution, it was easily possible to identify the scattered rays and prevent them from being recorded in the image. Because we know that scattered rays lose energy. Because gamma rays are single energy and their energy amount is completely known. Therefore, each photon with less energy will represent scattered rays, but due to the limited energy resolution of the gamma camera, a range is usually considered on the sides of the main energy, which is called the energy window. It is assumed that the photons recorded in this energy range are primary photons, but in fact, many photons scattered in the body are also recorded in this window. These scattered rays do not carry correct spatial information and lead to a decrease in image resolution and contrast and quantization errors in the image. In nuclear medicine, instead of researching and examining the patient or processing the image of the patient, simulated images can be examined. Simulators can provide information about each of the image destruction factors. The purpose of this research is to propose a new method for scattering correction, in this research, a combination of Monte Carlo and modeling is used for the rapid production of scattered views, and in the proposed method, the two-matrix method is used, this method At the stage of generating mathematical views, dispersion is added and this problem leads to the removal of scattered rays. As a result, an image is reconstructed that is free from the effects of attenuation and non-ideal dispersion and leads to an increase in contrast and improvement of power. Detecting waste, increasing the signal-to-noise ratio, and increasing the accuracy of quantification. Methods: In this study, the effect of applying attenuation and dispersion correction using two energy windows (DEW) and three energy windows (TEW) methods in cardiac aspect imaging was investigated and evaluated, and to simulate cardiac aspect imaging, a special code similar to SAR Monte Carlo GATE was used as the SPECT imaging system and XCAT digital phantom with activity distribution and realistic attenuation map was used to model the human trunk. Results: Comparison of image contrast improvement in different modes of attenuation and dispersion correction shows that the highest image contrast is obtained from the (TEW1+AC) method with an average increase of 25% and MSE in different modes of attenuation correction. And the dispersion compared to the reference image was reduced from 51. 5% to 54. 5%. Compared to the reference image, MSE decreased from 1. 4 in Un_Cor to 1. 15, 1. 13, 1. 12, and 1. 14 in AC+TEW1, AC+DEW, AC, and AC+TEW2, respectively, and the signal-to-noise ratio (SNR) increased up to 71% in all methods of applying dispersion correction along with attenuation correction compared to applying attenuation correction (AC). Conclusion: In this study, the effect of attenuation and dispersion correction in 5 non-correction modes, with attenuation correction, attenuation, and dispersion correction using two-window and three-window methods with triangular approximation and three-window with trapezoidal approximation on We evaluated XCAT phantom simulated images and heart muscle perfusion images by SPECT method and 4 different parameters were used to compare and evaluate the images, including profile, contrast, mean squared error (MSE) and signal to noise. According to the results of the quantification of reconstructed images, it is possible to apply dispersion correction along with attenuation correction.

Cone-Beam CT (CBCT) is well known for its role in dental imaging, diagnosis, and treatment planning, but xrays can be risky. This study aimed to provide an accurate and comprehensive database of organs and size-specific effective doses based on body mass indexes (BMI) of patients in dental-CBCT units. To simulate exposure geometry for three different imaging protocols with GIANO CBCT, one of the commonly used units in Iran, the Monte-Carlo (MC) method was used. The population of Extended-Cardiac Torso(XCAT) adult male and female computational phantoms with various BMIs were used in the simulation as input files. The measured doses from the Rando phantom and thermoluminescence dosimeters were compared with simulated doses based on CT images of the Rando phantom. This was done to validate the simulations. The results showed the organs doses for the different Fields-of-View(FOVs) varied widely, usually in adult females was higher. The maximum size-specific effective doses for temporomandibular-joint (TMJ), single, and both arch protocols were 94±5μSv, 63±4μSv, and 62±2μSv for adult males with BMIs 25.82, 21.70, and 21.71kg m-2, whereas, and 98±3μSv, 69±1 μSv and 66±1μSv for adult females with BMIs 21.69, 21.71 and 21.72kg m-2, respectively. Also, the difference between the minimum and maximum value of effective dose in TMJ, single, and both-arch protocols was 24%, 37%, and 32% for AM. These AF values were 24%, 32%, and 35%, respectively. Eventually, this study provides a comprehensive data set of patient doses for wide ranges of BMIs without experimental measurement.

Dynamic Positron Emission Tomography (PET) imaging has significant potential for extracting kinetic parameters of tracers, particularly the Ki parameter. This study evaluates the use of the Dual Time Point (DTP) technique to generate parametric Ki images from two 3-minute static PET scans. A simulation study was conducted using the XCAT phantom, generating six realistic heterogeneous tumors embedded in lung and liver tissues with various levels of [18F] FDG uptake. Parametric Ki images were generated and evaluated using Patlak analysis and a population-based input function (PBIF). Additionally, TBR and CNR parameters in SUV images and parametric images produced by DTP and full dynamic methods were compared and analyzed. The results showed a significant correlation (> 0.9) between the Ki parameter derived from DTP and full dynamic imaging methods. Moreover, the high TBR parameter in DTP images compared to SUV images (70% for lung tumors, 35% for liver tumors) indicates improved contrast and image quality. Consequently, DTP images can be a suitable alternative to complete dynamic PET and SUV images in clinical settings.

Introduction Patient set-up optimization is required in radiotherapy to fill the accuracy gap between personalized treatment planning and uncertainties in the irradiation set-up. In this study, we aimed to develop a new method based on neural network to estimate patient geometrical setup using 4-dimensional (4D) XCAT anthropomorphic phantom. Materials and Methods To access 4D modeling of motion of dynamic organs, a phantom employs non-uniform rational B-splines (NURBS)-based Cardiac-Torso method with spline-based model to generate 4D computed tomography (CT) images. First, to generate all the possible roto-translation positions, the 4D CT images were imported to Medical Image Data Examiner (AMIDE). Then, for automatic, real time verification of geometrical setup, an artificial neural network (ANN) was proposed to estimate patient displacement, using training sets. Moreover, three external motion markers were synchronized with a patient couch position as reference points. In addition, the technique was validated through simulated activities by using reference 4D CT data acquired from five patients. Results The results indicated that patient geometrical set-up is highly depended on the comprehensiveness of training set. By using ANN model, the average patient setup error in XCAT phantom was reduced from 17. 26 mm to 0. 50 mm. In addition, in the five real patients, these average errors were decreased from 18. 26 mm to 1. 48 mm various breathing phases ranging from inhalation to exhalation were taken into account for patient setup. Uncertainty error assessment and different setup errors were obtained from each respiration phase. Conclusion This study proposed a new method for alignment of patient setup error using ANN model. Additionally, our correlation model (ANN) could estimate true patient position with less error.