Investigation of SPECT/CT cardiac imaging using Geant4

Alfuraih, A.; Kadri, O.; Alzimami, K.

doi:10.1007/s41365-018-0435-8

Cited by 6 publications

(3 citation statements)

References 33 publications

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“…At our knowledge, this is the first time using the Geant4 Monte Carlo simulation to fully compute the buildup factors for 20 human body tissues followed by parametric search of the well-known geometric progression formula and thus providing necessary materials for point kernel calculation applied to the High-Definition Reference Korean-Man (HDRK-Man). 13 - 15 Our previous work mainly focused on using GP parameters to compute BUFs, for all human tissues and organs, with a simple verification of Geant4 ability to predict the exposure buildup factor of water for a photon energy of .1 MeV and penetration depths up to 10 mfp. 4 Also, the work carried out by Jarrah et al 16 focused on the energy absorption buildup factor simulations of some ICRU tissue-like using MCNP5 code.…”

Section: Introductionmentioning

confidence: 99%

Geant4 Simulation of Gamma-Ray Transmission Buildup Factors for Human Tissues

Alfuraih

Kadri

2022

Dose-Response

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Quantification of scattered photons in addition to unscattered primary particles, under realistic exposure scenario, is best dealt with a parameter called “Buildup factor”. The aim of this work is to simulate the transmission buildup factor (BUF) of gamma-ray in the energy range .15–15 MeV for 20 human tissues and organs using the Geant4 (version 10.5) Monte Carlo simulation followed by a geometrical progression (GP) parameterization procedure. Firstly, we verified the accuracy of Geant4 ability to predict the effective transmitted dose according to published data. Also, a comparison of simulated BUF for different geometrical configurations was carried out for some tissues and source energies. Then, we checked out the linear dependency of the K parameter (BUF is function of K) function of mean free path (mfp). Finally, we developed a fitting procedure according to GP method for BUF corresponding to 20 tissues and organs and different mfp (from 1 to 8) for energy range .15–15 MeV. We found a good agreement with previous published data. Proper comprehension of BUF for tissues leads to carefully controlling the energy absorption in the human body. Consequently, provided BUF could be of great interest for estimating safe dose levels in medical imaging and radiation therapy.

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Section: Introductionmentioning

confidence: 99%

Geant4 Simulation of Gamma-Ray Transmission Buildup Factors for Human Tissues

Alfuraih

Kadri

2022

Dose-Response

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“…For nonpoint sources, computation and determination of the coordinates will be very complicated. [ 8 9 10 11 12 ]…”

Section: Introductionmentioning

confidence: 99%

“…For nonpoint sources, computation and determination of the coordinates will be very complicated. [8][9][10][11][12] For this reason, many efforts have been made to correct the attenuation and different approaches have been proposed so far.…”

Section: Introductionmentioning

confidence: 99%

Attenuation correction in single-photon emission computed tomography for NURBS-based cardiac-torso phantom using dual-energy acquisition

et al. 2020

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Single photon emission tomography is widely used to detect photons emitted from the patient. Some of these emitted photons suffer from scattering and absorption because of the attenuation occurred through their path in patient's body. Therefore, the attenuation is the most important problem in single-photon emission computed tomography (SPECT) imaging. Some of the radioisotopes emit gamma rays in different energy levels, and consequently, they have different counts and attenuation coefficients. Calculation of the parameters used in the attenuation equation Nout=αNin= e− μ l Ninby mathematical methods is useful for the attenuation correction. Nurbs-based cardiac-torso (NCAT) phantom with an adequate attenuation coefficient and activity distribution is used in this study. Simulations were done using SimSET in 20—70 and 20—167 keV. A total of 128 projections were acquired over 360°. The corrected and reference images were compared using a universal image quality index (UIQI). The simulation repeated using NCAT phantom by SimSET. In the first group, no attenuation correction was used, but the Zubal coefficients were used for attenuation correction in the second image group. After the image reconstruction, a comparison between image groups was done using optimized UIQI to determine the quality of used reconstruction methods. Similarities of images were investigated by considering the average sinogram for every block size. The results showed that the proposed method improved the image quality. This study showed that simulation studies are useful tools in the investigation of nuclear medicine researches. We produced a nonattenuated model using Monte Carlo simulation method and compared it with an attenuated model. The proposed reconstruction method improved image resolution and contrast. Regional and general similarities of images could be determined, respectively, from acquired UIQI of small and large block sizes. Resulted curves from both small and large block sizes showed a good similarity between reconstructed and ideal images.

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Monte Carlo methods for medical imaging research

Lee

2024

Biomed. Eng. Lett.

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In radiation-based medical imaging research, computational modeling methods are used to design and validate imaging systems and post-processing algorithms. Monte Carlo methods are widely used for the computational modeling as they can model the systems accurately and intuitively by sampling interactions between particles and imaging subject with known probability distributions. This article reviews the physics behind Monte Carlo methods, their applications in medical imaging, and available MC codes for medical imaging research. Additionally, potential research areas related to Monte Carlo for medical imaging are discussed.

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Investigation of SPECT/CT cardiac imaging using Geant4

Cited by 6 publications

References 33 publications

Geant4 Simulation of Gamma-Ray Transmission Buildup Factors for Human Tissues

Geant4 Simulation of Gamma-Ray Transmission Buildup Factors for Human Tissues

Attenuation correction in single-photon emission computed tomography for NURBS-based cardiac-torso phantom using dual-energy acquisition

Monte Carlo methods for medical imaging research

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