• Nuclear Engineering and Technology
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• v.49 no.4
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• pp.776-780
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• 2017

To avoid imaging artifacts and interpretation mistakes, an improvement of the uniformity in gamma camera systems is a very important point. We can expect excellent uniformity using cadmium zinc telluride (CZT) photon counting detector (PCD) because of the direct conversion of the gamma rays energy into electrons. In addition, the uniformity performance such as integral uniformity (IU), differential uniformity (DU), scatter fraction (SF), and contrast-to-noise ratio (CNR) varies according to the energy window setting. In this study, we compared a PCD and conventional scintillation detector with respect to the energy windows (5%, 10%, 15%, and 20%) using a $^{99m}Tc$ gamma source with a Geant4 Application for Tomography Emission simulation tool. The gamma camera systems used in this work are a CZT PCD and NaI(Tl) conventional scintillation detector with a 1-mm thickness. According to the results, although the IU and DU results were improved with the energy window, the SF and CNR results deteriorated with the energy window. In particular, the uniformity for the PCD was higher than that of the conventional scintillation detector in all cases. In conclusion, our results demonstrated that the uniformity of the CZT PCD was higher than that of the conventional scintillation detector.

• Nuclear Engineering and Technology
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• v.56 no.6
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• pp.2412-2420
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• 2024

The International Atomic Energy Agency (IAEA) mandates safeguards to ensure non-proliferation of nuclear materials. Among inspection techniques used to detect partial defects within spent nuclear fuel (SNF), gamma emission tomography (GET) has been reported to be reliable for detection of partial defects on a pin-by-pin level. Conventional GET, however, is limited by low detection efficiency due to the high density of nuclear fuel rods and self-absorption. This paper proposes a new type of GET named Spent Fuel Internal Tomography (SFIT), which can acquire sinograms at the guide tube. The proposed device consists of the housing, shielding, C-shaped collimator, reflector, and gadolinium aluminum gallium garnet (GAGG) scintillator. For accurate attenuation correction, the source-distinguishable range of the SFIT device was determined using MC simulation to the region away from the proposed device to the second layer. For enhanced inspection accuracy, a proposed specific source-discrimination algorithm was applied. With this, the SFIT device successfully distinguished all source locations. The comparison of images of the existing and proposed inspection methods showed that the proposed method, having successfully distinguished all sources, afforded a 150 % inspection accuracy improvement.

• Journal of Radiation Protection and Research
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• v.49 no.1
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• pp.29-39
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• 2024

Background: The gamma emission tomography (GET) device has been reported a reliable technique to inspect partial defects within spent nuclear fuel (SNF) of pin-by-pin level. However, the existing GET devices have low accuracy owing to the high attenuation and scatter probability for SNF inspection condition. The purpose of this study is to design and optimize a Yonsei single-photon emission computed tomography version 2 (YSECT.v.2) for fast inspection of SNF in water storage by acquisition of high-quality tomographic images. Materials and Methods: Using Geant4 (Geant4 Collaboration) and DETECT-2000 (Glenn F. Knoll et al.) Monte Carlo simulation, the geometrical structure of the proposed device was determined and its performance was evaluated for the ¹³⁷Cs source in water. In a Geant4-based assessment, proposed device was compared with the International Atomic Energy Agency (IAEA)-authenticated device for the quality of tomographic images obtained for 12 fuel sources in a 14 × 14 Westinghouse-type fuel assembly. Results and Discussion: According to the results, the length, slit width, and septal width of the collimator were determined to be 65, 2.1, and 1.5 mm, respectively, and the material and length of the trapezoidal-shaped scintillator were determined to be gadolinium aluminum gallium garnet and 45 mm, respectively. Based on the results of performance comparison between the YSECT.v.2 and IAEA's device, the proposed device showed 200 times higher performance in gamma-detection sensitivity and similar source discrimination probability. Conclusion: In this study, we optimally designed the GET device for improving the SNF inspection accuracy and evaluated its performance. Our results show that the YSECT.v.2 device could be employed for SNF inspection.

• Journal of Korean Neurosurgical Society
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• v.60 no.1
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• pp.98-101
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• 2017

We report a case of primary intracranial malignant melanoma (PIMM) with extracranial metastases. The patient was an 82-year-old woman diagnosed with PIMM under the left cerebellar tentorium. We performed a tumor resection followed by gamma knife surgery. An magnetic resonance imaging at 11 months after surgery showed a local intracranial recurrence. At 12 months, vertebral metastasis was suspected, and 2-[fluorine-18]-fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (FDG-PET/CT) showed multiple extracranial metastases. She died at 13 months after surgery. Although extracranial metastases of PIMM are extremely rare, we should carefully follow up extracranial metastases together with intracranial ones, especially by FDG-PET/CT, even at an early asymptomatic stage.

• Nuclear Engineering and Technology
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• v.56 no.5
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• pp.1733-1737
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• 2024

In order to specify the location of the scintillation pixel that interacted with gamma rays in the positron emission tomography (PET) detector, conventionally, after acquiring a flood image, the location of interaction between the scintillation pixel and gamma ray could be specified through a pixel-segmentation process. In this study, the experimentally acquired signal was specified as the location of the scintillation pixel directly, without any conversion process, through the simulation data and the deep learning algorithm. To evaluate the accuracy of the specification of the scintillation pixel location through deep learning, a comparative analysis with experimental data through pixel segmentation was performed. In the same way as in the experiment, a detector was configured on the simulation, a model was built using the acquired data through deep learning, and the location was specified by applying the experimental data to the built model. Accuracy was calculated through comparative analysis between the specified location and the location obtained through the segmentation process. As a result, it showed excellent accuracy of about 85 %. When this method is applied to a PET detector, the position of the scintillation pixel of the detector can be specified simply and conveniently, without additional work.

• Nuclear Medicine and Molecular Imaging
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• v.42 no.2
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• pp.118-126
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• 2008

Statistical image reconstruction methods have played an important role in emission computed tomography (ECT) since they accurately model the statistical noise associated with gamma-ray projection data. Although the use of statistical methods in clinical practice in early days was of a difficult problem due to high per-iteration costs and large numbers of iterations, with the development of fast algorithms and dramatically improved speed of computers, it is now inevitably becoming more practical. Some statistical methods are indeed commonly available from nuclear medicine equipment suppliers. In this paper, we first describe a mathematical background for statistical reconstruction methods, which includes assumptions underlying the Poisson statistical model, maximum likelihood and maximum a posteriori approaches, and prior models in the context of a Bayesian framework. We then review a recent progress in developing fast iterative algorithms.

• Journal of Korean Neurosurgical Society
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• v.62 no.4
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• pp.476-486
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• 2019

Objective : The functional information of $^{11}C$-methionine positron emission tomography (MET-PET) images can be applied for Gamma knife radiosurgery (GKR) and its image quality may affect defining the tumor. This study conducted the phantom-based evaluation for geometric accuracy and functional characteristic of diagnostic MET-PET image co-registered with stereotactic image in Leksell $GammaPlan^{(R)}$ (LGP) and also investigated clinical application of these images in metastatic brain tumors. Methods : Two types of cylindrical acrylic phantoms fabricated in-house were used for this study : the phantom with an array-shaped axial rod insert and the phantom with different sized tube indicators. The phantoms were mounted on the stereotactic frame and scanned using computed tomography (CT), magnetic resonance imaging (MRI), and PET system. Three-dimensional coordinate values on co-registered MET-PET images were compared with those on stereotactic CT image in LGP. MET uptake values of different sized indicators inside phantom were evaluated. We also evaluated the CT and MRI co-registered stereotactic MET-PET images with MR-enhancing volume and PET-metabolic tumor volume (MTV) in 14 metastatic brain tumors. Results : Imaging distortion of MET-PET was maintained stable at less than approximately 3% on mean value. There was no statistical difference in the geometric accuracy according to co-registered reference stereotactic images. In functional characteristic study for MET-PET image, the indicator on the lateral side of the phantom exhibited higher uptake than that on the medial side. This effect decreased as the size of the object increased. In 14 metastatic tumors, the median matching percentage between MR-enhancing volume and PET-MTV was 36.8% on PET/MR fusion images and 39.9% on PET/CT fusion images. Conclusion : The geometric accuracy of the diagnostic MET-PET co-registered with stereotactic MR in LGP is acceptable on phantom-based study. However, the MET-PET images could the limitations in providing exact stereotactic information in clinical study.

• Nuclear Engineering and Technology
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• v.52 no.9
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• pp.2072-2077
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• 2020

The purpose of this study was to demonstrate the feasibility of sensing changes in a tumor during boron neutron capture therapy (BNCT) using a Monte Carlo simulation tool. In the simulation, an epi-thermal neutron source and a water phantom including boron uptake regions (BURs) were simulated. Moreover, this simulation also included a detector for positron emission tomography (PET) scanning and an adaptively-designed collimator (ADC) for PET. After the PET scanning of the water phantom, including the 511 keV source in the BUR, the ADC was positioned in the PET's gantry. Single prompt gamma rays were collected through the ADC during neutron irradiation. Then, single prompt gamma ray-based tomography images of different sized tumors were acquired by a four-step process. Both the signal-to-noise ratio (SNR) and tumor size were analyzed from each step image. From this analysis, we identified a decreasing trend of both the SNR and signal intensity as the tumor size decreased, which was confirmed in all images. In conclusion, we confirmed the feasibility of sensing changes in a tumor during BNCT using PET and an ADC through Monte Carlo simulation.

• The Korean Journal of Nuclear Medicine Technology
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• v.28 no.1
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• pp.35-40
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• 2024

Purpose: To improve the image quality in positron emission tomography (PET), the attenuation correction technique based on the computed tomography (CT) data is important process. However, the artifact is caused by metal material during PET/CT scan, and the image quality is degraded. Therefore, the purpose of this study was to evaluate image quality according to with and without iterative metal artifact reduction (iMAR) algorithm using customized 3D printing phantom. Materials and Methods: The Hoffman and Derenzo phantoms were designed. To protect the gamma ray transmission and express the metal portion, lead substance was located to the surface. The SiPM based PET/CT was used for acquisition of PET images according to application with and without iMAR algorithm. The quantitative methods were used by signal to noise ratio (SNR), coefficient of variation (COV), and contrast to noise ratio (CNR). Results and Discussion: The results shows that the image quality applying iMAR algorithm was higher 1.15, 1.19, and 1.11 times than image quality without iMAR algorithm for SNR, COV, and CNR. Conclusion: In conclusion, the iMAR algorithm was useful for improvement of image quality by reducing the metal artifact lesion.

• Nuclear Engineering and Technology
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• v.55 no.6
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• pp.2018-2025
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• 2023

In our previous study, we proposed an integrated PG-PET-based imaging method to increase the prediction accuracy for patient dose distributions. The purpose of the present study is to experimentally validate the feasibility of the PG-PET system. Based on the detector geometry optimized in the previous study, we constructed a dual-head PG-PET system consisting of a 16 × 16 GAGG scintillator and KETEK SiPM arrays, BaSO₄ reflectors, and an 8 × 8 parallel-hole tungsten collimator. The performance of this system as equipped with a proof of principle, we measured the PG and positron emission (PE) distributions from a 3 × 6 × 10 cm³ PMMA phantom for a 45 MeV proton beam. The measured depth was about 17 mm and the expected depth was 16 mm in the computation simulation under the same conditions as the measurements. In the comparison result, we can find a 1 mm difference between computation simulation and measurement. In this study, our results show the feasibility of the PG-PET system for in-vivo range verification. However, further study should be followed with the consideration of the typical measurement conditions in the clinic application.