• Journal of Radiation Industry
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• v.11 no.1
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• pp.39-45
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• 2017

A cyclotron is a kind of particle accelerator that produces a beam of charged particles for the production of medical, industrial, and research radioisotopes. More than 30 cyclotrons are operated in Korea to produce $^{18}F$, an FDG synthesis at hospitals. A 30-MeV cyclotron was installed at ARTI (Advanced Radiation Technology Institute, KAERI) mainly for research regarding isotope production. In this study, we analyze and estimate the items of risk such as the problems in the main components of the cyclotron, the loss of radioactive materials, the leakage of coolant, and the malfunction of utilities, fires and earthquakes. To estimate the occurrence frequency in an accident risk assessment, five levels, i.e., Almost certain, Likely, Possible, Unlikely, and Rare, are applied. The accident consequence level is classified under four grades based on the annual permissible dose for radiation workers and the public in the nuclear safety law. The analysis of the accident effect is focused on the radioactive contamination caused by radioisotope leakage and radioactive material leakage of a ventilation filter due to a fire. To analyze the risks, Occupation Safety and Health Acts is applied. In addition, action plans against an accident were prepared after a deep discussion among relevant researchers. In this acts, we will search for hazard and introduce the risk assessment for the research 30-MeV cyclotron facilities of ARTI.

• Journal of radiological science and technology
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• v.41 no.6
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• pp.553-560
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• 2018

PET-CT and PET-MRI which integrates CT using ionized radiation and MRI using phenomena of magnetic resonance are determined to have the limitation to apply the semi-quantitative index, standardized uptake value (SUV), with the same level due to the fundamental differences of image capturing principle and reorganization, hence, their correlations were analyzed to provide their clinical information. To 30 study subjects maintaining pre-treatment, $^{18}F-FDG$ (5.18 MBq/㎏) was injected and they were scanned continuously without delaying time using $Biograph^{TM}$ mMR 3T (Siemens, Munich) and Biograph mCT 64 (Siemens, Germany), which is an integral type, under the optimized condition except the structural differences of both scanners. Upon the measurement results of $SUV_{max}$ setting volume region of interest with evenly distributed radioactive pharmaceuticals by captured images, $SUV_{max}$ mean values of PET-CT and PET-MRI were $2.94{\pm}0.55$ and $2.45{\pm}0.52$, respectively, and the value of PET-MRI was measured lower by $-20.85{\pm}7.26%$ than that of PET-CT. Also, there was a statistically significant difference in SUVs between two scanners (P<0.001), hence, SUV of PET-CT and PET-MRI cannot express the clinical meanings in the same level. Therefore, in case of the patients who undergo cross follow-up tests with PET-CT and PET-MRI, diagnostic information should be analyzed considering the conditions of SUV differences in both scanners.

• Journal of radiological science and technology
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• v.44 no.6
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• pp.635-643
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• 2021

The results of empirical researches on the diagnosis of lung cancer are insufficient, so it is limited to objectively judge the clinical possibility and utilization according to the accuracy of diagnosis. Thus, this study retrospectively analyzed the lung cancer diagnostic performance of PET-MRI (Positron Emission Tomography-Magnetic Resonance Imaging) by using the decision matrix. This study selected and experimented total 165 patients who received both hematological CEA (Carcinoembryonic Antigen) test and hybrid PET-MRI (¹⁸F-FDG, 5.18 MBq/kg / Body TIM coil. VIVE-Dixon). After setting up the result of CEA (positive:>4 ㎍/ℓ. negative:<2.5㎍/ℓ) as golden data, the lung cancer was found in the image of PET-MRI, and then the SUV_max (positive:>4, negative:<1.5) was measured, and then evaluated the correlation and significance of results of relative diagnostic performance of PET-MRI compared to CEA through the statistical verification (t-test, P>0.05). Through this, the PET-MRI was analyzed as 96.29% of sensitivity, 95.23% of specificity, 3.70% of false negative rate, 4.76% of false positive rate, and 95.75% of accuracy. The false negative rate was 1.06% lower than the false positive rate. The PET-MRI that significant accuracy of diagnosis through high sensitivity and specificity, and low false negative rate and false positive rate of lung cancer, could acquire the fusion image of specialized soft tissue by combining the radio-pharmaceuticals with various sequences, so its clinical value and usefulness are regarded as latently sufficient.

• Journal of radiological science and technology
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• v.44 no.6
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• pp.655-661
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• 2021

Positron emission tomography (PET) images is affected by acquisition time, short acquisition times results in low gamma counts leading to degradation of image quality by statistical noise. Noise2Void(N2V) is self supervised denoising model that is convolutional neural network (CNN) based deep learning. The purpose of this study is to evaluate denoising performance of N2V for PET image with a short acquisition time. The phantom was scanned as a list mode for 10 min using Biograph mCT40 of PET/CT (Siemens Healthcare, Erlangen, Germany). We compared PET images using NEMA image-quality phantom for standard acquisition time (10 min), short acquisition time (2min) and simulated PET image (S2 min). To evaluate performance of N2V, the peak signal to noise ratio (PSNR), normalized root mean square error (NRMSE), structural similarity index (SSIM) and radio-activity recovery coefficient (RC) were used. The PSNR, NRMSE and SSIM for 2 min and S2 min PET images compared to 10min PET image were 30.983, 33.936, 9.954, 7.609 and 0.916, 0.934 respectively. The RC for spheres with S2 min PET image also met European Association of Nuclear Medicine Research Ltd. (EARL) FDG PET accreditation program. We confirmed generated S2 min PET image from N2V deep learning showed improvement results compared to 2 min PET image and The PET images on visual analysis were also comparable between 10 min and S2 min PET images. In conclusion, noisy PET image by means of short acquisition time using N2V denoising network model can be improved image quality without underestimation of radioactivity.

• Clinical Pain
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• v.19 no.1
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• pp.54-58
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• 2020

Skeletal muscle metastasis of gastric cancer is extremely rare and is associated with various symptoms. Here, we report on a 60-year-old woman with right hip pain after excessive walking. Two years earlier, the patient had been treated for advanced gastric cancer (surgery, adjuvant chemotherapy). Upon magnetic resonance imaging, diffuse muscle swelling and high signal intensity were observed in T2-weighted images of the right hip muscle. However, the FDG uptake in the right gluteal muscles was not obviously increased. Pathological examination of muscle biopsy revealed metastatic adenocarcinoma of stomach origin. The patient was treated with chemotherapy, and the swelling and pain in the right hip are progressively improving.

• Advances in nano research
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• v.12 no.2
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• pp.185-195
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• 2022

Deep learning is another field of artificial intelligence (AI) utilized for computer aided diagnosis (CAD) and image processing in scientific research. Considering numerous mechanical repetitive tasks, reading image slices need time and improper with geographical limits, so the counting of image information is hard due to its strong subjectivity that raise the error ratio in misdiagnosis. Regarding the highest mortality rate of Lung cancer, there is a need for biopsy for determining its class for additional treatment. Deep learning has recently given strong tools in diagnose of lung cancer and making therapeutic regimen. However, identifying the pathological lung cancer's class by CT images in beginning phase because of the absence of powerful AI models and public training data set is difficult. Convolutional Neural Network (CNN) was proposed with its essential function in recognizing the pathological CT images. 472 patients subjected to staging FDG-PET/CT were selected in 2 months prior to surgery or biopsy. CNN was developed and showed the accuracy of 87%, 69%, and 69% in training, validation, and test sets, respectively, for T1-T2 and T3-T4 lung cancer classification. Subsequently, CNN (or deep learning) could improve the CT images' data set, indicating that the application of classifiers is adequate to accomplish better exactness in distinguishing pathological CT images that performs better than few deep learning models, such as ResNet-34, Alex Net, and Dense Net with or without Soft max weights.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.322-323
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• 2002

Partial volume averaging effect of PET data influences on the accuracy of quantitative measurements of regional brain metabolism because spatial resolution of PET is limited. The purpose of this study was to evaluate the accuracy of partial volume correction carried out on $^{18}$ F-PET images using Hoffman brain phantom. $^{18}$ F-PET Hoffman phantom images were co-registered to MR slices of the same phantom. All the MR slices of the phantom were then segmented to be binary images. Each of these binary images was convolved in 2 dimensions with the spatial resolution of the PET. The original PET images were then divided by the smoothed binary images in slice-by-slice, voxel-by-voxel basis resulting in larger PET image volume in size. This enlarged partial volume corrected PET image volume was multiplied by original binary image volume to exclude extracortical region. The evaluation of partial volume corrected PET image volume was performed by region of interests (ROI) analysis applying ROIs, which were drawn on cortical regions of the original MR image slices, to corrected and original PET image volume. From the ROI analysis, range of regional mean values increases of partial volume corrected PET images was 4 to 14%, and average increase for all the ROIs was about 10% in this phantom study. Hoffman brain phantom study was useful for the objective evaluation of the partial volume correction method. This MR-based correction method would be applicable to patients in the. quantitative analysis of FDG-PET studies.

• Korean Journal of Radiology
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• v.24 no.6
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• pp.574-589
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• 2023

Radiopharmaceuticals targeting prostate-specific membrane antigens (PSMA) are essential for the diagnosis, evaluation, and treatment of prostate cancer (PCa), particularly metastatic castration-resistant PCa, for which conventional treatment is ineffective. These molecular probes include [⁶⁸Ga]PSMA, [¹⁸F]PSMA, [Al¹⁸F]PSMA, [^99mTc]PSMA, and [⁸⁹Zr]PSMA, which are widely used for diagnosis, and [¹⁷⁷Lu]PSMA and [²²⁵Ac]PSMA, which are used for treatment. There are also new types of radiopharmaceuticals. Due to the differentiation and heterogeneity of tumor cells, a subtype of PCa with an extremely poor prognosis, referred to as neuroendocrine prostate cancer (NEPC), has emerged, and its diagnosis and treatment present great challenges. To improve the detection rate of NEPC and prolong patient survival, many researchers have investigated the use of relevant radiopharmaceuticals as targeted molecular probes for the detection and treatment of NEPC lesions, including DOTA-TOC and DOTA-TATE for somatostatin receptors, 4A06 for CUB domain-containing protein 1, and FDG. This review focused on the specific molecular targets and various radionuclides that have been developed for PCa in recent years, including those mentioned above and several others, and aimed to provide valuable up-to-date information and research ideas for future studies.

• Korean Journal of Radiology
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• v.22 no.9
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• pp.1497-1513
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• 2021

The diagnostic and treatment methods of multiple myeloma (MM) have been rapidly evolving owing to advances in imaging techniques and new therapeutic agents. Imaging has begun to play an important role in the management of MM, and international guidelines are frequently updated. Since the publication of 2015 International Myeloma Working Group (IMWG) criteria for the diagnosis of MM, whole-body magnetic resonance imaging (MRI) or low-dose whole-body computed tomography (CT) and ¹⁸F-fluorodeoxyglucose positron emission tomography/CT have entered the mainstream as diagnostic and treatment response assessment tools. The 2019 IMWG guidelines also provide imaging recommendations for various clinical settings. Accordingly, radiologists have become a key component of MM management. In this review, we provide an overview of updates in the MM field with an emphasis on imaging modalities.

• Korean Journal of Radiology
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• v.22 no.5
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• pp.714-724
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• 2021

Objective: To evaluate the value of ¹⁸F-fluorodeoxyglucose PET/MRI added to contrast-enhanced CT (CECT) in initial staging, assessment of resectability, and postoperative follow-up of biliary tract cancer. Materials and Methods: This retrospective study included 100 patients (initial workup [n = 65] and postoperative follow-up [n = 35]) who had undergone PET/MRI and CECT for bile duct or gallbladder lesions between January 2013 and March 2020. Two radiologists independently reviewed the CECT imaging set and CECT plus PET/MRI set to determine the likelihood of malignancy, local and overall resectability, and distant metastasis in the initial workup group, and local recurrence and distant metastasis in the follow-up group. Diagnostic performances of the two imaging sets were compared using clinical-surgical-pathologic findings as standards of reference. Results: The diagnostic performance of CECT significantly improved after the addition of PET/MRI for liver metastasis (area under the receiver operating characteristic curve [A_z]: 0.77 vs. 0.91 [p = 0.027] for reviewer 1; 0.76 vs. 0.92 [p = 0.021] for reviewer 2), lymph node metastasis (0.73 vs. 0.92 [p = 0.004]; 0.81 vs. 0.92 [p = 0.023]), and overall resectability (0.79 vs. 0.92 [p = 0.007]; 0.82 vs. 0.94 [p = 0.021]) in the initial workup group. In the follow-up group, the diagnostic performance of CECT plus PET/MRI was significantly higher than that of CECT imaging for local recurrence (0.81 vs. 1.00 [p = 0.029]; 0.82 vs. 0.94 [p = 0.045]). Conclusion: PET/MRI may add value to CECT in patients with biliary tract cancer both in the initial workup for staging and determination of overall resectability and in follow-up for local recurrence.