• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.5C
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• pp.429-436
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• 2012

In this paper, an RFID system for the automatic preparation system of positron emission tomography (PET) radiopharmaceuticals is developed. Since the preparation system uses radioactive isotope, the preparation system is generally placed in lead-shielded hot-cell. Disposable cassettes including tubes and valves are used in the preparation system, since they are easily contaminated by radioactivity during preparation of radiopharmaceuticals. Currently, a system for preventing re-use of the cassette and managing the information about the preparation precess and result independently from the PC which control the preparation system is highly required for preventing danger from the radiation accident. Since RFID can store and re-write relatively large amount of information, it is suitable for the purpose. However, it is hard to read multiple cassettes' information using antennas installed on the metallic surfaces with current RFID systems. For the problem, we improve RFID system in two directions. First, the interface of the RFID reader is changed then it is possible that multiple readers can be daisy-chained. Also, antenna is tuned while inserting in a metallic coated antenna case, then the effect from the metallic surface of the preparation system is minimized. The test result using the developed system shows that the developed RFID system can read multiple tags using the antennas which are attached on the metallic surface.

• Journal of the Korean Society of Radiology
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• v.17 no.1
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• pp.31-36
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• 2023

Among imaging and treatment devices for small animals, positron emission tomography(PET) causes a change in spatial resolution within a field of view. This is a phenomenon caused by using a small gantry and a thin and long scintillation pixel, and detectors that measure the interaction depth are being developed and researched to solve this problem. In this study, a detector that measures the interaction depth was designed using several scintillator blocks and light guides with different reflector patterns. The scintillator block composed of 4 × 4 arrays of 3 mm × 3 mm × 5 mm scintillation pixels formed four layers, and a light guide was inserted in each layer to configure the entire detector. In order to check whether the interaction depth was measured, a gamma ray interaction was generated at the center of all scintillation pixels to acquire data and then reconstructed into a flood image. The reflector patterns of the light guides inserted between the layers were all different, so the positions of the scintillation pixels for each layer were formed in different locations. It is considered that even spatial resolution can be achieved over all regions of the field of view if all positions of the scintillation pixels thus formed are separated and used for image reconstruction.

• Progress in Medical Physics
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• v.14 no.3
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• pp.203-210
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• 2003

PET (positron emission tomography) permits the investigation of physiological and biochemical processes in vivo. The accuracy of quantifying PET data is affected by its finite spatial resolution, which causes partial volume effects. In this study, we developed a method for partial volume correction using Hoffman phantom PET and MR data, and applied various FWHM (full width at half maximum) levels. We also applied this method to PET images of normal controls and tested for the possibility of clinical application. $^{18}$ F-PET Hoffman phantom images were co-registered to MR slices. The gray matter and white matter regions were then segmented into binary images. Each binary image was convolved by 4, 8, 12, 16 mm FWHM levels. These convolved images of gray and white matter were merged corresponding to the same level of FWHM. The original PET images were then divided by the convolved binary images voxel-by-voxel. These corrected PET images were multiplied by binary images. The corrected PET images were evaluated by analyzing regions of interests, which were drawn on the gray and white matter regions of the original MR image slices. We calculated the ratio of white to gray matter. We also applied this method to the PET images of normal controls. On analyzing the corrected PET images of Hoffman phantom, the ratios of the corrected images increased more than that of the uncorrected images. With the normal controls, the ratio of the corrected images increased more than that of the uncorrected images. The ratio increase of the corrected PET images was lower than that of the corrected phantom PET images. In conclusion, the method developed for partial volume correction in PET data may be clinically applied, although further study may be required for optimal correction.

• Journal of Gastric Cancer
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• v.11 no.3
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• pp.173-179
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• 2011

Purpose: It is difficult to obtain biopsies from gastrointestinal stromal tumors (GISTs) prior to surgery because GISTs are submucoal tumors, despite being the most common nonepithelial neoplasms of the gastrointestinal tract. Unlike anatomic imaging techniques, PET-CT, which is a molecular imaging tool, can be a useful technique for assessing tumor activity and predicting the malignant potential of certain tumors. Thus, we aimed to evaluate the usefulness of PET-CT as a pre-operative prognostic factor for GISTs by analyzing the correlation between the existing post-operative prognostic factors and the maximum SUV uptake (SUVmax) of pre-operative 18F-fluoro-2-deoxyglucose (FDG) PET-CT. Materials and Methods: The study was conducted on 26 patients who were diagnosed with gastric GISTs and underwent surgery after being examined with pre-operative FDG PET-CT. An analysis of the correlation bewteen (i) NIH risk classification and the Ki-67 proliferation index, which are post-operative prognostic factors, and (ii) the SUVmax of PET-CT, which is a pre-operative prognostic factor, was performed. Results: There were significant correlations between (i) SUVmax and (ii) Ki-67 index, tumor size, mitotic count, and NIH risk group (r=0.854, 0.888, 0.791, and 0.756, respectively). The optimal cut-off value for SUVmax was 3.94 between "low-risk malignancy" and "high-risk malignancy" groups. The sensitivity and specificity of SUVmax for predicting the risk of malignancy were 85.7% and 94.7%, respectively. Conclusions: The SUVmax of PET-CT is associated with Ki-67 index, tumor size, mitotic count, and NIH classification. Therefore, it is believed that PET-CT is a relatively safe, non-invasive diagnostic tool for assessing malignant potential pre-operatively.

• Nuclear Medicine and Molecular Imaging
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• v.42 no.6
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• pp.444-450
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• 2008

Purpose: The aim of this study was to evaluate the usefulness of whole body positron emission tomography (PET) using $^{18}F-fluorodeoxyglucose$ ($^{18}F-FDG$) for cancer screening in asymptomatic subjects. Materials and Methods: The subjects were 1,762 men and 259 women who voluntarily underwent $^{18}F-FDG$ PET for cancer screening as a part of a routine health examination. Final diagnosis was decided by other diagnostic studies, pathological results or clinical follow-up for 1 year. Results: Of 2,021 subjects, 40 (2.0%) were finally proved to have cancer. Abnormal focal $^{18}F-FDG$ uptake suggesting malignancy was found in 102 subjects (5.0%). Among them, 21 subjects (1.0%) were proved to have cancer. Other tests in the routine health examination could not find 9 of 21 cancers (42.9%) detected by PET. The sensitivity, specificity, positive predictive value, and negative predictive value of PET for cancer screening were 52.5%, 95.9%, 20.6%, and 99.0%, respectively. Pathologies of cancers missed on PET were adenocarcinoma (n = 9; 3 colon cancers, 3 prostate cancers, 2 stomach cancers, and 1 rectal cancer), differentiated thyroid carcinoma (n = 6), bronchioalveolar cell carcinoma (n = 2), urinary bladder cancer (n = 1), and melanoma (n = 1). More than half of cancers which were not detected by PET were smaller than 1 cm in diameter. Conclusion: $^{18}F-FDG$ PET might be useful for cancer screening in asymptomatic subjects due to its high specificity and negative predictive value and playa supplementary role to the conventional health check-up, but it could not replace due to limited sensitivity for urological cancers, small-sized tumors and some hypometaboic cancers.

• Clinical and Experimental Pediatrics
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• v.52 no.7
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• pp.804-810
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• 2009

Purpose : We investigated whether ictal single-photon emission computed tomography (SPECT) with prolonged injection of technetium-99m (99mTc) ethyl cysteinate dimer during repeated spasms can localize the epileptogenic foci in children with infantile spasms. Methods : Fourteen children with infantile spasms (11 boys, 3 girls; mean age, $2.2{\pm}1.3$ years) were examined. When a cluster of spasms was detected during video electroencephalography (EEG) monitoring, $^{99m}Tc$ ethyl cysteinate dimer was slowly and continuously injected for 2 minutes to determine the presence of ictal SPECT. For 7 children, the ictal and interictal SPECT images were visually analyzed, while for the remaining 7 children, the SPECT images were analyzed using the subtraction ictal SPECT coregistered to magnetic resonance imaging (MRI) (SISCOM) technique. Subsequently, we analyzed the association between the ictal SPECT findings and those of other diagnostic modalities such as EEG, MRI, and positron emission tomography (PET). Results : Increase in cerebral blood flow on ictal SPECT involved the epileptogenic foci in 10 cases6 cases analyzed by visual assessment and 4 analyzed by the SISCOM technique. The ictal SPECT and video-EEG findings showed moderate agreement (Kappa=0.57; 95% confidence interval, 0.18-0.96). Conclusion : Ictal SPECT with prolonged injection of a tracer could provide supplementary information to localize the epileptogenic foci in infantile spasms.

• Tuberculosis and Respiratory Diseases
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• v.47 no.5
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• pp.642-649
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• 1999

Background: It is very important to determine an accurate staging of the non-small cell lung cancer(NSCLC) for an assessment of operability and it's prognosis. However, it is difficult to evaluate tumor involvement of mediastinal lymph nodes accurately utilizing noninvasive imaging modalities. PET is one of the sensitive and specific imaging modality. Unfortunately PET is limited use because of prohibitive cost involved with it's operation. Recently hybrid SPECT/PET(single photon emission computed tomography/positron emission tomography) camera based PET imaging was introduced with relatively low cost. We evaluated the usefulness of coincidence detection(CoDe) PET in the detection of metastasis to the mediastinal lymph nodes in patients with NSCLC. Methods: Twenty one patients with NSCLC were evaluated by CT or MRI and they were considered operable. CoDe PET was performed in all 21 patients prior to surgery. Tomographic slices of axial, coronal and sagittal planes were visually analysed. At surgery, mediastinal lymph nodes were removed and histological diagnosis was performed. CoDe PET findings were correlated with histological findings. Results: Twenty of 21 primary tumor masses were detected by the CoDe PET. Thirteen of 21 patients was correctly diagnosed mediastinal lymph node metastasis by the CoDe PET. Pathological N0 was 14 cases and the specificity of N0 of CoDe PET was 64.3%. Sensitivity, specificity, positive predictive value, negative predictive value and accuracy of N1 node was 83.3%, 73.3%, 55.6%, 91.7%, and 76.2% respectively. Sensitivity, specificity, positive predictive value, negative predictive value and accuracy of N2 node was 60.0%, 87.5%, 60.0%,87.5%, and 90.0% respectively. There were 3 false negative cases but the size of the 3 nodes were less than 1cm. The size of true positive nodes were 1.1cm, 1.0cm, 0.5cm respectively. There were 1 false positive among the 12 lymph nodes which were larger than 1cm. False positive cases consisted of 1 tuberculosis case, 1 pneumoconiosis case and 1 anthracosis case. Conclusion: CoDe PET has relatively high negative predictive value in the enlarged lymph node in staging of mediastinal nodes in patients with NSCLC. Therefore CoDe PET is useful in ruling out metastasis of enlarged N3 nodes. However, further study is needed including more number of patients in the future.

• Biomedical Science Letters
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• v.25 no.1
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• pp.99-106
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• 2019

Amyloid positron emission tomography (PET) allows early and accurate diagnosis in suspected cases of Alzheimer's disease (AD) and contributes to future treatment plans. In the present study, a method of implementing a diagnostic system to distinguish ${\beta}$-Amyloid ($A{\beta}$) positive from $A{\beta}$ negative with objectiveness and accuracy was proposed using a machine learning approach, such as the Principal Component Analysis (PCA) and Support Vector Machine (SVM). $^{18}F$-Florbetaben (FBB) brain PET images were arranged in control and patients (total n = 176) with mild cognitive impairment and AD. An SVM was used to classify the slices of registered PET image using PET template, and a system was created to diagnose patients comprehensively from the output of the trained model. To compare the per-slice classification, the PCA-SVM model observing the whole brain (WB) region showed the highest performance (accuracy 92.38, specificity 92.87, sensitivity 92.87), followed by SVM with gray matter masking (GMM) (accuracy 92.22, specificity 92.13, sensitivity 92.28) for $A{\beta}$ positivity. To compare according to per-subject classification, the PCA-SVM with WB also showed the highest performance (accuracy 89.21, specificity 71.67, sensitivity 98.28), followed by PCA-SVM with GMM (accuracy 85.80, specificity 61.67, sensitivity 98.28) for $A{\beta}$ positivity. When comparing the area under curve (AUC), PCA-SVM with WB was the highest for per-slice classifiers (0.992), and the models except for SVM with WM were highest for the per-subject classifier (1.000). We can classify $^{18}F$-Florbetaben amyloid brain PET image for $A{\beta}$ positivity using PCA-SVM model, with no additional effects on GMM.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.63-65
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• 2023

본 논문에서는 FDG-PET 영상을 사용하는 딥러닝 네트워크를 이용하여 직장암 환자의 치료 후 완치를 예측하는 연구를 수행하였다. 직장암은 흔한 악성 종양 중 하나이지만 병리학적으로 완전하게 치료되는 가능성이 매우 낮아, 치료 후의 반응을 예측하고 적절한 치료 방법을 선택하는 것이 중요하다. 따라서 본 연구에서는 FDG-PET 영상에 합성곱 신경망(CNN)모델을 활용하여 딥러닝 네트워크를 구축하고 직장암 환자의 치료반응을 예측하는 연구를 진행하였다. 116명의 직장암 환자의 FDG-PET 영상을 획득하였다. 대상군은 2cm 이상의 종양 크기를 가지는 환자를 대상으로 하였으며 치료 후 완치된 환자는 21명이었다. FDG-PET 영상은 전신 영역과 종양 영역으로 나누어 평가하였다. 딥러닝 네트워크는 2차원 및 3차원 영상입력에 대한 CNN 모델로 구성되었다. 학습된 CNN 모델을 사용하여 직장암의 치료 후 완치를 예측하는 성능을 평가하였다. 학습 결과에서 평균 정확도와 정밀도는 각각 0.854와 0.905로 나타났으며, 모든 CNN 모델과 영상 영역에 따른 성능을 보였다. 테스트 결과에서는 3차원 CNN 모델과 종양 영역만을 이용한 네트워크에서 정확도가 높게 평가됨을 확인하였다. 본 연구에서는 CNN 모델의 입력 영상에 따른 차이와 영상 영역에 따른 딥러닝 네트워크의 성능을 평가하였으며 딥러닝 네트워크 모델을 통해 직장암 치료반응을 예측하고 적절한 치료 방향 결정에 도움이 될 것으로 기대한다.

• Journal of information and communication convergence engineering
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• v.8 no.2
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• pp.205-211
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• 2010

In this study, a Magnetic stimulation Pulse Train control technique is introduced and applied to Flyback converter operating in discontinuous conduction mode. In contrast to the conventional pulse width modulation control scheme, the principal idea of a Magnetic stimulation Pulse Train is to achieve output voltage regulation using high and low power pulses. The proposed technique is applicable to any converter operating in discontinuous conduction. However, this work mainly focuses on Flyback topology. In this paper, the main mathematical concept of the new control algorithm is introduced and simulations as well as experimental results are presented.