• Journal of the Korean Society of Radiology
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• v.17 no.5
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• pp.767-773
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• 2023

To In this study, we sought to evaluate related factors affecting lung volume and their significance in pulmonary function and ventilation disorders. As experimental subjects, 206 normal adult men and women who underwent a low-dose chest CT scan and a spirometry test were selected at the same time. The experimental method was to measure lung volume using lung CT images obtained through a low-dose chest CT scan using deep learning-based AVIEW. Measurements were made using the LCS automatic diagnosis program. In addition, the results of measuring lung function were obtained using a spirometer, and gender and BMI were selected as related factors that affect lung volume, and significance was evaluated through an independent sample T-test with lung volume. As a result of the experiment, it was confirmed that in evaluating lung volume according to gender, all lung volumes of men were larger than all lung volumes of women. he result of an independent samples T-test using the respective average values for gender and lung volume showed that all lung volumes were larger in men than in women, which was significant (p<0.001). And in the evaluation of lung volume according to BMI index, it was confirmed that all lung volumes of adults with a BMI index of 24 or higher were larger than all lung volumes of adults with a BMI index of less than 24. However, the independent samples T-test using the respective average values for BMI index and lung volume did not show a significant result that all lung volumes were larger in BMI index 24 or higher than in BMI index less than 24 (p<0.055). In the evaluation of lung volume according to the presence or absence of pulmonary ventilation impairment, it was confirmed that all lung volumes of adults with normal pulmonary function ventilation were larger than all lung volumes of adults with pulmonary ventilation impairment. And as a result of the independent sample T-test using the respective average values for the presence or absence of pulmonary ventilation disorder and lung volume, the result was significant that all lung volumes were larger in adults with normal pulmonary function ventilation than in adults with pulmonary function ventilation disorder (p <0.001). Lung volume and spirometry test results are the most important indicators in evaluating lung health, and using these two indicators together to evaluate lung function is the most accurate evaluation method. Therefore, it is expected that this study will be used as basic data by presenting the average lung volume for adults with normal ventilation and adults with impaired lung function and ventilation in similar future studies on lung volume and vital capacity testing.

• Asian Spine Journal
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• v.12 no.6
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• pp.1010-1016
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• 2018

Study Design: Retrospective cohort study. Purpose: To report on spinal fusion assessment using computed tomography (CT) after adult spinal deformity (ASD) surgery using ultra-low dose recombinant human bone morphogenetic protein 2 (RhBMP-2). Overview of Literature: The reported dose of RhBMP-2 needed for successful spinal posterolateral fusion in ASD ranges from 10 to 20 mg per spinal level. This study reports the use of ultra-low dose of RhBMP-2 (0.07 mg per facet) to achieve spinal fusion in multilevel ASD surgery. Methods: Consecutive patients who underwent ASD surgery using ultra-low dose RhBMP-2 were recruited. Routine postoperative CT analysis for spinal fusion was performed by two spine surgeons. Inter-observer agreement was calculated for facet fusion (FF) and interbody fusion (IBF) at 6 and 12 months after the procedure. Results: Six consecutive ASD patients with a mean age of 62 years (28-72 years) were examined. Each patient received a total dose of 12 mg with an average dose of $0.69{\pm}0.2mg$ (0.42-1 mg) per single FF and $1.38{\pm}0.44mg$ (0.85-2 mg) for IBF. Total 131 FF and 15 IBF were examined in the study, with 88 FFs and nine IBFs being analyzed specifically at 6 months after the surgery. FF and IBF reported by surgeons A and B at 6 months were 97.7% vs. 91.9% FF, respectively (${\kappa}=0.95$) and 100% vs. 100% IBF, respectively (${\kappa}=1$). Two patients underwent longitudinal follow-up CT at 12 months, and the FF rates reported by surgeons A and B were 100% vs. 95.8%, respectively (${\kappa}=0.96$). Five out of nine facet (56%) non-unions were identified at the cross-links. The remaining four facet pseudarthrosis were noted at 1-2 spinal levels caudal to the cross-links. At the final clinical follow-up, there was no rod breakage, deformity progression, neurological deficit, or symptom recurrence. The Oswestry Disability Index improved by an average of $32.8{\pm}6.3$, while the mental component summary of the 36-item Short-Form Health Survey improved by an average of $4.7{\pm}2.1$, and physical component summary improved by an average of $10.5{\pm}2.1$. Conclusions: To our knowledge, this is the first study to report a CT that defined 92%-98% FF and 100% IBF using the lowest reported dose of RhBMP-2 in multilevel ASD surgery. The use of ultra-low dose RhBMP-2 reduces the RhBMP-2 related complications and healthcare costs.

• Journal of the Korean Society of Radiology
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• v.17 no.2
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• pp.215-221
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• 2023

Among brain CT scan conditions including the lens, the tube voltage was changed to 80, 100, and 120 kVp and applied. The change in dose was analyzed using lead, lead goggles and barium sulfate silicon shielding materials, and the degree of influence of the shielding materials on image quality was compared and analyzed by applying the SNR, CNR, and SSIM index analysis methods. As a result, it was analyzed that although the dose was reduced by applying all shielding materials, the difference in dose reduction was not large (P > 0.05). In addition, as for the change in image quality due to the application of the shielding material, SNR and CNR were the highest when lead goggles were applied, and the structural similarity was measured to be the best as it was closest to the reference value of 1 in SSIM analysis. Therefore, based on the results of this study, it is thought that if more diverse shielding materials and clinical test results are derived and applied, it will be helpful for the clinical application criteria in the case of shielding utilization inspection.

• Korean Journal of Radiology
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• v.22 no.6
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• pp.983-993
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• 2021

Objective: To investigate the image quality of ultralow-dose CT (ULDCT) of the chest reconstructed using a cycle-consistent generative adversarial network (CycleGAN)-based deep learning method in the evaluation of pulmonary tuberculosis. Materials and Methods: Between June 2019 and November 2019, 103 patients (mean age, 40.8 ± 13.6 years; 61 men and 42 women) with pulmonary tuberculosis were prospectively enrolled to undergo standard-dose CT (120 kVp with automated exposure control), followed immediately by ULDCT (80 kVp and 10 mAs). The images of the two successive scans were used to train the CycleGAN framework for image-to-image translation. The denoising efficacy of the CycleGAN algorithm was compared with that of hybrid and model-based iterative reconstruction. Repeated-measures analysis of variance and Wilcoxon signed-rank test were performed to compare the objective measurements and the subjective image quality scores, respectively. Results: With the optimized CycleGAN denoising model, using the ULDCT images as input, the peak signal-to-noise ratio and structural similarity index improved by 2.0 dB and 0.21, respectively. The CycleGAN-generated denoised ULDCT images typically provided satisfactory image quality for optimal visibility of anatomic structures and pathological findings, with a lower level of image noise (mean ± standard deviation [SD], 19.5 ± 3.0 Hounsfield unit [HU]) than that of the hybrid (66.3 ± 10.5 HU, p < 0.001) and a similar noise level to model-based iterative reconstruction (19.6 ± 2.6 HU, p > 0.908). The CycleGAN-generated images showed the highest contrast-to-noise ratios for the pulmonary lesions, followed by the model-based and hybrid iterative reconstruction. The mean effective radiation dose of ULDCT was 0.12 mSv with a mean 93.9% reduction compared to standard-dose CT. Conclusion: The optimized CycleGAN technique may allow the synthesis of diagnostically acceptable images from ULDCT of the chest for the evaluation of pulmonary tuberculosis.

• Progress in Medical Physics
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• v.9 no.4
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• pp.201-206
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• 1998

IMRT optimization method on multiple slice has been developed by using gradient based algorithm. On about 10-30 CT slices including treatment region of a patient, dose optimization has been performed slice by slice to meet the condition that each organ should be exposed below maximum tolerable doses and that the tumor dose within the range of 100$\pm$5 %. Field size was limited to 8$\times$8 cm$^2$ and in this condition, beam divergence was not taken into account to calculate dose distribution. Total dose distribution was calculated by superposing each beamlet whose dose distribution had been precalculated. In order to investigate beam number dependency, dose optimization was performed for one, three, five, seven, and nine coplanar beams and then each optimization index was evaluated. It is found that optimization time was proportional to number of slices to be optimized, and the most efficient plan was obtained from the case of three-to-seven incident beams with respect to calculation time and optimization index. In conclusion, dose optimization of multiple slice was able to be obtained by repeating dose optimization of single slice under condition that the beam size is not too large to ignore beam divergence. And it turns out that result of dose optimization was so sensitive to the position of isocenter that some method to optimize isocenter position is needed to improve it.

• Radiation Oncology Journal
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• v.34 no.4
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• pp.313-321
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• 2016

Purpose: Total scalp irradiation (TSI) is a rare but challenging indication. We previously reported that non-coplanar intensity-modulated radiotherapy (IMRT) was superior to coplanar IMRT in organ-at-risk (OAR) protection and target dose distribution. This consecutive treatment planning study compared IMRT with volumetric-modulated arc therapy (VMAT). Materials and Methods: A retrospective treatment plan databank search was performed and 5 patient cases were randomly selected. Cranial imaging was restored from the initial planning computed tomography (CT) and target volumes and OAR were redelineated. For each patients, three treatment plans were calculated (coplanar/non-coplanar IMRT, VMAT; prescribed dose 50 Gy, single dose 2 Gy). Conformity, homogeneity and dose volume histograms were used for plan. Results: VMAT featured the lowest monitor units and the sharpest dose gradient (1.6 Gy/mm). Planning target volume (PTV) coverage and homogeneity was better in VMAT (coverage, 0.95; homogeneity index [HI], 0.118) compared to IMRT (coverage, 0.94; HI, 0.119) but coplanar IMRT produced the most conformal plans (conformity index [CI], 0.43). Minimum PTV dose range was 66.8%-88.4% in coplanar, 77.5%-88.2% in non-coplanar IMRT and 82.8%-90.3% in VMAT. Mean dose to the brain, brain stem, optic system (maximum dose) and lenses were 18.6, 13.2, 9.1, and 5.2 Gy for VMAT, 21.9, 13.4, 14.5, and 6.3 Gy for non-coplanar and 22.8, 16.5, 11.5, and 5.9 Gy for coplanar IMRT. Maximum optic chiasm dose was 7.7, 8.4, and 11.1 Gy (non-coplanar IMRT, VMAT, and coplanar IMRT). Conclusion: Target coverage, homogeneity and OAR protection, was slightly superior in VMAT plans which also produced the sharpest dose gradient towards healthy tissue.

• Journal of the Korean Society of Radiology
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• v.16 no.4
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• pp.411-417
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• 2022

This study aimed to learn and evaluate the effectiveness of VGGNet in the detection of pulmonary emphysema using low-dose chest computed tomography images. In total, 8000 images with normal findings and 3189 images showing pulmonary emphysema were used. Furthermore, 60%, 24%, and 16% of the normal and emphysema data were randomly assigned to training, validation, and test datasets, respectively, in model learning. VGG16 and VGG19 were used for learning, and the accuracy, loss, confusion matrix, precision, recall, specificity, and F1-score were evaluated. The accuracy and loss for pulmonary emphysema detection of the low-dose chest CT test dataset were 92.35% and 0.21% for VGG16 and 95.88% and 0.09% for VGG19, respectively. The precision, recall, and specificity were 91.60%, 98.36%, and 77.08% for VGG16 and 96.55%, 97.39%, and 92.72% for VGG19, respectively. The F1-scores were 94.86% and 96.97% for VGG16 and VGG19, respectively. Through the above evaluation index, VGG19 is judged to be more useful in detecting pulmonary emphysema. The findings of this study would be useful as basic data for the research on pulmonary emphysema detection models using VGGNet and artificial neural networks.

• Journal of the Korean Society of Radiology
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• v.9 no.5
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• pp.287-293
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• 2015

Because of esophageal cancer has the long length of the lesion and also inhomogeneous in depth. So, the radiation dose distribution was inhomogeneous in radiation therapy. To overcomes the dose distribution uniformity using half beam method. Patient's CT image was used radiation treatment planning. We used two planning methods that one is the using normal beam and another is using half beam. Than comparing the two radiotherapy planning using target coverage, dose volume histogram, conformity index, homogeneity index and normal tissues - heart, spinal cord, lung -. In results, Treatment planning using half beam is little more than normal beam in target coverage, dose volume histogram, conformity index, homogeneity index and normal tissues covering. However, If the patient is not correct position patients may arise a side effect. Thus, the using in Half beam involving the geometrically exact under lung cancer is considered to advantage.

• The Journal of Korean Society for Radiation Therapy
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• v.26 no.2
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• pp.171-176
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• 2014

Purpose : Changing the calculation grid of AAA in Lung SABR plan and to analyze the changes in target dose, and investigated the effects associated with it, and considered a suitable method of application. Materials and Methods : 4D CT image that was used to plan all been taken with Brilliance Big Bore CT (Philips, Netherlands) and in Lung SABR plan($Eclipse^{TM}$ ver10.0.42, Varian, the USA), use anisotropic analytic algorithm(AAA, ver.10, Varian Medical Systems, Palo Alto, CA, USA) and, was calculated by the calculation grid 1.0, 3.0, 5.0 mm in each Lung SABR plan. Results : Lung SABR plan of 10 cases are using each of 1.0 mm, 3.0 mm, 5.0 mm calculation grid, and in case of use a 1.0 mm calculation grid $V_{98}$. of the prescribed dose is about $99.5%{\pm}1.5%$, $D_{min}$ of the prescribed dose is about $92.5{\pm}1.5%$ and Homogeneity Index(HI) is $1.0489{\pm}0.0025$. In the case of use a 3.0 mm calculation grid $V_{98}$ dose of the prescribed dose is about $90{\pm}4.5%$, $D_{min}$ of the prescribed dose is about $87.5{\pm}3%$ and HI is about $1.07{\pm}1$. In the case of use a 5.0 mm calculation grid $V_{98}$ dose of the prescribed dose is about $63{\pm}15%$, $D_{min}$ of the prescribed dose is about $83{\pm}4%$ and HI is about $1.13{\pm}0.2$, respectively. Conclusion : The calculation grid of 1.0 mm is better improves the accuracy of dose calculation than using 3.0 mm and 5.0 mm, although calculation times increase in the case of smaller PTV relatively. As lung, spread relatively large and low density and small PTV, it is considered and good to use a calculation grid of 1.0 mm.

• Korean Journal of Artificial Intelligence
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• v.12 no.1
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• pp.1-6
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• 2024

Recently, various techniques are being applied through the development of medical AI, and research has been conducted on the application of super-resolution AI models. In this study, evaluate the results of the application of the super-resolution AI model to brain CT as the basic data for future research. Acquiring CT images of the brain, algorithm for brain and bone windowing setting, and the resolution was downscaled to 5 types resolution image based on the original resolution image, and then upscaled to resolution to create an LR image and used for network input with the original imaging. The SRCNN model was applied to each of these images and analyzed using PSNR, SSIM, Loss. As a result of quantitative index analysis, the results were the best at 256×256, the brain and bone window setting PSNR were the same at 33.72, 35.2, and SSIM at 0.98 respectively, and the loss was 0.0004 and 0.0003, respectively, showing relatively excellent performance in the bone window setting CT image. The possibility of future studies aimed image quality and exposure dose is confirmed, and additional studies that need to be verified are also presented, which can be used as basic data for the above studies.