• Journal of Radiation Protection and Research
• /
• v.45 no.4
• /
• pp.171-177
• /
• 2020

Background: This study aims to determine the effective atomic number (Zeff) from dual-energy image sets obtained using a conventional computed tomography (CT) simulator. The estimated Zeff can be used for deriving the stopping power and material decomposition of CT images, thereby improving dose calculations in radiation therapy. Materials and Methods: An electron-density phantom was scanned using Philips Brilliance CT Big Bore at 80 and 140 kVp. The estimated Zeff values were compared with those obtained using the calibration phantom by applying the Rutherford, Schneider, and Joshi methods. The fitting parameters were optimized using the nonlinear least squares regression algorithm. The fitting curve and mass attenuation data were obtained from the National Institute of Standards and Technology. The fitting parameters obtained from stopping power and material decomposition of CT images, were validated by estimating the residual errors between the reference and calculated Zeff values. Next, the calculation accuracy of Zeff was evaluated by comparing the calculated values with the reference Zeff values of insert plugs. The exposure levels of patients under additional CT scanning at 80, 120, and 140 kVp were evaluated by measuring the weighted CT dose index (CTDIw). Results and Discussion: The residual errors of the fitting parameters were lower than 2%. The best and worst Zeff values were obtained using the Schneider and Joshi methods, respectively. The maximum differences between the reference and calculated values were 11.3% (for lung during inhalation), 4.7% (for adipose tissue), and 9.8% (for lung during inhalation) when applying the Rutherford, Schneider, and Joshi methods, respectively. Under dual-energy scanning (80 and 140 kVp), the patient exposure level was approximately twice that in general single-energy scanning (120 kVp). Conclusion: Zeff was calculated from two image sets scanned by conventional single-energy CT simulator. The results obtained using three different methods were compared. The Zeff calculation based on single-energy exhibited appropriate feasibility.

• Korean Journal of Radiology
• /
• v.25 no.4
• /
• pp.384-394
• /
• 2024

Objective: To evaluate the image quality of novel dark-blood computed tomography angiography (CTA) imaging combined with deep learning reconstruction (DLR) compared to delayed-phase CTA images with hybrid iterative reconstruction (HIR), to visualize the cervical artery wall in patients with Takayasu arteritis (TAK). Materials and Methods: This prospective study continuously recruited 53 patients with TAK (mean age: 33.8 ± 10.2 years; 49 females) between January and July 2022 who underwent head-neck CTA scans. The arterial- and delayed-phase images were reconstructed using HIR and DLR. Subtracted images of the arterial-phase from the delayed-phase were then added to the original delayed-phase using a denoising filter to generate the final-dark-blood images. Qualitative image quality scores and quantitative parameters were obtained and compared among the three groups of images: Delayed-HIR, Dark-blood-HIR, and Dark-blood-DLR. Results: Compared to Delayed-HIR, Dark-blood-HIR images demonstrated higher qualitative scores in terms of vascular wall visualization and diagnostic confidence index (all P < 0.001). These qualitative scores further improved after applying DLR (Dark-blood-DLR compared to Dark-blood-HIR, all P < 0.001). Dark-blood DLR also showed higher scores for overall image noise than Dark-blood-HIR (P < 0.001). In the quantitative analysis, the contrast-to-noise ratio (CNR) values between the vessel wall and lumen for the bilateral common carotid arteries and brachiocephalic trunk were significantly higher on Dark-blood-HIR images than on Delayed-HIR images (all P < 0.05). The CNR values were significantly higher for Dark-blood-DLR than for Dark-blood-HIR in all cervical arteries (all P < 0.001). Conclusion: Compared with Delayed-HIR CTA, the dark-blood method combined with DLR improved CTA image quality and enhanced visualization of the cervical artery wall in patients with TAK.

• Journal of Korean Neurosurgical Society
• /
• v.62 no.5
• /
• pp.567-576
• /
• 2019

Objective : Minimal data exist regarding non-operative management of suspected pseudarthrosis after pedicle subtraction osteotomy (PSO). This study reports radiographic and clinical outcomes of non-operative management for post-PSO pseudarthrosis at a minimum 5 years post-detection. Methods : Nineteen consecutive patients with implant breakage indicating probable pseudarthrosis after PSO surgery (13 women/six men; mean age at surgery, 58 years) without severe pain and disability were treated with non-operative management (mean follow-up, 5.8 years; range, 5-10 years). Non-operative management included medication, intermittent brace wearing and avoidance of excessive back strain. Radiographic and clinical outcomes analysis was performed. Results : Sagittal vertical axis (SVA), proximal junctional angle, thoracic kyphosis achieved by a PSO were maintained after detection of pseudarthrosis through ultimate follow-up. Lumbar lordosis and PSO angle decreased at final follow-up. There was no significant change in Oswestry Disability Index (ODI) scores and Scoliosis Research Society (SRS) total score, or subscales of pain, self-image, function, satisfaction and mental health between detection of pseudarthrosis and ultimate follow-up. SVA greater than 11 cm showed poorer ODI and SRS total score, as well as the pain, self-image, and function subscales (p<0.05). Conclusion : Non-operative management of implant failure of probable pseudarthrosis after PSO offers acceptable outcomes even at 5 years after detection of implant breakage, provided SVA is maintained. As SVA increased, outcome scores decreased in this patient population.

• The Korean Journal of Rehabilitation Nursing
• /
• v.20 no.1
• /
• pp.33-41
• /
• 2017

Purpose: This study is a descriptive study to analyze the relationship between the cognitive function, body image and pain, and the influencing factors on the daily life performance of brain injured patients. Methods: The study subjects were 119 inpatients with brain injury who gave informed consent. The activities of daily living (ADLs), cognitive function, pain and body image were measured by Modified Barthel Index (K-MBI), K-MMSE (Mini-Mental State Examination), Visual Analog Scale (VAS), Semantic Differential Method (SDM), respectively. Results: ADLs was significantly associated with body image, cognitive function, and pain. Multiple regression analysis showed that paralysis, consciousness, cognitive function, and pain were significant factors influencing ADLs. Overall, approximately 48% of total variability in the ADLs could be explained by the 4 variables ($R^2=.477$, p<.001). Conclusion: To improve ADLs of brain injury patients, a deeper understanding of paralysis, consciousness, cognitive function, and pain of patients is required and active nursing invention should be conducted.

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

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.14 no.12
• /
• pp.6346-6352
• /
• 2013

Radiotherapy of rectal cancer requires a stabilized image but the movement of patients is almost unavoidable in radiotherapy. In this study, the setup error using the radiation treatment technique was compared according to the loading time and BMI(Body Mass Index) for 14 patients with rectal cancer. In addition, the variation of the dose by the average setup error was compared. Therefore, the technique of a selective standard was established. As a result, 3DCRT(3-Dimensional Radiation Therapy) and VMAT(Volumetric Modulated Arc Therapy) showed a similar time and error. In comparison, IMRT(Intensity Modulated Radiation Therapy) increased the time two fold and the error four fold. In BMI, a more pyknic patient showed a larger error for all techniques. Regarding the dose, IMRT and VMAT increased much more than 3DCRT in the average error at the small bowel. Therefore, 3DCRT of the short time will be applied to pyknic rectal cancer. Moreover, VMAT selects than IMRT in the overexposure of the small bowel.

• Korean Journal of Radiology
• /
• v.24 no.7
• /
• pp.626-639
• /
• 2023

Objective: To investigate the association of clinical, pathologic, and magnetic resonance imaging (MRI) variables with progressive disease (PD) during neoadjuvant chemotherapy (NAC) and distant metastasis-free survival (DMFS) in patients with triple-negative breast cancer (TNBC). Materials and Methods: This single-center retrospective study included 252 women with TNBC who underwent NAC between 2010 and 2019. Clinical, pathologic, and treatment data were collected. Two radiologists analyzed the pre-NAC MRI. After random allocation to the development and validation sets in a 2:1 ratio, we developed models to predict PD and DMFS using logistic regression and Cox proportional hazard regression, respectively, and validated them. Results: Among the 252 patients (age, 48.3 ± 10.7 years; 168 in the development set; 84 in the validation set), PD was occurred in 17 patients and 9 patients in the development and validation sets, respectively. In the clinical-pathologic-MRI model, the metaplastic histology (odds ratio [OR], 8.0; P = 0.032), Ki-67 index (OR, 1.02; P = 0.044), and subcutaneous edema (OR, 30.6; P = 0.004) were independently associated with PD in the development set. The clinical-pathologic-MRI model showed a higher area under the receiver-operating characteristic curve (AUC) than the clinical-pathologic model (AUC: 0.69 vs. 0.54; P = 0.017) for predicting PD in the validation set. Distant metastases occurred in 49 patients and 18 patients in the development and validation sets, respectively. Residual disease in both the breast and lymph nodes (hazard ratio [HR], 6.0; P = 0.005) and the presence of lymphovascular invasion (HR, 3.3; P < 0.001) were independently associated with DMFS. The model consisting of these pathologic variables showed a Harrell's C-index of 0.86 in the validation set. Conclusion: The clinical-pathologic-MRI model, which considered subcutaneous edema observed using MRI, performed better than the clinical-pathologic model for predicting PD. However, MRI did not independently contribute to the prediction of DMFS.

• Journal of the Institute of Convergence Signal Processing
• /
• v.18 no.2
• /
• pp.76-83
• /
• 2017

In this study, the original medical image, DICOM file, was converted into TIFF, BITMAP, GIF, JPEG image file, and then the conversion loss ratio according to the image compression and conversion process was quantitatively evaluated using Origin pro and ICY image analysis program. As the evaluation method, 50% MTF, structural similarity index, MSE, RMSE, maximum signal - to - noise ratio and so on were evaluated. The TIFF image file showed the same result as DICOM image in all experimental groups, Image file format. In this study, we propose a new method for evaluating the quality of digital images by applying original evaluation program such as Origin pro or ICY medical image analysis program. Is expected to be used as research data in the field of medical image processing, and TIFF image file showing the same result as DICOM image in the basic research field using digital medical image and evaluation program that does not support DICOM file Therefore, it is believed that it will help to secure reliability in digital medical image processing research using image file.

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

• Journal of the Korean Society of Radiology
• /
• v.83 no.3
• /
• pp.669-679
• /
• 2022

Purpose To evaluate the feasibility of pediatric low-dose facial CT reconstructed with filtered back projection (FBP) using adequate kernels. Materials and Methods We retrospectively reviewed the clinical and imaging data of children aged < 10 years who underwent facial CT at our emergency department. The patients were divided into two groups: low-dose CT (LDCT; Group A, n = 73) with a fixed 80-kVp tube potential and automatic tube current modulation (ATCM) and standard-dose CT (SDCT; Group B, n = 40) with a fixed 120-kVp tube potential and ATCM. All images were reconstructed with FBP using bone and soft tissue kernels in Group A and only bone kernel in Group B. The groups were compared in terms of image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). Two radiologists subjectively scored the overall image quality of bony and soft tissue structures. The CT dose index volume and dose-length product were recorded. Results Image noise was higher in Group A than in Group B in bone kernel images (p < 0.001). Group A using a soft tissue kernel showed the highest SNR and CNR for all soft tissue structures (all p < 0.001). In the qualitative analysis of bony structures, Group A scores were found to be similar to or higher than Group B scores on comparing bone kernel images. In the qualitative analysis of soft tissue structures, there was no significant difference between Group A using a soft tissue kernel and Group B using a bone kernel with a soft tissue window setting (p > 0.05). Group A showed a 76.9% reduction in radiation dose compared to Group B (3.2 ± 0.2 mGy vs. 13.9 ± 1.5 mGy; p < 0.001). Conclusion The addition of a soft tissue kernel image to conventional CT reconstructed with FBP enables the use of pediatric low-dose facial CT protocol while maintaining image quality.