• Journal of Gastric Cancer
• /
• v.11 no.4
• /
• pp.234-238
• /
• 2011

A 67 year old male at a regular checkup underwent esophagogastroduodenoscopy. On performing esophagogastroduodenoscopy, a lesion about 1.2 cm depressed was noted at the gastric angle. The pathology of the biopsy specimen revealed a well-differentiated adenocarcinoma. On performing an abdominal computed tomography (CT) scan & positron emission tomography-computed tomography (PET-CT) scan, no definite evidence of gastric wall thickening or mass lesion was found. However, lymph node enlargement was found in the left gastric and prepancreatic spaces. This patient underwent laparoscopic assisted distal gastrectomy and D2 lymph node dissection. On final examination, it was found out that the tumor had invaded the mucosal layer. The lymph node was a metastasized large cell neuroendocrine carcinoma with an unknown primary site. The patient refused chemotherapy. He opted to undergo a close followup. At the postoperative month 27, he had a focal hypermetabolic lesion in the left lobe of the liver that suggested metastasis on PET-CT scan. He refused to undergo an operation. He underwent a radiofrequency ablation.

• Tuberculosis and Respiratory Diseases
• /
• v.69 no.2
• /
• pp.129-133
• /
• 2010

Extramedullary plasmacytoma (EMP) is a rare disorder that typically occurs in the upper airway. Although the condition rarely arises in the lungs, a few cases have been reported. Here, we report a case of pulmonary plasmacytoma in 66-year-old man, who had been treated with VAD (vincrestine, adriamycin, dexamethasone) chemotherapy for multiple myeloma. The patient had been declared clear of multiple myeloma after 4 cycles of chemotherapy. Three months later, the patient had multiple masses visible on computed tomography (CT) and on positron emission tomography-computed tomography (PET-CT) with hot uptake. Subsequent studies using CT-guided needle biopsy and immunohistochemical stain showed pulmonary plasmacytoma. Bone marrow biopsy, serum, and urine M protein tests were repeated, showing no evidence of multiple myeloma. Pulmonary plasmacytomas, as extramedullary plasmacytomas, were considered an isolated manifestation of multiple myeloma recurrence. We treated the patient with concurrent chemoradiotherapy and the pulmonary plasmacytomas regressed dramatically.

• Korean Journal of Radiology
• /
• v.19 no.6
• /
• pp.1089-1098
• /
• 2018

Objective: To investigate the diagnostic yield of contrast-enhanced computed tomography (CT) in Crohn's disease (CD) patients presenting with acute severe lower gastrointestinal bleeding (LGIB), and the role of CT in predicting the risk of rebleeding. Materials and Methods: A consecutive series of 110 CD patients presenting with acute severe LGIB between 2005 and 2016 were analyzed. Among them, 86 patients who had undergone contrast-enhanced CT constituted the study cohort. The diagnostic yield of CT for detecting contrast extravasation was obtained for the entire cohort and compared between different CT techniques. In a subgroup of 62 patients who had undergone CT enterography (CTE) and showed a negative result for extravasation on CTE, the association between various clinical and CTE parameters and the risk of rebleeding during subsequent follow-up was investigated using Cox regression analysis. Results: The diagnostic yield of CT was 10.5% (9 of 86 patients). The yield did not significantly differ between single-phase and multiphase examinations (p > 0.999), or between non-enterographic CT and CTE (p = 0.388). Extensive CD (adjusted hazard ratio [HR], 3.27; 95% confidence interval [CI], 1.09-9.80; p = 0.034) and bowel wall-to-artery enhancement ratio (adjusted HR, 2.81; 95% CI, 1.21-6.54; p = 0.016) were significantly independently associated with increased rebleeding risks, whereas anti-tumor necrosis factor-${\alpha}$ therapy after the bleeding independently decreased the risk of rebleeding (adjusted HR, 0.26; 95% CI, 0.07-0.95; p = 0.041). Conclusion: The diagnostic yield of contrast-enhanced CT was not high in CD patients presenting with acute severe LGIB. Nevertheless, even a negative CTE may be beneficial as it can help predict the risk of later rebleeding.

• Korean Journal of Radiology
• /
• v.1 no.1
• /
• pp.51-55
• /
• 2000

Objective: To determine the accuracy of CT and positron emission tomography (PET) in the diagnosis of recurrent uterine cervical cancer. Materials and Methods: Imaging findings of CT and PET in 36 patients (mean age, 53 years) in whom recurrent uterine cervical cancer was suspected were analyzed retrospectively. Between October 1997 and May 1998, they had undergone surgery and/or radiation therapy. Tumor recurrence was confirmed by pathologic examination or follow-up studies. Results: In detecting recurrent uterine cervical cancer, the sensitivity, specificity, and accuracy of CT were 77.8%, 83.3%, and 80.5%, respectively, while for PET, the corresponding figures were 100%, 94.4%, and 97.2%. The Chi-square test revealed no significant difference in specificity (p = .2888), but significant differences in sensitivity (p = .0339) and accuracy (p = .0244). Conclusion: PET proved to be a reliable screening method for detecting recurrent uterine cervical cancer, but to determine the anatomical localization of recurrent tumors, and thus decide an adequate treatment plan, CT was eventually needed.

• Tuberculosis and Respiratory Diseases
• /
• v.82 no.3
• /
• pp.234-241
• /
• 2019

Background: The utility of computed tomography (CT) in the differential diagnosis of patients with chronic obstructive pulmonary disease (COPD) exacerbation remains uncertain. However, due to the low cost associated with CT scan along with the impact of Koreas' health insurance system, there has been a rise in the number of CT scans in the patients with initial diagnosis of COPD exacerbations. Therefore, the utility of CT in the differential diagnosis was investigated to determine whether performing CT scans affect the clinical outcomes of the patients with an initial diagnosis of COPD exacerbation. Methods: This study involved 202 COPD patients hospitalized with an initial diagnosis of COPD exacerbation. We evaluated the change in diagnosis or treatment after performing a CT scan, and compared the clinical outcomes of patient groups with vs. without performing CT (non-CT group vs. CT group). Results: After performing CT, the diagnosis was changed for two (3.0%) while additional diagnoses were made for 27 of the 64 patients (42.1%). However, the treatment changed for only one (1.5%), and six patients (9.3%) received supplementary medication. There were no difference in the median length of hospital stay (8 [6-13] days vs. 8 [6-12] days, p=0.786) and intensive care unit care (14 [10.1%] vs. 11 [16.7%], p=0.236) between the CT and non-CT groups, respectively. These findings remained consistent even after the propensity score matching. Conclusion: Utility of CT in patients with acute COPD exacerbation might not be helpful; therefore, we do not recommend chest CT scan as a routine initial diagnostic tool.

• Journal of the Korean Society of Radiology
• /
• v.16 no.3
• /
• pp.295-302
• /
• 2022

Sparse-view computed tomography (CT) imaging technique is able to reduce radiation dose, ensure the uniformity of image characteristics among projections and suppress noise. However, the reconstructed images obtained by the sparse-view CT imaging technique suffer from severe artifacts, resulting in the distortion of image quality and internal structures. In this study, we proposed a convolutional neural network (CNN) with wavelet transformation and residual learning for reducing artifacts in sparse-view CT image, and the performance of the trained model was quantitatively analyzed. The CNN consisted of wavelet transformation, convolutional and inverse wavelet transformation layers, and input and output images were configured as sparse-view CT images and residual images, respectively. For training the CNN, the loss function was calculated by using mean squared error (MSE), and the Adam function was used as an optimizer. Result images were obtained by subtracting the residual images, which were predicted by the trained model, from sparse-view CT images. The quantitative accuracy of the result images were measured in terms of peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). The results showed that the trained model is able to improve the spatial resolution of the result images as well as reduce artifacts in sparse-view CT images effectively. Also, the trained model increased the PSNR and SSIM by 8.18% and 19.71% in comparison to the imaging model trained without wavelet transformation and residual learning, respectively. Therefore, the imaging model proposed in this study can restore the image quality of sparse-view CT image by reducing artifacts, improving spatial resolution and quantitative accuracy.

• Journal of Biomedical Engineering Research
• /
• v.42 no.4
• /
• pp.150-158
• /
• 2021

Intracranial hemorrhage (ICH) refers to acute bleeding inside the intracranial vault. Not only does this devastating disease record a very high mortality rate, but it can also cause serious chronic impairment of sensory, motor, and cognitive functions. Therefore, a prompt and professional diagnosis of the disease is highly critical. Noninvasive brain imaging data are essential for clinicians to efficiently diagnose the locus of brain lesion, volume of bleeding, and subsequent cortical damage, and to take clinical interventions. In particular, computed tomography (CT) images are used most often for the diagnosis of ICH. In order to diagnose ICH through CT images, not only medical specialists with a sufficient number of diagnosis experiences are required, but even when this condition is met, there are many cases where bleeding cannot be successfully detected due to factors such as low signal ratio and artifacts of the image itself. In addition, discrepancies between interpretations or even misinterpretations might exist causing critical clinical consequences. To resolve these clinical problems, we developed a diagnostic model predicting intracranial bleeding and its subtypes (intraparenchymal, intraventricular, subarachnoid, subdural, and epidural) by applying deep learning algorithms to CT images. We also constructed a visualization tool highlighting important regions in a CT image for predicting ICH. Specifically, 1) 27,758 CT brain images from RSNA were pre-processed to minimize the computational load. 2) Three different CNN-based models (ResNet, EfficientNet-B2, and EfficientNet-B7) were trained based on a training image data set. 3) Diagnosis performance of each of the three models was evaluated based on an independent test image data set: As a result of the model comparison, EfficientNet-B7's performance (classification accuracy = 91%) was a way greater than the other models. 4) Finally, based on the result of EfficientNet-B7, we visualized the lesions of internal bleeding using the Grad-CAM. Our research suggests that artificial intelligence-based diagnostic systems can help diagnose and treat brain diseases resolving various problems in clinical situations.

• Imaging Science in Dentistry
• /
• v.32 no.1
• /
• pp.27-33
• /
• 2002

Purpose: To evaluate the influence of threshold value of computed tomography on the accuracy of rapid prototyping (RP) medical model Material and Methods : CT datas of a human dry skull were transferred from CT scanner via compact disk to a personal computer (PC). 3-dimensional image reconstruction on PC by V-works/sup TM/ 3.0 (CyberMed. Inc.) software and RP models fabrication were followed. 2-RP models were produced by threshold value of 500 and 800 selected in surface rendering process. Linear measurements between arbitrary 12 anatomical landmarks on dry skull, 3-D image model, and 2-RP models were done and compared. Thus, the accuracy of 500 RP and 800RP models was respectively evaluated. Results: There was mean difference (% difference) in absolute value of 2.27 mm (2.73%) between linear measurements of dry skull and 500 RP model. There was mean difference (% difference) in absolute value of 1.94 mm (2.52%) between linear measurements of dry skull and 800 RP model. Conclusion: Slight difference of threshold value in rendering process of 3-D modelling made a influence on the accuracy of RP medical model.

• Radiation Oncology Journal
• /
• v.35 no.3
• /
• pp.274-280
• /
• 2017

Purpose: To see the gross tumor volume (GTV) dependency according to the phase selection and reconstruction methods, we measured and analyzed the changes of tumor volume and motion at each phase in 20 cases with lung cancer patients who underwent image-guided radiotherapy. Materials and Methods: We retrospectively analyzed four-dimensional computed tomography (4D-CT) images in 20 cases of 19 patients who underwent image-guided radiotherapy. The 4D-CT images were reconstructed by the maximum intensity projection (MIP) and the minimum intensity projection (Min-IP) method after sorting phase as 40%-60%, 30%-70%, and 0%-90%. We analyzed the relationship between the range of motion and the change of GTV according to the reconstruction method. Results: The motion ranges of GTVs are statistically significant only for the tumor motion in craniocaudal direction. The discrepancies of GTV volume and motion between MIP and Min-IP increased rapidly as the wider ranges of duty cycles are selected. Conclusion: As narrow as possible duty cycle such as 40%-60% and MIP reconstruction was suitable for lung cancer if the respiration was stable. Selecting the reconstruction methods and duty cycle is important for small size and for large motion range tumors.

• Journal of the Korea Safety Management & Science
• /
• v.12 no.2
• /
• pp.225-230
• /
• 2010

The purpose of the study was to apply and to expand the six sigma to reduce waiting times for computed tomography (CT) examination which manipulated by the department of radiology. It was preceded by DMAIC (Define, Measure, Analyze, Improve, and Control). In the stage of definition, it wereselected for total 5 critical to quality (CTQ), which were the kindness, the waiting time, the examination explanation, the waiting day and the waiting stand environment, that increased the reserved time of CT examination. In the stage of measurement, the number of examinations and of reservation waiting days performed and resulted in final CTQ(Y) which measured each 1.68 and 1.85 sigma. In the stage of analysis, the examination concentrated on morning time, non-scheduled examination of the day, the delayed time of booking, frequent telephone contacting and equipment malfunction were determined as variable key causes. In the stage of improvement, it were performed with expansion of the examination in the morning time, integration of laboratories that used to in each steps, developing the ability of simultaneous booking schedule for the multiple examinations, developing program of examination request, and the customer management team operations. For the control, the number of examinations and reserved waiting days were measured each 3.14 and 1.13 sigma.