• Journal of Trauma and Injury
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• v.36 no.3
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• pp.165-171
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• 2023

Trauma remains a significant healthcare burden, causing over five million yearly fatalities. Notably, the liver is a frequently injured solid organ in abdominal trauma, especially in patients under 40 years. It becomes even more critical given that uncontrolled hemorrhage linked to liver trauma can have mortality rates ranging from 10% to 50%. Liver injuries, mainly resulting from blunt trauma such as motor vehicle accidents, are traditionally classified using the American Association for the Surgery of Trauma grading scale. However, recent developments have introduced the World Society of Emergency Surgery classification, which considers the patient's physiological status. The diagnostic approach often involves multiphase computed tomography (CT). Still, newer methods like split-bolus single-pass CT and contrast-enhanced ultrasound (CEUS) aim to reduce radiation exposure. Concerning management, nonoperative strategies have emerged as the gold standard, especially for hemodynamically stable patients. Incorporating angiography with embolization has also been beneficial, with success rates reported between 80% and 97%. However, it is essential to identify the specific source of bleeding for effective embolization. Given the severity of liver trauma and its potential complications, innovations in diagnostic and therapeutic approaches have been pivotal. While CT remains a primary diagnostic tool, methods like CEUS offer safer alternatives. Moreover, nonoperative management, especially when combined with angiography and embolization, has demonstrated notable success. Still, the healthcare community must remain vigilant to complications and continuously seek improvements in trauma care.

• Journal of the Korean Society of Radiology
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• v.81 no.5
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• pp.1227-1233
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• 2020

Synovial sarcoma is a malignant soft tissue tumor that usually involves the extremities, particularly near the knees; a synovial sarcoma originating in the chest wall is extremely rare. We describe a 26-year-old woman diagnosed with a synovial sarcoma originating in the chest wall, based on CT and MRI findings. Contrast-enhanced CT images revealed a small, well-defined enhancing mass with calcification, in the subpleural area. This lesion was initially diagnosed as a benign tumor; however, the patient developed sudden severe pain with spontaneous bleeding and hemothorax, suggesting the possibility of malignancy. MRI revealed a multilobulated mass with a fluid-fluid level, which characterizes a synovial sarcoma.

• Korean Journal of Radiology
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• v.24 no.4
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• pp.294-304
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• 2023

Objective: We aimed to investigate whether image standardization using deep learning-based computed tomography (CT) image conversion would improve the performance of deep learning-based automated hepatic segmentation across various reconstruction methods. Materials and Methods: We collected contrast-enhanced dual-energy CT of the abdomen that was obtained using various reconstruction methods, including filtered back projection, iterative reconstruction, optimum contrast, and monoenergetic images with 40, 60, and 80 keV. A deep learning based image conversion algorithm was developed to standardize the CT images using 142 CT examinations (128 for training and 14 for tuning). A separate set of 43 CT examinations from 42 patients (mean age, 10.1 years) was used as the test data. A commercial software program (MEDIP PRO v2.0.0.0, MEDICALIP Co. Ltd.) based on 2D U-NET was used to create liver segmentation masks with liver volume. The original 80 keV images were used as the ground truth. We used the paired t-test to compare the segmentation performance in the Dice similarity coefficient (DSC) and difference ratio of the liver volume relative to the ground truth volume before and after image standardization. The concordance correlation coefficient (CCC) was used to assess the agreement between the segmented liver volume and ground-truth volume. Results: The original CT images showed variable and poor segmentation performances. The standardized images achieved significantly higher DSCs for liver segmentation than the original images (DSC [original, 5.40%-91.27%] vs. [standardized, 93.16%-96.74%], all P < 0.001). The difference ratio of liver volume also decreased significantly after image conversion (original, 9.84%-91.37% vs. standardized, 1.99%-4.41%). In all protocols, CCCs improved after image conversion (original, -0.006-0.964 vs. standardized, 0.990-0.998). Conclusion: Deep learning-based CT image standardization can improve the performance of automated hepatic segmentation using CT images reconstructed using various methods. Deep learning-based CT image conversion may have the potential to improve the generalizability of the segmentation network.

• The Korean Journal of Nuclear Medicine Technology
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• v.12 no.3
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• pp.235-240
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• 2008

Purpose: At the beginning of PET/CT, Computed Tomography was mainly used only for Attenuation Correction (AC), but as the performance of the CT have been increase, it could give improved diagnostic information with Contrast Media. But it was controversial that Contrast Media could affect AC on PET/CT scan. Some submitted thesis' show that Contrast Media could overestimate when it is for AC data processing. On the contrary, the opinion that Contrast Media could be possible to affect the alteration of SUV because of the overestimated AC. But it does not have a definite effect on the diagnosis. Thus, the affection of Contrast Media on AC was investigated in this study. Materials and Methods: Patient inclusion criteria required a history of a malignancy and performance of an integrated PET/CT scan and contrast- enhanced CT scan within a 1-day period. Thirty oncologic patients who had PET/CT scan from December 2007 to June 2008 underwent staging evaluation and met these criteria. All patients fasted for at least 6 hr before the IV injection of approximately 5.6 MBq/kg (0.15 mCi/kg) of $^{18}F$-FDG and were scanned about 60 min after injection. All patients had a whole body PET/CT performed without IV contrast media followed by a contrast-enhanced CT on the Discovery STe PET/CT scanner. CT data were used for AC and PET images came out after AC. The ROIs drew and measured SUV. A paired t-test of these results was performed to assess the significance of the difference between the SUV obtained from the two attenuation corrected PET images. Results: The mean and maximum Standardized Uptake Values (SUV) for different regions averaged over all Patients. Comparing before using Contrast Media and after using, Most of ROIs have the increased SUV when it did Contrast Enhanced CT compare to Non-Contrast enhanced CT. All regions have increased SUV and also their p value was under 0.05 except the mean SUV of the Heart region. Conclusion: In this regard, the effect on SUV measurements that occurs when a contrast-enhanced CT is used for attenuation correction could have significant clinical ramifications. But some submitted thesis insisted that the percentage change in SUV that can determine or modify clinical management of oncology patients is small. Because there was not much difference that could be discovered by interpreter. But obviously the numerical change was occurred and on the stage finding primary region, small change would be base line, such as the region of liver which has greater change than the other regions needs more attention.

• Journal of Veterinary Clinics
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• v.27 no.5
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• pp.588-592
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• 2010

A 15-year-old neutered male Yorkshire terrier was presented with a gait disorder of the pelvic limbs. For differential diagnosis of neural disease, magnetic resonance imaging (MRI) and computed tomography (CT) scan were performed. CT showed bone defect in the 4th lumbar vertebra and adjacent soft tissue mass. MRI revealed a mass in left side of the 4th lumbar vertebra. The mass was uniformly enhanced on contrast-enhanced T1-weighted imaging (T1W1). Excision of the mass alleviated back pain. Vertebral osteosarcoma was identified by the histopathological examination. Therefore, CT and MRI were helpful to diagnose vertebral osteosarcoma in the dog and to plan surgical excision of the mass.

• Korean Journal of Radiology
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• v.22 no.11
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• pp.1764-1776
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• 2021

Objective: This study aimed to validate a deep learning-based fully automatic calcium scoring (coronary artery calcium [CAC]_auto) system using previously published cardiac computed tomography (CT) cohort data with the manually segmented coronary calcium scoring (CAC_hand) system as the reference standard. Materials and Methods: We developed the CAC_auto system using 100 co-registered, non-enhanced and contrast-enhanced CT scans. For the validation of the CAC_auto system, three previously published CT cohorts (n = 2985) were chosen to represent different clinical scenarios (i.e., 2647 asymptomatic, 220 symptomatic, 118 valve disease) and four CT models. The performance of the CAC_auto system in detecting coronary calcium was determined. The reliability of the system in measuring the Agatston score as compared with CAC_hand was also evaluated per vessel and per patient using intraclass correlation coefficients (ICCs) and Bland-Altman analysis. The agreement between CAC_auto and CAC_hand based on the cardiovascular risk stratification categories (Agatston score: 0, 1-10, 11-100, 101-400, > 400) was evaluated. Results: In 2985 patients, 6218 coronary calcium lesions were identified using CAC_hand. The per-lesion sensitivity and false-positive rate of the CAC_auto system in detecting coronary calcium were 93.3% (5800 of 6218) and 0.11 false-positive lesions per patient, respectively. The CAC_auto system, in measuring the Agatston score, yielded ICCs of 0.99 for all the vessels (left main 0.91, left anterior descending 0.99, left circumflex 0.96, right coronary 0.99). The limits of agreement between CAC_auto and CAC_hand were 1.6 ± 52.2. The linearly weighted kappa value for the Agatston score categorization was 0.94. The main causes of false-positive results were image noise (29.1%, 97/333 lesions), aortic wall calcification (25.5%, 85/333 lesions), and pericardial calcification (24.3%, 81/333 lesions). Conclusion: The atlas-based CAC_auto empowered by deep learning provided accurate calcium score measurement as compared with manual method and risk category classification, which could potentially streamline CAC imaging workflows.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.38 no.1
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• pp.38-43
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• 2012

Introduction: The location of parotid gland tumors in the superficial or deep lobes can affect the time and difficulty of operations. Therefore, accurate preoperative evaluation of the tumor location is important for surgical outcomes. Materials and Methods: A total of 16 patients with parotid gland tumors and who underwent a parotidectomy between April 2003 and March 2011 were retrospectively reviewed in terms of demographic background, tumor location, surgical treatment, and treatment outcomes. Tumor location was estimated by four landmarks on contrast enhanced computerized tomography scans, which were Conn's arc, the facial nerve (FN) line, the Utrecht line, and the retromandibular vein. Tumor location was confirmed by relative position depending on the facial nerve during surgery. It was assumed positive since the tumor lies in the superficial lobe of the parotid gland, the sensitivity, specificity, positive predictive value, negative predictive value, and efficiency of each landmark were evaluated. Results: Our result revealed that the facial nerve line had a sensitivity of 83.3%, specificity of 100%, positive predictive value of 100%, negative predictive value of 71.4%, and efficiency of 87.5%. Some would be more efficient preoperative evaluation methods of the relationship of parotid gland tumors to the facial nerve than others. Conclusion: In our study, the FN line was found to be the most reliable analysis method.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.18
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• pp.7719-7724
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• 2014

Background: Lymph node metastasis is believed to be a dependent negative prognostic factor of esophageal cancer. To explore detection methods with high sensitivity and accuracy for metastases to regional and distant lymph nodes in the clinic is of great significance. This study focused on clinical application of FDG PET/CT and contrast-enhanced multiple-slice helical computed tomography (MSCT) in lymph node staging of esophageal cancer. Materials and Methods: One hundred and fifteen cases were examined with enhanced 64-slice-MSCT scan, and FDG PET/CT imaging was conducted for neck, chest and upper abdomen within one week. The primary lesion, location and numbers of metastatic lymph nodes were observed. Surgery was performed within one week after FDG PET/CT detection. All resected lesions were confirmed histopathologically as the gold standard. Comparative analysis of the sensitivity, specificity, and accuracy based on FDG PET/CT and MSCT was conducted. Results: There were 946 lymph node groups resected during surgery from 115 patients, and 221 were confirmed to have metastasis pathologically. The sensitivity, specificity, accuracy of FDG PET/CT in detecting lymph node metastasis were 74.7%, 97.2% and 92.0%, while with MSCT they were 64.7%, 96.4%, and 89.0%, respectively. A significance difference was observed in sensitivity (p=0.030), but not the others (p>0.05). The accuracy of FDG PET/CT in detecting regional lymph node with or without metastasis were 91.9%, as compared to 89.4% for MSCT, while FDG PET/CT and MSCT values for detecting distant lymph node with or without metastasis were 94.4% and 94.7%. No significant difference was observed for either regional or distant lymph node metastasis. Additionally, for detecting para-esophageal lymph nodes metastasis, the sensitivity of FDG PET/CT was 72%, compared with 54.7% for MSCT (p=0.029). Conclusions: FDG PET/CT is more sensitive than MSCT in detecting lymph node metastasis, especially for para-esophageal lymph nodes in esophageal cancer cases, although no significant difference was observed between FDG PET/CT and MSCT in detecting both regional and distant lymph node metastasis. However, enhanced MSCT was found to be of great value in distinguishing false negative metastatic lymph nodes from FDG PET/CT. The combination of FDG PET/CT with MSCT should improve the accuracy in lymph node metastasis staging of esophageal cancer.

• Journal of Veterinary Clinics
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• v.33 no.3
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• pp.168-171
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• 2016

Signalment: An 8-month-old female Alaskan malamute was presented for progressive cluster seizure disorder. Results: There were no abnormalities on neurological examination, survey radiographs, or blood analysis. Magnetic resonance (MR) imaging and computed tomography revealed extension of the olfactory bulb and frontal lobe into the nasal cavity. They also confirmed abnormal anatomy of the nasal turbinates within the rostral part of the nasal cavity and the absence of a cribriform plate. On T2-weighted and fluid-attenuated inversion recovery images, the herniated brain showed heterogeneous and hyperintense signals consistent with intraparenchymal edema. Transverse MR images showed brain herniation into the right frontal cavity and an asymmetrical lateral ventricle because of a left midline shift. On contrast-enhanced MR images, the protruding brain parenchyma was mildly enhanced. Ethmoidal encephalocele was suspected as the final diagnosis. Despite symptomatic treatment, the dog continued to exhibit seizures and was euthanized. Clinical relevance: Ethmoidal encephalocele is a rare disease in dogs. However, it could be considered as a cause of seizure in young dogs.

• Imaging Science in Dentistry
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• v.35 no.2
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• pp.111-114
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• 2005

A 15-year-old patient, who had been diagnosed and treated as Burkitt cell type acute lymphoblastic leukemia (ALL-L3) already, visited our department. He complained of gingival enlargement and loosening teeth 1 month ago. The clinical examination revealed anterior open bite, gingival enlargement, and nontender swelling particularly in molar regions of both jaws. Deep periodontal pockets and severe mobility was shown on most of the teeth. The panoramic radiographs showed severe bone destruction and extrusion of the molars. The contrast enhanced CT showed multiple enhanced mass and bone marrow obliteration in both jaws. Chemotherapy was done and the swelling was subsided at 1 month later. In conclusion, radiologic findings of leukemia with soft tissue mass, known as chloroma or granulocytic sarcoma, mimic those of lymphoma, so blood test may be needed for the final diagnosis.