• Pediatric Gastroenterology, Hepatology & Nutrition
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• 제18권2호
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• pp.144-148
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• 2015

Hepatocellular adenomas are a benign, focal, hepatic neoplasm that have been divided into four subtypes according to the genetic and pathological features. The ${\beta}$-catenin activated subtype accounts for 10-15% of all hepatocellular adenomas and specific magnetic resonance imaging features have been defined for different hepatocellular adenomas subtypes. The current study aimed to report the magnetic resonance imaging features of a well differentiated hepatocellular carcinoma that developed on the basis of ${\beta}$-catenin activated hepatocellular adenomas in a child. In this case, atypical diffuse steatosis was determined in the lesion. In the literature, diffuse steatosis, which is defined as a feature of the hepatocyte nuclear factor-$1{\alpha}$-inactivated hepatocellular adenomas subtype, has not been previously reported in any ${\beta}$-catenin activated hepatocellular adenomas case. Interlacing magnetic resonance imaging findings between subtypes show that there are still many mysteries about this topic and larger studies are warranted.

• Imaging Science in Dentistry
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• 제49권1호
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• pp.1-7
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• 2019

Purpose: Artificial intelligence (AI), represented by deep learning, can be used for real-life problems and is applied across all sectors of society including medical and dental field. The purpose of this study is to review articles about deep learning that were applied to the field of oral and maxillofacial radiology. Materials and Methods: A systematic review was performed using Pubmed, Scopus, and IEEE explore databases to identify articles using deep learning in English literature. The variables from 25 articles included network architecture, number of training data, evaluation result, pros and cons, study object and imaging modality. Results: Convolutional Neural network (CNN) was used as a main network component. The number of published paper and training datasets tended to increase, dealing with various field of dentistry. Conclusion: Dental public datasets need to be constructed and data standardization is necessary for clinical application of deep learning in dental field.

• Korean Journal of Radiology
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• 제24권11호
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• pp.1061-1080
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• 2023

Artificial intelligence (AI) in radiology is a rapidly developing field with several prospective clinical studies demonstrating its benefits in clinical practice. In 2022, the Korean Society of Radiology held a forum to discuss the challenges and drawbacks in AI development and implementation. Various barriers hinder the successful application and widespread adoption of AI in radiology, such as limited annotated data, data privacy and security, data heterogeneity, imbalanced data, model interpretability, overfitting, and integration with clinical workflows. In this review, some of the various possible solutions to these challenges are presented and discussed; these include training with longitudinal and multimodal datasets, dense training with multitask learning and multimodal learning, self-supervised contrastive learning, various image modifications and syntheses using generative models, explainable AI, causal learning, federated learning with large data models, and digital twins.

• Korean Journal of Radiology
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• 제22권1호
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• pp.106-117
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• 2021

Objective: To explore the value of magnetic resonance imaging (MRI)-based whole tumor texture analysis in differentiating borderline epithelial ovarian tumors (BEOTs) from FIGO stage I/II malignant epithelial ovarian tumors (MEOTs). Materials and Methods: A total of 88 patients with histopathologically confirmed ovarian epithelial tumors after surgical resection, including 30 BEOT and 58 MEOT patients, were divided into a training group (n = 62) and a test group (n = 26). The clinical and conventional MRI features were retrospectively reviewed. The texture features of tumors, based on T2-weighted imaging, diffusion-weighted imaging, and contrast-enhanced T1-weighted imaging, were extracted using MaZda software and the three top weighted texture features were selected by using the Random Forest algorithm. A non-texture logistic regression model in the training group was built to include those clinical and conventional MRI variables with p value < 0.10. Subsequently, a combined model integrating non-texture information and texture features was built for the training group. The model, evaluated using patients in the training group, was then applied to patients in the test group. Finally, receiver operating characteristic (ROC) curves were used to assess the diagnostic performance of the models. Results: The combined model showed superior performance in categorizing BEOTs and MEOTs (sensitivity, 92.5%; specificity, 86.4%; accuracy, 90.3%; area under the ROC curve [AUC], 0.962) than the non-texture model (sensitivity, 78.3%; specificity, 84.6%; accuracy, 82.3%; AUC, 0.818). The AUCs were statistically different (p value = 0.038). In the test group, the AUCs, sensitivity, specificity, and accuracy were 0.840, 73.3%, 90.1%, and 80.8% when the non-texture model was used and 0.896, 75.0%, 94.0%, and 88.5% when the combined model was used. Conclusion: MRI-based texture features combined with clinical and conventional MRI features may assist in differentitating between BEOT and FIGO stage I/II MEOT patients.

• Korean Journal of Radiology
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• 제24권12호
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• pp.1176-1178
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• 2023

• Investigative Magnetic Resonance Imaging
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• 제22권1호
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• pp.10-17
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• 2018

Purpose: To evaluate interpretation errors involving spine MRIs by residents in their second to fourth year of training, classified as minor, intermediate and major discrepancies, as well as the types of commonly discordant lesions with or without clinical significance. Materials and Methods: A staff radiologist evaluated both preliminary and final reports of 582 spine MRIs performed in the emergency room from March 2011 to February 2013, involving (1) the incidence of report discrepancy, classified as minor if there was sufficient description of the main MR findings without ancillary or incidental lesions not influencing the main diagnosis, treatment, or patients' clinical course; intermediate if the correct diagnosis was made with insufficient or inadequate explanation, potentially influencing treatment or clinical course; and major if the discrepancy affected the main diagnosis; and (2) the common causes of discrepancy. We analyzed the differences in the incidence of discrepancy with respect to the training years of residents, age and sex of patients. Results: Interpretation discrepancy occurred in 229 of the 582 cases (229/582, 39.3%), including 146 minor (146/582, 25.1%), 40 intermediate (40/582, 6.9%), and 43 major cases (43/582, 7.4%). The common causes of major discrepancy were: over-diagnosis of fracture (n = 10), missed cord lesion (n = 9), missed signal abnormalities associated with diffuse marrow (n = 5), and failure to provide differential diagnosis of focal abnormal marrow signal intensity (n = 5). No significant difference was found in the incidence of minor, intermediate, and major discrepancies according to the levels of residency, patients' age or sex. Conclusion: A 7.4% rate of major discrepancies was found in preliminary reporting of emergency MRIs of spine interpreted by radiology residents, probably related to a relative lack of clinical experience, indicating the need for additional training, especially involving spine trauma, spinal cord and bone marrow lesions.

• 대한방사선기술학회지:방사선기술과학
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• 제40권3호
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• pp.501-508
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• 2017

본 연구는 연구용원자로(하나로)와 국가방사선연구시설을 이용한 전문교육과정을 개발 운영함으로써 방사선학 전공 대학생들에게 전문화된 교육 기회를 제공하고 현장적응 능력을 증진시킬 목적으로 수행되었다. 이를 위해 하나로와 국가방사선연구시설을 이용한 전문 교육과정을 개발하고 운영함으로써 대학생들에게 하나로 활용 기회를 제공하였고, 대학생을 대상으로 하는 방사선학과 실험 실습을 운영함으로써 차세대 전문가를 양성하였다. 방사선학과 대학생들에게 현장실험실습 기회를 제공함으로써 향후 방사선학 연구 분야의 잠재 이용자를 육성하여 방사선학 인력의 저변 확대를 하고자 하였다. 본 실험실습 과정을 위해 서술형 교재와 강의용 교재, 설문지를 개발하고 활용하였다. 2006년부터 2017년까지 방사선학과 대학생을 대상으로 운영된 실험실습교육과정에 714명이 수료하였다. 방사선학과 대학생들을 대상으로 개발 운영되는 교육과정은 하나로와 국가방사선연구시설의 이용을 더욱 활성화하여 궁극적으로 방사선 산업인력의 저변을 확대하고 올바른 정책 결정 및 기술기반을 확립하는 주요 자원이 될 것이며 방사선 분야의 활성화에도 기여하게 될 것이다.

• Korean Journal of Radiology
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• 제22권3호
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• pp.395-404
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• 2021

Objective: To compare the utility of computed tomography perfusion (CTP) and three different 4-point scoring systems in computed tomography angiography (CTA) in confirming brain death (BD) in patients with and without skull defects. Materials and Methods: Ninety-two patients clinically diagnosed as BD using CTA and/or CTP for confirmation were retrospectively reviewed. For the final analysis, 86 patients were included in this study. Images were re-evaluated by three radiologists according to the 4-point scoring systems that consider the vessel opacification on 1) the venous phase for both M4 segments of the middle cerebral arteries (MCAs-M4) and internal cerebral veins (ICVs) (A60-V60), 2) the arterial phase for the MCA-M4 and venous phase for the ICVs (A20-V60), 3) the venous phase for the ICVs and superior petrosal veins (ICV-SPV). The CTP images were independently reviewed. The presence of an open skull defect and stasis filling was noted. Results: Sensitivities of the ICV-SPV, A20-V60, A60-V60 scoring systems, and CTP in the diagnosis of BD were 89.5%, 82.6%, 67.4%, and 93.3%, respectively. The sensitivity of A20-V60 scoring was higher than that of A60-V60 in BD patients (p < 0.001). CTP was found to be the most sensitive method (86.5%) in patients with open skull defect (p = 0.019). Interobserver agreement was excellent in the diagnosis of BD, in assessing A20-V60, A60-V60, ICV-SPV, CTP, and good in stasis filling (κ: 0.84, 0.83, 0.83, 0.83, and 0.67, respectively). Conclusion: The sensitivity of CTA confirming brain death differs between various proposed 4-point scoring systems. Although the ICV-SPV is the most sensitive, evaluation of the SPV is challenging. Adding CTP to the routine BD CTA protocol, especially in cases with open skull defect, could increase sensitivity as a useful adjunct.

• Korean Journal of Radiology
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• 제23권9호
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• pp.921-930
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• 2022

Objective: To identify epidermal growth factor receptor (EGFR) mutations in lung adenocarcinoma based on ¹⁸F-fluorodeoxyglucose (FDG) PET/CT radiomics and clinical features and to distinguish EGFR exon 19 deletion (19 del) and exon 21 L858R missense (21 L858R) mutations using FDG PET/CT radiomics. Materials and Methods: We retrospectively analyzed 179 patients with lung adenocarcinoma. They were randomly assigned to training (n = 125) and testing (n = 54) cohorts in a 7:3 ratio. A total of 2632 radiomics features were extracted from the tumor region of interest from the PET (1316) and CT (1316) images. Six PET/CT radiomics features that remained after the feature selection step were used to calculate the radiomics model score (rad-score). Subsequently, a combined clinical and radiomics model was constructed based on sex, smoking history, tumor diameter, and rad-score. The performance of the combined model in identifying EGFR mutations was assessed using a receiver operating characteristic (ROC) curve. Furthermore, in a subsample of 99 patients, a PET/CT radiomics model for distinguishing 19 del and 21 L858R EGFR mutational subtypes was established, and its performance was evaluated. Results: The area under the ROC curve (AUROC) and accuracy of the combined clinical and PET/CT radiomics models were 0.882 and 81.6%, respectively, in the training cohort and 0.837 and 74.1%, respectively, in the testing cohort. The AUROC and accuracy of the radiomics model for distinguishing between 19 del and 21 L858R EGFR mutational subtypes were 0.708 and 66.7%, respectively, in the training cohort and 0.652 and 56.7%, respectively, in the testing cohort. Conclusion: The combined clinical and PET/CT radiomics model could identify the EGFR mutational status in lung adenocarcinoma with moderate accuracy. However, distinguishing between EGFR 19 del and 21 L858R mutational subtypes was more challenging using PET/CT radiomics.

• Imaging Science in Dentistry
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• 제43권4호
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• pp.253-259
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• 2013

Purpose: Radiographs is an integral part of patient management in dentistry, despite their detrimental effects. As the literature pertaining to radiation protection among Indian dental practitioners is sparse, exploring such protection is needed. Materials and Methods: All private dental practitioners in Mangalore, India were included in the study. A structured, pre-tested, self-administered questionnaire was employed to assess the knowledge, attitudes, practices, previous training, perceptions towards the need to spread awareness, and willingness to gain and implement knowledge about radiation hazards and protection. Information regarding each respondent's age, gender, education, and type and duration of practice was collected. Results: Overall, 87 out of 120 practitioners participated in the study. The mean knowledge, attitude, and practice scores were $9.54{\pm}2.54$, $59.39{\pm}7.01$, and $5.80{\pm}3.19$, respectively. Overall, 25.3% of the respondents had undergone training in radiation protection, 98.9% perceived a need to spread awareness, and 94.3% were willing to improve their knowledge. Previous training showed a significant correlation with age, sex, and duration of practice; attitude was significantly correlated with education and type of practice; and knowledge scores showed a significant correlation with type of practice. Conclusion: Although the knowledge and practices of respondents were poor, they had a positive attitude and were willing to improve their knowledge. Age, sex, and duration of practice were associated with previous training; education and type of practice with attitude scores; and type of practice with knowledge scores. The findings of this study suggest a policy is needed to ensure the adherence of dental practitioners to radiation protection guidelines.