• Imaging Science in Dentistry
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• 제51권2호
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• pp.129-136
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• 2021

Purpose: This study investigated the effects of 1 year of training on imaging diagnosis, using static ultrasonography (US) salivary gland images of Sjögren syndrome patients. Materials and Methods: This study involved 3 inexperienced radiologists with different levels of experience, who received training 1 or 2 days a week under the supervision of experienced radiologists. The training program included collecting patient histories and performing physical and imaging examinations for various maxillofacial diseases. The 3 radiologists (observers A, B, and C) evaluated 400 static US images of salivary glands twice at a 1-year interval. To compare their performance, 2 experienced radiologists evaluated the same images. Diagnostic performance was compared between the 2 evaluations using the area under the receiver operating characteristic curve (AUC). Results: Observer A, who was participating in the training program for the second year, exhibited no significant difference in AUC between the first and second evaluations, with results consistently comparable to those of experienced radiologists. After 1 year of training, observer B showed significantly higher AUCs than before training. The diagnostic performance of observer B reached the level of experienced radiologists for parotid gland assessment, but differed for submandibular gland assessment. For observer C, who did not complete the training, there was no significant difference in the AUC between the first and second evaluations, both of which showed significant differences from those of the experienced radiologists. Conclusion: These preliminary results suggest that the training program effectively helped inexperienced radiologists reach the level of experienced radiologists for US examinations.

• Korean Journal of Radiology
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• 제25권1호
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• pp.11-23
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• 2024

Objective: To investigate whether reader training improves the performance and agreement of radiologists in interpreting unenhanced breast magnetic resonance imaging (MRI) scans using diffusion-weighted imaging (DWI). Materials and Methods: A study of 96 breasts (35 cancers, 24 benign, and 37 negative) in 48 asymptomatic women was performed between June 2019 and October 2020. High-resolution DWI with b-values of 0, 800, and 1200 sec/mm² was performed using a 3.0-T system. Sixteen breast radiologists independently reviewed the DWI, apparent diffusion coefficient maps, and T1-weighted MRI scans and recorded the Breast Imaging Reporting and Data System (BI-RADS) category for each breast. After a 2-h training session and a 5-month washout period, they re-evaluated the BI-RADS categories. A BI-RADS category of 4 (lesions with at least two suspicious criteria) or 5 (more than two suspicious criteria) was considered positive. The per-breast diagnostic performance of each reader was compared between the first and second reviews. Inter-reader agreement was evaluated using a multi-rater κ analysis and intraclass correlation coefficient (ICC). Results: Before training, the mean sensitivity, specificity, and accuracy of the 16 readers were 70.7% (95% confidence interval [CI]: 59.4-79.9), 90.8% (95% CI: 85.6-94.2), and 83.5% (95% CI: 78.6-87.4), respectively. After training, significant improvements in specificity (95.2%; 95% CI: 90.8-97.5; P = 0.001) and accuracy (85.9%; 95% CI: 80.9-89.8; P = 0.01) were observed, but no difference in sensitivity (69.8%; 95% CI: 58.1-79.4; P = 0.58) was observed. Regarding inter-reader agreement, the κ values were 0.57 (95% CI: 0.52-0.63) before training and 0.68 (95% CI: 0.62-0.74) after training, with a difference of 0.11 (95% CI: 0.02-0.18; P = 0.01). The ICC was 0.73 (95% CI: 0.69-0.74) before training and 0.79 (95% CI: 0.76-0.80) after training (P = 0.002). Conclusion: Brief reader training improved the performance and agreement of interpretations by breast radiologists using unenhanced MRI with DWI.

• 대한영상의학회지
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• 제83권2호
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• pp.284-292
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• 2022

급변하고 있는 의료환경에서 전공의에게 양질의 수련을 제공하기 위해 연차별 수련교과과정을 역량 중심으로 개선하고, 수련병원이 수련에 적합한 환경을 유지하도록 하는 것은 매우 중요하다. 대한영상의학회는 그동안 수련체계 개선을 꾸준히 진행해 왔고, 전공의 역량평가와 지도전문의의 내용을 강화하여 역량 중심 전공의 수련체계 개선을 제시하였다. 현재 대한 영상의학회는 2021년 7월 제2차 연차별 수련교과과정 체계화 구축 사업에 선정되어 구축 사업을 추진하고 있으며, 구축 사업에서 요구하는 위임가능 전문직무와 핵심역량 평가항목 및 평가 가이드라인을 개발하였다. 이에 대한 개발과정과 평가항목 및 평가 가이드라인을 소개하여 전공의와 지도전문의들에게 정보를 제공하고자 한다.

• Korean Journal of Radiology
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• 제22권3호
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• pp.415-424
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• 2021

Objective: To determine whether noncontrast computed tomography (NCCT) models based on multivariable, radiomics features, and machine learning (ML) algorithms could further improve the discrimination of early hematoma expansion (HE) in patients with spontaneous intracerebral hemorrhage (sICH). Materials and Methods: We retrospectively reviewed 261 patients with sICH who underwent initial NCCT within 6 hours of ictus and follow-up CT within 24 hours after initial NCCT, between April 2011 and March 2019. The clinical characteristics, imaging signs and radiomics features extracted from the initial NCCT images were used to construct models to discriminate early HE. A clinical-radiologic model was constructed using a multivariate logistic regression (LR) analysis. Radiomics models, a radiomics-radiologic model, and a combined model were constructed in the training cohort (n = 182) and independently verified in the validation cohort (n = 79). Receiver operating characteristic analysis and the area under the curve (AUC) were used to evaluate the discriminative power. Results: The AUC of the clinical-radiologic model for discriminating early HE was 0.766. The AUCs of the radiomics model for discriminating early HE built using the LR algorithm in the training and validation cohorts were 0.926 and 0.850, respectively. The AUCs of the radiomics-radiologic model in the training and validation cohorts were 0.946 and 0.867, respectively. The AUCs of the combined model in the training and validation cohorts were 0.960 and 0.867, respectively. Conclusion: NCCT models based on multivariable, radiomics features and ML algorithm could improve the discrimination of early HE. The combined model was the best recommended model to identify sICH patients at risk of early HE.

• Korean Journal of Radiology
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• 제24권11호
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• pp.1043-1045
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• 2023

• Korean Journal of Radiology
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• 제24권5호
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• pp.478-479
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• 2023

• Korean Journal of Radiology
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• 제20권1호
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• pp.166-170
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• 2019

Objective: To establish a cost-effective and easily available phantom for training residents in ultrasound-guided fine needle thyroid nodule targeting punctures. Materials and Methods: Tofu, drinking straws filled with coupling gel, a urine tube, and 21-gauge needles were used to generate a phantom thyroid with nodules for training. Twelve radiology residents were involved in the study. The puncture success rates were recorded and compared before and after phantom training using the Wilcoxon signed-rank test. Results: On ultrasonography, tofu mimicked the texture of the thyroid. Drinking straws filled with coupling gel mimicked vessels. The urine tube filled with air mimicked the trachea, and 21-gauge needles mimicked small nodules in the transverse section. The entire phantom was similar to the structure of the thyroid and surrounding tissues. The puncture success rates of radiology residents were significantly increased from 34.4 ± 14.2% to 66.7 ± 19.5% after training (p = 0.003). The phantom was constructed in approximately 10 minutes and materials cost less than CNY 10 (approximately $ 1.5) at a local store. Conclusion: The tofu model was cost-effective, easily attainable, and effective for training residents in ultrasound-guided fine needle thyroid nodule targeting punctures in vitro.

• 한국방사선학회논문지
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• 제6권4호
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• pp.291-298
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• 2012

방사선(학)과는 학생들의 실무적응과 진료기술의 수용을 도모하고자 병원 임상실습교육을 실시하고 있다. 그러나 임상실습현장에서 낯선 환경과 진료업무를 체험함으로써 많은 학생들이 복합적이고 다양한 스트레스를 경험하고 있다. 때로는 실습의 부담감과 전공에 대한 회의로 이어져 실습교육에 부정적인 결과를 초래할 수도 있다. 이에 방사선(학)과 학생들의 임상실습 시 경험할 수 있는 스트레스에 대해 그 요인들을 파악하고자 전국 3년제 4년제 대학 중 6개 대학의 방사선(학)과 재학생을 대상으로 2011년 9월 15일에서 10월 25일까지 설문조사를 실시하였다. 방사선(학)과 학생들이 임상실습에서 경험하는 스트레스 정도는 비용적인 측면(3.06)과 임상지도자(3.02)에 관련한 영역에서 높게 나타났으며, 이어서 가치와 이상(2.94), 역할과 실습활동(2.93), 실습환경(2.74), 실습생 간 관계(2.64)의 순으로 나타났다. 임상실습 스트레스 요인에 대해 비용적인 측면을 제외한 모든 요인에서 여성이 남성보다 스트레스 수준이 높게 나타났으며(P<.05), BEPSI-K 구분에 따른 스트레스군 간에는 실습환경, 실습생 간 관계, 역할과 실습활동 영역에서 유의한 차이를 나타냈다(P<.01, P<.001, P<.05). 따라서 임상실습에 임하는 학생들의 스트레스가 임상실습의 만족도와 상호 밀접한 상관관계를 가짐을 확인하였다.

• Korean Journal of Radiology
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• 제25권2호
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• pp.126-133
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• 2024

Large language models (LLMs) have revolutionized the global landscape of technology beyond natural language processing. Owing to their extensive pre-training on vast datasets, contemporary LLMs can handle tasks ranging from general functionalities to domain-specific areas, such as radiology, without additional fine-tuning. General-purpose chatbots based on LLMs can optimize the efficiency of radiologists in terms of their professional work and research endeavors. Importantly, these LLMs are on a trajectory of rapid evolution, wherein challenges such as "hallucination," high training cost, and efficiency issues are addressed, along with the inclusion of multimodal inputs. In this review, we aim to offer conceptual knowledge and actionable guidance to radiologists interested in utilizing LLMs through a succinct overview of the topic and a summary of radiology-specific aspects, from the beginning to potential future directions.

• Korean Journal of Radiology
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• 제21권6호
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• pp.670-683
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• 2020

Objective: The presence of coagulative necrosis (CN) in clear cell renal cell carcinoma (ccRCC) indicates a poor prognosis, while the absence of CN indicates a good prognosis. The purpose of this study was to build and validate a radiomics signature based on preoperative CT imaging data to estimate CN status in ccRCC. Materials and Methods: Altogether, 105 patients with pathologically confirmed ccRCC were retrospectively enrolled in this study and then divided into training (n = 72) and validation (n = 33) sets. Thereafter, 385 radiomics features were extracted from the three-dimensional volumes of interest of each tumor, and 10 traditional features were assessed by two experienced radiologists using triple-phase CT-enhanced images. A multivariate logistic regression algorithm was used to build the radiomics score and traditional predictors in the training set, and their performance was assessed and then tested in the validation set. The radiomics signature to distinguish CN status was then developed by incorporating the radiomics score and the selected traditional predictors. The receiver operating characteristic (ROC) curve was plotted to evaluate the predictive performance. Results: The area under the ROC curve (AUC) of the radiomics score, which consisted of 7 radiomics features, was 0.855 in the training set and 0.885 in the validation set. The AUC of the traditional predictor, which consisted of 2 traditional features, was 0.843 in the training set and 0.858 in the validation set. The radiomics signature showed the best performance with an AUC of 0.942 in the training set, which was then confirmed with an AUC of 0.969 in the validation set. Conclusion: The CT-based radiomics signature that incorporated radiomics and traditional features has the potential to be used as a non-invasive tool for preoperative prediction of CN in ccRCC.