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Conventional Versus Artificial Intelligence-Assisted Interpretation of Chest Radiographs in Patients With Acute Respiratory Symptoms in Emergency Department: A Pragmatic Randomized Clinical Trial

Hwang EJ, Goo JM, Nam JG, Park CM, Hong KJ, Kim KH

Objective: It is unknown whether artificial intelligence-based computer-aided detection (AI-CAD) can enhance the accuracy of chest radiograph (CR) interpretation in real-world clinical practice. We aimed to compare the accuracy of...
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Tissue Adequacy and Safety of Percutaneous Transthoracic Needle Biopsy for Molecular Analysis in Non-Small Cell Lung Cancer: A Systematic Review and Meta-analysis

Nam BD, Yoon SH, Hong H, Hwang JH, Goo JM, Park S

Objective: We conducted a systematic review and meta-analysis of the tissue adequacy and complication rates of percutaneous transthoracic needle biopsy (PTNB) for molecular analysis in patients with non-small cell lung...
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CT Examinations for COVID-19: A Systematic Review of Protocols, Radiation Dose, and Numbers Needed to Diagnose and Predict

Lee JH, Hong H, Kim H, Lee CH, Goo JM, Yoon SH

Purpose Although chest CT has been discussed as a first-line test for coronavirus disease 2019 (COVID-19), little research has explored the implications of CT exposure in the population. To review...
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Use of Artificial Intelligence-Based Software as Medical Devices for Chest Radiography: A Position Paper from the Korean Society of Thoracic Radiology

Eui Jin EJ, Goo JM, Yoon SH, Beck KS, Seo JB, Choi BW, Chung MJ, Park CM, Jin KN, Lee SM

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Cone-Beam CT-Guided Percutaneous Transthoracic Needle Lung Biopsy of Juxtaphrenic Lesions: Diagnostic Accuracy and Complications

Hong W, Yoon SH, Goo JM, Park CM

Objective: To investigate the diagnostic accuracy and complications of cone-beam CT-guided percutaneous transthoracic needle biopsy (PTNB) of juxtaphrenic lesions and identify the risk factors for diagnostic failure and complications. Materials and...
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Automated Lung Segmentation on Chest Computed Tomography Images with Extensive Lung Parenchymal Abnormalities Using a Deep Neural Network

Yoo SJ, Yoon SH, Lee JH, Kim KH, Choi HI, Park SJ, Goo JM

Objective: We aimed to develop a deep neural network for segmenting lung parenchyma with extensive pathological conditions on non-contrast chest computed tomography (CT) images. Materials and Methods: Thin-section non-contrast chest CT...
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Volume and Mass Doubling Time of Lung Adenocarcinoma according to WHO Histologic Classification

Hong JH, Park S, Kim H, Goo JM, Park IK, Kang CH, Kim YT, Yoon SH

Objective: This study aimed to evaluate the tumor doubling time of invasive lung adenocarcinoma according to the International Association of the Study for Lung Cancer (IASLC)/American Thoracic Society (ATS)/European Respiratory...
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Interstitial Lung Abnormalities: What Radiologists Should Know

Chae KJ, Jin GY, Goo JM, Chung MJ

Interstitial lung abnormalities (ILAs) are radiologic abnormalities found incidentally on chest CT that are potentially related to interstitial lung diseases. Several articles have reported that ILAs are associated with increased...
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Role of Chest Radiographs and CT Scans and the Application of Artificial Intelligence in Coronavirus Disease 2019

Yoo SJ, Goo JM, Yoon SH

Coronavirus disease (COVID-19) has threatened public health as a global pandemic. Chest CT and radiography are crucial in managing COVID-19 in addition to reverse transcription-polymerase chain reaction, which is the...
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Implementation of a Deep Learning-Based ComputerAided Detection System for the Interpretation of Chest Radiographs in Patients Suspected for COVID-19

Hwang EJ, Kim H, Yoon SH, Goo JM, Park CM

Objective: To describe the experience of implementing a deep learning-based computer-aided detection (CAD) system for the interpretation of chest X-ray radiographs (CXR) of suspected coronavirus disease (COVID-19) patients and investigate...
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Development of Protocol for Korean Lung Cancer Screening Project (K-LUCAS) to Evaluate Effectiveness and Feasibility to Implement National Cancer Screening Program

Lee J, Lim J, Kim Y, Kim HY, Goo JM, Lee CT, Jang SH, Lee WC, Lee CW, An JY, Ko KD, Lee MK, Choi KS, Park B, Lee DH

PURPOSE: To reduce lung cancer mortality, lung cancer screening was recommended using low-dose computed tomography (LDCT) to high-risk population. A protocol for multicenter lung cancer screening pilot project was developed...
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Risk Prediction Model for Lung Cancer Screening

Kim TJ, Kim HY, Goo JM, Sun JS

Lung cancer screening in high-risk subjects using low-dose CT can reduce mortality by 20%. Current evidence suggests that the development of a risk prediction model for lung cancer is one...
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Lung Cancer Screening with Low-Dose CT: Current Status in Other Countries

Goo JM

Lung cancer is the leading cause of death from cancer worldwide. The most effective way to reduce lung cancer mortality is early detection and treatment. Two large randomized controlled trials...
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Significant Abnormalities Other than Lung Cancer in Korean Lung Cancer CT Screening

Yoon SH, Hong J, Hwang EJ, Kim H, Lim HJ, Suh YJ, Kim HY, Goo JM

A low-dose chest CT is performed for early detection of lung cancer, but the CT scan frequently shows several incidental abnormalities. Identification of the incidental findings may enable early detection...
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Preface for Special Issue on Update of Lung Cancer Screening with Low-Dose CT

Goo JM

No abstract available.
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Quantitative Thoracic Magnetic Resonance Criteria for the Differentiation of Cysts from Solid Masses in the Anterior Mediastinum

Hwang EJ, Paek M, Yoon SH, Kim J, Lee HY, Goo JM, Kim H, Kim H, Ackman JB

OBJECTIVE: To evaluate quantitative magnetic resonance imaging (MRI) parameters for differentiation of cysts from and solid masses in the anterior mediastinum. MATERIALS AND METHODS: The development dataset included 18 patients from...
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Learning Curve of C-Arm Cone-beam Computed Tomography Virtual Navigation-Guided Percutaneous Transthoracic Needle Biopsy

Ahn SY, Park CM, Yoon SH, Kim H, Goo JM

OBJECTIVE: To evaluate the learning curve for C-arm cone-beam computed tomography (CBCT) virtual navigation-guided percutaneous transthoracic needle biopsy (PTNB) and to determine the amount of experience needed to develop appropriate...
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Distinguishing between Thymic Epithelial Tumors and Benign Cysts via Computed Tomography

Lee SH, Yoon SH, Nam JG, Kim HJ, Ahn SY, Kim HK, Lee HJ, Lee HH, Cheon GJ, Goo JM

OBJECTIVE: To investigate whether computed tomography (CT) and fluorine-18-labeled fluoro-2-deoxy-D-glucose (FDG) positron emission tomography (PET) may be applied to distinguish thymic epithelial tumors (TETs) from benign cysts in the anterior...
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Size-Specific Dose Estimation In the Korean Lung Cancer Screening Project: Does a 32-cm Diameter Phantom Represent a Standard-Sized Patient in Korean Population?

Kim EY, Kim TJ, Goo JM, Kim HY, Lee JW, Lee S, Lim JT, Kim Y

OBJECTIVE: The purposes of this study were to evaluate size-specific dose estimate (SSDE) of low-dose CT (LDCT) in the Korean Lung Cancer Screening (K-LUCAS) project and to determine whether CT...
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Open Bronchus Sign on CT: A Risk Factor for Hemoptysis after Percutaneous Transthoracic Biopsy

Kim H, Park CM, Yoon SH, Hwang EJ, Lee JH, Ahn SY, Goo JM

OBJECTIVE: We hypothesized that open bronchi within target pulmonary lesions are associated with percutaneous transthoracic needle biopsy (PTNB)-related hemoptysis. We sought to analyze and compare patient characteristics and target features...
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