• Journal of the Korean Society of Radiology
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• v.82 no.5
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• pp.1163-1185
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• 2021

Sudden cardiac death is an unexpected death originating from the heart that occurs within an hour of the onset of symptoms. The main cause of sudden cardiac death is arrhythmia; however, diagnosing underlying structural heart disease significantly contributes to predicting the long-term risk. Cardiovascular CT and MR provide important information for diagnosing and evaluating structural heart disease, enabling the prediction and preparation of the risk of sudden cardiac death. Therefore, we would like to focus on the various structural heart diseases that increase the risk of clinically-important sudden cardiac death and the importance of imaging findings.

• Korean Journal of Radiology
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• v.22 no.3
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• pp.308-323
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• 2021

An increasing number of adult congenital heart disease (ACHD) patients continue to require life-long diagnostic imaging surveillance using cardiac CT and MRI. These patients typically exhibit a large spectrum of unique anatomical and functional changes resulting from either single- or multi-stage palliation and surgical correction. Radiologists involved in the diagnostic task of monitoring treatment effects and detecting potential complications should be familiar with common cardiac CT and MRI findings observed in patients with repaired complex ACHD. This review article highlights the contemporary role of CT and MRI in three commonly encountered repaired ACHD: repaired tetralogy of Fallot, transposition of the great arteries after arterial switch operation, and functional single ventricle after Fontan operation.

• The Journal of the Korea Contents Association
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• v.9 no.12
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• pp.339-347
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• 2009

Purpose : This study was to investigate the influence of heart rate and coronary calcification on diagnostic accuracy of 64-slice multidetector CT(MDCT) in coronary artery disease. Methods : 178 patients(84 men, 94 women) undergoing cardiac CT were included in this study. 3 coronary arteries(LAD, LCX, RCA) were assessed the presence of significant stenosis($\geq50%$) and the results compared with those of coronary angiography. Results : On a patient-based analysis, the diagnostic accuracy of 64-slice MDCT was 96.6%. The diagnostic accuracy on left anterior descending, left circumflex, right coronary artery were 86.5%, 84.3%, 92.1% respectively. Body mass index and blood pressure were not influenced on diagnostic accuracy of 64-slice MDCT. In less than 60/min of heart rate, accuracy was 90.1% and $\kappa$ value was 0.78. While in more than 70/min of heart rate, accuracy was 75.8% and $\kappa$ value was 0.52. In less than 100 of coronary calcification, accuracy was 91.3% and $\kappa$ value was 0.81. While in more than 400, accuracy was 68.6% and $\kappa$ value was 0.33. Conclusion : 64-slice MDCT shows similar diagnostic accuracy as coronary angiography. But in the context of more than 70/min of heart rate and 400 of coronary calcification, diagnostic accuracy was decreased. So there needs to identify heart rate and coronary calcification in cardiac CT, and if heart rate shows more than 70/min, use beta-blocker to regulate it.

• Journal of the Korean Society of Radiology
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• v.83 no.1
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• pp.3-27
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• 2022

Cardiac CT has been proven to provide diagnostic and prognostic evaluation of coronary artery disease for cardiovascular risk stratification and treatment decision-making based on rapid technological development and various research evidence. Coronary CT angiography has emerged as a gateway test for coronary artery disease that can reduce invasive angiography due to its high negative predictive value, but the diagnostic specificity is relatively low. However, coronary CT angiography is likely to overcome its limitations through functional evaluation to identify the hemodynamic significance of coronary artery disease by analyzing myocardial perfusion and fractional flow reserve through cardiac CT. Recently, studies have been actively conducted to incorporate artificial intelligence to make this more objective and reproducible. In this review, functional imaging techniques of cardiac computerized tomography are explored.

• Journal of the Korean Society of Radiology
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• v.13 no.5
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• pp.683-689
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• 2019

We are trying to evaluate usefulness of Wide Coverage Volume Axial Mode by comparing and analyzing for exposure doses to patients and video quality extracted from two materials. First material is a computer tomography scanning of paediatric cardiac made by using High Pitch Mode, which is designed for diagnosing Congenital cardiac diseases. Second material is computer tomography scanning of paediatric cardiac made by using Wide Coverage Volume Axial Mode. When we did computer tomography scanning of paediatric cardiac, we used High Pitch Mode and Wide Coverage Volume Axial Mode to 50 patients of each, overall 100 patients. Also, we compared exposure doses to patients using videos got from each protocol. Then we compared video quality by calculating SNR and CNR by setting ROI of each. Not only exposure doses to patients were reduced by 13.07 %, but also SNR and CNR were improved when testing used Wide Coverage Volume Axial Mode rather than using High Pitch Mode. Wide Coverage Volume Axial Mode reduced testing time by using high-speed scanner. Furthermore, we can find out that Wide Coverage Volume Axial Mode is an useful method through improving video quality and reducing exposure doses to patients than using High Pitch Mode from ASiR-V, which is low-dose technology.

• Tuberculosis and Respiratory Diseases
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• v.56 no.2
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• pp.127-143
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• 2004

Computed tomography (CT) plays an important supplementary role in the evaluation of patients with heart disease. CT can be used to evaluate the aorta, pulmonary artery, pulmonary vein, cardiac chambers, coronary artery, valves and systemic veins (superior vena cava, inferior vena cava and hepatic veins). The "Learning Objectives" describe the normal anatomy and typical pathological conditions seen on axial scans and reformatted images from CT in patients with heart disease, focusing focus on frequent, fatal, and rare but characteristic diseases encountered in routine practice.

• Korean Journal of Radiology
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• v.22 no.10
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• pp.1597-1608
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• 2021

Cardiovascular computed tomography (CT) is among the most active fields with ongoing technical innovation related to image acquisition and analysis. Artificial intelligence can be incorporated into various clinical applications of cardiovascular CT, including imaging of the heart valves and coronary arteries, as well as imaging to evaluate myocardial function and congenital heart disease. This review summarizes the latest research on the application of deep learning to cardiovascular CT. The areas covered range from image quality improvement to automatic analysis of CT images, including methods such as calcium scoring, image segmentation, and coronary artery evaluation.

• Korean Journal of Radiology
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• v.22 no.9
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• pp.1441-1450
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• 2021

Anomalous origin of the coronary artery from the pulmonary artery is a rare and potentially fatal congenital heart defect. Up to 90% of infants with an anomaly involving the left coronary artery die within the first year of life if left untreated. Patients who survive beyond infancy are at risk of sudden cardiac death. Cardiac CT and MRI are increasingly being used for the accurate diagnosis of this anomaly for prompt surgical restoration of the dual coronary artery system. Moreover, life-long imaging surveillance after surgery is necessary for these patients. In this pictorial review, multimodal cardiac imaging findings of this rare and potentially fatal coronary artery anomaly are comprehensively discussed, and representative images are provided to facilitate the understanding of this anomaly.

• Journal of the Korean Society of Radiology
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• v.81 no.5
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• pp.1151-1163
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• 2020

Purpose This study aimed to evaluate changes of subprosthetic pannus on cardiac CT and determine its relationship to echocardiographic findings in patients with mechanical aortic valve replacement (AVR). Materials and Methods Between April 2011 and November 2017, 17 AVR patients (56.8 ± 8.9 years, 12% male) who showed pannus formation on CT and had undergone both follow-up CT and echocardiography were included. The mean interval from AVR to the date of pannus detection was 10.5 ± 7.1 years. In the initial and follow-up CT and echocardiography, the pannus extent and echocardiographic parameters were compared using paired t-tests. The relationship between the opening angle of the prosthetic valve and the pannus extent was evaluated using Pearson correlation analysis. Results The pannus extent was significantly increased on CT (p < 0.05). The peak velocity (3.9 ± 0.8 m/s vs. 4.2 ± 0.8 m/s, p = 0.03) and mean pressure gradient (36.4 ± 15.5 mm Hg vs. 42.1 ± 15.8 mm Hg, p = 0.03) were significantly increased. The mean opening angles of the mechanical aortic leaflets were slightly decreased, but there was no statistical significance (73.1 ± 8.3° vs. 69.4 ± 12.1°, p = 0.12). The opening angle of the prosthetic leaflets was inversely correlated with the pannus extent (r = -0.57, p < 0.001). Conclusion The pannus extent increases over time, increasing transvalvular peak velocity and the pressure gradient. CT can be used to evaluate the pannus extent associated with hemodynamic changes that need to be managed by surgical intervention.

• 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.