• Journal of the Korean Society of Radiology
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• v.15 no.5
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• pp.603-612
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• 2021

The effect of Advanced Modeled Iterative Reconstruction (ADMIRE) on the coronary artery calcium (CAC) score of computed tomography was evaluated. Coronary artery calcium images (348 calcium, 6 groups, total of 2088 calcium) were acquired by 128-slice dual-source CT of 89 patients.Volume score and Agatston score were measured from images reconstructed with filtered back projection (FBP) and ADMIRE (1-5). The difference between FBP and ADMIRE Strength (1-5) was confirmed through the Kruskal-Wallis test, and the post-hoc analysis was performed using the Mann-Whitney U test based on FBP. Both volume score and Agatston score showed statistically significant differences between FBP and ADMIRE (1-5) (P=0.015, P=0.0.38). As a result of post hoc analysis, the volume score decreased to 9.5% in ADMIRE 4 (Z=-2.359, P=0.018) and 13.2% in ADMIRE 5 (Z=-3.113, P=0.002) based on FBP. Agatston score decreased to 10.4% in ADMIRE 4 (Z=-2.051, P=0.040) and 14.0% in ADMIRE 5 (Z=-2.718, P=0.007) based on FBP. High ADMIRE strength affected the volume score and Agatston score due to the decrease in calcium area. In addition, the change in the Density factor due to the decrease in Maximum HU may affect the calculation of the Agatston score.

• Korean Journal of Radiology
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• v.22 no.11
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• pp.1777-1785
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• 2021

Objective: To investigate the accuracy of the Agatston score obtained with the ultra-high-pitch (UHP) acquisition mode using tin-filter spectral shaping (Sn150 kVp) and a kVp-independent reconstruction algorithm to reduce the radiation dose. Materials and Methods: This prospective study included 114 patients (mean ± standard deviation, 60.3 ± 9.8 years; 74 male) who underwent a standard 120 kVp scan and an additional UHP Sn150 kVp scan for coronary artery calcification scoring (CACS). These two datasets were reconstructed using a standard reconstruction algorithm (120 kVp + Qr36d, protocol A; Sn150 kVp + Qr36d, protocol B). In addition, the Sn150 kVp dataset was reconstructed using a kVp-independent reconstruction algorithm (Sn150 kVp + Sa36d, protocol C). The Agatston scores for protocols A and B, as well as protocols A and C, were compared. The agreement between the scores was assessed using the intraclass correlation coefficient (ICC) and the Bland-Altman plot. The radiation doses for the 120 kVp and UHP Sn150 kVp acquisition modes were also compared. Results: No significant difference was observed in the Agatston score for protocols A (median, 63.05; interquartile range [IQR], 0-232.28) and C (median, 60.25; IQR, 0-195.20) (p = 0.060). The mean difference in the Agatston score for protocols A and C was relatively small (-7.82) and with the limits of agreement from -65.20 to 49.56 (ICC = 0.997). The Agatston score for protocol B (median, 34.85; IQR, 0-120.73) was significantly underestimated compared with that for protocol A (p < 0.001). The UHP Sn150 kVp mode facilitated an effective radiation dose reduction by approximately 30% (0.58 vs. 0.82 mSv, p < 0.001) from that associated with the standard 120 kVp mode. Conclusion: The Agatston scores for CACS with the UHP Sn150 kVp mode with a kVp-independent reconstruction algorithm and the standard 120 kVp demonstrated excellent agreement with a small mean difference and narrow agreement limits. The UHP Sn150 kVp mode allowed a significant reduction in the radiation dose.

• 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 Society of Radiology
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• v.10 no.4
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• pp.285-290
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• 2016

The purpose of our study was to retrospectively evaluate the cause of a decreased calcium score of follow-up studies on coronary artery calcium scores (CACs) computed tomography (CT). The subjects were healthy 100 people(85 males $60.6{\pm}6.9$ years, 15 females $67.2{\pm}7.3$ years). The subjects decreased CACs were divided into 4 subgroups depending on Agatston classification, minimal (1-10), mild (11-100), moderate (101-400), severe (400<). As a result of decreased CACs were scan location disagreement 51%, motion artifact 26%, equipment changes 14%, operator mistakes 5%, input miss 2%, image loss 1%, arrhythmia 1%. In the mild group, the most common decreased CACs were 49 people. In the minimal group, the most significant variation reduction has occurred to 6 people. Scan location disagreement was considered a partial volume effects due to the scan starting position. It showed less than 100 CACs a high variation (19.7%) in more than 100 CACs, a lower variation (2.2%), these could be seen that the variation range is different that can be tolerated according to the calcification score. Motion artifact factor was found in 26%, which is so closely related to the preceding tests that affect the higher heart rate like this pulmonary function test, exercise stress test.

• Korean Journal of Radiology
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• v.24 no.4
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• pp.284-293
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• 2023

Objective: To validate a simplified ordinal scoring method, referred to as modified length-based grading, for assessing coronary artery calcium (CAC) severity on non-electrocardiogram (ECG)-gated chest computed tomography (CT). Materials and Methods: This retrospective study enrolled 120 patients (mean age ± standard deviation [SD], 63.1 ± 14.5 years; male, 64) who underwent both non-ECG-gated chest CT and ECG-gated cardiac CT between January 2011 and December 2021. Six radiologists independently assessed CAC severity on chest CT using two scoring methods (visual assessment and modified length-based grading) and categorized the results as none, mild, moderate, or severe. The CAC category on cardiac CT assessed using the Agatston score was used as the reference standard. Agreement among the six observers for CAC category classification was assessed using Fleiss kappa statistics. Agreement between CAC categories on chest CT obtained using either method and the Agatston score categories on cardiac CT was assessed using Cohen's kappa. The time taken to evaluate CAC grading was compared between the observers and two grading methods. Results: For differentiation of the four CAC categories, interobserver agreement was moderate for visual assessment (Fleiss kappa, 0.553 [95% confidence interval {CI}: 0.496-0.610]) and good for modified length-based grading (Fleiss kappa, 0.695 [95% CI: 0.636-0.754]). The modified length-based grading demonstrated better agreement with the reference standard categorization with cardiac CT than visual assessment (Cohen's kappa, 0.565 [95% CI: 0.511-0.619 for visual assessment vs. 0.695 [95% CI: 0.638-0.752] for modified length-based grading). The overall time for evaluating CAC grading was slightly shorter in visual assessment (mean ± SD, 41.8 ± 38.9 s) than in modified length-based grading (43.5 ± 33.2 s) (P < 0.001). Conclusion: The modified length-based grading worked well for evaluating CAC on non-ECG-gated chest CT with better interobserver agreement and agreement with cardiac CT than visual assessment.

• Journal of radiological science and technology
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• v.40 no.2
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• pp.253-259
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• 2017

The study examines changes in calcium volume on born by comparing two figures; one is measured by dual energy computed tomography(DECT) followed by applying variation in monochromatic energy selection(keV), material decomposition(MD), and material suppressed iodine(MSI) analysis, and the other is measured by conventional single source computed tomography(CSCT). For this study, based on CSCT images taken by using human mimicked phantom, 70, 100, 140 keV and MSI, MD material calcium weighting(MCW) and MD material iodine weighting(MIW) of DECT were applied respectively. Then calculated calcium volume was converted to Agatston score for comparison. Volume of human mimicked phantom was in inverse proportion to keV. The volume decreased while keV increased(p<0.05). The most similar DECT volumes were reconstructed at 70 keV, the difference was showed $35.8{\pm}12.2$ for rib, femur ($16.1{\pm}24.1$), pelvis($13.7{\pm}18.8$), and spine($179.0{\pm}61.8$). However, the volume of MSI was down for each organ; the volume of rib was 5.55%, femur(76.34%), pelvis(55.16%) and spine(87.58%). The volume of MSI decreased 55.9% for rib, femur(80.7%), pelvis(69.6%) and spine(54.2%) while MD MIW reduced for rib(83.51%), femur(87.68%), pelvis(86.64%), and spine(82.62%). With the results, the study found that outcomes were affected by the method which examiners employed. When using DECT, calcium volume of born dropped with keV increased. It also found that the most similar DECT images were reconstructed at 70 keV. The results of experiments implied that the users of MSI and MD should be cautious of errors as there are big differences in scores between those two methods.

• Journal of the Korean Society of Radiology
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• v.82 no.6
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• pp.1493-1504
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• 2021

Purpose This study aimed to evaluate the utility of the 16-cm axial volume scan technique for calculating the coronary artery calcium score (CACS) using non-enhanced chest CT. Materials and Methods This study prospectively enrolled 20 participants who underwent both, non-enhanced chest CT (16-cm-coverage axial volume scan technique) and calcium-score CT, with the same parameters, differing only in slice thickness (in non-enhanced chest CT = 0.625, 1.25, 2.5 mm; in calcium score CT = 2.5 mm). The CACS was calculated using the conventional Agatston method. The difference between the CACS obtained from the two CT scans was compared, and the degree of agreement for the clinical significance of the CACS was confirmed through sectional analysis. Each calcified lesion was classified by location and size, and a one-to-one comparison of non-contrast-enhanced chest CT and calcium score CT was performed. Results The correlation coefficients of the CACS obtained from the two CT scans for slice thickness of 2.5, 1.25, and 0.625 mm were 0.9850, 0.9688, and 0.9834, respectively. The mean differences between the CACS were -21.4% at 0.625 mm, -39.4% at 1.25 mm, and -76.2% at 2.5 mm slice thicknesses. Sectional analysis revealed that 16 (80%), 16 (80%), and 13 (65%) patients showed agreement for the degree of coronary artery disease at each slice interval, respectively. Inter-reader agreement was high for each slice interval. The 0.625 mm CT showed the highest sensitivity for detecting calcified lesions. Conclusion The values in the non-contrast-enhanced chest CT, using the 16-cm axial volume scan technique, were similar to those obtained using the CACS in the calcium score CT, at 0.625 mm slice thickness without electrocardiogram gating. This can ultimately help predict cardiovascular risk without additional radiation exposure.

• Korean Journal of Radiology
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• v.20 no.4
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• pp.631-640
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• 2019

Objective: To evaluate the value of airway computed tomography (CT) in patients with obstructive sleep apnea (OSA) as a predictor of cerebrocardiovascular disease (CCVD) clinically, by quantitatively analyzing carotid arterial calcification (CarAC). Materials and Methods: This study included 287 patients aged 40-80 years, who had undergone both polysomnography (PSG) and airway CT between March 2011 and October 2015. The carotid arterial calcium score (CarACS) was quantified using the modified Agatston method on each upper airway CT. The OSA severity was categorized as normal, mild, moderate, and severe using the PSG results. Clinical characteristics, comorbid diseases, and lipid profiles of all patients were analyzed, and the prevalence of CCVDs was investigated during the follow up period (52.2 ± 16.0 months). Results: CCVD occurred in 27 patients (9.3%) at the end of follow-up, and the CCVD-present groups showed a significantly older mean age (57.5 years vs. 54.2 years), higher prevalence of hypertension (59% vs. 34%) and CarAC (51.9% vs. 20.8%), whereas sex, other comorbid diseases, and severity of OSA were not significantly different from the CCVD-absent group. A univariate analysis showed that age, hypertension, incidence of CarAC, and CarACS were risk factors for the occurrence of CCVD events. In a multivariate analysis, the incidence of CarAC was the only independent risk factor for CCVD. Conclusion: CarAC is an independent risk factor for CCVD, whereas the severity of OSA is not a contributory risk factor in patients with OSA. Therefore, additional analysis of CarACS based on airway CT scans may be useful for predicting CCVD.