Feasibility of the Threshold-Based Quantification of Myocardial Fibrosis on Cardiac CT as a Prognostic Marker in Nonischemic Dilated Cardiomyopathy.

OBJECTIVE: This study investigated the feasibility and prognostic relevance of threshold-based quantification of myocardial delayed enhancement (MDE) on CT in patients with nonischemic dilated cardiomyopathy (NIDCM). MATERIALS AND METHODS: Forty-three patients with NIDCM (59.3 ± 17.1 years; 21 male) were included in the study and underwent cardiac CT and MRI. MDE was quantified manually and with a threshold-based quantification method using cutoffs of 2, 3, and 4 standard deviations (SDs) on three sets of CT images (100 kVp, 120 kVp, and 70 keV). Interobserver agreement in MDE quantification was assessed using the intraclass correlation coefficient (ICC). Agreement between CT and MRI was evaluated using the Bland-Altman method and the concordance correlation coefficient (CCC). Patients were followed up for the subsequent occurrence of the primary composite outcome, including cardiac death, heart transplantation, heart failure hospitalization, or appropriate use of an implantable cardioverter-defibrillator. The Kaplan-Meier method was used to estimate event-free survival according to MDE levels. RESULTS: Late gadolinium enhancement (LGE) was observed in 29 patients (67%, 29/43), and the mean LGE found with the 5-SD threshold was 4.1% ± 3.6%. The 4-SD threshold on 70-keV CT showed excellent interobserver agreement (ICC = 0.810) and the highest concordance with MRI (CCC = 0.803). This method also yielded the smallest bias with the narrowest range of 95% limits of agreement compared to MRI (bias, -0.119%; 95% limits of agreement, -4.216% to 3.978%). During a median follow-up of 1625 days (interquartile range, 712-1430 days), 10 patients (23%, 10/43) experienced the primary composite outcome. Event-free survival significantly differed between risk subgroups divided by the optimal MDE cutoff of 4.3% (log-rank P = 0.005). CONCLUSION: The 4-SD threshold on 70-keV monochromatic CT yielded results comparable to those of MRI for quantifying MDE as a marker of myocardial fibrosis, which showed prognostic value in patients with NIDCM.

Radiation dose reduction using deep learning-based image reconstruction for a low-dose chest computed tomography protocol: a phantom study.

Background: The aim of this study was to compare the dose reduction potential and image quality of deep learning-based image reconstruction (DLIR) with those of filtered back-projection (FBP) and iterative reconstruction (IR) and to determine the clinically usable dose of DLIR for low-dose chest computed tomography (LDCT) scans. Methods: Multi-slice computed tomography (CT) scans of a chest phantom were performed with various tube voltages and tube currents, and the images were reconstructed using seven methods to control the amount of noise reduction: FBP, three stages of IR, and three stages of DLIR. For subjective image analysis, four radiologists compared 48 image data sets with reference images and rated on a 5-point scale. For quantitative image analysis, the signal to noise ratio (SNR), contrast to noise ratio (CNR), nodule volume, and nodule diameter were measured. Results: In the subjective analysis, DLIR-Low (0.46 mGy), DLIR-Medium (0.31 mGy), and DLIR-High (0.18 mGy) images showed similar quality to the FBP (2.47 mGy) image. Under the same dose conditions, the SNR and CNR were higher with DLIR-High than with FBP and all the IR methods (all P<0.05). The nodule volume and size with DLIR-High were significantly closer to the real volume than with FBP and all the IR methods (all P<0.001). Conclusions: DLIR can improve the image quality of LDCT compared to FBP and IR. In addition, the appropriate effective dose for LDCT would be 0.24 mGy with DLIR-High.

Comparison of Coronary Computed Tomography Angiography Image Quality With High-concentration and Low-concentration Contrast Agents: The Randomized CONCENTRATE Trial.

PURPOSE: To confirm that the image quality of coronary computed tomography (CT) angiography with a low tube voltage (80 to 100 kVp), iterative reconstruction, and low-concentration contrast agents (iodixanol 270 to 320 mgI/mL) was not inferior to that with conventional high tube voltage (120 kVp) and high-concentration contrast agent (iopamidol 370 mgI/mL). MATERIALS AND METHODS: This prospective, multicenter, noninferiority, randomized trial enrolled a total of 318 patients from 8 clinical sites. All patients were randomly assigned 1: 1: 1 for each contrast medium of 270, 320, and 370 mgI/mL. CT scans were taken with a standard protocol in the high-concentration group (370 mgI/mL) and with 20 kVp lower protocol in the low-concentration group (270 or 320 mgI/mL). Image quality and radiation dose were compared between the groups. Image quality was evaluated with a score of 1 to 4 as subject image quality. RESULTS: The mean HU, signal-to-noise ratio, and contrast-to-noise ratio of the 3 groups were significantly different (all P<0.0001). The signal-to-noise ratio and contrast-to-noise ratio of the low-concentration groups were significantly lower than those of the high-concentration group (P<0.05). However, the image quality scores were not significantly different among the 3 groups (P=0.745). The dose length product and effective dose of the high-concentration group were significantly higher than those of the low-concentration group (P<0.0001 and 0.003, respectively). CONCLUSIONS: The CT protocol with iterative reconstruction and lower tube voltage for low-concentration contrast agents significantly reduced the effective radiation dose (mean: 3.7±2.7 to 4.1±3.1 mSv) while keeping the subjective image quality as good as the standard protocol (mean: 5.7±3.4 mSv).

Development and Validation of a Deep Learning-Based Synthetic Bone-Suppressed Model for Pulmonary Nodule Detection in Chest Radiographs.

Importance: Dual-energy chest radiography exhibits better sensitivity than single-energy chest radiography, partly due to its ability to remove overlying anatomical structures. Objectives: To develop and validate a deep learning-based synthetic bone-suppressed (DLBS) nodule-detection algorithm for pulmonary nodule detection on chest radiographs. Design, Setting, and Participants: This decision analytical modeling study used data from 3 centers between November 2015 and July 2019 from 1449 patients. The DLBS nodule-detection algorithm was trained using single-center data (institute 1) of 998 chest radiographs. The DLBS algorithm was validated using 2 external data sets (institute 2, 246 patients; and institute 3, 205 patients). Statistical analysis was performed from March to December 2021. Exposures: DLBS nodule-detection algorithm. Main Outcomes and Measures: The nodule-detection performance of DLBS model was compared with the convolution neural network nodule-detection algorithm (original model). Reader performance testing was conducted by 3 thoracic radiologists assisted by the DLBS algorithm or not. Sensitivity and false-positive markings per image (FPPI) were compared. Results: Training data consisted of 998 patients (539 men [54.0%]; mean [SD] age, 54.2 [9.82] years), and 2 external validation data sets consisted of 246 patients (133 men [54.1%]; mean [SD] age, 55.3 [8.7] years) and 205 patients (105 men [51.2%]; mean [SD] age, 51.8 [9.1] years). Using the external validation data set of institute 2, the bone-suppressed model showed higher sensitivity compared with that of the original model for nodule detection (91.5% [109 of 119] vs 79.8% [95 of 119]; P < .001). The overall mean of FPPI with the bone-suppressed model was reduced compared with the original model (0.07 [17 of 246] vs 0.09 [23 of 246]; P < .001). For the observer performance testing with the data of institute 3, the mean sensitivity of 3 radiologists was 77.5% (95% [CI], 69.9%-85.2%), whereas that of radiologists assisted by DLBS modeling was 92.1% (95% CI, 86.3%-97.3%; P < .001). The 3 radiologists had a reduced number of FPPI when assisted by the DLBS model (0.071 [95% CI, 0.041-0.111] vs 0.151 [95% CI, 0.111-0.210]; P < .001). Conclusions and Relevance: This decision analytical modeling study found that the DLBS model was more sensitive to detecting pulmonary nodules on chest radiographs compared with the original model. These findings suggest that the DLBS model could be beneficial to radiologists in the detection of lung nodules in chest radiographs without need of the specialized equipment or increase of radiation dose.

Detection of acute thoracic aortic dissection based on plain chest radiography and a residual neural network (Resnet).

Acute thoracic aortic dissection is a life-threatening disease, in which blood leaking from the damaged inner layer of the aorta causes dissection between the intimal and adventitial layers. The diagnosis of this disease is challenging. Chest x-rays are usually performed for initial screening or diagnosis, but the diagnostic accuracy of this method is not high. Recently, deep learning has been successfully applied in multiple medical image analysis tasks. In this paper, we attempt to increase the accuracy of diagnosis of acute thoracic aortic dissection based on chest x-rays by applying deep learning techniques. In aggregate, 3,331 images, comprising 716 positive images and 2615 negative images, were collected from 3,331 patients. Residual neural network 18 was used to detect acute thoracic aortic dissection. The diagnostic accuracy of the ResNet18 was observed to be 90.20% with a precision of 75.00%, recall of 94.44%, and F1-score of 83.61%. Further research is required to improve diagnostic accuracy based on aorta segmentation.

CT-based radiomics signature for differentiation between cardiac tumors and a thrombi: a retrospective, multicenter study.

The study aimed to develop and validate whether the computed tomography (CT) radiomics analysis is effective in differentiating cardiac tumors and thrombi. For this retrospective study, a radiomics model was developed on the basis of a training dataset of 192 patients (61.9 ± 13.3 years, 90 men) with cardiac masses detected in cardiac CT from January 2010 to September 2019. We constructed three models for discriminating between a cardiac tumor and a thrombus: a radiomics model, a clinical model, which included clinical and conventional CT variables, and a model that combined clinical and radiomics models. In the training dataset, the radiomics model and the combined model yielded significantly higher differentiation performance between cardiac tumors and cardiac thrombi than the clinical model (AUC 0.973 vs 0.870, p < 0.001 and AUC 0.983 vs 0.870, p < 0.001, respectively). In the external validation dataset with 63 patients (59.8 ± 13.2 years, 26 men), the combined model yielded a larger AUC compared to the clinical model (AUC 0.911 vs 0.802, p = 0.037). CT radiomics analysis is effective in differentiating cardiac tumors and thrombi. In conclusion, the combination of clinical, conventional CT, and radiomics features demonstrated an additional benefit in differentiating between cardiac tumor and thrombi compared to clinical data and conventional CT features alone.

The image quality and diagnostic accuracy of T1-mapping-based synthetic late gadolinium enhancement imaging: comparison with conventional late gadolinium enhancement imaging in real-life clinical situation.

BACKGROUNDS: Synthetic late gadolinium enhancement (LGE) images are less sensitive to inversion time (TI) and robust to motion artifact, because it is generated retrospectively by post-contrast T1-mapping images. To explore the clinical applicability of synthetic LGE, we investigated the image quality and diagnostic accuracy of synthetic LGE images, in comparison to that of conventional LGE for various disease groups. METHOD AND MATERIALS: From July to November 2019, a total of 98 patients who underwent cardiovascular magnetic resonance imaging (CMR), including LGE and T1-mapping sequences, with suspicion of myocardial abnormality were retrospectively included. Synthetic magnitude inversion-recovery (IR) and phase-sensitive IR (PSIR) images were generated through calculations based on the post-contrast T1-mapping sequence. Three cardiothoracic radiologists independently analyzed the image quality of conventional and synthetic LGE images on an ordinal scale with per-segment basis and the image qualities were compared with chi-square test. The agreement of LGE detection was analyzed on per-patient and per-segment basis with Cohen's kappa test. In addition, the LGE area and percentage were semi-quantitatively analyzed for LGE positive ischemic (n = 14) and hypertrophic cardiomyopathy (n = 13) subgroups by two cardiothoracic radiologists. The difference of quantified LGE area and percentage between conventional and synthetic LGE images were assessed with Mann-Whitney U-test and the inter-reader agreement was assessed with Bland-Altman analysis. RESULTS: The image quality of synthetic images was significantly better than conventional images in both magnitude IR and PSIR through all three observers (P < 0.001, all). The agreements of per-patient and per-segment LGE detection rates were excellent (kappa = 0.815-0.864). The semi-quantitative analysis showed no significant difference in the LGE area and percentage between conventional and synthetic LGE images. In the inter-reader agreement showed only small systematic differences in both magnitude IR and PSIR and synthetic LGE images showed smaller systematic biases compared to conventional LGE images. CONCLUSION: Compared to conventional LGE images, synthetic LGE images have better image quality in real-life clinical situation.

Synthetic Extracellular Volume Fraction Derived Using Virtual Unenhanced Attenuation of Blood on Contrast-Enhanced Cardiac Dual-Energy CT in Nonischemic Cardiomyopathy.

BACKGROUND. Current methods for calculating the myocardial extracellular volume (ECV) fraction require blood sampling to determine the serum hematocrit. Synthetic hematocrit and thus synthetic ECV may be derived using unenhanced attenuation of blood. By use of virtual unenhanced (VUE) attenuation of blood, contrast-enhanced dual-energy CT (DECT) may allow synthetic ECV calculations without unenhanced acquisition. OBJECTIVE. The purpose of this study was to compare synthetic ECV calculated using synthetic hematocrit derived from VUE images and conventional ECV calculated using serum hematocrit, both of which were obtained by contrast-enhanced DECT, with ECV derived from MRI used as the reference standard. METHODS. This retrospective study included 51 patients (26 men and 25 women; mean age, 59.9 ± 15.6 [SD] years) with nonischemic cardiomyopathy who, as part of an earlier prospective investigation, underwent equilibrium phase contrast-enhanced cardiac DECT and cardiac MRI and had serum hematocrit measured within 6 hours of both tests. A separate retrospective sample of 198 patients who underwent contrast-enhanced thoracic DECT performed on the same day for suspected pulmonary embolism and serum hematocrit measurement was identified to derive a synthetic hematocrit formula using VUE attenuation of blood by linear regression analysis. In the primary sample, two radiologists independently used DECT iodine maps to obtain the conventional ECV using serum hematocrit and the synthetic ECV using synthetic hematocrit based on the independently derived formula. The concordance correlation coefficient (CCC) was computed between conventional ECV and synthetic ECV from DECT. Conventional ECV and synthetic ECV from DECT were compared with the ECV derived from MRI in Bland-Altman analyses. RESULTS. In the independent sample, the linear regression formula for synthetic hematocrit was as follows: synthetic hematocrit = 0.85 × (VUE attenuation of blood) - 5.40. In the primary sample, the conventional ECV and synthetic ECV from DECT showed excellent agreement (CCC, 0.95). Bland-Altman analysis showed a small bias of -0.44% (95% limits of agreement, -5.10% to 4.22%) between MRI-derived ECV and conventional ECV from DECT as well as a small bias of -0.78% (95% limits of agreement, -5.25% to 3.69%) between MRI-derived ECV and synthetic ECV from DECT. CONCLUSION. Synthetic ECV and conventional ECV derived from DECT show excel lent agreement and a comparable association with ECV derived from cardiac MRI. CLINICAL IMPACT. Synthetic hematocrit from VUE attenuation of blood may allow myocardial tissue characterization on DECT without the inconvenience of blood sampling.

Dual-Energy CT for Pulmonary Embolism: Current and Evolving Clinical Applications.

Pulmonary embolism (PE) is a potentially fatal disease if the diagnosis or treatment is delayed. Currently, multidetector computed tomography (MDCT) is considered the standard imaging method for diagnosing PE. Dual-energy CT (DECT) has the advantages of MDCT and can provide functional information for patients with PE. The aim of this review is to present the potential clinical applications of DECT in PE, focusing on the diagnosis and risk stratification of PE.

Coronary CT Angiography CAD-RADS versus Coronary Artery Calcium Score in Patients with Acute Chest Pain.

Background The Coronary Artery Disease Reporting and Data System (CAD-RADS) was established in 2016 to standardize the reporting of coronary artery disease at coronary CT angiography (CCTA). Purpose To assess the prognostic value of CAD-RADS at CCTA for major adverse cardiovascular events (MACEs) in patients presenting to the emergency department with chest pain. Materials and Methods This multicenter retrospective observational cohort study was conducted at four qualifying university teaching hospitals. Patients presenting to the emergency department with acute chest pain underwent CCTA between January 2010 and December 2017. Multivariable Cox regression analysis was used to evaluate risk factors for MACEs, including clinical factors, coronary artery calcium score (CACS), and CAD-RADS categories. The prognostic value compared with clinical risk factors and CACS was also assessed. Results A total of 1492 patients were evaluated (mean age, 58 years ± 14 years [standard deviation]; 759 men). During a median follow-up period of 31.5 months, 103 of the 1492 patients (7%) experienced MACEs. Multivariable Cox regression analysis showed that a moderate to severe CACS was associated with MACEs after adjusting for clinical risk factors (hazard ratio [HR] range, 2.3-4.4; P value range, <.001 to <.01). CAD-RADS categories from 3 to 4 or 5 (HR range, 3.2-8.5; P < .001) and high-risk plaques (HR = 3.6, P < .001) were also associated with MACEs. The C statistics revealed that the CAD-RADS score improved risk stratification more than that using clinical risk factors alone or combined with CACS (C-index, 0.85 vs 0.63 [P < .001] and 0.76 [P < .01], respectively). Conclusion The Coronary Artery Disease Reporting and Data System classification had an incremental prognostic value compared with the coronary artery calcium score in the prediction of major adverse cardiovascular events in patients presenting to the emergency department with acute chest pain. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Vliegenthart in this issue.

Prognostic Value of Coronary Artery Disease-Reporting and Data System Score for Major Adverse Cardiac Events in Patients Attending the Emergency Department With Acute Chest Pain.

OBJECTIVE: This study aimed to compare the prognostic performance of Coronary Artery Disease (CAD)-Reporting and Data System (CAD-RADS) score with those of clinical risk factors and the extent of CAD classification for predicting major adverse cardiac events in emergency department patients. METHODS: A total of 779 patients with acute chest pain at low to intermediate risk for CAD underwent cardiac computed tomography angiography. The primary end point was early and late major adverse cardiac events. We developed the following models: model 1, clinical risk factors; model 2, clinical risk factors and CAD-RADS scores; model 3, clinical risk factors and extent of CAD. RESULTS: The C-statistics revealed that both CAD-RADS score and CAD extent improved risk stratification over the clinical risk factors (C-index for early events: C-index: 0.901 vs 0.814 and 0.911 vs 0.814; C-index for late events: 0.897 vs 0.808 and 0.905 vs 0.808; all P < 0.05). CONCLUSIONS: The CAD-RADS score had additional risk prediction benefits over clinical risk factors for emergency department patients.

Serial T1 mapping of right ventricle in pulmonary hypertension: comparison with histology in an animal study.

BACKGROUND: Right ventricular (RV) free wall fibrosis is an important component of adverse remodeling with RV dysfunction in pulmonary hypertension (PH). However, no previous reports have compared cardiovascular magnetic resonance (CMR) findings and histological analysis for RV free wall fibrosis in PH. We aimed to assess the feasibility of CMR T1 mapping with extracellular volume fraction (ECV) for evaluating the progression of RV free wall fibrosis in PH, and compared imaging findings to histological collagen density through an animal study. METHODS: Among 42 6-week-old Wistar male rats, 30 were classified according to disease duration (baseline before monocrotaline injection, and 2, 4, 6 and 8 weeks after injection) and 12 were used to control for aging (4 and 8 weeks after the baseline). We obtained pre and post-contrast T1 maps for native T1 and ECV of RV and left ventricular (LV) free wall for six animals in each disease-duration group. Collagen density of RV free wall was calculated with Masson's trichrome staining. The Kruskall-Wallis test was performed to compare the groups. Native T1 and ECV to collagen density were analyzed with Spearman's correlation. RESULTS: The mean values of native T1, ECV and collagen density of the RV free wall at baseline were 1541 ± 33 ms, 17.2 ± 1.3%, and 4.7 ± 0.5%, respectively. The values of RV free wall did not differ according to aging (P = 0.244, 0.504 and 0.331, respectively). However, the values significantly increased according to disease duration (P < 0.001 for all). Significant correlations were observed between native T1 and collagen density (r = 0.770, P < 0.001), and between ECV and collagen density for the RV free wall (r = 0.815, P < 0.001) in PH. However, there was no significant difference in native T1 and ECV values for the LV free wall according to the disease duration from the baseline (P = 0.349 and 0.240, respectively). CONCLUSIONS: We observed significantly increased values for native T1 and ECV of the RV free wall without significant increase of the LV free wall according to the disease duration of PH, and findings were well correlated with histological collagen density.

Predictive factors of recurrence after resection of subsolid clinical stage IA lung adenocarcinoma.

BACKGROUND: Ongoing studies are currently investigating the extent of surgical resection required for subsolid cancers. This study aimed to investigate the predictive factors related to recurrence in patients with clinical stage IA subsolid cancer who underwent either lobectomy or sublobar resection. METHODS: This was a prospective multicenter observational study conducted in eight qualifying university teaching hospitals between April 2014 and December 2016. A total of 173 patients with subsolid nodules pathologically confirmed to have primary lung adenocarcinoma and stage IA disease were included in the final analysis. All patients underwent lobectomy, segmentectomy, or wedge resection performed by experienced thoracoscopic surgeons at each site. The surgical procedure was chosen based on the decision of the surgeons involved. The primary endpoint was time to recurrence (TTR). RESULTS: The study population was 43.9% (76 of 173) male with a mean age of 60.7 years. During the median follow-up period of 5.01 years, nine patients (5%) experienced disease recurrence. In the multivariable analysis, tumor size (size ≥2 cm) (hazard ratio: 73.717, 95% confidence interval [CI]: 3.635-895.036; p < 0.001) and stage IA3 (hazard ratio: 62.010, 95% CI: 2.837-855.185; p < 0.001) were independent predictors of tumor recurrence. When analyzing the recurrence outcome in patients according to surgical procedure, no significant difference was found in TTR among the three groups (i.e., lobectomy, segmentectomy, and wedge resection; p = 0.99). CONCLUSIONS: Patients with radiologically subsolid lung adenocarcinoma measuring <3 cm could be candidates for sublobar resection instead of lobectomy.

Prognostic Value of Dual-Energy CT-Based Iodine Quantification versus Conventional CT in Acute Pulmonary Embolism: A Propensity-Match Analysis.

OBJECTIVE: The present study aimed to investigate whether quantitative dual-energy computed tomography (DECT) parameters offer an incremental risk stratification benefit over the CT ventricular diameter ratio in patients with acute pulmonary embolism (PE) by using propensity score analysis. MATERIALS AND METHODS: This study was conducted on 480 patients with acute PE who underwent CT pulmonary angiography (CTPA) or DECT pulmonary angiography (DE CT-PA). This propensity-matched study population included 240 patients with acute PE each in the CTPA and DECT groups. Altogether, 260 (54.1%) patients were men, and the mean age was 64.9 years (64.9 ± 13.5 years). The primary endpoint was all-cause death within 30 days. The Cox proportional hazards regression model was used to identify associations between CT parameters and outcomes and to identify potential predictors. Concordance (C) statistics were used to compare the prognoses between the two groups. RESULTS: In both CTPA and DECT groups, right to left ventricle diameter ratio ≥ 1 was associated with an increased risk of all-cause death within 30 days (hazard ratio: 3.707, p < 0.001 and 5.573, p < 0.001, respectively). However, C-statistics showed no statistically significant difference between the CTPA and DECT groups for predicting death within 30 days (C-statistics: 0.759 vs. 0.819, p = 0.117). CONCLUSION: Quantitative measurement of lung perfusion defect volume by DECT had no added benefit over CT ventricular diameter ratio for predicting all-cause death within 30 days.

Role of Cardiac Computed Tomography for Etiology Evaluation of Newly Diagnosed Heart Failure with Reduced Ejection Fraction.

Delayed-enhanced dual-energy computed tomography (DECT) can evaluate the extent and degree of myocardial fibrosis while coronary CT angiography (CCTA) is a widely accepted coronary artery evaluation method. We sought to describe the role of combined cardiac CT for the evaluation of underlying etiology in patients with newly diagnosed heart failure with reduced ejection fraction (HFrEF). Sixty-three consecutive patients (31 men, 63 ± 16 years) with newly diagnosed HFrEF were enrolled in this prospective study. Coronary artery disease and myocardial fibrosis were evaluated on CCTA and DECT, respectively, and the tentative underlying etiologies of heart failure (HF) were determined with combinations of findings from both CTs. Concordance between tentative etiologies from cardiac CT and final etiologies from clinical decisions within a 2-year follow-up was assessed. Eighteen patients were diagnosed with ischemic HF on initial cardiac CT, and the final diagnosis was not changed. Another 45 patients with nonischemic HF included tentative etiologies of dilated cardiomyopathy (n = 32, 71.1%), sarcoidosis or myocarditis (n = 8, 17.8%), amyloidosis (n = 2, 4.4%), noncompaction (n = 2, 4.4%) and arrhythmogenic right ventricular cardiomyopathy (n = 1, 2.2%). Five nonischemic HF patients showed different etiologies between initial cardiac CT and clinical decisions. The concordance between cardiac CT and clinical decisions was 92.1%. A high degree of concordance was achieved between tentative etiologies from cardiac CT and final diagnoses from clinical decisions. Combined cardiac CT is a feasible, safe and effective imaging tool for the initial evaluation of newly diagnosed HFrEF patients.

Cohort Profile: Firefighter Research on the Enhancement of Safety and Health (FRESH), a Prospective Cohort Study on Korean Firefighters.

Firefighters have a high risk of developing cardiovascular and mental disorders due to their physical and chemical environments. However, in Korea, few studies have been conducted on environmental risk of firefighters. The Firefighter Research on the Enhancement of Safety and Health (FRESH) study aimed to discover the risk factors for cardiovascular disease and mental disorders among firefighters. Former and current firefighters were recruited from three university hospitals. A total of 1022 participants completed baseline health examinations from 2016 to 2017. All participants were scheduled for follow-ups every 2 years. Baseline health survey, laboratory testing of blood and urine samples, blood heavy metal concentration, urine polycyclic aromatic hydrocarbons (PAHs) metabolites, stress-related hormone test, natural killer cell activity, as well as physical and mental health examinations that focused on cardiovascular and mental disorders, were conducted. In addition, 3 Tesla (3T) brain magnetic resonance imaging (MRI) and neuropsychological tests were also performed to investigate structural and functional changes in the brains of 352 firefighters aged >40 years or new hires with less than 1 year of service.

Guidelines for Cardiovascular Magnetic Resonance Imaging from the Korean Society of Cardiovascular Imaging-Part 3: Perfusion, Delayed Enhancement, and T1- and T2 Mapping.

This document is the third part of the guidelines for the protocol, the interpretation and post-processing of cardiac magnetic resonance (CMR) studies. These consensus recommendations have been developed by the Consensus Committee of the Korean Society of Cardiovascular Imaging to standardize the requirements for image interpretation and post-processing of CMR. This third part of the recommendations describes tissue characterization modules, including perfusion, late gadolinium enhancement, and T1- and T2 mapping. Additionally, this document provides guidance for visual and quantitative assessment consisting of "What-to-See," "How-To," and common pitfalls for the analysis of each module. The Consensus Committee hopes that this document will contribute to the standardization of image interpretation and post-processing of CMR studies.

Guidelines for Cardiovascular Magnetic Resonance Imaging from the Korean Society of Cardiovascular Imaging-Part 2: Interpretation of Cine, Flow, and Angiography Data.

Cardiovascular magnetic resonance imaging (CMR) is expected to be increasingly used in Korea due to technological advances and the expanded national insurance coverage of CMR assessments. For improved patient care, proper acquisition of CMR images as well as their accurate interpretation by well-trained personnel are equally important. In response to the increased demand for CMR, the Korean Society of Cardiovascular Imaging (KOSCI) has issued interpretation guidelines in conjunction with the Korean Society of Radiology. KOSCI has also created a formal Committee on CMR guidelines to create updated practices. The members of this committee review previously published interpretation guidelines and discuss the patterns of CMR use in Korea.

Guideline for Cardiovascular Magnetic Resonance Imaging from the Korean Society of Cardiovascular Imaging-Part 1: Standardized Protocol.

Cardiac magnetic resonance (CMR) imaging is widely used in many areas of cardiovascular disease assessment. This is a practical, standard CMR protocol for beginners that is designed to be easy to follow and implement. This protocol guideline is based on previously reported CMR guidelines and includes sequence terminology used by vendors, essential MR physics, imaging planes, field strength considerations, MRI-conditional devices, drugs for stress tests, various CMR modules, and disease/symptom-based protocols based on a survey of cardiologists and various appropriate-use criteria. It will be of considerable help in planning and implementing tests. In addressing CMR usage and creating this protocol guideline, we particularly tried to include useful tips to overcome various practical issues and improve CMR imaging. We hope that this document will continue to standardize and simplify a patient-based approach to clinical CMR and contribute to the promotion of public health.