Objective: Iterative reconstruction degrades image quality. Thus, further advances in image reconstruction are necessary to overcome some limitations of this technique in low-dose computed tomography (LDCT) scan of the chest. Deep-learning image reconstruction (DLIR) is a new method used to reduce dose while maintaining image quality. The purposes of this study was to evaluate image quality and noise of LDCT scan images reconstructed with DLIR and compare with those of images reconstructed with the adaptive statistical iterative reconstruction-Veo at a level of 30% (ASiR-V 30%). Materials and Methods: This retrospective study included 58 patients who underwent LDCT scan for lung cancer screening. Datasets were reconstructed with ASiR-V 30% and DLIR at medium and high levels (DLIR-M and DLIR-H, respectively). The objective image signal and noise, which represented mean attenuation value and standard deviation in Hounsfield units for the lungs, mediastinum, liver, and background air, and subjective image contrast, image noise, and conspicuity of structures were evaluated. The differences between CT scan images subjected to ASiR-V 30%, DLIR-M, and DLIR-H were evaluated. Results: Based on the objective analysis, the image signals did not significantly differ among ASiR-V 30%, DLIR-M, and DLIR-H (p = 0.949, 0.737, 0.366, and 0.358 in the lungs, mediastinum, liver, and background air, respectively). However, the noise was significantly lower in DLIR-M and DLIR-H than in ASiR-V 30% (all p < 0.001). DLIR had higher signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) than ASiR-V 30% (p = 0.027, < 0.001, and < 0.001 in the SNR of the lungs, mediastinum, and liver, respectively; all p < 0.001 in the CNR). According to the subjective analysis, DLIR had higher image contrast and lower image noise than ASiR-V 30% (all p < 0.001). DLIR was superior to ASiR-V 30% in identifying the pulmonary arteries and veins, trachea and bronchi, lymph nodes, and pleura and pericardium (all p < 0.001). Conclusion: DLIR significantly reduced the image noise in chest LDCT scan images compared with ASiR-V 30% while maintaining superior image quality.

ObjectiveThe aim of this study was to determine the inter- and intra-observer reliabilities of magnetic resonance imaging (MRI) for the diagnosis of lateral epicondylitis, to examine whether degree of common extensor tendon (CET) injury is related to other elbow abnormalities on MRI, and to investigate the correlation between elbow abnormalities on MRI and patients' symptoms.MethodsFifty-one patients (32 women and 19 men; mean age: 50 years (range, 22–63)) with a diagnosis of lateral epicondylitis were included in the study. The average duration of symptoms was 2.3 years. MRI scoring system was used to grade the CET injuries and associated injuries in the elbow joint. Three independent radiologists retrospectively reviewed MRI images. Inter- and intra-observer reliabilities for diagnosing lateral epicondylitis were calculated using kappa statistics, and Spearman's rank correlation analysis was used to analyze relationships between degree of CET injury and the associated abnormalities of elbow joints. Statistical relations were considered significant for p values of <0.05. In addition, using Spearman's rank correlation analysis, CET injuries and associated abnormalities of elbow joints were correlated with clinical symptoms using visual analog scale pain scores.ResultsVarious degrees of CET injuries were found in total of 51 patients. Radial collateral ligament and lateral ulnar collateral ligament (RCL/LCL) was the most common accompanying elbow abnormality other than CET injuries. Inter- and intra-observer agreements of CET and RCL/LUCL injuries on MRI were excellent. There were significant correlation between degrees of CET and RCL/LUCL injuries (correlation coefficient r = 0.667, p < 0.01) and between degree of RCL/LUCL injuries and visual analog 11-point pain box scale (VAS) scores (correlation coefficient r = 0.478, p = 0.033).ConclusionMRI showed excellent inter- and intra-observer reliabilities for the evaluation of lateral epicondylitis. In addition to common extensor tendinopathy, RCL/LUCL abnormality was the most common accompanying finding and degree of RCL/LUCL injuries positively correlated with degree of CET injuries. Furthermore, degree of RCL/LUCL injuries positively correlates with severity of pain.Level of evidenceLevel IV, Diagnostic study.

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Background: Chronic obstructive pulmonary disease (COPD) has variable subtypes involving mixture of large airway inflammation, small airway disease, and emphysema. This study evaluated the relationship between visually assessed computed tomography (CT) subtypes and clinical/imaging characteristics. Methods: In total, 452 participants were enrolled in this study between 2012 and 2017. Seven subtypes were defined by visual evaluation of CT images using Fleischner Society classification: normal, paraseptal emphysema (PSE), bronchial disease, and centrilobular emphysema (trace, mild, moderate and confluent/ advanced destructive). The differences in several variables, including clinical, laboratory, spirometric, and quantitative CT features among CT-based visual subtypes, were compared using the chi-square tests and one-way analysis of variance. Results: Subjects who had PSE had better forced expiratory volume in 1 second (FEV1) (P=0.03) percentage and higher lung density (P<0.05) than those with moderate to confluent/advanced destructive centrilobular emphysema. As the visual grade of centrilobular emphysema worsened, pulmonary function declined and modified Medical Research Council, COPD assessment test (CAT) score, and quantitative assessment (emphysema index and air trapping) increased. The bronchial subtype was associated with higher body mass index (BMI), better lung function and higher lung density. Participants with trace emphysema showed a rapid increase in functional small airway disease Conclusions:Classifying subtypes using visual CT imaging features can reflect heterogeneity and pathological processes of COPD.

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Background: Local fat distribution patterns and their local or systemic effects have recently attracted significant attention. The aim of this study was to assess the impact of thoracic adiposity on lung function in a population without respiratory diseases according to sex. Methods: A total of 455 subjects (282 males and 173 females), who had undergone spirometry, and chest and abdominal computed tomography between June 2012 and June 2016 at medical healthcare center, were included. Pericardial fat, intrathoracic fat, subcutaneous thoracic fat, and both visceral and subcutaneous abdominal fat were measured by directly assessing tissue volume using computed tomography. Multiple linear regression analyses adjusted for pack-years of smoking, high-density lipoprotein, and high-sensitivity C-reactive protein were performed to evaluate the association between fat volumes and lung function. Results: In males, intrathoracic fat and visceral abdominal fat were inversely associated with forced expiratory volume in 1 s (FEV 1 ) % predicted (P=0.025, P=0.010, respectively), and subcutaneous thoracic fat volumes showed a negative correlation with both FEV 1 % and forced vital capacity (FVC) % predicted (P=0.019, P=0.045, respectively). In females, subcutaneous thoracic fat demonstrated a negative correlation with both FEV 1 % and FVC % predicted (P=0.031 and P=0.008, respectively). Conclusions: The influence of local thoracic fat distribution on lung function differed according to sex. Visceral fat and subcutaneous thoracic fat in males and subcutaneous fat in females were significantly associated with decreased lung function.