Purpose: This study examined longitudinal changes in interstitial lung abnormalities (ILAs) and predictors of clinically significant interstitial lung diseases (ILDs) in a screening population with ILAs. Materials and Methods: We retrieved 36891 low-dose chest CT records from screenings between January 2003 and May 2021. After identifying 101 patients with ILAs, the clinical findings, spirometry results, and initial and follow-up CT findings, including visual and artificial intelligence-based quantitative analyses, were compared between patients diagnosed with ILD (n = 23, 23%) and those who were not (n = 78, 77%). Logistic regression analysis was used to identify significant parameters for the clinical diagnosis of ILD. Results: Twenty-three patients (n = 23, 23%) were subsequently diagnosed with clinically significant ILDs at follow-up (mean, 8.7 years). Subpleural fibrotic ILAs on initial CT and signs of progression on follow-up CT were common in the ILD group (both p < 0.05). Logistic regression analysis revealed that emerging respiratory symptoms (odds ratio [OR], 5.56; 95% confidence interval [CI], 1.28–24.21; p = 0.022) and progression of ILAs at follow-up chest CT (OR, 4.07; 95% CI, 1.00–16.54; p = 0.050) were significant parameters for clinical diagnosis of ILD. Conclusion Clinically significant ILD was subsequently diagnosed in approximately one-quarter of the screened population with ILAs. Emerging respiratory symptoms and progression of ILAs at followup chest CT can be predictors of clinically significant ILDs.

Interstitial lung disease (ILD) is often observed in connective tissue diseases (CTDs), frequently in rheumatoid arthritis, systemic sclerosis, primary Sjögren’s syndrome, and inflammatory myositis. Early detection of ILDs secondary to rheumatic diseases is important as timely initiation of proper management affects the prognosis. Among many imaging modalities, high-resuloution computed tomography (HRCT) serves the gold standard for finding early lung inflammatory and fibrotic changes as well as monitoring afterwards because of its superior spatial resolution. Additionally, lung ultrasound (LUS) and magnetic resonance imaging (MRI) are the rising free-radiation imaging tools that can get images of lungs of CTD-ILD. In this review article, we present the subtypes of ILD images found in each CTD acquired by HRCT as well as some images taken by LUS and MRI with comparative HRCT scans. It is expected that this discussion would be helpful in discussing recent advances in imaging modalities for CTDILD and raising critical points for diagnosis and tracing of the images from the perspective of rheumatologists.

Purpose: This study examined longitudinal changes in interstitial lung abnormalities (ILAs) and predictors of clinically significant interstitial lung diseases (ILDs) in a screening population with ILAs. Materials and Methods: We retrieved 36891 low-dose chest CT records from screenings between January 2003 and May 2021. After identifying 101 patients with ILAs, the clinical findings, spirometry results, and initial and follow-up CT findings, including visual and artificial intelligence-based quantitative analyses, were compared between patients diagnosed with ILD (n = 23, 23%) and those who were not (n = 78, 77%). Logistic regression analysis was used to identify significant parameters for the clinical diagnosis of ILD. Results: Twenty-three patients (n = 23, 23%) were subsequently diagnosed with clinically significant ILDs at follow-up (mean, 8.7 years). Subpleural fibrotic ILAs on initial CT and signs of progression on follow-up CT were common in the ILD group (both p < 0.05). Logistic regression analysis revealed that emerging respiratory symptoms (odds ratio [OR], 5.56; 95% confidence interval [CI], 1.28–24.21; p = 0.022) and progression of ILAs at follow-up chest CT (OR, 4.07; 95% CI, 1.00–16.54; p = 0.050) were significant parameters for clinical diagnosis of ILD. Conclusion Clinically significant ILD was subsequently diagnosed in approximately one-quarter of the screened population with ILAs. Emerging respiratory symptoms and progression of ILAs at followup chest CT can be predictors of clinically significant ILDs.

Purpose: This study examined longitudinal changes in interstitial lung abnormalities (ILAs) and predictors of clinically significant interstitial lung diseases (ILDs) in a screening population with ILAs. Materials and Methods: We retrieved 36891 low-dose chest CT records from screenings between January 2003 and May 2021. After identifying 101 patients with ILAs, the clinical findings, spirometry results, and initial and follow-up CT findings, including visual and artificial intelligence-based quantitative analyses, were compared between patients diagnosed with ILD (n = 23, 23%) and those who were not (n = 78, 77%). Logistic regression analysis was used to identify significant parameters for the clinical diagnosis of ILD. Results: Twenty-three patients (n = 23, 23%) were subsequently diagnosed with clinically significant ILDs at follow-up (mean, 8.7 years). Subpleural fibrotic ILAs on initial CT and signs of progression on follow-up CT were common in the ILD group (both p < 0.05). Logistic regression analysis revealed that emerging respiratory symptoms (odds ratio [OR], 5.56; 95% confidence interval [CI], 1.28–24.21; p = 0.022) and progression of ILAs at follow-up chest CT (OR, 4.07; 95% CI, 1.00–16.54; p = 0.050) were significant parameters for clinical diagnosis of ILD. Conclusion Clinically significant ILD was subsequently diagnosed in approximately one-quarter of the screened population with ILAs. Emerging respiratory symptoms and progression of ILAs at followup chest CT can be predictors of clinically significant ILDs.

To develop Korean coronavirus disease (COVID-19) chest imaging justification guidelines, eight key questions were selected and the following recommendations were made with the evidence-based clinical imaging guideline adaptation methodology. It is appropriate not to use chest imaging tests (chest radiograph or CT) for the diagnosis of COVID-19 in asymptomatic patients. If reverse transcription-polymerase chain reaction testing is not available or if results are delayed or are initially negative in the presence of symptoms suggestive of COVID-19, chest imaging tests may be considered. In addition to clinical evaluations and laboratory tests, chest imaging may be contemplated to determine hospital admission for asymptomatic or mildly symptomatic unhospitalized patients with confirmed COVID-19. In hospitalized patients with confirmed COVID-19, chest imaging may be advised to determine or modify treatment alternatives. CT angiography may be considered if hemoptysis or pulmonary embolism is clinically suspected in a patient with confirmed COVID-19. For COVID-19 patients with improved symptoms, chest imaging is not recommended to make decisions regarding hospital discharge. For patients with functional impairment after recovery from COVID-19, chest imaging may be considered to distinguish a potentially treatable disease.

An increased pericoronary fat attenuation index (FAI) on computed tomography angiography (CTA) is associated with increased all-cause and cardiac mortality in the general population. However, the ability of pericoronary FAI to predict long-term outcomes in chronic kidney disease (CKD) patients is unknown. Methods: In this single-center retrospective longitudinal cohort study, we assessed the utility of CTA-based pericoronary FAI measurement to predict mortality of CKD patients, including those with end-stage renal disease (ESRD). Mapping and analysis of pericoronary FAI involved three major proximal coronary arteries. The prognostic value of pericoronary FAI for long-term mortality was assessed with multivariable Cox regression models. Results: Among 268 CKD participants who underwent coronary CTA, 209 participants with left anterior descending artery (LAD) FAI measurements were included. The pericoronary FAI measured at the LAD was not significantly associated with adjusted risk of allcause mortality (hazard ratio [HR], 2.08; 95% confidence interval [CI], 0.94–3.51) in any CKD group. However, ESRD patients with elevated pericoronary FAI values had a greater adjusted risk of all-cause mortality compared with the low-FAI group (HR, 2.26; 95% CI, 1.11–4.61). Conclusion: The pericoronary FAI measured at the LAD predicted long-term mortality in patients with ESRD, which could provide an opportunity for early primary intervention in ESRD patients.

Background: We analyzed the differences between clinical characteristics and computed tomography (CT) findings in patients with coronavirus disease 2019 (COVID-19) to establish potential relationships with mediastinal lymphadenopathy and clinical outcomes. Methods: We compared the clinical characteristics and CT findings of COVID-19 patients from a nationwide multicenter cohort who were grouped based on the presence or absence of mediastinal lymphadenopathy. Differences between clinical characteristics and CT findings in these groups were analyzed. Univariate and multivariate analyses were performed to determine the impact of mediastinal lymphadenopathy on clinical outcomes. Results: Of the 344 patients included in this study, 53 (15.4%) presented with mediastinal lymphadenopathy. The rate of diffuse alveolar damage pattern pneumonia and the visual CT scores were significantly higher in patients with mediastinal lymphadenopathy than in those without (P < 0.05). A positive correlation between the number of enlarged mediastinal lymph nodes and visual CT scores was noted in patients with mediastinal lymphadenopathy (Spearman’s ρ = 0.334, P < 0.001). Multivariate analysis showed that mediastinal lymphadenopathy was independently associated with a higher risk of intensive care unit (ICU) admission (odds ratio, 95% confidence interval; 3.25, 1.06-9.95) but was not significantly associated with an increased risk of in-hospital death in patients with COVID-19. Conclusion COVID-19 patients with mediastinal lymphadenopathy had a larger extent of pneumonia than those without. Multivariate analysis adjusted for clinical characteristics and CT findings revealed that the presence of mediastinal lymphadenopathy was significantly associated with ICU admission.

Background: Remdesivir is widely used for the treatment of coronavirus disease 2019 (COVID-19), but controversies regarding its efficacy still remain. Methods: A retrospective cohort study was conducted to evaluate the effect of remdesivir on clinical and virologic outcomes of severe COVID-19 patients from June to July 2020. Primary clinical endpoints included clinical recovery, additional mechanical ventilator (MV) support, and duration of oxygen or MV support. Viral load reduction by hospital day (HD) 15 was evaluated by calculating changes in cycle threshold (Ct) values. Results: A total of 86 severe COVID-19 patients were evaluated including 48 remdesivirtreated patients. Baseline characteristics were not significantly different between the two groups. Remdesivir was administered an average of 7.42 days from symptom onset. The proportions of clinical recovery of the remdesivir and supportive care group at HD 14 (56.3% and 39.5%) and HD 28 (87.5% and 78.9%) were not statistically different. The proportion of patients requiring MV support by HD 28 was significantly lower in the remdesivir group than in the supportive care group (22.9% vs. 44.7%, P = 0.032), and MV duration was significantly shorter in the remdesivir group (average, 1.97 vs. 5.37 days; P = 0.017). Analysis of upper respiratory tract specimens demonstrated that increases of Ct value from HD 1–5 to 11–15 were significantly greater in the remdesivir group than the supportive care group (average, 10.19 vs. 5.36; P = 0.007), and the slope of the Ct value increase was also significantly steeper in the remdesivir group (average, 5.10 vs. 2.68; P = 0.007). Conclusion The remdesivir group showed clinical and virologic benefit in terms of MV requirement and viral load reduction, supporting remdesivir treatment for severe COVID-19.

Background: Few studies have classified chest computed tomography (CT) findings of coronavirus disease 2019 (COVID-19) and analyzed their correlations with prognosis. The present study aimed to evaluate retrospectively the clinical and chest CT findings of COVID-19 and to analyze CT findings and determine their relationships with clinical severity. Methods: Chest CT and clinical features of 271 COVID-19 patients were assessed. The presence of CT findings and distribution of parenchymal abnormalities were evaluated, and CT patterns were classified as bronchopneumonia, organizing pneumonia (OP), or diffuse alveolar damage (DAD). Total extents were assessed using a visual scoring system and artificial intelligence software. Patients were allocated to two groups based on clinical outcomes, that is, to a severe group (requiring O2 therapy or mechanical ventilation, n = 55) or a mild group (not requiring O2 therapy or mechanical ventilation, n = 216). Clinical and CT features of these two groups were compared and univariate and multivariate logistic regression analyses were performed to identify independent prognostic factors. Results: Age, lymphocyte count, levels of C-reactive protein, and procalcitonin were significantly different in the two groups. Forty-five of the 271 patients had normal chest CT findings. The most common CT findings among the remaining 226 patients were groundglass opacity (98%), followed by consolidation (53%). CT findings were classified as OP (93%), DAD (4%), or bronchopneumonia (3%) and all nine patients with DAD pattern were included in the severe group. Uivariate and multivariate analyses showed an elevated procalcitonin (odds ratio [OR], 2.521; 95% confidence interval [CI], 1.001–6.303, P = 0.048), and higher visual CT scores (OR, 1.137; 95% CI, 1.042–1.236; P = 0.003) or higher total extent by AI measurement (OR, 1.048; 95% CI, 1.020–1.076; P < 0.001) were significantly associated with a severe clinical course. Conclusion CT findings of COVID-19 pneumonia can be classified into OP, DAD, or bronchopneumonia patterns and all patients with DAD pattern were included in severe group. Elevated inflammatory markers and higher CT scores were found to be significant predictors of poor prognosis in patients with COVID-19 pneumonia.