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Background: Pulmonary metastases of bone and soft tissue sarcoma are common and have a high recurrence rate after metastatectomy. Factors associated with post-metastatectomy recurrence are not well studied. Objective: To investigate the association of the volume doubling time (VDT) of pulmonary metastases with the subsequent development of new pulmonary nodules and survival after metastasectomy in patients with bone or soft tissue sarcoma. Methods: This retrospective study included patients with bone or soft tissue sarcoma who, between July 2020 and December 2020, underwent first complete metastasectomy of pulmonary nodules visualized on two sequential preoperative CT scans. Semi-automatic volumetric segmentation of the pulmonary metastases was performed on the two CT scans, and VDTs were calculated. VDT was compared between patients with and without subsequent new metastases after metastatectomy. Cox proportional hazards regression analyses were performed to determine risk factors for recurrence-free survival (RFS) after metastasectomy and for post-metastasectomy overall survival (OS). Results: Forty patients (21 women, 19 men; mean age, 51.1±14.3 years) were included. Of these patients, 23 (57.5%) developed new metastatic nodules after metastasectomy, and 10 (25%) died during follow-up. Median VDT was shorter in patients with, versus without, new metastases after metastasectomy (56 vs. 140 days, p=.002). Only four of 23 patients with new metastases had VDT ≥140 days. In multivariable analysis, older age [hazard ratio (HR), 1.06; p=.004), female sex (HR, 2.80; p=.03), and VDT

BACKGROUND. CT-guided percutaneous transthoracic needle biopsy (PTNB) is widely used for evaluation of indeterminate pulmonary lesions, although guidelines are lacking regarding the experience need...

Background The clinical information on patients with severe C. striatum pneumonia who require intensive care unit admission is currently limited. Methods We investigated the incidence and characteristics of severe Corynebacterium striatum pneumonia during a 6-year period at Asan Medical Center in comparison with severe pneumonia associated with MRSA. Results Between 2014 and 2019, there were 27 adult cases of severe C. striatum pneumonia. The majority of the cases (70.4%) were hospital-acquired pneumonia (HAP), and about half of the patients (51.9%) were immunocompromised. The incidence of C. striatum HAP significantly increased from 1.0% (2/200) in 2014-2015 to 5.4% (10/185) in 2018-2019 (P < 0.001), while the incidence of severe methicillin-resistant Staphylococcus aureus (MRSA) HAP significantly decreased from 12.0% to 2.7% during the same period. Of the 75 HAP cases whose bacterial pathogens were identified in 2018–2019, C. striatum was responsible for 13.3% of the cases. The 90-day mortality rates were similarly high in the C. striatum and MRSA groups (59.3% vs. 50.5%, P = 0.42). Conclusion In conclusion, C. striatum was a major pathogen of recent severe HAP and was associated with a substantially high mortality rate. Disclosures All Authors: No reported disclosures.

Background Studies on the optimal CT section thickness for detecting subsolid nodules (SSNs) with computer-aided detection (CAD) are lacking. Purpose To assess the effect of CT section thickness on CAD performance in the detection of SSNs and to investigate whether deep learning-based super-resolution algorithms for reducing CT section thickness can improve performance. Materials and Methods CT images obtained with 1-, 3-, and 5-mm-thick sections were obtained in patients who underwent surgery between March 2018 and December 2018. Patients with resected synchronous SSNs and those without SSNs (negative controls) were retrospectively evaluated. The SSNs, which ranged from 6 to 30 mm, were labeled ground-truth lesions. A deep learning-based CAD system was applied to SSN detection on CT images of each section thickness and those converted from 3- and 5-mm section thickness into 1-mm section thickness by using the super-resolution algorithm. The CAD performance on each section thickness was evaluated and compared by using the jackknife alternative free response receiver operating characteristic figure of merit. Results A total of 308 patients (mean age ± standard deviation, 62 years ± 10; 183 women) with 424 SSNs (310 part-solid and 114 nonsolid nodules) and 182 patients without SSNs (mean age, 65 years ± 10; 97 men) were evaluated. The figures of merit differed across the three section thicknesses (0.92, 0.90, and 0.89 for 1, 3, and 5 mm, respectively; P = .04) and between 1- and 5-mm sections (P = .04). The figures of merit varied for nonsolid nodules (0.78, 0.72, and 0.66 for 1, 3, and 5 mm, respectively; P < .001) but not for part-solid nodules (range, 0.93-0.94; P = .76). The super-resolution algorithm improved CAD sensitivity on 3- and 5-mm-thick sections (P = .02 for 3 mm, P < .001 for 5 mm). Conclusion Computer-aided detection (CAD) of subsolid nodules performed better at 1-mm section thickness CT than at 3- and 5-mm section thickness CT, particularly with nonsolid nodules. Application of a super-resolution algorithm improved the sensitivity of CAD at 3- and 5-mm section thickness CT. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Goo in this issue.

Background The solid portion size of lung cancer lesions manifesting as subsolid lesions is key in their management, but the automatic measurement of such lesions by means of a deep learning (DL) algorithm needs evaluation. Purpose To evaluate the performance of a commercially available DL algorithm for automatic measurement of the solid portion of surgically proven lung adenocarcinomas manifesting as subsolid lesions. Materials and Methods Surgically proven lung adenocarcinomas manifesting as subsolid lesions on CT images between January 2018 and December 2018 were retrospectively included. Five radiologists independently measured the maximal axial diameter of the solid portion of lesions. The DL algorithm automatically segmented and measured the maximal axial diameter of the solid portion. Reader measurements, software measurements, and invasive component size at pathologic examination were compared by using intraclass correlation coefficient (ICC) and Bland-Altman plots. Results A total of 448 patients (mean age, 63 years ± 10 [standard deviation]; 264 women) with 448 lesions were evaluated (invasive component size, 3-65 mm). The measurement agreements between each radiologist and the DL algorithm were very good (ICC range, 0.82-0.89). When a radiologist was replaced with the DL algorithm, the ICCs ranged from 0.87 to 0.90, with an ICC of 0.90 among five radiologists. The mean difference between the DL algorithm and each radiologist ranged from -3.7 to 1.5 mm. The widest 95% limit of agreement between the DL algorithm and each radiologist (-15.7 to 8.3 mm) was wider than pairwise comparisons of radiologists (-7.7 to 13.0 mm). The agreement between the DL algorithm and invasive component size at pathologic evaluation was good, with an ICC of 0.67. Measurements by the DL algorithm (mean difference, -6.0 mm) and radiologists (mean difference, -7.5 to -2.3 mm) both underestimated invasive component size. Conclusion Automatic measurements of solid portions of lung cancer manifesting as subsolid lesions by the deep learning algorithm were comparable with manual measurements and showed good agreement with invasive component size at pathologic evaluation. © RSNA, 2021 Online supplemental material is available for this article.

To assess whether pulmonary vein injury is detectable on CT and associated with air embolism after percutaneous transthoracic needle biopsy (PTNB) in a tertiary referral hospital.Between January 2012 and November 2021, 11,691 consecutive CT-guided PTNBs in 10,685 patients were retrospectively evaluated. Air embolism was identified by reviewing radiologic reports. Pulmonary vein injury was defined as the presence of the pulmonary vein in the needle pathway or shooting range of the cutting needle with the presence of parenchymal hemorrhage. The association between pulmonary vein injury and air embolism was assessed using logistic regression analysis in matched patients with and without air embolism with a ratio of 1:4.A total of 27 cases of air embolism (median age, 67 years; range, 48-80 years; 24 men) were found with an incidence of 0.23% (27/11,691). Pulmonary vein injury during the procedures was identifiable on CT in 24 of 27 patients (88.9%), whereas it was 1.9% (2/108) for matched patients without air embolism The veins beyond the target lesion (70.8% [17/24]) were injured more frequently than the veins in the needle pathway before the target lesion (29.2% [7/24]). In univariable and multivariable analyses, pulmonary vein injury was associated with air embolism (odds ratio, 485.19; 95% confidence interval, 68.67-3428.19, p.001).Pulmonary vein injury was detected on CT and was associated with air embolism. Avoiding pulmonary vein injury with careful planning of the needle pathway on CT may reduce air embolism risk.• Pulmonary vein injury during CT-guided biopsy was identifiable on CT in most of the patients (88.9% [24/27]). • The veins beyond the target lesion (70.8% [17/24]) were injured more frequently than the veins in the needle pathway before the target lesion (29.2% [7/24]). • Avoiding the distinguishable pulmonary vein along the pathway or shooting range of the needle on CT may reduce the air embolism risk.

Background The timeline of infections after lung transplantation has been changed with the introduction of new immunosuppressants and prophylaxis strategies. The study aimed to investigate the epidemiological characteristics of infectious diseases after lung transplantation in the current era. Materials and methods All patients who underwent lung or heart-lung transplantation at our institution between October 29, 2008 and April 3, 2019 were enrolled. We retrospectively reviewed the patients' medical records till April 2, 2020. Results In total, 100 consecutive lung transplant recipients were enrolled. The median follow-up period was 28 months after lung transplantation. A total of 127 post-lung transplantation bacterial infections occurred. Catheter-related bloodstream infection (25/84, 29.8%) was the most common within 6 months and pneumonia (23/43, 53.5%) was the most common after 6 months. Most episodes (35/40, 87.5%) of respiratory viral infections occurred after 6 months, mainly as upper respiratory infections. The remaining episodes (5/40, 12.5%) mostly manifested as lower respiratory tract infections. Seventy cytomegalovirus infections observed in 43 patients were divided into 23 episodes occurring before and 47 episodes occurring after discontinuing prophylaxis. Of 10 episodes of cytomegalovirus disease, four occurred during prophylaxis and six occurred after prophylaxis. Of 23 episodes of post-lung transplantation fungal infection, 7 were aspergillosis and all occurred after the discontinuation of prophylaxis. Conclusion Lung transplant recipients experienced a high burden of infection even after 6 months, especially after the end of the prophylaxis period. Therefore, these patients should be continued to be monitored long-term for infectious disease.

Editor's Note.-Articles in the RadioGraphics Update section provide current knowledge to supplement or update information found in full-length articles previously published in RadioGraphics. Authors of the previously published article provide a brief synopsis that emphasizes important new information such as technological advances, revised imaging protocols, new clinical guidelines involving imaging, or updated classification schemes. Articles in this section are published solely online and are linked to the original article.

Background The volume doubling time (VDT) is a key parameter in the differentiation of aggressive tumors from slow-growing tumors. How different histologic subtypes of primary lung adenocarcinomas vary in their VDT and the prognostic value of this measurement is unknown. Purpose To investigate differences in VDT between the predominant histologic subtypes of primary lung adenocarcinomas and to assess the correlation between VDT and prognosis. Materials and Methods This retrospective study included patients who underwent at least two serial CT examinations before undergoing operation between July 2010 and December 2018. Three-dimensional tumor segmentation was performed on two CT images and VDTs were calculated. VDTs were compared between predominant histologic subtypes and lesion types by using Kruskal-Wallis tests. Disease-free survival (DFS) was obtained in patients undergoing surgical procedures before July 2017. Univariable and multivariable Cox proportional hazards regression analyses were performed to determine predictors of DFS. Results Among 268 patients (mean age, 64 years ± 8 [standard deviation]; 143 men), there were 30 lepidic, 87 acinar, 109 papillary, and 42 solid or micropapillary predominant subtypes. The median VDT was 529 days (interquartile range, 278-872 days) for lung adenocarcinomas. VDTs differed across subtypes (P < .001) and were shortest in solid or micropapillary subtypes (229 days; interquartile range, 77-530 days). Solid lesions (VDT, 248 days) had shorter VDTs than subsolid lesions (part-solid lesions, 665 days; nonsolid lesions, 648 days) (P < .001). In the 148 patients (mean age, 64 years ± 8; 89 men) included in the survival analysis, 35 patients had disease recurrence and 17 patients died. VDT (

Lung adenocarcinoma shows broad spectrum of prognosis and histologic heterogeneity. This study was to investigate the prognostic value of CT radiomics in resectable lung adenocarcinoma patients and assess its incremental value over clinical-pathologic risk factors. This retrospective analysis evaluated 1058 patients who underwent curative surgery for lung adenocarcinoma (training cohort: N = 754; temporal validation cohort: N = 304). Radiomics features were extracted from preoperative contrast-enhanced CT. Radiomics signature to predict disease-free survival (DFS) and overall survival (OS) was generated. Association between the radiomics signature and prognosis were evaluated using univariable and multivariable Cox proportional hazards regression analyses. Incremental value of the radiomics signature beyond clinical-pathologic risk factors was assessed using concordance index (C-index). The radiomics signatures were independently associated with DFS (hazard ratio [HR], 1.920; p

To investigate CT imaging features associated with poor clinical outcome after corticosteroid treatment in patients diagnosed with cryptogenic organizing pneumonia (COP) and connective tissue disease–related organizing pneumonia (CTD-OP) and to assess the difference in CT findings and treatment responses between COP and CTD-OP. Chest CT images from 166 patients (COP, 131; CTD-OP, 35) with pathologically proven organizing pneumonia were reviewed by two thoracic radiologists. The type, distribution pattern, and extent of parenchymal abnormalities, along with other associated imaging features, were assessed for each patient. Logistic regression analyses were used to identify features associated with poor clinical outcomes such as residual disease (RD) and disease relapse. The differences between COP and CTD-OP were also analyzed. Consolidation involving more than 10% of parenchyma (hazard ratio [HR], 2.27), detectable bronchiectasis (HR, 3.59), and diagnosis of CTD-OP (HR, 4.31) were associated with a higher risk of RD after adjustments for patient age and sex. More than 10% consolidation involvement (HR, 2.54) and diagnosis of CTD-OP (HR, 6.42) were also associated with a higher risk of disease relapse. Compared with COP, CTD-OP demonstrated a greater extent of parenchymal abnormalities, especially consolidation, and was less likely to show a peribronchovascular distribution pattern. Bronchiectasis and a greater extent of consolidation were associated with RD, with the latter also being associated with disease relapse. Compared with COP, CTD-OP was associated with worse treatment outcomes and demonstrated a greater extent of parenchymal abnormalities, which were also less likely to show a peribronchovascular pattern. • The presence of bronchiectasis and a high parenchymal involvement of consolidation on initial chest CT were associated with a worse response to corticosteroids in patients with organizing pneumonia. • Connective tissue disease–related organizing pneumonia (CTD-OP) was associated with worse treatment outcomes than its idiopathic counterpart cryptogenic organizing pneumonia (COP). • Compared with COP, CTD-OP generally demonstrated a greater extent of parenchymal abnormalities, especially consolidation, and was less likely to show a peribronchovascular distribution pattern.

We report a case series of severe human bocavirus-associated pneumonia in adults in Seoul, South Korea. The virus accounted for 0.5% of all severe pneumonia cases. Structural lung disease and hematologic malignancy were common underlying diseases. Overall death rate was 54.5%. Higher death rates were associated with co-infection (83.3%) and immunocompromise (80.0%).

The purpose of this study was to evaluate the implications of the 2018 updated guideline for the diagnosis of idiopathic pulmonary fibrosis (IPF) in clinical practice compared to 2011 guideline. This study involved 535 patients including 339 IPF and 196 non-IPF, and we retrospectively evaluated CT classifications of usual interstitial pneumonia (UIP) by two guidelines. Interobserver agreement of 2018 criteria showed moderate reliability (κ = 0.53) comparable to 2011 (κ = 0.56) but interobserver agreement for probable UIP was fair (κ = 0.40). CT pattern of indeterminate for UIP was associated with better prognosis compared with the other groups (adjusted hazard ratio [HR] = 0.36, p

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.

To identify clinical and staging chest CT characteristics predictive of brain metastasis in patients with newly diagnosed NSCLC dichotomized according to resectability. Patients newly diagnosed with NSCLC of clinical stages II–IV between November 2017 and October 2018 were enrolled and classified into resectable (stage II+IIIA) and unresectable stages (stage IIIB/C+IV) according to chest CT. Associations of clinicopathological characteristics and CT findings with brain metastasis were analyzed using logistic regression. Predictive models were evaluated using receiver operating characteristics curve analysis. A subgroup analysis for unresectable-stage patients with known epidermal growth factor receptor gene (EGFR) mutation status was performed. This study included 911 NSCLC patients (mean age, 65 ± 11 years; 620 men), 194 of whom were diagnosed with brain metastasis. For resectable stages, independent predictors for brain metastasis were N2-stage (13 of 25 patients), absence of air-bronchogram/bubble lucency (23 of 25 patients), and presence of spiculation (15 of 25 patients), with a model combining the two imaging features showing an AUC of 0.723. In unresectable stages, independent predictors of brain metastasis were younger age, female sex, extrathoracic metastasis, and adenocarcinoma, with models combining these showing AUCs of 0.675–0.766. In the subgroup with known EGFR-mutation status, extrathoracic metastasis and positive EGFR mutation were independent predictors of brain metastasis, with the model showing AUCs of 0.641–0.732. CT-derived imaging features, clinical stages, lung cancer subtype, and EGFR mutation were associated with brain metastasis in patients with newly diagnosed NSCLC. The predictors were completely different between resectable and unresectable stages. • In resectable stages of NSCLC, two imaging features (absence of air-bronchogram/bubble lucency and presence of spiculation) and N2 stage were independent predictors of brain metastasis. • In unresectable stages of NSCLC, younger age, female sex, extrathoracic metastasis, and adenocarcinoma were associated with brain metastasis. • In the subgroup of NSCLC with known EGFR-mutation status, extrathoracic metastasis and positive EGFR mutation were independent predictors of brain metastasis.

To determine whether sirolimus has beneficial effects on lymphangioleiomyomatosis (LAM) lung cysts in CT with long-term follow-up (FU) and to investigate whether CT is an appropriate imaging biomarker to monitor and evaluate LAM progression. In this retrospective study, 73 female patients diagnosed with definite LAM between May 2001 and June 2018 were included. Among these, 39 (53.4%) were treated with sirolimus. Quantitative and qualitative CT scoring for lung cysts (CS) were performed and compared between time points (baseline vs. FU at starting sirolimus, baseline vs. last FU, and FU at starting sirolimus vs. last FU for patients treated with sirolimus; baseline vs. last FU for patients without sirolimus). The correlation between CS at each time point and pulmonary function tests (PFTs) at each time point in the patients treated with sirolimus was also investigated. The quantitative and qualitative analyses and PFT results were compared between time points. In both quantitative and qualitative analyses, CS significantly increased from baseline to FU after starting sirolimus, and from baseline to last FU (all p

Background Krebs von den Lungen 6 (KL-6) is a sensitive marker for diagnosing, monitoring, and predicting the prognoses of interstitial lung diseases (ILDs). This study aimed to evaluate the performance of the Nanopia KL-6 assay (Sekisui Medical, Tokyo, Japan) and to test the relationship between KL-6 concentrations and clinical results. Methods In total, 230 patients diagnosed as having ILDs were enrolled. All underwent high-resolution computed tomography (HRCT) followed by the pulmonary function test (PFT). We also enrolled 116 disease controls and 200 healthy controls. Evaluation of the Nanopia KL-6 assay involved determination of precision, linearity, and limit of quantification (LOQ). Results from the Nanopia KL-6 assay were compared with those from ELISA and correlated with the HRCT and PFT results. Results The within-laboratory precisions were

OBJECTIVE The aim of our study was to develop and validate a convolutional neural network (CNN) architecture to convert CT images reconstructed with one kernel to images with different reconstruction kernels without using a sinogram. MATERIALS AND METHODS This retrospective study was approved by the Institutional Review Board. Ten chest CT scans were performed and reconstructed with the B10f, B30f, B50f, and B70f kernels. The dataset was divided into six, two, and two examinations for training, validation, and testing, respectively. We constructed a CNN architecture consisting of six convolutional layers, each with a 3 × 3 kernel with 64 filter banks. Quantitative performance was evaluated using root mean square error (RMSE) values. To validate clinical use, image conversion was conducted on 30 additional chest CT scans reconstructed with the B30f and B50f kernels. The influence of image conversion on emphysema quantification was assessed with Bland-Altman plots. RESULTS Our scheme rapidly generated conversion results at the rate of 0.065 s/slice. Substantial reduction in RMSE was observed in the converted images in comparison with the original images with different kernels (mean reduction, 65.7%; range, 29.5-82.2%). The mean emphysema indices for B30f, B50f, converted B30f, and converted B50f were 5.4 ± 7.2%, 15.3 ± 7.2%, 5.9 ± 7.3%, and 16.8 ± 7.5%, respectively. The 95% limits of agreement between B30f and other kernels (B50f and converted B30f) ranged from -14.1% to -2.6% (mean, -8.3%) and -2.3% to 0.7% (mean, -0.8%), respectively. CONCLUSION CNN-based CT kernel conversion shows adequate performance with high accuracy and speed, indicating its potential clinical use.

To develop and validate a CT-based radiomic model to simultaneously diagnose anaplastic lymphoma kinase (ALK) rearrangements and epidermal growth factor receptor (EGFR) mutation status of lung adenocarcinoma and to assess whether peritumoural radiomic features add value in the prediction of mutation status.503 patients with pathologically proven lung adenocarcinoma containing information on the mutation status were retrospectively included. Intratumoural and peritumoural radiomic features of the primary lesion were extracted from CT. We proposed two-level stepwise binary radiomics-based classification models to diagnose ALK (step1) and EGFR mutation status (step2). The performance of proposed models and added value of peritumoural radiomic features were evaluated by using the areas under receiver operating characteristic curves (AUC) and Obuchowski index in the development and validation sets.Regarding the prediction of ALK rearrangement, the diagnostic performance of the intratumoural radiomic model showed the AUC of 0.77 and 0.68 for the development and validation sets, respectively. As for EGFR mutation, the diagnostic performance of the intratumoural radiomic model showed the AUCs of 0.64 and 0.62 for the development and validation sets, respectively. The radiomics added value to the model based on clinical features (development set [radiomics + clinical model vs. clinical model]: Obuchowski index, 0.76 vs. 0.66, p0.001; validation set: 0.69 vs. 0.61, p = 0.075). Adding peritumoural features resulted in no improvement in terms of model performance.The CT radiomics-based model allowed the simultaneous prediction of the presence of ALK and EGFR mutations while adding value to the clinical features.

Background A new clinical guideline for idiopathic pulmonary fibrosis (IPF) uses high-resolution computed tomography (HRCT) patterns for diagnostic purposes. However, it is unknown how they relate to the IPF clinical course. We aimed to investigate whether HRCT patterns could be used to predict lung function changes and survival in patients with IPF. Methods Clinical data were retrospectively reviewed in 337 patients with IPF (all biopsy-proven cases). HRCT patterns were classified according to the 2018 IPF diagnostic criteria. Results The median follow-up was 46.9 months. The mean age was 62.5 years, and 74.2% were men. Among the HRCT patterns, usual interstitial pneumonia (UIP), probable UIP, indeterminate for UIP, and an alternative diagnosis were identified in 163 (48.4%), 110 (32.6%), 33 (9.8%), and 31 (9.2%) patients, respectively. The indeterminate for UIP group showed higher lung function and exercise capacity and better prognosis than the other groups. They also had a lesser decline in lung function than the other groups during follow-up. In the multivariate Cox analysis, which was adjusted by age, smoking status, lung function, exercise capacity, and use of antifibrotic agents, indeterminate for UIP pattern was found to be an independent prognostic factor (hazard ratio 0.559, 95% confidence interval 0.335–0.933, P = 0.026). However, the probable UIP group had similar lung function changes and prognosis when compared the UIP group. Conclusions Our results suggest that indeterminate for UIP pattern on HRCT may predict a more favorable clinical course in patients with IPF, supporting the validity of the new IPF diagnostic guidelines.

Objective: To understand the status of pre-procedural safety practices in radiological examinations at radiology residency training institutions in various Asian regions. Methods: A questionnaire based on the Joint Commission International Accreditation Standards was electronically sent to 3 institutions each in 10 geographical regions across 9 Asian countries. Questions addressing 45 practices were divided into 3 categories. A five-tier scale with numerical scores was used to evaluate safety practices in each institution. Responses obtained from three institutions in the United States were used to validate the execution rate of each surveyed safety practice. Results: The institutional response rate was 70.0% (7 Asian regions, 21 institutions). 44 practices (all those surveyed except for the application of wrist tags for identifying patients with fall risks) were validated using the US participants. Overall, the Asian participants reached a consensus on 89% of the safety practices. Comparatively, most Asian participants did not routinely perform three pre-procedural practices in the examination appropriateness topic. Conclusion: Based on the responses from 21 participating Asian institutions, most routinely perform standard practices during radiological examinations except when it comes to examination appropriateness. This study can provide direction for safety policymakers scrutinizing and improving regional standards of care. Advances in knowledge: This is the first multicenter survey study to elucidate pre-procedural safety practices in radiological examinations in seven Asian regions.

To compare image quality and radiation dose between dual-energy subtraction (DES)–based bone suppression images (D-BSIs) and software-based bone suppression images (S-BSIs). Chest radiographs (CXRs) of forty adult patients were obtained with the two X-ray devices, one with DES and one with bone suppression software. Three image quality metrics (relative mean absolute error (RMAE), peak signal-to-noise ratio (PSNR), and structural similarity index (SSIM)) between original CXR and BSI for each of D-BSI and S-SBI groups were calculated for each bone and soft tissue areas. Two readers rated the visual image quality for original CXR and BSI for each of D-BSI and S-SBI groups. The dose area product (DAP) values were recorded. Paired t test was used to compare the image quality and DAP values between D-BSI and S-BSI groups. In bone areas, S-BSIs had better SSIM values than D-BSI (94.57 vs. 87.77) but worse RMAE and PSNR values (0.50 vs. 0.20; 20.93 vs. 34.37) (all p

To investigate whether CT slice thickness influences the performance of radiomics prognostic models in non-small-cell lung cancer (NSCLC) patients. CT images including 1-, 3-, and 5-mm slice thicknesses acquired from 311 patients who underwent surgical resection for NSCLC between May 2014 and December 2015 were evaluated. Tumor segmentation was performed on CT of each slice thickness and total 94 radiomics features (shape, tumor intensity, and texture) were extracted. The study population was temporally split into development (n = 185) and validation sets (n = 126) for prediction of disease-free survival (DFS). Three radiomics models were built from three different slice thickness datasets (Rad-1, Rad-3, and Rad-5), respectively. Model performance was assessed and compared in three slice thickness datasets and mixed slice thickness dataset using C-indices. In corresponding slice thickness datasets, the C-indices of Rad-1, Rad-3, and Rad-5 for prediction of DFS were 0.68, 0.70, and 0.68 in the development set, and 0.73, 0.73, and 0.76 in the validation set (p = 0.40–0.89 and 0.27–0.90, respectively). Performance of the models was not significantly changed when they were applied to different slice thicknesses data in the validation set (C-index, 0.73–0.76, 0.72–0.73, 0.75–0.76; p = 0.07–0.92). In the mixed slice thickness dataset, performances of the models were similar to or slightly lower than their performances in the corresponding slice thickness datasets (C-index, 0.72–0.75 vs. 0.73–0.76) in the validation set. The performance of radiomics models for predicting DFS in NSCLC patients was not significantly affected by CT slice thickness. • Three radiomics models based on 1-, 3-, and 5-mm CT datasets showed C-indices for predicting disease-free survival of 0.68–0.70 in the development set and 0.73–0.76 in the validation set, without statistical differences (p = 0.27–0.90). • Application of the radiomics models to different slice thickness datasets showed no significant differences in performance between the values in the prediction of disease-free survival (p = 0.07–0.99). • Three radiomics models based on 1-, 3-, and 5-mm CT datasets performed well in mixed slice thickness datasets, showing similar or slightly lower performances.

To evaluate the longitudinal changes of chest CT findings in patients with chronic hypersensitivity pneumonitis (HP) and identify risk factors for fibrotic progression and acute exacerbation (AE). This retrospective study included patients with chronic HP with follow-up CT. Baseline and serial follow-up CT were evaluated semi-quantitatively. Fibrosis score was defined as the sum of the area with reticulation and honeycombing. The modified CT pattern of Fleischner Society idiopathic pulmonary fibrosis diagnostic guidelines was evaluated. Cox proportional hazards regression was performed to determine significant variables associated with fibrotic progression and AEs. Of 91 patients, mean age was 59.1 years and 61.5% were women. The median follow-up period was 4.9 years. Seventy-nine patients (86.8%) showed fibrotic progression with persistent areas of mosaic attenuation, finally replaced by fibrosis, and 20 (22.0%) developed AE. Baseline fibrosis score and CT pattern of usual interstitial pneumonia (UIP)/probable UIP were independent risk factors for predicting fibrotic progression (hazard ratio [HR] = 1.05, 95% confidence interval [CI] = 1.02–1.09, p < 0.001, for fibrosis score; HR = 2.50, CI = 1.50–4.16, p < 0.001, for CT pattern) and AEs (HR = 1.07, CI = 1.01–1.13, p = 0.019, for fibrosis score; HR = 5.47, CI = 1.23–24.45, p = 0.026, for CT pattern) after adjusting clinical covariables. Fibrotic progression and AE were identified in 86.8% and 22.0% of patients with chronic HP. Fibrosis score and CT pattern of UIP/probable UIP on baseline chest CT may predict fibrotic progression and AE. • Most patients (87%) showed fibrotic progression on long-term follow-up with persistent areas of mosaic attenuation that were finally replaced by fibrosis at a later stage. • One-fifth of patients (22%) experienced acute exacerbation associated with worse prognosis. • Fibrosis score (sum of reticulation and honeycombing) and CT pattern of UIP/probable UIP on baseline CT were independent predictors for predicting fibrotic progression and acute exacerbation.

Disease progression (DP) in interstitial lung disease (ILD) is variable and difficult to predict. In previous reports, serum Krebs von den Lungen-6 (KL-6) was suggested to be useful in diagnosing and predicting survival in ILD. The aim of our study was to investigate the usefulness of serum KL-6 as a predictor of DP in ILD. Clinical data of 199 patients with ILD (idiopathic pulmonary fibrosis: 22.8%) were prospectively collected and serum KL-6 levels were measured. DP was defined as a relative decline in forced vital capacity (FVC) ≥ 10%, acute exacerbation, or death during follow-up. The median follow-up period was 11.1 months. The mean age of the subjects was 62.2 years, and 59.8% were male. DP occurred in 21.6% of patients. The progressed group showed lower FVC, lower diffusing capacity for carbon monoxide, lower the minimum oxygen saturation during the 6-minute walk test, higher fibrosis scores on high-resolution computed tomography, and higher KL-6 levels (826.3 vs. 629.0 U/mL; p < 0.001) than those of the non-progressed group. In receiver operating characteristic curve analysis, serum KL-6 levels were a significant predictor of DP in ILD (area under the curve = 0.629, p = 0.009, and the optimal cut-off level was 811 U/mL). In multivariable Cox analysis, high serum KL-6 levels (≥ 800 U/mL) were only independently associated with DP in ILD (HR 2.689, 95% CI 1.445–5.004, P = 0.002). Serum KL-6 levels might be useful to predict DP in patients with ILD.

In 2014, the American College of Radiology (ACR) announced the guideline for the appropriate diagnostic approach and treatment of patients according to the severity of hemoptysis and risk for lung cancer. However, the application of the ACR guideline in Korea may not be appropriate, because many patients in Korea have active tuberculosis or pulmonary fibrosis due to previous tuberculosis. The Korean Society of Radiology and Korean Society of Thoracic Radiology have proposed a new guideline suitable for Korean practice. This new guideline was prepared through the consensus of a development committee, working party, and an advisory committee. The guideline proposal process was based on an evidence-based clinical imaging guideline proposed by the development committee. Clinical imaging guideline for adult patients with hemoptysis is as follows: Chest radiography is an initial imaging modality to evaluate hemoptysis. Contrast-enhanced chest CT is recommended in patients with two risk factors for lung cancer (> 40 years old and > 30 pack-year smoking history), moderate hemoptysis (> 30 mL/24 hours) or recurrent hemoptysis. Contrast-enhanced chest CT is also recommended in patients with massive hemoptysis (> 400 mL/24 hours) without cardiopulmonary compromise.