Chest Radiography of Tuberculosis: Determination of Activity Using Deep Learning Algorithm / 결핵및호흡기질환

Background@#Inactive or old, healed tuberculosis (TB) on chest radiograph (CR) is often found in high TB incidence countries, and to avoid unnecessary evaluation and medication, differentiation from active TB is important. This study develops a deep learning (DL) model to estimate activity in a single chest radiographic analysis. @*Methods@#A total of 3,824 active TB CRs from 511 individuals and 2,277 inactive TB CRs from 558 individuals were retrospectively collected. A pretrained convolutional neural network was fine-tuned to classify active and inactive TB. The model was pretrained with 8,964 pneumonia and 8,525 normal cases from the National Institute of Health (NIH) dataset. During the pretraining phase, the DL model learns the following tasks: pneumonia vs. normal, pneumonia vs. active TB, and active TB vs. normal. The performance of the DL model was validated using three external datasets. Receiver operating characteristic analyses were performed to evaluate the diagnostic performance to determine active TB by DL model and radiologists. Sensitivities and specificities for determining active TB were evaluated for both the DL model and radiologists. @*Results@#The performance of the DL model showed area under the curve (AUC) values of 0.980 in internal validation, and 0.815 and 0.887 in external validation. The AUC values for the DL model, thoracic radiologist, and general radiologist, evaluated using one of the external validation datasets, were 0.815, 0.871, and 0.811, respectively. @*Conclusion@#This DL-based algorithm showed potential as an effective diagnostic tool to identify TB activity, and could be useful for the follow-up of patients with inactive TB in high TB burden countries.

Effects of Fasting versus Non-Fasting on Emetic Complications in Radiological Examinations Using Intravascular Non-Ionic Iodinated Contrast Media:A Systematic Review and Meta-Analysis

Objective@#To compare the incidence of aspiration pneumonia, nausea, and vomiting after intravascular administration of nonionic iodinated contrast media (ICM) between patients who fasted before contrast injection and those who did not. @*Materials and Methods@#Ovid-MEDLINE and Embase databases were searched from their inception dates until September 2022 to identify original articles that met the following criteria: 1) randomized controlled trials or observational studies, 2) separate reports of the incidence of aspiration pneumonia, nausea, and vomiting after intravascular injection of non-ionic ICM, and 3) inclusion of patients undergoing radiological examinations without fasting. A bivariate beta-binomial model was used to compare the risk difference in adverse events between fasting and non-fasting groups. The I2 statistic was used to assess heterogeneity across the studies. @*Results@#Ten studies, encompassing 308013 patients (non-fasting, 158442), were included in this meta-analysis. No cases of aspiration pneumonia were reported. The pooled incidence of nausea was 4.6% (95% confidence interval [CI]: 1.4%, 7.8%) in the fasting group and 4.6% (95% CI: 1.1%, 8.1%) in the non-fasting group. The pooled incidence of vomiting was 2.1% (95% CI: 0.0%, 4.2%) in the fasting group and 2.5% (95% CI: 0.7%, 4.2%) in the non-fasting group. The risk difference (incidence in the non-fasting group–incidence in the fasting group) in the incidence of nausea and vomiting was 0.0% (95% CI: -4.7%, 4.7%) and 0.4% (95% CI: -2.3%, 3.1%), respectively. Heterogeneity between the studies was low (I2 = 0%–13.5%). @*Conclusion@#Lack of fasting before intravascular administration of non-ionic ICM for radiological examinations did not increase the risk of emetic complications significantly. This finding suggests that hospitals can relax fasting policies without compromising patient safety.

Generative Adversarial Network-Based Image Conversion Among Different Computed Tomography Protocols and Vendors: Effects on Accuracy and Variability in Quantifying Regional Disease Patterns of Interstitial Lung Disease

Objective@#To assess whether computed tomography (CT) conversion across different scan parameters and manufacturers using a routable generative adversarial network (RouteGAN) can improve the accuracy and variability in quantifying interstitial lung disease (ILD) using a deep learning-based automated software. @*Materials and Methods@#This study included patients with ILD who underwent thin-section CT. Unmatched CT images obtained using scanners from four manufacturers (vendors A-D), standard- or low-radiation doses, and sharp or medium kernels were classified into groups 1–7 according to acquisition conditions. CT images in groups 2–7 were converted into the target CT sty le (Group 1: vendor A, standard dose, and sharp kernel) using a RouteGAN. ILD was quantified on original and converted CT images using a deep learning-based software (Aview, Coreline Soft). The accuracy of quantification was analyzed using the dice similarity coefficient (DSC) and pixel-wise overlap accuracy metrics against manual quantification by a radiologist. Five radiologists evaluated quantification accuracy using a 10-point visual scoring system. @*Results@#Three hundred and fifty CT slices from 150 patients (mean age: 67.6 ± 10.7 years; 56 females) were included. The overlap accuracies for quantifying total abnormalities in groups 2–7 improved after CT conversion (original vs. converted: 0.63vs. 0.68 for DSC, 0.66 vs. 0.70 for pixel-wise recall, and 0.68 vs. 0.73 for pixel-wise precision; P < 0.002 for all). The DSCs of fibrosis score, honeycombing, and reticulation significantly increased after CT conversion (0.32 vs. 0.64, 0.19 vs. 0.47, and 0.23 vs. 0.54, P < 0.002 for all), whereas those of ground-glass opacity, consolidation, and emphysema did not change significantly or decreased slightly. The radiologists’ scores were significantly higher (P < 0.001) and less variable on converted CT. @*Conclusion@#CT conversion using a RouteGAN can improve the accuracy and variability of CT images obtained using different scan parameters and manufacturers in deep learning-based quantification of ILD.

A Critical Systematic Review for Inhaled Corticosteroids on Lung Cancer Incidence: Not Yet Concluded Story / 결핵및호흡기질환

Background@#To systematically review studies on inhaled corticosteroids (ICS) and lung cancer incidence in chronic airway disease patients. @*Methods@#We conducted electronic bibliographic searches on OVID-MEDLINE, EM- BASE, and the Cochrane Database before May 2020 to identify relevant studies. Detailed data on the study population, exposure, and outcome domains were reviewed. @*Results@#Of 4,058 screened publications, 13 eligible studies in adults with chronic obstructive pulmonary disease (COPD) or asthma evaluated lung cancer incidence after ICS exposure. Pooled hazard ratio and odds ratio for developing lung cancer in ICS exposure were 0.81 (95% confidence interval, 0.64 to 1.02; I2=95.7%) from 10 studies and 1.02 (95% confidence interval 0.50 to 2.07; I2=94.7%) from three studies. Meta-regression failed to explain the substantial heterogeneity of pooled estimates. COPD and asthma were variously defined without spirometry in 11 studies. Regarding exposure assessment, three and 10 studies regarded ICS exposure as a time-dependent and fixed variable, respectively. Some studies assessed ICS use for the entire study period, whereas others assessed ICS use for 6 months to 2 years within or before study entry. Smoking was adjusted in four studies, and only four studies introduced 1 to 2 latency years in their main or subgroup analysis. @*Conclusion@#Studies published to date on ICS and lung cancer incidence had heterogeneous study populations, exposures, and outcome assessments, limiting the generation of a pooled conclusion. The beneficial effect of ICS on lung cancer incidence has not yet been established, and understanding the heterogeneities will help future researchers to establish robust evidence on ICS and lung cancer incidence.

Deep Learning-Based Computed Tomography Image Standardization to Improve Generalizability of Deep Learning-Based Hepatic Segmentation

Objective@#We aimed to investigate whether image standardization using deep learning-based computed tomography (CT) image conversion would improve the performance of deep learning-based automated hepatic segmentation across various reconstruction methods. @*Materials and Methods@#We collected contrast-enhanced dual-energy CT of the abdomen that was obtained using various reconstruction methods, including filtered back projection, iterative reconstruction, optimum contrast, and monoenergetic images with 40, 60, and 80 keV. A deep learning based image conversion algorithm was developed to standardize the CT images using 142 CT examinations (128 for training and 14 for tuning). A separate set of 43 CT examinations from 42 patients (mean age, 10.1 years) was used as the test data. A commercial software program (MEDIP PRO v2.0.0.0, MEDICALIP Co. Ltd.) based on 2D U-NET was used to create liver segmentation masks with liver volume. The original 80 keV images were used as the ground truth. We used the paired t-test to compare the segmentation performance in the Dice similarity coefficient (DSC) and difference ratio of the liver volume relative to the ground truth volume before and after image standardization. The concordance correlation coefficient (CCC) was used to assess the agreement between the segmented liver volume and ground-truth volume. @*Results@#The original CT images showed variable and poor segmentation performances. The standardized images achieved significantly higher DSCs for liver segmentation than the original images (DSC [original, 5.40%–91.27%] vs. [standardized, 93.16%–96.74%], all P < 0.001). The difference ratio of liver volume also decreased significantly after image conversion (original, 9.84%–91.37% vs. standardized, 1.99%–4.41%). In all protocols, CCCs improved after image conversion (original, -0.006–0.964 vs. standardized, 0.990–0.998). @*Conclusion@#Deep learning-based CT image standardization can improve the performance of automated hepatic segmentation using CT images reconstructed using various methods. Deep learning-based CT image conversion may have the potential to improve the generalizability of the segmentation network.

Impact of Mediastinal Lymphadenopathy on the Severity of COVID-19 Pneumonia: A Nationwide Multicenter Cohort Study

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.

CT Examinations for COVID-19: A Systematic Review of Protocols, Radiation Dose, and Numbers Needed to Diagnose and Predict

Purpose@#Although chest CT has been discussed as a first-line test for coronavirus disease 2019 (COVID-19), little research has explored the implications of CT exposure in the population. To review chest CT protocols and radiation doses in COVID-19 publications and explore the number needed to diagnose (NND) and the number needed to predict (NNP) if CT is used as a first-line test. @*Materials and Methods@#We searched nine highly cited radiology journals to identify studies discussing the CT-based diagnosis of COVID-19 pneumonia. Study-level information on the CT protocol and radiation dose was collected, and the doses were compared with each national diagnostic reference level (DRL). The NND and NNP, which depends on the test positive rate (TPR), were calculated, given a CT sensitivity of 94% (95% confidence interval [CI]: 91%–96%) and specificity of 37% (95% CI: 26%–50%), and applied to the early outbreak in Wuhan, New York, and Italy. @*Results@#From 86 studies, the CT protocol and radiation dose were reported in 81 (94.2%) and 17 studies (19.8%), respectively. Low-dose chest CT was used more than twice as often as standarddose chest CT (39.5% vs.18.6%), while the remaining studies (44.2%) did not provide relevant information. The radiation doses were lower than the national DRLs in 15 of the 17 studies (88.2%) that reported doses. The NND was 3.2 scans (95% CI: 2.2–6.0). The NNPs at TPRs of 50%, 25%, 10%, and 5% were 2.2, 3.6, 8.0, 15.5 scans, respectively. In Wuhan, 35418 (TPR, 58%; 95% CI: 27710–56755) to 44840 (TPR, 38%; 95% CI: 35161–68164) individuals were estimated to have undergone CT examinations to diagnose 17365 patients. During the early surge in New York and Italy, daily NNDs changed up to 5.4 and 10.9 times, respectively, within 10 weeks. @*Conclusion@#Low-dose CT protocols were described in less than half of COVID-19 publications, and radiation doses were frequently lacking. The number of populations involved in a first-line diagnostic CT test could vary dynamically according to daily TPR; therefore, caution is required in future planning.

Renal Safety of Repeated Intravascular Administrations of Iodinated or Gadolinium-Based Contrast Media within a Short Interval

Objective@#We aimed to investigate whether repeated intravascular administration of iodinated contrast media (ICM) or gadolinium-based contrast agents (GBCAs) within a short interval was associated with an increased risk of post-contrast acute kidney injury (PC-AKI). @*Materials and Methods@#This retrospective study included 300 patients (mean age ± standard deviation, 68.5 ± 8.1 years; 131 male and 169 female) who had undergone at least one ICM-enhanced perfusion brain CT scan, had their baseline and follow-up serum creatinine levels available, and had not undergone additional contrast-enhanced examinations 72 hours before and after a time window of interest were included. The study population was divided into three groups: single-dose group and groups of patients who had received multiple contrast administrations in the time window of interest with the minimum contrast repeat interval either within 4 hours (0–4-hour group) or between 4 to 48 hours (4–48-hour group).Multivariable logistic regression analysis was conducted to evaluate the association between AKI and repeated ICM administrations. A similar supplementary analysis was performed including both ICM and GBCA. @*Results@#When ICM was only considered ignoring GBCA, among 300 patients, 207 patients received a single dose of ICM, 58 had repeated doses within 4 hours (0–4-hour group), and 35 patients had repeated doses between 4 to 48 hours (4–48-hour group). Most patients (> 95%) had a baseline estimated glomerular filtration rate (eGFR) of ≥ 30 mL/min/1.73 m2 . AKI occurred in 7.2%, 13.8%, and 8.6% of patients in the single-dose, 0–4-hour, and 4–48-hour groups, respectively. In the 0–4-hour and 4–48-hour groups, additional exposure to ICM was not associated with AKI after adjusting for comorbidities and nephrotoxic drugs (all p values > 0.05). @*Conclusion@#Repeated intravascular administrations of ICM within a short interval did not increase the risk of AKI in our study patients suspected of acute stroke with a baseline eGFR of ≥ 30 mL/min/1.73 m2 .

Cone-Beam CT-Guided Percutaneous Transthoracic Needle Lung Biopsy of Juxtaphrenic Lesions:Diagnostic Accuracy and Complications

Objective@#To investigate the diagnostic accuracy and complications of cone-beam CT-guided percutaneous transthoracic needle biopsy (PTNB) of juxtaphrenic lesions and identify the risk factors for diagnostic failure and complications. @*Materials and Methods@#In total, 336 PTNB procedures for lung lesions (mean size ± standard deviation [SD], 4.3 ± 2.3 cm) abutting the diaphragm in 326 patients (189 male and 137 female; mean age ± SD, 65.2 ± 11.4 years) performed between January 2010 and December 2014 were included. The accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the PTNB procedures for the diagnosis of malignancy were measured based on the intentionto-diagnose principle. The risk factors for diagnostic failures and complications were evaluated using logistic regression analysis. @*Results@#The accuracy, sensitivity, specificity, PPV, and NPV were 92.7% (293/316), 91.3% (219/240), 91.4% (74/81), 96.9% (219/226), and 77.9% (74/95), respectively. There were 23 diagnostic failures (7.3%), and lesion sizes ≤ 2 cm (p = 0.045) were the only significant risk factors for diagnostic failure. Complications occurred in 98 cases (29.2%), including 89 cases of pneumothorax (26.5%) and 7 cases of hemoptysis (2.1%). The multivariable analysis showed that old age (> 65 years) (p = 0.002), lesion size of ≤ 2 cm (p = 0.003), emphysema (p = 0.006), and distance from the pleura to the target lesion (> 2 cm) (p = 0.010) were significant risk factors for complications. @*Conclusion@#The diagnostic accuracy of cone-beam CT-guided PTNB of juxtaphrenic lesions for malignancy was fairly high, and the target lesion size was the only significant predictor of diagnostic failure. Complications of cone-beam CT-guided PTNB of juxtaphrenic lesions occurred at a reasonable rate.

Korean Clinical Imaging Guidelines for the Appropriate Use of Chest MRI

MRI has the advantages of having excellent soft-tissue contrast and providing functional information without any harmful ionizing radiation. Although previous technical limitations restricted the use of chest MRI, recent technological advances and expansion of insurance coverage are increasing the demand for chest MRI. Recognizing the need for guidelines on appropriate use of chest MRI in Korean clinical settings, the Korean Society of Radiology has composed a development committee, working committee, and advisory committee to develop Korean chest MRI justification guidelines. Five key questions were selected and recommendations have been made with the evidence-based clinical imaging guideline adaptation methodology.Recommendations are as follows. Chest MRI can be considered in the following circumstances:for patients with incidentally found anterior mediastinal masses to exclude non-neoplastic conditions, for pneumoconiosis patients with lung masses to differentiate progressive massive fibrosis from lung cancer, and when invasion of the chest wall, vertebrae, diaphragm, or major vessels by malignant pleural mesothelioma or non-small cell lung cancer is suspected. Chest MRI without contrast enhancement or with minimal dose low-risk contrast media can be considered for pregnant women with suspected pulmonary embolism. Lastly, chest MRI is recommended for patients with pancoast tumors planned for radical surgery.

Renal Safety of Repeated Intravascular Administrations of Iodinated or Gadolinium-Based Contrast Media within a Short Interval

Objective@#We aimed to investigate whether repeated intravascular administration of iodinated contrast media (ICM) or gadolinium-based contrast agents (GBCAs) within a short interval was associated with an increased risk of post-contrast acute kidney injury (PC-AKI). @*Materials and Methods@#This retrospective study included 300 patients (mean age ± standard deviation, 68.5 ± 8.1 years; 131 male and 169 female) who had undergone at least one ICM-enhanced perfusion brain CT scan, had their baseline and follow-up serum creatinine levels available, and had not undergone additional contrast-enhanced examinations 72 hours before and after a time window of interest were included. The study population was divided into three groups: single-dose group and groups of patients who had received multiple contrast administrations in the time window of interest with the minimum contrast repeat interval either within 4 hours (0–4-hour group) or between 4 to 48 hours (4–48-hour group).Multivariable logistic regression analysis was conducted to evaluate the association between AKI and repeated ICM administrations. A similar supplementary analysis was performed including both ICM and GBCA. @*Results@#When ICM was only considered ignoring GBCA, among 300 patients, 207 patients received a single dose of ICM, 58 had repeated doses within 4 hours (0–4-hour group), and 35 patients had repeated doses between 4 to 48 hours (4–48-hour group). Most patients (> 95%) had a baseline estimated glomerular filtration rate (eGFR) of ≥ 30 mL/min/1.73 m2 . AKI occurred in 7.2%, 13.8%, and 8.6% of patients in the single-dose, 0–4-hour, and 4–48-hour groups, respectively. In the 0–4-hour and 4–48-hour groups, additional exposure to ICM was not associated with AKI after adjusting for comorbidities and nephrotoxic drugs (all p values > 0.05). @*Conclusion@#Repeated intravascular administrations of ICM within a short interval did not increase the risk of AKI in our study patients suspected of acute stroke with a baseline eGFR of ≥ 30 mL/min/1.73 m2 .

Cone-Beam CT-Guided Percutaneous Transthoracic Needle Lung Biopsy of Juxtaphrenic Lesions:Diagnostic Accuracy and Complications

Objective@#To investigate the diagnostic accuracy and complications of cone-beam CT-guided percutaneous transthoracic needle biopsy (PTNB) of juxtaphrenic lesions and identify the risk factors for diagnostic failure and complications. @*Materials and Methods@#In total, 336 PTNB procedures for lung lesions (mean size ± standard deviation [SD], 4.3 ± 2.3 cm) abutting the diaphragm in 326 patients (189 male and 137 female; mean age ± SD, 65.2 ± 11.4 years) performed between January 2010 and December 2014 were included. The accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the PTNB procedures for the diagnosis of malignancy were measured based on the intentionto-diagnose principle. The risk factors for diagnostic failures and complications were evaluated using logistic regression analysis. @*Results@#The accuracy, sensitivity, specificity, PPV, and NPV were 92.7% (293/316), 91.3% (219/240), 91.4% (74/81), 96.9% (219/226), and 77.9% (74/95), respectively. There were 23 diagnostic failures (7.3%), and lesion sizes ≤ 2 cm (p = 0.045) were the only significant risk factors for diagnostic failure. Complications occurred in 98 cases (29.2%), including 89 cases of pneumothorax (26.5%) and 7 cases of hemoptysis (2.1%). The multivariable analysis showed that old age (> 65 years) (p = 0.002), lesion size of ≤ 2 cm (p = 0.003), emphysema (p = 0.006), and distance from the pleura to the target lesion (> 2 cm) (p = 0.010) were significant risk factors for complications. @*Conclusion@#The diagnostic accuracy of cone-beam CT-guided PTNB of juxtaphrenic lesions for malignancy was fairly high, and the target lesion size was the only significant predictor of diagnostic failure. Complications of cone-beam CT-guided PTNB of juxtaphrenic lesions occurred at a reasonable rate.

Korean Clinical Imaging Guidelines for the Appropriate Use of Chest MRI

MRI has the advantages of having excellent soft-tissue contrast and providing functional information without any harmful ionizing radiation. Although previous technical limitations restricted the use of chest MRI, recent technological advances and expansion of insurance coverage are increasing the demand for chest MRI. Recognizing the need for guidelines on appropriate use of chest MRI in Korean clinical settings, the Korean Society of Radiology has composed a development committee, working committee, and advisory committee to develop Korean chest MRI justification guidelines. Five key questions were selected and recommendations have been made with the evidence-based clinical imaging guideline adaptation methodology.Recommendations are as follows. Chest MRI can be considered in the following circumstances:for patients with incidentally found anterior mediastinal masses to exclude non-neoplastic conditions, for pneumoconiosis patients with lung masses to differentiate progressive massive fibrosis from lung cancer, and when invasion of the chest wall, vertebrae, diaphragm, or major vessels by malignant pleural mesothelioma or non-small cell lung cancer is suspected. Chest MRI without contrast enhancement or with minimal dose low-risk contrast media can be considered for pregnant women with suspected pulmonary embolism. Lastly, chest MRI is recommended for patients with pancoast tumors planned for radical surgery.

Volume and Mass Doubling Time of Lung Adenocarcinoma according to WHO Histologic Classification

Objective@#This study aimed to evaluate the tumor doubling time of invasive lung adenocarcinoma according to the International Association of the Study for Lung Cancer (IASLC)/American Thoracic Society (ATS)/European Respiratory Society (ERS) histologic classification. @*Materials and Methods@#Among the 2905 patients with surgically resected lung adenocarcinoma, we retrospectively included 172 patients (mean age, 65.6 ± 9.0 years) who had paired thin-section non-contrast chest computed tomography (CT) scans at least 84 days apart with the same CT parameters, along with 10 patients with squamous cell carcinoma (mean age, 70.9 ± 7.4 years) for comparison. Three-dimensional semiautomatic segmentation of nodules was performed to calculate the volume doubling time (VDT), mass doubling time (MDT), and specific growth rate (SGR) of volume and mass. Multivariate linear regression, one-way analysis of variance, and receiver operating characteristic curve analyses were performed. @*Results@#The median VDT and MDT of lung cancers were as follows: acinar, 603.2 and 639.5 days; lepidic, 1140.6 and 970.1 days; solid/micropapillary, 232.7 and 221.8 days; papillary, 599.0 and 624.3 days; invasive mucinous, 440.7 and 438.2 days; and squamous cell carcinoma, 149.1 and 146.1 days, respectively. The adjusted SGR of volume and mass of the solid-/ micropapillary-predominant subtypes were significantly shorter than those of the acinar-, lepidic-, and papillary-predominant subtypes. The histologic subtype was independently associated with tumor doubling time. A VDT of 465.2 days and an MDT of 437.5 days yielded areas under the curve of 0.791 and 0.795, respectively, for distinguishing solid-/micropapillary-predominant subtypes from other subtypes of lung adenocarcinoma. @*Conclusion@#The tumor doubling time of invasive lung adenocarcinoma differed according to the IASCL/ATS/ERS histologic classification.

Automated Lung Segmentation on Chest Computed Tomography Images with Extensive Lung Parenchymal Abnormalities Using a Deep Neural Network

Objective@#We aimed to develop a deep neural network for segmenting lung parenchyma with extensive pathological conditions on non-contrast chest computed tomography (CT) images. @*Materials and Methods@#Thin-section non-contrast chest CT images from 203 patients (115 males, 88 females; age range, 31–89 years) between January 2017 and May 2017 were included in the study, of which 150 cases had extensive lung parenchymal disease involving more than 40% of the parenchymal area. Parenchymal diseases included interstitial lung disease (ILD), emphysema, nontuberculous mycobacterial lung disease, tuberculous destroyed lung, pneumonia, lung cancer, and other diseases. Five experienced radiologists manually drew the margin of the lungs, slice by slice, on CT images. The dataset used to develop the network consisted of 157 cases for training, 20 cases for development, and 26 cases for internal validation. Two-dimensional (2D) U-Net and three-dimensional (3D) U-Net models were used for the task. The network was trained to segment the lung parenchyma as a whole and segment the right and left lung separately. The University Hospitals of Geneva ILD dataset, which contained high-resolution CT images of ILD, was used for external validation. @*Results@#The Dice similarity coefficients for internal validation were 99.6 ± 0.3% (2D U-Net whole lung model), 99.5 ± 0.3% (2D U-Net separate lung model), 99.4 ± 0.5% (3D U-Net whole lung model), and 99.4 ± 0.5% (3D U-Net separate lung model).The Dice similarity coefficients for the external validation dataset were 98.4 ± 1.0% (2D U-Net whole lung model) and 98.4 ± 1.0% (2D U-Net separate lung model). In 31 cases, where the extent of ILD was larger than 75% of the lung parenchymal area, the Dice similarity coefficients were 97.9 ± 1.3% (2D U-Net whole lung model) and 98.0 ± 1.2% (2D U-Net separate lung model). @*Conclusion@#The deep neural network achieved excellent performance in automatically delineating the boundaries of lung parenchyma with extensive pathological conditions on non-contrast chest CT images.

2020 Clinical Practice Guideline for Percutaneous Transthoracic Needle Biopsy of Pulmonary Lesions: A Consensus Statement and Recommendations of the Korean Society of Thoracic Radiology

Percutaneous transthoracic needle biopsy (PTNB) is one of the essential diagnostic procedures for pulmonary lesions. Its role is increasing in the era of CT screening for lung cancer and precision medicine. The Korean Society of Thoracic Radiology developed the first evidence-based clinical guideline for PTNB in Korea by adapting pre-existing guidelines. The guideline provides 39 recommendations for the following four main domains of 12 key questions: the indications for PTNB, pre-procedural evaluation, procedural technique of PTNB and its accuracy, and management of post-biopsy complications. We hope that these recommendations can improve the diagnostic accuracy and safety of PTNB in clinical practice and promote standardization of the procedure nationwide.

Tissue Adequacy and Safety of Percutaneous Transthoracic Needle Biopsy for Molecular Analysis in Non-Small Cell Lung Cancer: A Systematic Review and Meta-analysis

Objective@#We conducted a systematic review and meta-analysis of the tissue adequacy and complication rates of percutaneous transthoracic needle biopsy (PTNB) for molecular analysis in patients with non-small cell lung cancer (NSCLC). @*Materials and Methods@#We performed a literature search of the OVID-MEDLINE and Embase databases to identify original studies on the tissue adequacy and complication rates of PTNB for molecular analysis in patients with NSCLC published between January 2005 and January 2020. Inverse variance and random-effects models were used to evaluate and acquire meta-analytic estimates of the outcomes. To explore heterogeneity across the studies, univariable and multivariable metaregression analyses were performed. @*Results@#A total of 21 studies with 2232 biopsies (initial biopsy, 8 studies; rebiopsy after therapy, 13 studies) were included.The pooled rates of tissue adequacy and complications were 89.3% (95% confidence interval [CI]: 85.6%–92.6%; I2 = 0.81) and 17.3% (95% CI: 12.1%–23.1%; I2 = 0.89), respectively. These rates were 93.5% and 22.2% for the initial biopsies and 86.2% and 16.8% for the rebiopsies, respectively. Severe complications, including pneumothorax requiring chest tube placement and massive hemoptysis, occurred in 0.7% of the cases (95% CI: 0%–2.2%; I2 = 0.67). Multivariable meta-regression analysis showed that the tissue adequacy rate was not significantly lower in studies on rebiopsies (p = 0.058). The complication rate was significantly higher in studies that preferentially included older adults (p = 0.001). @*Conclusion@#PTNB demonstrated an average tissue adequacy rate of 89.3% for molecular analysis in patients with NSCLC, with a complication rate of 17.3%. PTNB is a generally safe and effective diagnostic procedure for obtaining tissue samples for molecular analysis in NSCLC. Rebiopsy may be performed actively with an acceptable risk of complications if clinically required.

Implementation of a Deep Learning-Based ComputerAided Detection System for the Interpretation of Chest Radiographs in Patients Suspected for COVID-19

Objective@#To describe the experience of implementing a deep learning-based computer-aided detection (CAD) system for the interpretation of chest X-ray radiographs (CXR) of suspected coronavirus disease (COVID-19) patients and investigate the diagnostic performance of CXR interpretation with CAD assistance. @*Materials and Methods@#In this single-center retrospective study, initial CXR of patients with suspected or confirmed COVID-19 were investigated. A commercialized deep learning-based CAD system that can identify various abnormalities on CXR was implemented for the interpretation of CXR in daily practice. The diagnostic performance of radiologists with CAD assistance were evaluated based on two different reference standards: 1) real-time reverse transcriptase-polymerase chain reaction (rRT-PCR) results for COVID-19 and 2) pulmonary abnormality suggesting pneumonia on chest CT. The turnaround times (TATs) of radiology reports for CXR and rRT-PCR results were also evaluated. @*Results@#Among 332 patients (male:female, 173:159; mean age, 57 years) with available rRT-PCR results, 16 patients (4.8%) were diagnosed with COVID-19. Using CXR, radiologists with CAD assistance identified rRT-PCR positive COVID-19 patients with sensitivity and specificity of 68.8% and 66.7%, respectively. Among 119 patients (male:female, 75:44; mean age, 69 years) with available chest CTs, radiologists assisted by CAD reported pneumonia on CXR with a sensitivity of 81.5% and a specificity of 72.3%. The TATs of CXR reports were significantly shorter than those of rRT-PCR results (median 51 vs. 507 minutes; p < 0.001). @*Conclusion@#Radiologists with CAD assistance could identify patients with rRT-PCR-positive COVID-19 or pneumonia on CXR with a reasonably acceptable performance. In patients suspected with COVID-19, CXR had much faster TATs than rRT-PCRs.

Establishment of a Nationwide Korean Imaging Cohort of Coronavirus Disease 2019

Background@#The Korean Society of Thoracic Radiology (KSTR) recently constructed a nation-wide coronavirus disease 2019 (COVID-19) database and imaging repository, referred to the Korean imaging cohort of COVID-19 (KICC-19) based on the collaborative efforts of its members. The purpose of this study was to provide a summary of the clinico-epidemiological data and imaging data of the KICC-19. @*Methods@#The KSTR members at 17 COVID-19 referral centers retrospectively collected imaging data and clinical information of consecutive patients with reverse transcription polymerase chain reaction-proven COVID-19 in respiratory specimens from February 2020 through May 2020 who underwent diagnostic chest computed tomography (CT) or radiograph in each participating hospital. @*Results@#The cohort consisted of 239 men and 283 women (mean age, 52.3 years; age range, 11–97 years). Of the 522 subjects, 201 (38.5%) had an underlying disease. The most common symptoms were fever (n = 292) and cough (n = 245). The 151 patients (28.9%) had lymphocytopenia, 86 had (16.5%) thrombocytopenia, and 227 patients (43.5%) had an elevated CRP at admission. The 121 (23.4%) needed nasal oxygen therapy or mechanical ventilation (n = 38; 7.3%), and 49 patients (9.4%) were admitted to an intensive care unit.Although most patients had cured, 21 patients (4.0%) died. The 465 (89.1%) subjects underwent a low to standard-dose chest CT scan at least once during hospitalization, resulting in a total of 658 CT scans. The 497 subjects (95.2%) underwent chest radiography at least once during hospitalization, which resulted in a total of 1,475 chest radiographs. @*Conclusion@#The KICC-19 was successfully established and comprised of 658 CT scans and 1,475 chest radiographs of 522 hospitalized Korean COVID-19 patients. The KICC-19 will provide a more comprehensive understanding of the clinical, epidemiological, and radiologic characteristics of patients with COVID-19.

Chest Radiographic and CT Findings of the 2019 Novel Coronavirus Disease (COVID-19): Analysis of Nine Patients Treated in Korea

OBJECTIVE: This study presents a preliminary report on the chest radiographic and computed tomography (CT) findings of the 2019 novel coronavirus disease (COVID-19) pneumonia in Korea.MATERIALS AND METHODS: As part of a multi-institutional collaboration coordinated by the Korean Society of Thoracic Radiology, we collected nine patients with COVID-19 infections who had undergone chest radiography and CT scans. We analyzed the radiographic and CT findings of COVID-19 pneumonia at baseline. Fisher's exact test was used to compare CT findings depending on the shape of pulmonary lesions.RESULTS: Three of the nine patients (33.3%) had parenchymal abnormalities detected by chest radiography, and most of the abnormalities were peripheral consolidations. Chest CT images showed bilateral involvement in eight of the nine patients, and a unilobar reversed halo sign in the other patient. In total, 77 pulmonary lesions were found, including patchy lesions (39%), large confluent lesions (13%), and small nodular lesions (48%). The peripheral and posterior lung fields were involved in 78% and 67% of the lesions, respectively. The lesions were typically ill-defined and were composed of mixed ground-glass opacities and consolidation or pure ground-glass opacities. Patchy to confluent lesions were primarily distributed in the lower lobes (p = 0.040) and along the pleura (p < 0.001), whereas nodular lesions were primarily distributed along the bronchovascular bundles (p = 0.006).CONCLUSION: COVID-19 pneumonia in Korea primarily manifested as pure to mixed ground-glass opacities with a patchy to confluent or nodular shape in the bilateral peripheral posterior lungs. A considerable proportion of patients with COVID-19 pneumonia had normal chest radiographs.