Pectoralis Muscle Area as a Predictor of Mortality in Patients Hospitalized with Bronchiectasis Exacerbation

INTRODUCTION

Data on factors related to mortality in patients with bronchiectasis exacerbation are insufficient. Computed tomography (CT) can measure the pectoralis muscle area (PMA) and is a useful tool to diagnose sarcopenia. This study aimed to evaluate whether PMA can predict mortality in patients with bronchiectasis exacerbation.

METHODS

Patients hospitalized due to bronchiectasis exacerbation at a single center were retrospectively divided into survivors and non-survivors based on 1-year mortality. Thereafter, a comparison of the clinical and radiologic characteristics was conducted between the two groups.

RESULTS

A total of 66 (14%) patients died at 1 year. In the multivariate analysis, age, BMI <18.4 kg/m2, sex-specific PMA quartile, ≥3 exacerbations in the previous year, serum albumin <3.5 g/dL, cystic bronchiectasis, tuberculosis-destroyed lung, and diabetes mellitus were independent predictors for the 1-year mortality in patients hospitalized with bronchiectasis exacerbation. A lower PMA was associated with a lower overall survival rate in the survival analysis according to sex-specific quartiles of PMA. PMA had the highest area under the curve during assessment of prognostic performance in predicting the 1-year mortality. The lowest sex-specific PMA quartile group exhibited higher disease severity than the highest quartile group.

CONCLUSIONS

CT-derived PMA was an independent predictor of 1-year mortality in patients hospitalized with bronchiectasis exacerbation. Patients with lower PMA exhibited higher disease severity. These findings suggest that PMA might be a useful marker for providing additional information regarding prognosis of patients with bronchiectasis exacerbation.

Predictive factors for severe radiation-induced lung injury in patients with lung cancer and coexisting interstitial lung disease

BACKGROUND AND PURPOSE

This study aimed to investigate the predictive factors of severe radiation-induced lung injury (RILI) in patients with lung cancer and coexisting interstitial lung disease (ILD) undergoing conventionally fractionated thoracic radiotherapy.

MATERIALS AND METHODS

The study includes consecutive patients treated with thoracic radiotherapy for lung cancer at two tertiary centers between 2010 and 2021. RILI severity was graded using the National Cancer Institute Common Terminology Criteria version 5.0, with severe RILI defined as toxicity grade ≥4, and symptomatic RILI as grade ≥2. The absolute neutrophil count (ANC), absolute lymphocyte count (ALC), and C-reactive protein were collected within 4 weeks before starting radiotherapy. Neutrophil-lymphocyte ratios (NLR) were calculated as ANC/ALC. The median follow-up was 9 (range, 6-114) months.

RESULTS

Among 54 patients, 22 (40.7 %) had severe RILI. On multivariate logistic regression analysis, high pretreatment ANC (p = 0.030, OR = 4.313), pretreatment NLR (p = 0.007, OR = 5.784), and ILD severity (p = 0.027, OR = 2.416) were significant predictors of severe RILI. Dosimetric factors were not associated with severe RP. Overall survival was significantly worse for patients with severe RILI than those without, with 1-year cumulative overall survival rates of 7.4 % and 62.8 %, respectively.

CONCLUSION

Pretreatment blood NLR, ANC, and ILD severity were associated with severe RILI. Overall survival was dismal for patients with severe RILI.

Development and Validation of a Robust and Interpretable Early Triaging Support System for Patients Hospitalized With COVID-19: Predictive Algorithm Modeling and Interpretation Study

BACKGROUND

Robust and accurate prediction of severity for patients with COVID-19 is crucial for patient triaging decisions. Many proposed models were prone to either high bias risk or low-to-moderate discrimination. Some also suffered from a lack of clinical interpretability and were developed based on early pandemic period data. Hence, there has been a compelling need for advancements in prediction models for better clinical applicability.

OBJECTIVE

The primary objective of this study was to develop and validate a machine learning-based Robust and Interpretable Early Triaging Support (RIETS) system that predicts severity progression (involving any of the following events: intensive care unit admission, in-hospital death, mechanical ventilation required, or extracorporeal membrane oxygenation required) within 15 days upon hospitalization based on routinely available clinical and laboratory biomarkers.

METHODS

We included data from 5945 hospitalized patients with COVID-19 from 19 hospitals in South Korea collected between January 2020 and August 2022. For model development and external validation, the whole data set was partitioned into 2 independent cohorts by stratified random cluster sampling according to hospital type (general and tertiary care) and geographical location (metropolitan and nonmetropolitan). Machine learning models were trained and internally validated through a cross-validation technique on the development cohort. They were externally validated using a bootstrapped sampling technique on the external validation cohort. The best-performing model was selected primarily based on the area under the receiver operating characteristic curve (AUROC), and its robustness was evaluated using bias risk assessment. For model interpretability, we used Shapley and patient clustering methods.

RESULTS

Our final model, RIETS, was developed based on a deep neural network of 11 clinical and laboratory biomarkers that are readily available within the first day of hospitalization. The features predictive of severity included lactate dehydrogenase, age, absolute lymphocyte count, dyspnea, respiratory rate, diabetes mellitus, c-reactive protein, absolute neutrophil count, platelet count, white blood cell count, and saturation of peripheral oxygen. RIETS demonstrated excellent discrimination (AUROC=0.937; 95% CI 0.935-0.938) with high calibration (integrated calibration index=0.041), satisfied all the criteria of low bias risk in a risk assessment tool, and provided detailed interpretations of model parameters and patient clusters. In addition, RIETS showed potential for transportability across variant periods with its sustainable prediction on Omicron cases (AUROC=0.903, 95% CI 0.897-0.910).

CONCLUSIONS

RIETS was developed and validated to assist early triaging by promptly predicting the severity of hospitalized patients with COVID-19. Its high performance with low bias risk ensures considerably reliable prediction. The use of a nationwide multicenter cohort in the model development and validation implicates generalizability. The use of routinely collected features may enable wide adaptability. Interpretations of model parameters and patients can promote clinical applicability. Together, we anticipate that RIETS will facilitate the patient triaging workflow and efficient resource allocation when incorporated into a routine clinical practice.

Clinical Role of Upfront F-18 FDG PET/CT in Determining Biopsy Sites for Lung Cancer Diagnosis

PURPOSE

This study aimed to investigate the impact of FDG PET/CT timing for biopsy site selection in patients with stage IV lung cancer regarding complications and diagnostic yield.

METHODS

This retrospective analysis was performed on 1297 patients (924 men and 373 women with a mean age of 71.4 ± 10.2 years) who underwent percutaneous needle biopsy (PNB) for stage IV lung cancer diagnosis in two hospitals. Data collected included the patient's characteristics, order date of the biopsy and PET/CT exams, biopsy target site (lung or non-lung), guidance modality, complications, sample adequacy, and diagnostic success. Based on the order date of the PNB and PET/CT exams, patients were categorized into upfront and delayed PET/CT groups.

RESULTS

PNB for non-lung targets resulted in significantly lower rates of minor (8.1% vs. 16.2%), major (0.2% vs. 3.4%), and overall complications (8.3% vs. 19.6%) compared to PNB for lung targets (p < 0.001 for all types of complications). Compared to the delayed PET/CT group, the upfront PET/CT group exhibited a lower probability of lung target selection of PNB (53.9% vs. 67.1%, p < 0.001), including a reduced incidence of major complications (1.0% vs. 2.9%, p = 0.031). Moreover, there was no significant difference in the occurrence of minor and total complications between the two groups. Upfront PET/CT and delayed PET/CT groups showed no significant difference regarding sample adequacy and diagnostic success.

CONCLUSIONS

Upfront PET/CT may have an impact on the selection of the biopsy site for patients with advanced lung cancer, which could result in a lower rate of major complications with no change in the diagnostic yield. Upfront PET/CT demonstrates potential clinical implications for enhancing the safety of lung cancer diagnosis in clinical practice.

Efficacy of Bronchial Artery Embolization for Clinically Suspected Bronchial Dieulafoy's Disease

BACKGROUND

The efficacy of bronchial artery embolization (BAE) for bronchial Dieulafoy's disease (BDD) has not been well established.

OBJECTIVE

This study aimed to evaluate the safety and efficacy of BAE in patients with clinically suspected BDD presenting with major hemoptysis, and to describe angiographic findings.

METHODS

17 patients (all men; mean age, 53.5 years) diagnosed with clinically suspected BDD by bronchoscopy (n = 7) or CT angiography (CTA) (n = 10) and who underwent BAE after directional and segmental localization of the target bronchus were enrolled. BAE was performed at the culprit bronchial artery traveling toward the target bronchus, regardless of the pathologic angiographic findings. Angiographic findings and clinical outcomes of BAE, including technical and clinical success, complication, recurrent hemoptysis, and follow-up imaging, were retrospectively reviewed.

RESULTS

Representative angiographic findings included parenchymal hypervascularity prominent in the lobe where the BDD was located (82.4%), bronchial artery hypertrophy (70.6%), and contrast extravasation into the bleeding bronchus (17.6%). BAE was technically successful in all patients. All hemoptysis ceased within 24 h. No procedure-related complications occurred. During a mean follow-up of 491.9 days, 1 (6%) patient experienced recurrent hemoptysis. Follow-up bronchoscopy or CT performed in 10 (58.8%) patients showed the disappearance of pre-existing lesions (n = 9) or glue cast within the target bronchial artery (n = 1).

CONCLUSION

Bronchial angiography showed pathologic findings in most patients with clinically suspected BDD. BAE assisted by bronchoscopy or CTA localization is a safe and effective treatment for patients with clinically suspected BDD with excellent short- to mid-term results.

Immunoglobulin G4-Related Lung Disease with Waxing and Waning Pulmonary Infiltrates: A Case Report

Immunoglobulin G4 (IgG4)-related lung disease can have various clinical courses. To our knowledge, reports of IgG4-related lung disease with waxing and waning pulmonary infiltrates only are very rare. A few lung nodules and ground glass opacities were incidentally found in a pre-operative evaluation in a 36-year-old female. The lung lesions showed waxing and waning in the follow-up chest CT. She underwent a surgical biopsy, and IgG4-related lung disease was confirmed.

Erratum: Correction of Affiliations in the Article "Establishment of a Nationwide Korean Imaging Cohort of Coronavirus Disease 2019"

This corrects the article on p. e413 in vol. 35, PMID: 33258333.

Correction: Deep Learning With Chest Radiographs for Making Prognoses in Patients With COVID-19: Retrospective Cohort Study

[This corrects the article DOI: 10.2196/42717.].

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 style (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: 0.63 vs. 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.

Hemoptysis as the presenting manifestation of bronchiectasis-associated hospitalization in Korea

BACKGROUND

Patients with bronchiectasis commonly experience disease exacerbations, which cause significant morbidity and mortality. However, data regarding the clinical features of bronchiectasis patients hospitalized with hemoptysis are scarce.

METHODS

We retrospectively collected the data of patients with bronchiectasis-associated hospitalization at a tertiary referral center in Korea, and classified them into the hemoptysis and infective exacerbation (IE) groups. The presence of hemoptysis was defined as a volume of expectorated blood larger than 10 mL per 24 hours. The clinical, radiological, and laboratory parameters were compared between the two groups.

RESULTS

Patients were classified into the hemoptysis [267 (54.5%)] and IE [223 (45.5%)] groups. Among the 44 patients of the hemoptysis group, 37 (84.1%) presented with hemoptysis than with IE at the recurrent episode. The hemoptysis group had a significantly lower 30-day mortality than that of the IE group. Previous pulmonary tuberculosis (TB), mycetoma, and bronchial artery hypertrophy were independently associated with the hemoptysis group. In contrast, male sex, poor performance status, colonization of Pseudomonas aeruginosa, ≥3 involved lobes, cystic bronchiectasis, and emphysema were inversely associated with the hemoptysis group. The absence of hemoptysis was one of the independent predictors of 30-day mortality in patients with bronchiectasis-associated hospitalization.

CONCLUSIONS

In Korea, bronchiectasis patients hospitalized with hemoptysis exhibit a distinct phenotype, and are more likely to have previous pulmonary TB, mycetoma, and bronchial artery hypertrophy. Hemoptysis is associated with a lower risk of short-term mortality compared to IE in bronchiectasis-associated hospitalization.

Nontuberculous Mycobacterial Infection Mimicking Lung Cancer in A Patient with Usual Interstitial Pneumonia Pattern Interstitial Lung Disease: A Case Report

BACKGROUND

It has been reported that structure damage in the parenchymal lung disease such as idiopathic pulmonary fibrosis (IPF) is associated with high susceptibility to nontuberculous mycobacterial (NTM) infection. Radiologic features of NTM lung disease in destructive lung parenchyma can be atypical, which can cause confusion with other diseases including malignancy. Prompt and accurate identification of newly developed lesions in the follow-up computed tomography (CT) of IPF patients is challenging but crucial.

CASE REPORT

We reported a case of an NTM infection in a patient with IPF, manifested as a mass-like consolidation with cavitation on chest CT, mimicking lung cancer.

CONCLUSION

Being aware of the unusual radiologic features of NTM lung disease in IPF patients can be useful in the differential diagnosis of newly detected lesions.

Ultrasound-guided lung biopsy for small (≤2 cm) subpleural lung lesions: comparison of diagnostic yield and safety with larger lesions

Background

Ultrasound (US)-guided percutaneous core needle biopsy (PCNB) has been used to diagnose subpleural lung lesions with high diagnostic performance and acceptable complication rates. However, with regard to the role of US-guided needle biopsy for the diagnosis of small (≤2 cm) subpleural lesions, limited information is available.

Methods

From April 2011 to October 2021, a total of 572 US-guided PCNBs in 572 patients were retrospectively reviewed. The lesion size, pleural contact length (PCL), lesion location, and operator's experience were analyzed. Computed tomography features including peri-lesional emphysema, air-bronchogram, and cavitary change were also included in image analysis. The patients were divided into three groups according to lesion size (lesions ≤2 cm vs. 2 cm< lesions ≤5 cm vs. lesions >5 cm). The sample adequacy, diagnostic success rate, diagnostic accuracy, and complication rate was calculated. For statistical analysis, one-way ANOVA, Kruskal-Wallis test, or the chi-square test were used.

Results

The overall sample adequacy, diagnostic success rate, and diagnostic accuracy were 96.2%, 82.9%, and 90.4%, respectively. In the subgroup analysis, sample adequacy (93.1% vs. 96.1% vs. 96.9%, P=0.307), diagnostic success rate (75.0% vs. 81.6% vs. 85.7%, P=0.079), and diagnostic accuracy (84.7% vs. 90.8% vs. 90.5%, P=0.301) were not significantly different. Operator's experience (OR, 0.64; 95% CI: 0.49-0.80; P<0.001), lesion size (OR, 0.68; 95% CI: 0.54-0.83; P<0.001), PCL (OR, 0.68; 95% CI: 0.52-0.84; P=0.001), and presence of air-bronchogram (OR, 14.36; 95% CI: 4.18-48.53; P<0.001) were independently associated with complication rate.

Conclusions

US-guided PCNB performed by an experienced radiologist could be an effective and safe diagnostic approach for subpleural lesions, even in small lesions.

Atypical Radiological Findings of Capillary Hemangioma in Right Atrium: A Case Report

BACKGROUND

Cardiac hemangiomas account for only 2.8% of primary cardiac tumors and are caused by the abnormal proliferation of endothelial cells and excess blood vessels. Typical radiological findings of cardiac hemangioma demonstrate intense contrast enhancement.

CASE PRESENTATION

Here we report the case of a 69-year-old man who presented with a right atrial mass found incidentally with multimodal imaging findings, including echocardiography, computed tomography (CT), and magnetic resonance imaging (MRI). This case presented with poor enhancement within right atrial mass on dynamic contrast-enhanced CT scan and gadolinium-enhanced first-pass perfusion image of cardiac MRI. After surgical resection, the pathologic diagnosis of cardiac capillary hemangioma was made.

CONCLUSION

Cardiac hemangioma could be included in the differential diagnosis for cardiac neoplasms demonstrating poor enhancements on CT and MRI scans.

Clinical relevance of bronchiectasis in patients with community-acquired pneumonia

BACKGROUND

Data regarding the clinical characteristics and treatment outcomes of patients with community-acquired pneumonia (CAP) and bronchiectasis (BE) are rare. This study aims to elucidate the clinical relevance of BE in patients with CAP.

METHODS

Patients hospitalized with CAP in a single center were retrospectively analyzed and divided into significant BE (BE with ≥ 3 lobes or cystic BE on computed tomography) and control groups. Clinical and microbiological characteristics were compared between the two groups.

RESULTS

In the final analysis, 2112 patients were included, and 104 (4.9%) had significant BE. The significant BE group exhibited a higher prevalence of sputum production, dyspnea, and complicated parapneumonic effusion or empyema than the control group. Pseudomonas aeruginosa was more frequently isolated in the significant BE group than in the control group, whereas Mycoplasma pneumoniae was less commonly identified. Length of hospital stay (LOS) was significantly longer in the significant BE group than the control group (12 [8-17] days vs. 9 [6-13] days, p < 0.001). In contrast, 30-day and in-hospital mortality rates did not significantly differ between the two groups. Furthermore, significant BE was an independent predictor of prolonged hospitalization in two models based on CURB-65 and pneumonia severity index.

CONCLUSIONS

Significant BE occurred in approximately 5% of patients with CAP and was more likely to be associated with sputum, dyspnea, complicated parapneumonic effusion or empyema, and isolation of P. aeruginosa. Significant BE was an independent predictor of LOS in patients with CAP.

Deep Learning With Chest Radiographs for Making Prognoses in Patients With COVID-19: Retrospective Cohort Study

BACKGROUND

An artificial intelligence (AI) model using chest radiography (CXR) may provide good performance in making prognoses for COVID-19.

OBJECTIVE

We aimed to develop and validate a prediction model using CXR based on an AI model and clinical variables to predict clinical outcomes in patients with COVID-19.

METHODS

This retrospective longitudinal study included patients hospitalized for COVID-19 at multiple COVID-19 medical centers between February 2020 and October 2020. Patients at Boramae Medical Center were randomly classified into training, validation, and internal testing sets (at a ratio of 8:1:1, respectively). An AI model using initial CXR images as input, a logistic regression model using clinical information, and a combined model using the output of the AI model (as CXR score) and clinical information were developed and trained to predict hospital length of stay (LOS) ≤2 weeks, need for oxygen supplementation, and acute respiratory distress syndrome (ARDS). The models were externally validated in the Korean Imaging Cohort of COVID-19 data set for discrimination and calibration.

RESULTS

The AI model using CXR and the logistic regression model using clinical variables were suboptimal to predict hospital LOS ≤2 weeks or the need for oxygen supplementation but performed acceptably in the prediction of ARDS (AI model area under the curve [AUC] 0.782, 95% CI 0.720-0.845; logistic regression model AUC 0.878, 95% CI 0.838-0.919). The combined model performed better in predicting the need for oxygen supplementation (AUC 0.704, 95% CI 0.646-0.762) and ARDS (AUC 0.890, 95% CI 0.853-0.928) compared to the CXR score alone. Both the AI and combined models showed good calibration for predicting ARDS (P=.079 and P=.859).

CONCLUSIONS

The combined prediction model, comprising the CXR score and clinical information, was externally validated as having acceptable performance in predicting severe illness and excellent performance in predicting ARDS in patients with COVID-19.

Peritumoral imaging features of thymic epithelial tumors for the prediction of transcapsular invasion: beyond intratumoral analysis

PURPOSE

The purpose of this study was to differentiate cases without transcapsular invasion (Masaoka-Koga stage I) from cases with transcapsular invasion (Masaoka-Koga stage II or higher) in patients with thymic epithelial tumors (TETs) using tumoral and peritumoral computed tomography (CT) features.

METHODS

This retrospective study included 116 patients with pathological diagnoses of TETs. Two radiologists evaluated clinical variables and CT features, including size, shape, capsule integrity, presence of calcification, internal necrosis, heterogeneous enhancement, pleural effusion, pericardial effusion, and vascularity grade. Vascularity grade was defined as the extent of peritumoral vascular structures in the anterior mediastinum. The factors associated with transcapsular invasion were analyzed using multivariable logistic regression. In addition, the interobserver agreement for CT features was assessed using Cohen's or weighted kappa coefficients. The difference between the transcapsular invasion group and that without transcapsular invasion was evaluated statistically using the Student's t-test, Mann-Whitney U test, chi-square test, and Fisher's exact test.

RESULTS

Based on pathology reports, 37 TET cases without and 79 with transcapsular invasion were identified. Lobular or irregular shape [odds ratio (OR): 4.19; 95% confidence interval (CI): 1.53-12.09; P = 0.006], partial complete capsule integrity (OR: 5.03; 95% CI: 1.85-15.13; P = 0.002), and vascularity grade 2 (OR: 10.09; 95% CI: 2.59-45.48; P = 0.001) were significantly associated with transcapsular invasion. The interobserver agreement for shape classification, capsule integrity, and vascularity grade was 0.840, 0.526, and 0.752, respectively (P < 0.001 for all).

CONCLUSION

Shape, capsule integrity, and vascularity grade were independently associated with transcapsular invasion of TETs. Furthermore, three CT TET features demonstrated good reproducibility and help differentiate between TET cases with and without transcapsular invasion.

Feasibility of Single-Shot Whole Thoracic Time-Resolved MR Angiography to Evaluate Patients with Multiple Pulmonary Arteriovenous Malformations

OBJECTIVE

To evaluate the feasibility of single-shot whole thoracic time-resolved MR angiography (TR-MRA) to identify the feeding arteries of pulmonary arteriovenous malformations (PAVMs) and reperfusion of the lesion after embolization in patients with multiple PAVMs.

MATERIALS AND METHODS

Nine patients (8 females and 1 male; age range, 23-65 years) with a total of 62 PAVMs who underwent percutaneous embolization for multiple PAVMs and were subsequently followed up using TR-MRA and CT obtained within 6 months from each other were retrospectively reviewed. All imaging analyses were performed by two independent readers blinded to clinical information. The visibility of the feeding arteries on maximum intensity projection (MIP) reconstruction and multiplanar reconstruction (MPR) TR-MRA images was evaluated by comparing them to CT as a reference. The accuracy of TR-MRA for diagnosing reperfusion of the PAVM after embolization was assessed in a subgroup with angiographic confirmation. The reliability between the readers in interpreting the TR-MRA results was analyzed using kappa (κ) statistics.

RESULTS

Feeding arteries were visible on the original MIP images of TR-MRA in 82.3% (51/62) and 85.5% (53/62) of readers 1 and 2, respectively. Using the MPR, the rates increased to 93.5% (58/62) and 95.2% (59/62), respectively (κ = 0.760 and 0.792, respectively). Factors for invisibility were the course of feeding arteries in the anteroposterior plane, proximity to large enhancing vessels, adjacency to the chest wall, pulsation of the heart, and small feeding arteries. Thirty-seven PAVMs in five patients had angiographic confirmation of reperfusion status after embolization (32 occlusions and 5 reperfusions). TR-MRA showed 100% (5/5) sensitivity and 100% (32/32, including three cases in which the feeding arteries were not visible on TR-MRA) specificity for both readers.

CONCLUSION

Single-shot whole thoracic TR-MRA with MPR showed good visibility of the feeding arteries of PAVMs and high accuracy in diagnosing reperfusion after embolization. Single-shot whole thoracic TR-MRA may be a feasible method for the follow-up of patients with multiple PAVMs.

Self-evolving vision transformer for chest X-ray diagnosis through knowledge distillation

Although deep learning-based computer-aided diagnosis systems have recently achieved expert-level performance, developing a robust model requires large, high-quality data with annotations that are expensive to obtain. This situation poses a conundrum that annually-collected chest x-rays cannot be utilized due to the absence of labels, especially in deprived areas. In this study, we present a framework named distillation for self-supervision and self-train learning (DISTL) inspired by the learning process of the radiologists, which can improve the performance of vision transformer simultaneously with self-supervision and self-training through knowledge distillation. In external validation from three hospitals for diagnosis of tuberculosis, pneumothorax, and COVID-19, DISTL offers gradually improved performance as the amount of unlabeled data increase, even better than the fully supervised model with the same amount of labeled data. We additionally show that the model obtained with DISTL is robust to various real-world nuisances, offering better applicability in clinical setting.

Although deep learning-based computer-aided diagnosis systems have recently achieved expert level performance, developing a robust model requires large, high-quality data with annotations. Here, the authors present a framework which can improve the performance of vision transformer simultaneously with self-supervision and self-training.

Unilateral Pulmonary Vein Atresia Initially Presenting as Interstitial Lung Disease in an Elderly Female: Serial Chest Radiograph Changes and Its Literature Review

Unilateral pulmonary vein atresia (PVA) is a rare congenital cardiovascular anomaly occurring after the common pulmonary vein fails to incorporate into the left atrium. It is most commonly diagnosed in childhood, and diagnosis after reaching adulthood is extremely rare. Dyspnea on exertion and hemoptysis are common clinical features in adult PVA patients, whereas lung parenchymal abnormalities are indirect signs of PVA, which can manifest as interstitial lung disease. Herein, we present the case of a 62-year-old female diagnosed with unilateral PVA presenting as unilateral interstitial lung disease and report the changes in her chest radiographs over 12 years.

Multi-task vision transformer using low-level chest X-ray feature corpus for COVID-19 diagnosis and severity quantification

Developing a robust algorithm to diagnose and quantify the severity of the novel coronavirus disease 2019 (COVID-19) using Chest X-ray (CXR) requires a large number of well-curated COVID-19 datasets, which is difficult to collect under the global COVID-19 pandemic. On the other hand, CXR data with other findings are abundant. This situation is ideally suited for the Vision Transformer (ViT) architecture, where a lot of unlabeled data can be used through structural modeling by the self-attention mechanism. However, the use of existing ViT may not be optimal, as the feature embedding by direct patch flattening or ResNet backbone in the standard ViT is not intended for CXR. To address this problem, here we propose a novel Multi-task ViT that leverages low-level CXR feature corpus obtained from a backbone network that extracts common CXR findings. Specifically, the backbone network is first trained with large public datasets to detect common abnormal findings such as consolidation, opacity, edema, etc. Then, the embedded features from the backbone network are used as corpora for a versatile Transformer model for both the diagnosis and the severity quantification of COVID-19. We evaluate our model on various external test datasets from totally different institutions to evaluate the generalization capability. The experimental results confirm that our model can achieve state-of-the-art performance in both diagnosis and severity quantification tasks with outstanding generalization capability, which are sine qua non of widespread deployment.

Quantitative CT Image-Based Structural and Functional Changes during Asthma Acute Exacerbations

Asthma acute exacerbations (AE) have been investigated using quantitative computed tomography (QCT)-based imaging metrics, but QCT has not yet been used to investigate a comprehensive set of imaging metrics during AE. This study aims to explore imaging features, captured both at segmental and parenchymal scales, during asthma AE, compared to stable asthma (SA). Two sets of the QCT images at total lung capacity (TLC) and functional residual capacity (FRC) were captured for 14 subjects during asthma AE and in SA phase, respectively. We calculated airway wall thickness (WT), hydraulic diameter (D_h), and airway circularity (Cr) of the 36 segmental airways, percentage of functional small airway disease (fSAD%), percentage of emphysema, tissue fraction (β_tiss), and coefficient of variation of β_tiss (CV of β_tiss). We performed Spearman correlation tests for changes in QCT metrics and pulmonary function tests, measured in AE and SA. During asthma AE, structural metrics, i.e., WT, D_h, and Cr, were not changed significantly. In functional metrics, CV of β_tiss at FRC indicating the heterogeneity of lung tissue distribution was significantly increased, while the mean of β_tiss at FRC did not change during AE. An increase of fSAD% during AE was most correlated with a decrease of forced expiratory volume in 1 second and forced vital capacity, especially in the lower lobes. This study demonstrates that the heterogeneous feature of β_tiss measured at lower lobes is more noticeable during asthma AE, compared with other traditional imaging metrics. This metric could be utilized to identify unique features during asthma AE.

Odderon Exchange from Elastic Scattering Differences between pp and pp[over ¯] Data at 1.96 TeV and from pp Forward Scattering Measurements

We describe an analysis comparing the pp[over ¯] elastic cross section as measured by the D0 Collaboration at a center-of-mass energy of 1.96 TeV to that in pp collisions as measured by the TOTEM Collaboration at 2.76, 7, 8, and 13 TeV using a model-independent approach. The TOTEM cross sections, extrapolated to a center-of-mass energy of sqrt[s]=1.96  TeV, are compared with the D0 measurement in the region of the diffractive minimum and the second maximum of the pp cross section. The two data sets disagree at the 3.4σ level and thus provide evidence for the t-channel exchange of a colorless, C-odd gluonic compound, also known as the odderon. We combine these results with a TOTEM analysis of the same C-odd exchange based on the total cross section and the ratio of the real to imaginary parts of the forward elastic strong interaction scattering amplitude in pp scattering for which the significance is between 3.4σ and 4.6σ. The combined significance is larger than 5σ and is interpreted as the first observation of the exchange of a colorless, C-odd gluonic compound.

Impact of Computed Tomography-Quantified Emphysema Score on Clinical Outcome in Patients with COVID-19

Background

Chronic obstructive pulmonary disease (COPD) is considered a risk factor for poor outcomes in patients with coronavirus disease 2019 (COVID-19). However, data on the prognostic impact of radiological emphysema extent on patients with COVID-19 are limited. Thus, this study aimed to examine whether computed tomography (CT)-quantified emphysema score is associated with a worse clinical outcome in patients with COVID-19.

Methods

Volumetric quantitative analyses of CT images were performed to obtain emphysema scores in COVID-19 patients admitted to four tertiary referral hospitals in Daegu, South Korea, between February 18 and March 25, 2020. Patients were divided into three groups according to emphysema score (emphysema score ≤1%, 1%< emphysema score ≤5%, and emphysema score >5%).

Results

A total of 146 patients with confirmed SARS-CoV-2 infection were included. The median emphysema score was 1.0% (interquartile range, 0.5–1.8%). Eight patients (6%) had a previous COPD diagnosis. Eighty (55%), 55 (38%), and 11 (8%) patients had emphysema scores ≤1%, between 1% and 5%, and >5%, respectively. The number of patients who received oxygen therapy two weeks after admission was significantly higher in the group with emphysema scores >5% than in other groups (p=0.025). The frequency of deaths was three (27%) in the group with emphysema scores >5% and tended to be higher than that in other groups. Multivariate analysis revealed that age, COPD, and serum lactate dehydrogenase levels were associated with a greater risk of in-hospital mortality in patients with COVID-19.

Conclusion

The current study demonstrated that patients with CT-quantified emphysema scores >5% tended to progress to severe disease over time; however, they did not exhibit an increased risk of mortality in our COVID-19 cohort. Further studies with consideration of both emphysema extent and airflow limitation degree are warranted.

COVID-19 pneumonia on chest X-rays: Performance of a deep learning-based computer-aided detection system

Chest X-rays (CXRs) can help triage for Coronavirus disease (COVID-19) patients in resource-constrained environments, and a computer-aided detection system (CAD) that can identify pneumonia on CXR may help the triage of patients in those environment where expert radiologists are not available. However, the performance of existing CAD for identifying COVID-19 and associated pneumonia on CXRs has been scarcely investigated. In this study, CXRs of patients with and without COVID-19 confirmed by reverse transcriptase polymerase chain reaction (RT-PCR) were retrospectively collected from four and one institution, respectively, and a commercialized, regulatory-approved CAD that can identify various abnormalities including pneumonia was used to analyze each CXR. Performance of the CAD was evaluated using area under the receiver operating characteristic curves (AUCs), with reference standards of the RT-PCR results and the presence of findings of pneumonia on chest CTs obtained within 24 hours from the CXR. For comparison, 5 thoracic radiologists and 5 non-radiologist physicians independently interpreted the CXRs. Afterward, they re-interpreted the CXRs with corresponding CAD results. The performance of CAD (AUCs, 0.714 and 0.790 against RT-PCR and chest CT, respectively hereinafter) were similar with those of thoracic radiologists (AUCs, 0.701 and 0.784), and higher than those of non-radiologist physicians (AUCs, 0.584 and 0.650). Non-radiologist physicians showed significantly improved performance when assisted with the CAD (AUCs, 0.584 to 0.664 and 0.650 to 0.738). In addition, inter-reader agreement among physicians was also improved in the CAD-assisted interpretation (Fleiss' kappa coefficient, 0.209 to 0.322). In conclusion, radiologist-level performance of the CAD in identifying COVID-19 and associated pneumonia on CXR and enhanced performance of non-radiologist physicians with the CAD assistance suggest that the CAD can support physicians in interpreting CXRs and helping image-based triage of COVID-19 patients in resource-constrained environment.

Deep Learning Models for Predicting Severe Progression in COVID-19-Infected Patients: Retrospective Study

BACKGROUND

Many COVID-19 patients rapidly progress to respiratory failure with a broad range of severities. Identification of high-risk cases is critical for early intervention.

OBJECTIVE

The aim of this study is to develop deep learning models that can rapidly identify high-risk COVID-19 patients based on computed tomography (CT) images and clinical data.

METHODS

We analyzed 297 COVID-19 patients from five hospitals in Daegu, South Korea. A mixed artificial convolutional neural network (ACNN) model, combining an artificial neural network for clinical data and a convolutional neural network for 3D CT imaging data, was developed to classify these cases as either high risk of severe progression (ie, event) or low risk (ie, event-free).

RESULTS

Using the mixed ACNN model, we were able to obtain high classification performance using novel coronavirus pneumonia lesion images (ie, 93.9% accuracy, 80.8% sensitivity, 96.9% specificity, and 0.916 area under the curve [AUC] score) and lung segmentation images (ie, 94.3% accuracy, 74.7% sensitivity, 95.9% specificity, and 0.928 AUC score) for event versus event-free groups.

CONCLUSIONS

Our study successfully differentiated high-risk cases among COVID-19 patients using imaging and clinical features. The developed model can be used as a predictive tool for interventions in aggressive therapies.

Quantitative CT imaging and advanced visualization methods: potential application in novel coronavirus disease 2019 (COVID-19) pneumonia

Increasingly, quantitative lung computed tomography (qCT)-derived metrics are providing novel insights into chronic inflammatory lung diseases, including chronic obstructive pulmonary disease, asthma, interstitial lung disease, and more. Metrics related to parenchymal, airway, and vascular anatomy together with various measures associated with lung function including regional parenchymal mechanics, air trapping associated with functional small airways disease, and dual-energy derived measures of perfused blood volume are offering the ability to characterize disease phenotypes associated with the chronic inflammatory pulmonary diseases. With the emergence of COVID-19, together with its widely varying degrees of severity, its rapid progression in some cases, and the potential for lengthy post-COVID-19 morbidity, there is a new role in applying well-established qCT-based metrics. Based on the utility of qCT tools in other lung diseases, previously validated supervised classical machine learning methods, and emerging unsupervised machine learning and deep-learning approaches, we are now able to provide desperately needed insight into the acute and the chronic phases of this inflammatory lung disease. The potential areas in which qCT imaging can be beneficial include improved accuracy of diagnosis, identification of clinically distinct phenotypes, improvement of disease prognosis, stratification of care, and early objective evaluation of intervention response. There is also a potential role for qCT in evaluating an increasing population of post-COVID-19 lung parenchymal changes such as fibrosis. In this work, we discuss the basis of various lung qCT methods, using case-examples to highlight their potential application as a tool for the exploration and characterization of COVID-19, and offer scanning protocols to serve as templates for imaging the lung such that these established qCT analyses have the best chance at yielding the much needed new insights.

Pulmonary arteriovenous malformation (PAVM) embolization: prediction of angiographically-confirmed recanalization according to PAVM Diameter changes on CT

Background

To assess pulmonary arteriovenous malformation (PAVM) recanalization after embolization based on PAVM diameter changes on computed tomography (CT), with pulmonary angiography used as a gold standard.

Methods

A retrospective review was done of patients from 2008 to 2019 with a PAVM treated with endovascular embolization. The treatment outcome was determined by conventional angiography. Follow-up pulmonary angiography was performed when recanalization was suspected on CT, or embolization of all lesions in multiple PAVM patients could not be completed in a single session. Patients who had no preprocedural or follow-up CT were excluded. Draining vein, feeding artery, and venous sac diameter were measured on CT, and diameter reduction rates were compared with the widely-used, binary 70 % criteria.

Results

Forty-one patients with 114 PAVMs were treated during the study period. Eight patients with 50 PAVMs met the inclusion criteria. Mean vein, artery, and venous sac diameter reduction rates were as follows: 59.2 ± 9.3 %, 47.5 ± 10.6 %, and 62.6 ± 13.2 %, respectively, in the occluded group and 5.4 ± 19.5 %, 11.3 ± 17.7 %, and 26.8 ± 14.2 %, respectively, in the recanalized group. The area under the receiver operating characteristic curves for PAVM recanalization for the draining vein was 1.00, showing a better result than the artery (0.97) and sac (0.99). Patients showed > 42 % draining vein diameter reduction in the occluded group and < 32 % in the recanalized group. The widely-used 70 % criteria showed low specificity for predicting recanalization (draining vein, 7.3 %; venous sac, 41.7 %) but 100 % sensitivity for both the draining vein and venous sac.

Conclusions

The widely-used 70 % binary criteria showed limited performance in predicting outcomes in this angiographically-confirmed case series. Further investigations are warranted to establish a strategy for detecting recanalization after PAVM embolization.

Deep-learning algorithms for the interpretation of chest radiographs to aid in the triage of COVID-19 patients: A multicenter retrospective study

The recent medical applications of deep-learning (DL) algorithms have demonstrated their clinical efficacy in improving speed and accuracy of image interpretation. If the DL algorithm achieves a performance equivalent to that achieved by physicians in chest radiography (CR) diagnoses with Coronavirus disease 2019 (COVID-19) pneumonia, the automatic interpretation of the CR with DL algorithms can significantly reduce the burden on clinicians and radiologists in sudden surges of suspected COVID-19 patients. The aim of this study was to evaluate the efficacy of the DL algorithm for detecting COVID-19 pneumonia on CR compared with formal radiology reports. This is a retrospective study of adult patients that were diagnosed as positive COVID-19 cases based on the reverse transcription polymerase chain reaction among all the patients who were admitted to five emergency departments and one community treatment center in Korea from February 18, 2020 to May 1, 2020. The CR images were evaluated with a publicly available DL algorithm. For reference, CR images without chest computed tomography (CT) scans classified as positive for COVID-19 pneumonia were used given that the radiologist identified ground-glass opacity, consolidation, or other infiltration in retrospectively reviewed CR images. Patients with evidence of pneumonia on chest CT scans were also classified as COVID-19 pneumonia positive outcomes. The overall sensitivity and specificity of the DL algorithm for detecting COVID-19 pneumonia on CR were 95.6%, and 88.7%, respectively. The area under the curve value of the DL algorithm for the detection of COVID-19 with pneumonia was 0.921. The DL algorithm demonstrated a satisfactory diagnostic performance comparable with that of formal radiology reports in the CR-based diagnosis of pneumonia in COVID-19 patients. The DL algorithm may offer fast and reliable examinations that can facilitate patient screening and isolation decisions, which can reduce the medical staff workload during COVID-19 pandemic situations.

Providing essential clinical care for non-COVID-19 patients in a Seoul metropolitan acute care hospital amidst ongoing treatment of COVID-19 patients

We assessed infection control efforts by comparing data collected over 20 weeks during a pandemic under a dual-track healthcare system. A decline in non-COVID-19 patients visiting the emergency department by 37.6% (P<0.01) was observed since admitting COVID-19 cases. However, patients with acute myocardial infarction (AMI), stroke, severe trauma and acute appendicitis presenting for emergency care did not decrease. Door-to-balloon time (34.3 (± 11.3) min vs 22.7 (± 8.3) min) for AMI improved significantly (P<0.01) while door-to-needle time (55.7 (± 23.9) min vs 54.0 (± 18.0) min) in stroke management remained steady (P=0.80). Simultaneously, time-sensitive care involving other clinical services, including patients requiring chemotherapy, radiation therapy and haemodialysis did not change.

Clinical Impact of N-Terminal Prohormone of Brain Natriuretic Peptide on Patients Hospitalized with Community-Acquired Pneumonia

BACKGROUND

Risk stratification is important for the management of community-acquired pneumonia (CAP). The present study aimed to investigate the clinical impact of N-terminal prohormone of brain natriuretic peptide (NT-proBNP) on prognosis and to identify clinical characteristics associated with NT-proBNP elevation in CAP patients.

METHODS

This retrospective study included patients hospitalized for CAP at a tertiary referral center and who underwent measurement plasma NT-proBNP levels. Based on 30-day mortality, patients (n = 1,821) were divided into 2 groups, survivors (n = 150) and nonsurvivors (n = 1,671), and clinical and laboratory findings were compared.

RESULTS

In multivariate analysis, blood levels of NT-proBNP (>942.5 pg/mL), albumin (<3.3 g/dL), and troponin I (>0.018 ng/mL) independently predicted 30-day mortality. Of these blood biomarkers, NT-proBNP exhibited the highest C-statistic, followed by albumin. NT-proBNP level/CURB-65 score and NT-proBNP level/pneumonia severity index (PSI) class exhibited significantly higher C-statistics than CURB-65 score and PSI class alone, respectively. The 3-test combinations of CURB-65 score/NT-proBNP level/albumin level and PSI class/NT-proBNP level/albumin level exhibited significantly higher C-statistics than the 2-test combinations. NT-proBNP elevation was associated with increased age, heart disease and chronic kidney disease and NT-proBNP levels only weakly or moderately correlated with other blood biomarkers.

CONCLUSIONS

NT-proBNP level was a useful marker for the prediction of 30-day mortality in patients hospitalized with CAP, and provided additional prognostic value to PSI or CURB-65 alone.

Brachiocephalic Venous Aneurysm Mimicking Metastatic Cervical Lymphadenopathy in a Patient with Gastric Cancer: A Case Report

Brachiocephalic venous aneurysm (BVA) development is an extremely rare, particularly as a primary vascular disorder. BVAs may be misinterpreted as lymphadenopathies owing to the variable degrees of enhancement seen in imaging studies, especially among patients with underlying malignancy. We report a BVA that mimicked lymph node metastasis on CT in a 60-year-old female who had undergone subtotal gastrectomy for stomach cancer. After follow-up chest CT with different bolus times and Doppler ultrasonography, a venous aneurysm originating from the brachiocephalic vein was diagnosed. We emphasize that, to make an accurate diagnosis, physicians should be aware of the potential diagnostic pitfalls and have a high index of suspicion for BVA when encountering certain lesions in the cervical area.

Spondylodiscitis initially presenting as exudative pleural effusion: A case report and review of the literature

Pleural effusions are associated with a variety of disease states, rendering the differential diagnosis challenging. Spondylodiscitis is an uncommon disease, and its prompt diagnosis can reduce morbidity and mortality. However, an atypical manifestation of the disease, such as pleural effusion, can result in delayed diagnosis. A 76-year-old woman presented with back pain and right pleural effusion. Magnetic resonance imaging revealed paravertebral soft tissue infiltration, with enhancement of bone marrow and intervertebral disk at the T8 and T9 levels, suggesting spondylodiscitis. In patients with exudative pleural effusion, spondylodiscitis may be the cause, so careful analysis of imaging is necessary.

Clinical and radiological features of pulmonary tuberculosis in patients with idiopathic pulmonary fibrosis

BACKGROUND

Data regarding the radiological and clinical features of pulmonary tuberculosis (PTB) in patients with idiopathic pulmonary fibrosis (IPF) are limited. Accordingly, the aim of this study was to investigate the clinico-radiological features of PTB in patients with IPF.

METHODS

Clinico-radiological variables were retrospectively compared between PTB patients with and without IPF (TB-IPF and TB-control, respectively), and computed tomography (CT) findings were compared between the TB-IPF group and patients with nontuberculous mycobacterial lung disease and IPF (NTM-IPF).

RESULTS

Of 609 IPF patients, 28 (4.6%) were diagnosed with PTB. In the TB-IPF group, incidental radiological finding was the most common presenting manifestation, and the rate of treatment success was significantly lower than in the TB-control group. On CT scan, the typical locations of reactivated PTB were significantly less often involved in the TB-IPF group than in the TB-control group. The TB-IPF group exhibited a significantly lower frequency of centrilobular nodules and a higher rate of consolidation-predominant pattern than did the TB-control group. CT findings in the TB-IPF group were similar to those in the NTM-IPF group.

CONCLUSIONS

Incidental radiological findings were the most common presenting manifestations in TB-IPF patients, who were more likely to present with atypical PTB manifestations on CT scan and who experienced poorer treatment outcomes.

Can emphysema influence size discrepancy between radiologic and pathologic size measurement in subsolid lung adenocarcinomas?

Background

To investigate the difference in the measured diameter of subsolid lung adenocarcinomas of thin‐section computed tomography (TSCT) and pathology according to presence of emphysema.

Methods

A total of 268 surgically resected pathologic T1 or T2 adenocarcinomas visualized as subsolid nodules (SSNs) on TSCT were analyzed in 252 patients. Two observers measured the greatest diameters of the whole tumor (WTsize) and solid tumor (STsize) on TSCT in lung windows, classified nodules as part‐solid or nonsolid, and recorded the presence of regional emphysema. Interobserver variability was determined with intraclass correlation coefficients (ICC). CT measurements were compared to pathologic size (Psize) and invasive size (PIsize) using the Wilcoxon signed‐rank test.

Results

The interobserver agreement between the diameters measured by the two observers was strong for WTsize (ICC = 0.968 [95% confidence interval, 0.960–0.975]) and STsize (ICC = 0.966 [95% CI, 0.950–0.969]). Radiologic WTsize was significantly greater than Psize (P < 0.001), while STsize was less than PIsize. The WTsize of the emphysema group was better correlated with Psize than WTsize of the normal lung group (P = 0.001), while the STsize of the normal lung group was better correlated with PIsize than STsize of the emphysema group. The concordance rate in T staging between CT and pathologic analysis was better correlated in patients with normal lungs than in those with emphysema (P = 0.023).

Conclusion

STsize on TSCT was underestimated in patients with emphysema, resulting in higher discordance in T staging between TSCT and pathologic analysis for subsolid lung adenocarcinomas.

Clinical relevance of chronic respiratory disease in Korean patients with pulmonary thromboembolism

Background

Data regarding clinical and radiological features of patients with pulmonary thromboembolism (PTE) and concomitant chronic respiratory disease (CRD) are limited. Accordingly, the aim of the present study was to investigate clinico-radiological features of this patient population.

Methods

Patients with PTE were retrospectively classified into one of two groups: those with and without CRD. Clinical characteristics, blood biomarkers, and computed tomographic (CT) findings were compared between the groups.

Results

Of 1,207 PTE patients included, CRD was detected in 128 (11%). The most common CRD was chronic obstructive pulmonary disease [41 (32%)], followed by bronchial anthracofibrosis [32 (25%)]. In multivariate analysis, unprovoked PTE [odds ratio (OR) 1.99, 95% confidence interval (CI): 1.29-3.05, P=0.002], dyspnea (OR 1.54, 95% CI: 1.11-2.34, P=0.041), lower respiratory tract infection (LRTI) (OR 3.90, 95% CI: 2.13-7.14, P<0.001), Pulmonary Embolism Severity Index (PESI) class IV-V (OR 5.24, 95% CI: 3.43-8.00, P<0.001), in-situ pulmonary artery thrombosis (OR 10.62, 95% CI: 3.71-30.45, P<0.001), and pulmonary artery enlargement (OR 1.65, 95% CI: 3.71-30.45, P<0.001) were found to be independent clinical factors related to CRD in patients with PTE. CRD was an independent predictor of PTE-related in-hospital mortality (OR 3.96, 95% CI: 1.32-11.88, P=0.014).

Conclusions

Patients with PTE and concomitant CRD were characterized by higher incidences of dyspnea, LRTI, PESI class IV-V, and in-situ pulmonary artery thrombosis, compared with non-CRD patients. In these patients, CRD was a predictor of PTE-related in-hospital mortality.

Catalytic co-pyrolysis of sugarcane bagasse and waste high-density polyethylene over faujasite-type zeolite

This study investigated the catalytic co-pyrolysis of sugarcane bagasse (SCB) and waste high-density polyethylene (HDPE) over faujasite-type zeolite derived from electric arc furnace slag (FAU-EAFS) in a fixed-bed reactor. The effects of reaction temperature, catalyst-to-feedstock ratio, and HDPE-to-SCB ratio on product fractional yields and chemical compositions were discussed. The co-pyrolysis of SCB and HDPE over FAU-EAFS increased the liquid yield and enhanced the quality of bio-oil. The maximum bio-oil (68.56 wt%) and hydrocarbon yield (74.55%) with minimum yield of oxygenated compounds (acid = 0.57% and ester = 0.67%) were achieved under the optimum experimental conditions of catalyst-to-feedstock ratio of 1:6, HDPE-to-SCB ratio of 40:60, and temperature of 500 °C. The oil produced by catalytic co-pyrolysis had higher calorific value than the oil produced by the pyrolysis of SCB alone.

Contemporary HCV pangenotypic DAA treatment protocols are exclusionary to real world HIV-HCV co-infected patients

Background

Treatments for Hepatitis C virus (HCV) infection have vastly improved over the past few decades with current regimens now offering pangenotypic activity with excellent cure rates reported in clinical trials, including in the HIV-HCV coinfected population. However, there is some concern that stringent inclusion and exclusion criteria in the trials may lead to results that are not achievable in real-world populations.

Methods

Our study evaluated a real-world HIV-HCV coinfected population and compared them to the eligibility criteria for trials of two of the most recent approved HCV agents; sofosbuvir/velpatasvir and glecaprevir/pibrentasvir.

Results

Our study included 219 HIV-HCV coinfected patients and found that 89% met exclusion criteria for the sofosbuvir/velpatasvir trial and 90% met exclusion criteria for the glecaprevir/pibrentasvir trial. The majority of patients met more than one exclusion criteria with the most frequent criteria for exclusion being a non-approved ART regimen (58 and 47% respectively), having a psychiatric disorder (52%), active alcohol or injection drug use (27%), having an HIV viral load > 50 copies/ml (15%), a CrCl < 60 ml/min (13%) and a history of decompensated cirrhosis (13%).

Conclusion

Although the newer Hepatitis C treatments are very effective, the real world HIV-HCV coinfected population often have comorbidities and other characteristics that make them ineligible for clinical trials, such that they are barriers to treatment. These barriers need to be recognized and addressed in order to optimize treatment outcomes in the HIV patient population.

Can Quantitative Volumetric Analysis Predict Tumor Recurrence in the Patients with Mucinous Adenocarcinoma of the Lung After Surgical Resection?

RATIONALE AND OBJECTIVES

Mucinous adenocarcinoma (MAC) is a distinct histologic variant subtype of lung adenocarcinomas. However, detailed radiologic findings and prognostic factors are still poorly understood. Thus, this study aimed to investigate the prognostic value of quantitative volumetric analysis of the computed tomography images of patients with MAC after. surgical resection.

MATERIALS AND METHODS

Semiautomatic segmentation from computed tomography images of 60 patients with pathologically confirmed MAC was performed and retrospectively reviewed. The main cutoff value in Hounsfield Units (HU) to predict tumor recurrence was defined by receiver-operating curve analysis. Solid volume of mass (SVM) was defined as the volume of HU greater than this cutoff, and solid ratio (Sratio) was defined as SVM divided by total volume. Each parameter was compared to clinicopathologic characteristics and maximum standardized uptake value. Disease-free survival (DFS) was assessed and was compared among patients. Univariate and multivariate Cox regression was performed to predict DFS of MAC.

RESULTS

The cutoff value of HU as determined by ROC analysis was 20 HU. SVM and Sratio were positively correlated with the maximum standardized uptake and pathologic invasion size, respectively (p < 0.001). SVM and Sratio were significantly higher in the recurrence group than in the no-recurrence group (p < 0.001). Multivariate Cox proportional hazards regression analysis revealed that the SVM (Hazard Ratio 1.016; 95% Confidence Interval 1.000-1.032; p = 0.048) and Sratio (Hazard Ratio 29.136; 95% Confidence Interval 1.419-598.191; p = 0.029) were independent significant predictors of DFS.

CONCLUSION

Quantitative volumetric parameters can predict the prognosis of patients with MAC after surgical resection.

Clinical and radiological manifestations of lipoid pneumonia according to etiology: Squalene, omega-3-acid ethyl esters, and idiopathic

OBJECTIVES

Clinical manifestations of lipoid pneumonia (LP) vary depending on the causative agents or underlying causes. The aim of the present study was to investigate the clinical and radiological features of LP, classified according to etiologic agents.

METHODS

The clinico-radiological characteristics of LP patients were retrospectively compared among groups: exogenous versus idiopathic and squalene versus omega-3-acid ethyl esters (O-3-AEE) versus idiopathic. Idiopathic group was defined as LP with no proven or reported etiological evidence.

RESULTS

Twenty-two patients met the diagnostic criteria for LP: squalene (9 [41%]), O-3-AEE (6 [27%]), olive oil (1 [5%]), and idiopathic (7 [32%]). Compared with the exogenous group, the idiopathic group showed a higher recurrence rate; higher frequencies of bronchial anthracofibrosis (BAF) and bronchoalveolar lavage (BAL) lymphocytosis; and a higher rate of crazy-paving pattern and lower rate of consolidation on computed tomography scan. In three-group tests, compared with the O-3-AEE group, the squalene group exhibited a significantly higher percentage of neutrophils and a higher rate of right middle lobe (RML) involvement.

CONCLUSIONS

In comparison with the exogenous group, the idiopathic group demonstrated BAL lymphocytosis, higher rates of recurrence and BAF, and a higher rate of crazy-paving pattern. Compared with the O-3-AEE group, the squlaene group showed a higher percentage of BAL neutrophils and predominant RML involvement.

Femoral versus jugular access for Denali Vena Cava Filter placement: Analysis of fluoroscopic time, filter tilt and retrieval outcomes

PURPOSE

To analyze relevant metrics involved in Denali Vena Cava Filter placement via different venous access sites.

MATERIALS AND METHODS

Patients with Denali filters inserted between March 2017 and February 2018 were retrospectively analyzed. Pre-procedural and pre-retrieval computed tomography (CT) were reviewed. We compared inferior vena cava (IVC) diameter, filter tilt angle, filter tip IVC wall abutment, fluoroscopy time, and retrieval outcomes by venous access site. Filter tip abutment/limb penetration and procedure-related complications were investigated.

RESULTS

Seventy-eight patients had successfully-placed Denali filters. Seventy-one of 78 (91%) patients had both pre-procedural and pre-retrieval CT. The majority (35 [49%]) were placed via the right femoral vein (left femoral vein: 22 [31%]; right internal jugular vein: 14 [20%]). The jugular approach involved a longer fluoroscopy time (mean 117 ± 37 s [s]) than the right and left femoral approaches (mean 64 ± 21 s, mean 67 ± 15 s, respectively [p < 0.05]). Filter tilt and filter tip abutment were not significantly different between the 3 access routes. Filter tip abutment and limb penetration were observed in 8/71 (11%) and 2/71 (3%) patients, respectively. Filter retrieval was attempted in 68 of 78 (87%) cases, and all filters were successfully retrieved. One filter arm fractured during advanced retrieval; no other procedure related complications were recorded.

CONCLUSIONS

Both femoral venous approaches can be safely used for placement of the Denali filter. Femoral venous access involved a shorter fluoroscopy time without any differences in filter tilt and filter tip abutment compared to transjugular access.

Measurement of the Effective Weak Mixing Angle in pp[over ¯]→Z/γ^{*}→ℓ^{+}ℓ^{-} Events

We present a measurement of the effective weak mixing angle parameter sin^{2}θ_{eff}^{ℓ} in pp[over ¯]→Z/γ^{*}→μ^{+}μ^{-} events at a center-of-mass energy of 1.96 TeV, collected by the D0 detector at the Fermilab Tevatron Collider and corresponding to 8.6  fb^{-1} of integrated luminosity. The measured value of sin^{2}θ_{eff}^{ℓ}[μμ]=0.23016±0.00064 is further combined with the result from the D0 measurement in pp[over ¯]→Z/γ^{*}→e^{+}e^{-} events, resulting in sin^{2}θ_{eff}^{ℓ}[comb]=0.23095±0.00040. This combined result is the most precise measurement from a single experiment at a hadron collider and is the most precise determination using the coupling of the Z/γ^{*} to light quarks.

Relationship Between Clinical Features and Computed Tomographic Findings in Hospitalized Adult Patients With Community-Acquired Pneumonia

Background

Data on the relationship between the clinical and microbiological features of community-acquired pneumonia (CAP) and its computed tomography (CT) findings are limited. The aim of the present study was to investigate the clinic-microbiological features of patients with CAP presenting with ground-glass opacity (GGO) and centrilobular nodules or tree-in-bud pattern on CT images.

Methods

Patients with CAP who underwent a CT scan at presentation were retrospectively classified using CT findings into consolidation, GGO and bronchiolitis groups. These 3 groups were compared in terms of clinical parameters and microbiological data.

Results

A total of 40 patients (2.4%) were allocated to the bronchiolitis group and 46 (2.8%) to the GGO group. The most common pathogen in the bronchiolitis group was Mycoplasma pneumoniae, which was significantly more frequently isolated in this group. The bronchiolitis group was characterized by a higher percentage of cough, a lower percentage of chest pain and lower blood levels of inflammatory markers. Common pathogens in the GGO group were not significantly different from those in the other 2 groups. Unlike that observed in the consolidation group, complicated parapneumonic effusion or empyema was not observed in the bronchiolitis or GGO group. Outcome variables were similar in the 3 groups.

Conclusions

The bronchiolitis group was characterized by a higher frequency of M. pneumoniae and a less severe form of CAP. The GGO and consolidation groups was similar with respect to causative microorganisms and the clinical features of CAP. No patient in the bronchiolitis or GGO group exhibited complicated parapneumonic effusion or empyema.

Central venous catheterization-induced right brachiocephalic vein pseudoaneurysm: Successfully treated with stent-assisted coiling

INTRODUCTION

Central venous catheterization-induced central vein pseudoaneurysm is rare. Several treatment options have been recommended. We describe a case of central venous catheterization-induced right brachiocephalic vein pseudoaneurysm successfully treated with an uncovered self-expandable stent-assisted coil embolization and discuss the imaging findings, treatment strategy, and review of literature associated with thoracic venous pseudoaneurysm.

CASE REPORT

A 77-year-old woman was referred to our trauma center to undergo treatment for central venous catheterization-induced central vein pseudoaneurysm. The initial contrast-enhanced chest computed tomography revealed a 3.4-cm pseudoaneurysm arising from the right brachiocephalic vein and a surrounding mediastinal hematoma. The pseudoaneurysm was successfully embolized with stent-assisted coiling. Computed tomography angiography was performed 10 days after the procedure and demonstrated a completely embolized pseudoaneurysm and resolved mediastinal hematoma. Blood flow from the right subclavian and left innominate veins was not disturbed by the stent-assisted coils.

CONCLUSION

To our knowledge, this is the first report of treatment of a right brachiocephalic vein pseudoaneurysm with stent-assisted coil embolization. We think that uncovered stent-assisted coil embolization is the safest and most fundamental treatment for wide-neck venous pseudoaneurysm especially in a hemodynamically unstable setting.

Granulomatous reaction of primary mediastinal seminoma leading to diagnostic delay: a case report

Primary mediastinal seminoma (PMS) is a rare tumor. PMS can be morphologically related to secondary changes in the form of thymic remnants, cystic degeneration, epithelioid granulomas, fibrotic change, and syncytiotrophoblast-like cells. Ours was an interesting case where a 26-year-old male presented with an incidentally-found anterior mediastinal mass. Even though he had no pulmonary symptoms, the transthoracic co-axial needle biopsy of the mass suggested tuberculosis (TB). However, on follow-up computed tomography (CT) and magnetic resonance image (MRI) in 2 months, the mass slightly increased in size, and a small part of low density or signal intensity appeared, despite the regular anti-TB treatment regimen. Surgical resection was performed, and the resected specimens revealed scattered and irregular-shaped seminoma cells with an intervening chronic granulomatous reaction. The aim of this article is to report a case of PMS in a young male patient who had a granulomatous reaction that mimicked a neoplastic population of cells leading to an erroneous diagnosis of the small biopsy. Therefore, awareness of the secondary changes that can mimic a primary lesion can help with an early correction of this misdiagnosis.

Combined Forward-Backward Asymmetry Measurements in Top-Antitop Quark Production at the Tevatron

The CDF and D0 experiments at the Fermilab Tevatron have measured the asymmetry between yields of forward- and backward-produced top and antitop quarks based on their rapidity difference and the asymmetry between their decay leptons. These measurements use the full data sets collected in proton-antiproton collisions at a center-of-mass energy of sqrt[s]=1.96  TeV. We report the results of combinations of the inclusive asymmetries and their differential dependencies on relevant kinematic quantities. The combined inclusive asymmetry is A_{FB}^{tt[over ¯]}=0.128±0.025. The combined inclusive and differential asymmetries are consistent with recent standard model predictions.

Detection of Deep Vein Thrombosis by Follow-up Indirect Computed Tomography Venography after Pulmonary Embolism

Background

Information regarding the incidence and risk factors for deep vein thrombosis (DVT) detected by follow-up computed tomographic (CT) venography after pulmonary embolism (PE) is sparse. The aim of the present study was to identify the predictors of DVT in follow-up CT images, and to elucidate their clinical significance.

Methods

Patients with PE were classified into the following three cohorts based on the time of indirect CT venography follow-up: within 1 month, 1 to 3 months, and 3 to 9 months after the initial CT scan. Each cohort was subdivided into patients with or without DVT detected by follow-up CT. Clinical variables were compared between the two groups.

Results

Follow-up CT revealed DVT in 61% of patients with PE within 1 month, in 15% of patients with PE at 1 to 3 months, and in 9% of patients with PE at 3 to 9 months after the initial CT scan. Right ventricular (RV) dilation on the initial CT (odds ratio [OR], 8.30; 95% confidence interval [CI], 1.89–36.40; p=0.005) and proximal DVT at the initial presentation (OR, 6.93; 95% CI, 1.90–25.20; p=0.003) were found to independently predict DVT in follow-up CT images within 1 month, proximal DVT at the initial presentation was found to independently predict DVT in follow-up CT images at 1 to 3 months (OR, 6.69; 95% CI, 1.53–29.23; p=0.012), and central PE was found to independently predict DVT in follow-up CT images at 3 to 9 months (OR, 4.25; 95% CI, 1.22–4.83; p=0.023) after the initial CT scan. Furthermore, the detection of DVT by follow-up CT independently predicted the recurrence of venous thromboembolism (VTE) (OR, 4.67; 95% CI, 2.24–9.74; p<0.001).

Conclusion

Three months after PE, DVT was not detected by follow-up CT in most patients with PE. RV dilation on the initial CT, central PE, and proximal DVT at the initial presentation were found to predict DVT on follow-up CT, which might predict VTE recurrence.

Pulmonary embolism concurrent with lung cancer and central emboli predict mortality in patients with lung cancer and pulmonary embolism

Background

Patients with lung cancer commonly experience pulmonary embolism (PE). The aim of the present study was to examine the clinical features of patients with lung cancer and PE and to investigate prognostic factors in these patients.

Methods

This retrospective study divided patients with lung cancer and PE into a group of patients with PE diagnosed concomitantly with lung cancer (concurrent group) and a group with PE detected after lung cancer (sequential group), compared the clinical characteristics of patients in the two groups, and investigated prognostic factors in these patients.

Results

The study population consisted of the concurrent group [27 patients (10.1%)] and the sequential group [240 patients (89.9%)]. The concurrent group exhibited higher percentages of stage I cancer at the diagnosis of PE [6 (22.2%) vs. 8 (3.3%), P<0.001] and right ventricular (RV) dilation on computed tomography (CT) [14 (51.9%) vs. 41 (17.1%), P<0.001], as well as lower rate of small cell carcinoma [1 (3.7%) vs. 49 (20.4%), P=0.036] than the sequential group. PE concurrent with lung cancer [hazard ratio (HR) =2.64, 95% confidence interval (CI): 1.57-4.43, P<0.001] and central PE (HR =1.46, 95% CI: 1.02-2.10, P=0.04) were independent predictors of mortality in patients with lung cancer and PE.

Conclusions

PE concurrent with lung cancer is characterized by more severe PE and infrequent small cell carcinoma. PE concurrent with lung cancer and central emboli may be independent prognostic factors in patients with lung cancer and PE.