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Introduction: This study aimed to determine the frequency of thyroid gland involvement in chest CT scans of patients with COVID-19 admitted to university-affiliated hospitals and assess its relationship with the severity of lung involvement and patient survival in 2020. Material and methods: In this retrospective cross-sectional study, 1000 PCR-positive patients with COVID-19 who were referred to University-affiliated Hospital in 2020 and had chest CT performed within 72 hours of admission to the hospital were examined. The data was collected by patient file information and CT findings recorded in the PACS system, including thyroid involvement, the severity of lung involvement, and findings related to the death and recovery of patients. Results: The mean age of the examined patients was 56 years. 525 people (52.5%) were men, and 475 (47.5%) were women. 14% had severe pulmonary involvement, and 9.3% had very severe involvement. Moreover, 15.9 percent of them had deceased. 19.7% had focal thyroid involvement, 14% had diffuse involvement, and 66.3% were healthy subjects. Male gender and older age showed a significant relationship with thyroid gland involvement. The severity of lung involvement, the death rate in patients, and hospitalization in ICU were also significantly related to thyroid gland involvement in patients with COVID. Discussion and conclusion: This study highlights the importance of considering thyroid-gland involvement in the comprehensive management of COVID-19 patients. Routine screening and monitoring of thyroid-function may facilitate earlier detection and appropriate management of thyroid-related complications, potentially improving clinical outcomes. This study suggests that in COVID-19 infection the monitoring of thyroid function is prudent, particularly in cases of more serious disease. [ABSTRACT FROM AUTHOR]

Background and Objective: This study investigated the accuracy of portable ultrasonography in the diagnosis of traumatic thoracic lesions (hemothorax, pneumothorax, contusions and fractures) compared to Computed Tomography scan (CT-scan). Materials and Methods: This descriptive-analytical cross-sectional study was carried out on 50 patients with thoracic trauma to assess the diagnostic value of portable ultrasonography compared to CT scan. First, ultrasonography of the lungs and CT scan of the chest were performed. Then, the sensitivity, specificity, and positive and negative predictive values were investigated to examine the accuracy and precision of ultrasonography compared to CT scan. Results: In this study, the sensitivity, specificity, and positive and negative predictive values of ultrasonography for detecting thoracic lesions and complications following trauma were 56.82%, 100.0%, 100%, and 91.52%, respectively, with a diagnostic accuracy of 92.37%. Conclusion: The findings of the present study suggested that in the initial evaluation of patients with traumatic thoracic injuries, ultrasonography, in addition to being an accessible, simple, low-cost and feasible method for all patients, has a high diagnostic value, especially in diagnosing pneumothorax and sternum fracture. [ABSTRACT FROM AUTHOR]

Introduction: Bronchiectasis is a chronic progressive respiratory disease characterized by permanent dilatation of the bronchi. It is a complex condition with numerous different etiologies, co-morbidities, and a heterogeneous presentation. As we know, there is a lack of studies that describe the differences and compare the characteristics between focal and multifocal bronchiectasis. The aim of this study is to identify differences in clinical characteristics presentation, severity or distribution in focal and multifocal bronchiectasis, and prognostic implications. Methods: 126 patients with computed tomography (CT)-verified bronchiectasis were enrolled. Baseline characteristics that included age, sex, smoking history, and respiratory symptoms were recorded, with special attention paid to hemoptysis appearance, body mass index, and comorbidities. The type of bronchiectasis determined by CT scan and the modified Reiff scores indicating radiological severity were recorded. Patients were divided in two groups (I is focal and II is multifocal). Results: There were no statistically significant differences in age, smoking status, comorbidity, and BMI between the two groups. Multifocality was associated with a significantly higher proportion of females (p = 0.014), the rate of hemoptysis (p = 0.023), and the number of hospitalizations, but not of exacerbations and prevalence of immunodeficiency (p = 0.049). Significantly, a high number of subjects with multifocality had bronchiectasis of moderate severity, and post-infective and asthma-associated phenotypes were the dominant in this group. Unexpectedly, the cystic and varicose radiological phenotype (which need more time to develop) were more dominant in the focal group. The cylindrical phenotype was equally observed in the multifocal and focal groups. Conclusions: Our study suggests that multifocality is not related to age, number of exacerbations, or radiological phenotype, but it seems to be associated with the clinical post-infective phenotype, immunodeficiency, frequent hospitalizations, and severity. Thus, the presence of multifocal bronchiectasis may act as a biomarker of severity and poor outcomes in these patients. [ABSTRACT FROM AUTHOR]

Deep learning is a machine learning technique that has been optimized for image classification and object detection. Deep learning has brought huge advancement to the medical field as it helps to diagnose various diseases through computed tomography (CT) scan or X-ray images. Pneumonia is a respiratory disease, and it is one of the killer diseases that causes numerous death all around the world. In 2019, the outbreak of COVID-19 has increased the number of pneumonia patients tremendously. With the increasing number of patients, the clinical and medical facilities have become insufficient. The lack of doctors and radiologists to diagnose pneumonia has caused a high number of patients to be misdiagnosed. Chest image is one of the most effective methods to diagnose this disease, however, examining the X-ray or CT images requires specialists such as radiologists. Meanwhile, examining chest CT or X-ray images might be subjective as the presence of pneumonia can be unclear in the images. The main objective of this paper is to provide a comprehensive review of recent advancement in the diagnosis of pneumonia with deep learning, including state-of-art methodology, datasets, discussion, challenges, and future improvements. [ABSTRACT FROM AUTHOR]

To study the possibility of using acoustic parameters, i.e., Acoustic Voice Quality Index (AVQI) and Maximum Phonation Time (MPT) for predicting the degree of lung involvement in COVID-19 patients. This cross-sectional case–control study was conducted on the voice samples collected from 163 healthy individuals and 181 patients with COVID-19. Each participant produced a sustained vowel/a/, and a phonetically balanced Persian text containing 36 syllables. AVQI and MPT were measured using Praat scripts. Each patient underwent a non-enhanced chest computed tomographic scan and the Total Opacity score was rated to assess the degree of lung involvement. The results revealed significant differences between patients with COVID-19 and healthy individuals in terms of AVQI and MPT. A significant difference was also observed between male and female participants in AVQI and MPT. The results from the receiver operating characteristic curve analysis and area under the curve indicated that MPT (0.909) had higher diagnostic accuracy than AVQI (0.771). A significant relationship was observed between AVQI and TO scores. In the case of MPT, however, no such relationship was observed. The findings indicated that MPT was a better classifier in differentiating patients from healthy individuals, in comparison with AVQI. The results also showed that AVQI can be used as a predictor of the degree of patients' and recovered individuals' lung involvement. A formula is suggested for calculating the degree of lung involvement using AVQI. [ABSTRACT FROM AUTHOR]

BACKGROUND: Inconsistent results from COVID-19 studies raise the issue of patient heterogeneity. OBJECTIVE: The objective of this study was to identify homogeneous subgroups of patients (clusters) using baseline characteristics including inflammatory biomarkers and the extent of lung parenchymal lesions on CT, and to compare their outcomes. DESIGN: Retrospective single-center study. SETTING: Medical ICU of the University Hospital of Clermont-Ferrand, France. PATIENTS: All consecutive adult patients aged greater than or equal to 18 years, admitted between March 20, 2020, and August 31, 2021, for COVID-19 pneumonia. INTERVENTIONS: Characteristics at baseline, during ICU stay, and outcomes at day 60 were recorded. On the chest CT performed at admission the extent of lung parenchyma lesions was established by artificial intelligence software. MEASUREMENTS AND MAIN RESULTS: Clusters were determined by hierarchical clustering on principal components using principal component analysis of admission characteristics including plasma interleukin-6, human histocompatibility leukocyte antigen-DR expression rate on blood monocytes (HLA-DR) monocyticexpression rate (mHLA-DR), and the extent of lung parenchymal lesions. Factors associated with day 60 mortality were investigated by univariate survival analysis. Two hundred seventy patients were included. Four clusters were identified and three were fully described. Cluster 1 (obese patients, with moderate hypoxemia, moderate extent of lung parenchymal lesions, no inflammation, and no downregulation of mHLA-DR) had a better prognosis at day 60 (hazard ratio [HR] = 0.27 [0.15-0.46], p < 0.01), whereas cluster 2 (older patients with comorbidities, moderate extent of lung parenchyma lesions but significant hypoxemia, inflammation, and down-regulation of mHLA-DR) and cluster 3 (patients with severe parenchymal disease, hypoxemia, inflammatory reaction, and down-regulation of mHLA-DR) had an increased risk of mortality (HR = 2.07 [1.37-3.13], p < 0.01 and HR = 1.52 [1-2.32], p = 0.05, respectively). In multivariate analysis, only clusters 1 and 2 were independently associated with day 60 death. CONCLUSIONS: Three clusters with distinct characteristics and outcomes were identified. Such clusters could facilitate the identification of targeted populations for the next trials. [ABSTRACT FROM AUTHOR]

The diagnosis, prognostication, and differentiation of phenotypes of COPD can be facilitated by CT scan imaging of the chest. CT scan imaging of the chest is a prerequisite for lung volume reduction surgery and lung transplantation. Quantitative analysis can be used to evaluate extent of disease progression. Evolving imaging techniques include micro-CT scan, ultra-high-resolution and photon-counting CT scan imaging, and MRI. Potential advantages of these newer techniques include improved resolution, prediction of reversibility, and obviation of radiation exposure. This article discusses important emerging techniques in imaging patients with COPD. The clinical usefulness of these emerging techniques as they stand today are tabulated for the benefit of the practicing pulmonologist. [ABSTRACT FROM AUTHOR]

As COVID-19 has spread rapidly, detection of the COVID-19 infection from radiology and radiography images is probably one of the quickest ways to diagnose the patients. Many researchers found the necessity to utilize chest X-ray and chest computed tomography imaging to diagnose COVID-19 infection. In this paper, our objective is to minimize the false negatives and false positives in the detection process. Reduction in the number of false negatives minimizes community spread of the COVID-19 pandemic. Reducing false positives help people avoid mental trauma and wasteful expenses. This paper proposes a novel weighted consensus model to minimize the number of false negatives and false positives without compromising accuracy. In the proposed novel weighted consensus model, the accuracy of individual classification models is normalized. While predicting, different models predict different classes, and the sum of the normalized accuracy for a particular class is then considered based on a predefined threshold value. We used traditional Machine Learning classification algorithms like Linear Regression, Support Vector Machine, k-Nearest Neighbours, Decision Tree, and Random Forest for the weighted consensus experimental evaluation. We predicted the classes, which provided better insights into the condition. The proposed model can perform as well as the existing state-of-the-art technique in terms of accuracy (99.64%) and reduce false negatives and false positives. [ABSTRACT FROM AUTHOR]

COPD is a condition characterized by chronic airflow obstruction resulting from chronic bronchitis, emphysema, or both. The clinical picture is usually progressive with respiratory symptoms such as exertional dyspnea and chronic cough. For many years, spirometry was used to establish a diagnosis of COPD. Recent advancements in imaging techniques allow quantitative and qualitative analysis of the lung parenchyma as well as related airways and vascular and extrapulmonary manifestations of COPD. These imaging methods may allow prognostication of disease and shed light on the efficacy of pharmacologic and nonpharmacologic interventions. This is the first of a two-part series of articles on the usefulness of imaging methods in COPD, and it highlights useful information that clinicians can obtain from these imaging studies to make more accurate diagnosis and therapeutic decisions. [ABSTRACT FROM AUTHOR]

The coronavirus (SARS-CoV-2), which causes severe acute respiratory syndrome (COVID-19), is the most current virus with the potential to kill a substantial number of people around the world. Current procedures are restrictive, time-consuming, inefficient, and obsolete. This is due to their exclusive reliance on the technical expertise of a radiologist or medical consultant. Deep learning and technological advancement have also enabled medical researchers and scientists to investigate various neural networks and algorithms to develop apps, tools, and gadgets that can assist medical radiologists. This paper aims to give an overview of deep learning techniques that have been used in chest radiography of COVID-19 and pneumonia cases, as well as the most important datasets that help researchers test algorithms. [ABSTRACT FROM AUTHOR]

Background: Coccidioidomycosis (cocci) is an endemic fungal disease that can cause asymptomatic or post-symptomatic lung nodules which are visible on chest CT scanning. Lung nodules are common and can represent early lung cancer. Differentiating lung nodules due to cocci from those due to lung cancer can be difficult and lead to invasive and expensive evaluations. Materials and Methods: We identified 302 patients with biopsy-proven cocci or bronchogenic carcinoma seen in our multidisciplinary nodule clinic. Two experienced radiologists who were blinded to the diagnosis read the chest CT scans and identified radiographic characteristics to determine their utility in differentiating lung cancer nodules from those due to cocci. Results: Using univariate analysis, we identified several radiographic findings that differed between lung cancer and cocci infection. We then entered these variables along with age and gender into a multivariate model and found that age, nodule diameter, nodule cavitation, presence of satellite nodules and radiographic presence of chronic lung disease differed significantly between the two diagnoses. Three findings, cavitary nodules, satellite nodules and chronic lung disease, have sufficient discrimination to potentially be useful in clinical decision-making. Conclusions: Careful evaluation of the three obtained radiographic findings can significantly improve our ability to differentiate benign coccidioidomycosis infection from lung cancer in an endemic region for the fungal disease. Using these data may significantly reduce the cost and risk associated with distinguishing the cause of lung nodules in these patients by preventing unnecessary invasive studies. [ABSTRACT FROM AUTHOR]

Copyright of CT Theory & Applications is the property of Editorial Department of CT Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Nonspecific clinical features and imaging findings of COVID-19 may lead to misdiagnosis with other diseases that have specific risks and treatments. Here a patient is reported with Pneumocystis Pneumonia with an undiagnosed HIV disease who was treated for COVID-19 with no response after one week. COVID-19 was diagnosed by CT findings but PCR was negative. Further evaluation for ground glass opacities confirmed AIDS and clinical response to Pneumocystis Pneumonia treatment. [ABSTRACT FROM AUTHOR]

Background: Detection of COVID-19 in cancer patients is challenging due to probable preexisting pulmonary infiltration caused by many infectious and non-infectious etiologies. We evaluated chest CT scan findings of COVID-19 pneumonia in cancer patients and explored its prognostic role in mortality. Methods: We studied 266 COVID-19 patients with a history of cancer diagnosis between 2020 and 2022. Chest CT images were reported based on Radiological Society of North America (RSNA) structural report and the CT score and pattern of involvement were noted. We used multivariate logistic regression models to determine the association between CT scan findings and mortality of the cancer COVID-19 patients. Results: The mean age was 56.48 (± 18.59), and 53% were men. Gastrointestinal (29.3%), hematologic (26.3%), and breast (10.5%) cancers were the most frequent types of cancer. The prevalence of atypical or indeterminate findings in the chest CT was 42.8%. Most radiologic findings were consolidation mixed with ground-glass opacity (44.4%), pleural effusion (33.5%), and pure ground-glass opacity (19.5%). The risk of death was higher among those who had typical chest CT for COVID-19 (OR 3.47; 95% CI 1.14–8.98) and those who had a severity of score higher than 18 (OR 1.89; 95% CI 1.07–3.34). Also, presence of consolidation (P value 0.040), pleural effusion (P value 0.000), centrilobular nodules (P value 0.013), and architectural distortion (P value 0.005) were associated with a poorer prognosis. Conclusion: Less than half of COVID-19 patients with a history of cancer had typical imaging features of COVID-19. Radiologists should be aware of atypical, rare, or subtle chest CT findings in patients with pre-existing cancer. [ABSTRACT FROM AUTHOR]

aim to determine the utility of CT scan as a method to accurately confirm pediatric airway foreign bodies (AFBs), the current gold standard of which is chest X-ray as the primary imaging modality in the investigation screening of AFBs with progression to microlaryngobronchoscopy. Methods: A retrospective cohort study of children diagnosed with suspected AFBs between July 2019 and June 2020 was conducted. The primary outcome of missed AFBs from radiologic investigations was recorded. Results: A total of 226 children with an average age of 1.94 years were included in this study. One hundred and two children were eventually admitted to the hospital for microlaryngobronchoscopy. A total of 89 cases were initially examined by chest X-ray with the diagnosis confirmed in 26 cases. The initial examination was chest CT scan in 105 cases, of which the diagnosis was confirmed in 46 cases. The initial examination was chest CT scan with airway reconstruction in 32 cases, and the diagnosis was confirmed in 17 cases. Patients with negative chest CT scan with airway reconstruction were observed to have resolution of symptoms with no further need for bronchoscopy. Conclusion: Chest CT scan with airway reconstruction had the highest rate of confirmed diagnosis of pediatric AFBs on initial scanning, followed by chest CT scan, and finally chest X-ray with fluoroscopy; there was no missed diagnosis in chest CT scan with airway reconstruction. Chest CT scan with airway reconstruction can accurately and quickly detect AFBs and reduce unnecessary bronchoscopy. [ABSTRACT FROM AUTHOR]

Current research indicates that for the identification of lung disorders, comprising pneumonia and COVID-19, structural distortions of bronchi and arteries (BA) should be taken into account. CT scans are an effective modality to detect lung anomalies. However, anomalies in bronchi and arteries can be difficult to detect. Therefore, in this study, alterations of bronchi and arteries are considered in the classification of lung diseases. Four approaches to highlight these are introduced: (a) a Hessian-based approach, (b) a region-growing algorithm, (c) a clustering-based approach, and (d) a color-coding-based approach. Prior to this, the lungs are segmented, employing several image preprocessing algorithms. The utilized COVID-19 Lung CT scan dataset contains three classes named Non-COVID, COVID, and community-acquired pneumonia, having 6983, 7593, and 2618 samples, respectively. To classify the CT scans into three classes, two deep learning architectures, (a) a convolutional neural network (CNN) and (b) a CNN with long short-term memory (LSTM) and an attention mechanism, are considered. Both these models are trained with the four datasets achieved from the four approaches. Results show that the CNN model achieved test accuracies of 88.52%, 87.14%, 92.36%, and 95.84% for the Hessian, the region-growing, the color-coding, and the clustering-based approaches, respectively. The CNN with LSTM and an attention mechanism model results in an increase in overall accuracy for all approaches with an 89.61%, 88.28%, 94.61%, and 97.12% test accuracy for the Hessian, region-growing, color-coding, and clustering-based approaches, respectively. To assess overfitting, the accuracy and loss curves and k-fold cross-validation technique are employed. The Hessian-based and region-growing algorithm-based approaches produced nearly equivalent outcomes. Our proposed method outperforms state-of-the-art studies, indicating that it may be worthwhile to pay more attention to BA features in lung disease classification based on CT images. [ABSTRACT FROM AUTHOR]

Background: In the setting of a coronary care unit (CCU), the early detection of pneumonia is of paramount important to prevent severe complications. This study was designed aiming to evaluate the diagnostic accuracy of lung ultrasound (LUS) in the detection of pneumonia and compared with chest X-ray (CXR). Method: We enrolled 110 consecutive patients admitted to the CCU of Federico II University Hospital. Each patient underwent CXR and bedside LUS on admission. The final diagnosis (pneumonia vs. no pneumonia) was established by another clinician reviewing clinical and laboratory data independent of LUS results and possibly prescribing chest contrast-enhanced CT (n = 34). Results: The mean age was 70 ± 11 years old, and 68% were males. Pneumonia was clinically diagnosed in 26 (23%) patients. LUS was positive for pneumonia in 24 patients (sensitivity 92%, specificity 81%). Chest radiography was positive for pneumonia in nine patients (sensitivity 43%, specificity 95%). Using CT scan as a reference, LUS exhibited 92% sensitivity and a specificity of 96%. In ROC curve analysis, the diagnostic accuracy of CXR and LUS for the diagnosis of pneumonia was 0.86 (95% CI 0.77–0.94), which was higher than CXR 0.68 (95% CI 0.55–0.84), p < 0.05. Conclusion: Based on the findings of the present study, the accuracy of LUS in the detection of pneumonia was significantly higher than chest X-ray with comparable sensibility to CT scan. [ABSTRACT FROM AUTHOR]

Introduction: In order to allow the resumption of diving activities after a COVID-19 infection, French military divers are required to undergo a medical fitness to dive (FTD) assessment. We present here the results of this medical evaluation performed 1 month after the infection. Methods: We retrospectively analyzed between April 2020 and February 2021 200 records of divers suspected of COVID-19 contamination. Data collected included physical examination, ECG, blood biochemistry, chest CT scan and spirometry. Results: 145 PCR-positive subjects were included, representing 8.5% of the total population of French military divers. Two divers were hospitalized, one for pericarditis and the other for non-hypoxemic pneumonia. For the other 143 divers, physical examination, electrocardiogram and blood biology showed no abnormalities. However 5 divers (3.4%) had persistent subjective symptoms including fatigability, exertional dyspnea, dysesthesias and anosmia. 41 subjects (29%) had significant decreases in forced expiratory flows at 25-75% and 50% on spirometry (n = 20) or bilateral ground-glass opacities on chest CT scan (n = 24). Only 3 subjects were affected on both spirometry and chest CT. 45% of these abnormalities were found in subjects who were initially asymptomatic or had non-respiratory symptoms. In case of abnormalities, normalization was obtained within 3 months. The median time to return to diving was 45 days (IQR 30, 64). Conclusion: Our study confirms the need for standardized follow-up in all divers after COVID-19 infection and for maintaining a rest period before resuming diving activities. [ABSTRACT FROM AUTHOR]

Spontaneous pneumomediastinum (SPM) associated with SARS-CoV-2 infection is a rare condition but can represent a medical emergency. It is probably related to alveolar damage secondary to SARS-CoV-2 infection, which allows air to escape in the surrounding lung tissue. Cough and airways' barotrauma are also mentioned as contributing mechanisms. Treatment is generally conservative, but surgery may be required in severe cases. This paper presents the case of a 16-year-old girl with COVID-19-associated SPM who was treated conservatively in our department. The clinical course was favorable with resolution of respiratory symptoms and radiological (chest CT scan) image of pneumomediastinum. The patient was discharged 7 days after the confirmation of the initial SP diagnosis with appropriate treatment and recommendations for isolation. The sudden occurrence of chest pain and dyspnea should raise the suspicion of SPM in COVID-19 patients. Close surveillance and proper radiological monitoring are required in such cases. Treatment should be strictly individualized based on clinical course and radiological appearance. [ABSTRACT FROM AUTHOR]

Copyright of Annales Françaises de Médecine d'Urgence is the property of John Libbey Eurotext Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Timely and accurate diagnosis of coronavirus disease 2019 (COVID-19) is crucial in curbing its spread. Slow testing results of reverse transcription-polymerase chain reaction (RT-PCR) and a shortage of test kits have led to consider chest computed tomography (CT) as an alternative screening and diagnostic tool. Many deep learning methods, especially convolutional neural networks (CNNs), have been developed to detect COVID-19 cases from chest CT scans. Most of these models demand a vast number of parameters which often suffer from overfitting in the presence of limited training data. Moreover, the linearly stacked single-branched architecture based models hamper the extraction of multi-scale features, reducing the detection performance. In this paper, to handle these issues, we propose an extremely lightweight CNN with multi-scale feature learning blocks called as MFL-Net. The MFL-Net comprises a sequence of MFL blocks that combines multiple convolutional layers with $3 \times 3$ filters and residual connections effectively, thereby extracting multi-scale features at different levels and preserving them throughout the block. The model has only 0.78M parameters and requires low computational cost and memory space compared to many ImageNet pretrained CNN architectures. Comprehensive experiments are carried out using two publicly available COVID-19 CT imaging datasets. The results demonstrate that the proposed model achieves higher performance than pretrained CNN models and state-of-the-art methods on both datasets with limited training data despite having an extremely lightweight architecture. The proposed method proves to be an effective aid for the healthcare system in the accurate and timely diagnosis of COVID-19. [ABSTRACT FROM AUTHOR]

COVID-19 which was announced as a pandemic on 11 March 2020, is still infecting millions to date as the vaccines that have been developed do not prevent the disease but rather reduce the severity of the symptoms. Until a vaccine is developed that can prevent COVID-19 infection, the testing of individuals will be a continuous process. Medical personnel monitor and treat all health conditions; hence, the time-consuming process to monitor and test all individuals for COVID-19 becomes an impossible task, especially as COVID-19 shares similar symptoms with the common cold and pneumonia. Some off-the-counter tests have been developed and sold, but they are unreliable and add an additional burden because false-positive cases have to visit hospitals and perform specialized diagnostic tests to confirm the diagnosis. Therefore, the need for systems that can automatically detect and diagnose COVID-19 automatically without human intervention is still an urgent priority and will remain so because the same technology can be used for future pandemics and other health conditions. In this paper, we propose a modified machine learning (ML) process that integrates deep learning (DL) algorithms for feature extraction and well-known classifiers that can accurately detect and diagnose COVID-19 from chest CT scans. Publicly available datasets were made available by the China Consortium for Chest CT Image Investigation (CC-CCII). The highest average accuracy obtained was 99.9% using the modified ML process when 2000 features were extracted using GoogleNet and ResNet18 and using the support vector machine (SVM) classifier. The results obtained using the modified ML process were higher when compared to similar methods reported in the extant literature using the same datasets or different datasets of similar size; thus, this study is considered of added value to the current body of knowledge. Further research in this field is required to develop methods that can be applied in hospitals and can better equip mankind to be prepared for any future pandemics. [ABSTRACT FROM AUTHOR]

Background: Computed tomography (CT) is a routine procedure for diagnosing using ionization radiation which has hazardous effects especially on sensitive organs. Objective: The aim of this study was to quantify the dose reduction effect of lead apron shielding on the testicular region during routine chest CT scans.Material and Methods: In this measurement study, the routine chest CT examinations were performed for 30 male patients with common lead aprons folded and positioned in testis regions. The patient’s mean body mass index (BMI) was 26.2 ± 4.6 kg/m2. To calculate the doses at testis region, three thermoluminescent dosimeters (TLD-100) were attached at the top surface of the apron as an indicator of the doses without shielding, and three TLDs under the apron for doses with shielding. The TLD readouts were compared using SPSS software (Wilcoxon test) version 16. Results: The radiation dose in the testicular regions was reduced from 0.46 ± 0.04 to 0.20 ± 0.04 mGy in the presence of lead apron shielding (p < 0.001), the reduction was equal to 56%. Furthermore, the heritable risk probability was obtained at 2.0 ×10-5 % and 4.6 ×10-5 % for the patients using the lead apron shield versus without shield, respectively. Conclusion: Applying common lead aprons as shielding in the testis regions of male patients undergoing chest CT scans can reduce the radiation doses significantly. Therefore, this shield can be recommended for routine chest CT examinations.

Introduction: Whether diagnostic computed tomography (CT) scans to cardiac implantable electronic devices (CIED) is safe in recent models remains unknown. Methods: A two‐centers observational study. Over 14 years, consecutive 2362 chest CT scans (1666 pacemakers [PMs], 145 cardiac resynchronization therapy PM, 316 implantable cardioverter‐defibrillator, and 233 cardiac resynchronization therapy defibrillator) were interrogated and monitored upon imaging. Results: Electromagnetic interference occurred only in a few old models: InSync 8040 (n = 14), InSync III Marquis (n = 1), and Kappa (n = 4), which resulted no adverse events. Conclusion: CIEDs, especially recent ones, are confirmed safe on chest CT. [ABSTRACT FROM AUTHOR]

Background: Septic pulmonary embolism (SPE) is an unusual condition characterized by the implantation of infected thrombi into the pulmonary vasculature from a variety of infectious sources. This study aimed to illustrate the clinicoradiological features, microbiological spectrum, and clinical course of patients with SPE, as well as to promote the early identification, diagnosis, and prognosis of this unusual disease. Methods: Nineteen patients with SPE collected from the electronic medical records of our hospital were retrospectively reviewed during three years. Results: The study included twelve men and seven women with a mean age of 49 (15– 78). The most common presenting features were fever (79%) and shortness of breath (73.7%). Chronic kidney disease (68.4%) and diabetes (36.8%) were the most common comorbidities. The most common source of infection was venous catheters (58%). Staphylococcus aureus was the most predominant pathogen in about 52.6% of the cases. According to the CT findings, bilateral opacities were detected in all cases, flowing by nodular in 73.9% and cavitations in 57.9%. Central distributions were the most patterns regarding the location of the lesion seen in 47.4% of the patients. All patients received antimicrobial treatment, while 13 cases administered systemic anticoagulant. Most of the patients (73.7%) recovered from their illness, while 26.3% died. The median duration of hospitalization was 11.5 days. Oxygen saturation level and altered mental status were significantly associated with the mortality rate of SPE patients. Conclusion: The study's findings presented that altered mental status and low oxygen saturation are associated with a high mortality rate in SPE patients, especially those requiring critical care. Early diagnosis of an embolic phenomenon to other organ systems like the central nervous system can greatly influence the patient's outcome. [ABSTRACT FROM AUTHOR]

We experienced a case of silent Coronavirus disease 2019 (COVID-19) pneumonia that was found by an optional chest computed tomography (CT) scan during a health check. A 62-year-old man with a present medical history of hypertension visited the health screening center at Tokai University Tokyo Hospital on August 7th, 2020. Prior to entry into the hospital, his body temperature was measured and his history was obtained (called 'COVID-19 triage'), but there were no remarkable findings. Subsequently, patchy ground glass opacities were observed with peripheral distribution in bilateral multiple lobes. Based on this finding COVID-19 pneumonia was highly suspected. Subsequently, a PCR test was positive for COVID-19. Even in health check settings, we should be aware of possible encounters with COVID-19 infections. The high risk of silent spread plays a significant role in the ongoing pandemic. Chest CT scans, which can efficiently identify silent COVID-19 pneumonia, should be performed earlier during health check examinations, at least before gastroendoscopy, which causes significant droplet dispersion. Health check examination providers should not cancel or postpone health checks; rather, it is necessary for them to provide health check examinees with a safe environment with minimal delay in access to recommended health care services. [ABSTRACT FROM AUTHOR]

Background/aim: This study was to describe the clinical characteristics, chest CT image findings, and potential role of T cells immunity in adenovirus positive pneumonia. Materials/methods: In this retrospective study, medical records of 53 adult Adv+ patients who were admitted to the Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, from May 2015 to August 2019 were included. The presence of adenovirus and other respiratory viruses was detected using polymerase chain reaction of throat swabs samples. Clinical features and chest computed tomography (CT) findings were compared between patients with Adv+ pneumonia and Adv+ non-pneumonia. Results: The top 3 most commonly occurring symptoms in Adv+ pneumonia patients were fever (66.7%), cough (63.3%), and tachypnea (16.7%). Patients with Adv+ pneumonia showed significantly higher rates of cough and fever and longer duration of hospitalization than patients with Adv+ non-pneumonia. In the Adv+ pneumonia group, consolidation (73.3%) was the most common imaging finding on chest CT scan, and the likelihood of involvement of bilateral lobes (60%) was high. Classical conspicuous consolidation with surrounding ground-glass opacity was observed in 5 (16.6%) patients with Adv+ pneumonia. Patients with Adv+ pneumonia showed a higher inhibition of T-cell immunity than did patients with Adv+ non-pneumonia, and counts of CD3+, CD4+, and CD8+ T-cells may predict the presence of pneumonia in Adv+ patients. Conclusion: With regard to Adv+ pneumonia, the most frequent symptoms were cough and fever, and the most common CT pattern was consolidation; classical CT findings such as consolidation with surrounding ground-glass opacity could also be observed. Furthermore, our data indicated the incidence of abrogated cellular immunity in patients with Adv+ pneumonia. [ABSTRACT FROM AUTHOR]

Background: Coronavirus disease 2019 acute respiratory distress syndrome (COVID‐19 ARDS) is a disease that often requires invasive ventilation. Little is known about COVID‐19 ARDS sequelae. We assessed the mid‐term lung status of COVID‐19 survivors and investigated factors associated with pulmonary sequelae. Methods: All adult COVID‐19 patients admitted to the intensive care unit from 25th February to 27th April 2020 were included. Lung function was evaluated through chest CT scan and pulmonary function tests (PFT). Logistic regression was used to identify predictors of persisting lung alterations. Results: Forty‐nine patients (75%) completed lung assessment. Chest CT scan was performed after a median (interquartile range) time of 97 (89–105) days, whilst PFT after 142 (133–160) days. The median age was 58 (52–65) years and most patients were male (90%). The median duration of mechanical ventilation was 11 (6–16) days. Median tidal volume/ideal body weight (TV/IBW) was 6.8 (5.71–7.67) ml/Kg. 59% and 63% of patients showed radiological and functional lung sequelae, respectively. The diffusion capacity of carbon monoxide (DLCO) was reduced by 59%, with a median per cent of predicted DLCO of 72.1 (57.9–93.9) %. Mean TV/IBW during invasive ventilation emerged as an independent predictor of persistent CT scan abnormalities, whilst the duration of mechanical ventilation was an independent predictor of both CT and PFT abnormalities. The extension of lung involvement at hospital admission (evaluated through Radiographic Assessment of Lung Edema, RALE score) independently predicted the risk of persistent alterations in PFTs. Conclusions: Both the extent of lung parenchymal involvement and mechanical ventilation protocols predict morphological and functional lung abnormalities months after COVID‐19. [ABSTRACT FROM AUTHOR]

Chest computed tomography (CT) scan is one of the main modalities to detect COVID-19 infection. Several CT scan findings are the hallmark to rapidly detect suspected COVID-19 infection, therefore timely treatment could be administered. This study aims to describe chest CT scan findings of confirmed COVID-19 patients based on clinical symptom onset patterns. This study is a descriptive study with a retrospective design in confirmed COVID-19 patients. Data regarding characteristics of chest CT scan findings and the patient's history including clinical symptoms onset were collected. There were 123 subjects in this study. The study data were categorized into modified clinical symptom onset patterns which were early, progressive, peak, absorption, and advanced phases. Most of male (57%) and female (43%) patients that were admitted to the hospital were in absorption phase of the disease with fever, cough, and dyspnea as the most prevalent symptoms. Chest CT scan findings of absorption phase included GGO (ground glass opacity) in 28 patients (76%), crazy paving pattern in 18 patients (49%), consolidation in 22 patients (59%), and fibrosis in 31 patients (84%). Chest CT scan findings of confirmed COVID-19 patients vary depending on the phase of the disease. Risk factors and secondary bacterial infection may contribute to long-term persistence of symptoms. [ABSTRACT FROM AUTHOR]

The novel coronavirus outbreak has spread worldwide, causing respiratory infections in humans, leading to a huge global pandemic COVID-19. According to World Health Organization, the only way to curb this spread is by increasing the testing and isolating the infected. Meanwhile, the clinical testing currently being followed is not easily accessible and requires much time to give the results. In this scenario, remote diagnostic systems could become a handy solution. Some existing studies leverage the deep learning approach to provide an effective alternative to clinical diagnostic techniques. However, it is difficult to use such complex networks in resource constraint environments. To address this problem, we developed a fine-tuned deep learning model inspired by the architecture of the MobileNet V2 model. Moreover, the developed model is further optimized in terms of its size and complexity to make it compatible with mobile and edge devices. The results of extensive experimentation performed on a real-world dataset consisting of 2482 chest Computerized Tomography scan images strongly suggest the superiority of the developed fine-tuned deep learning model in terms of high accuracy and faster diagnosis time. The proposed model achieved a classification accuracy of 96.40%, with approximately ten times shorter response time than prevailing deep learning models. Further, McNemar's statistical test results also prove the efficacy of the proposed model. [ABSTRACT FROM AUTHOR]

Background: There is an urgent need for population-based studies on managing patients with pulmonary nodules.Research Question: Is it possible to identify pulmonary nodules and associated characteristics using an automated method?Study Design and Methods: We revised and refined an existing natural language processing (NLP) algorithm to identify radiology transcripts with pulmonary nodules and greatly expanded its functionality to identify the characteristics of the largest nodule, when present, including size, lobe, laterality, attenuation, calcification, and edge. We compared NLP results with a reference standard of manual transcript review in a random test sample of 200 radiology transcripts. We applied the final automated method to a larger cohort of patients who underwent chest CT scan in an integrated health care system from 2006 to 2016, and described their demographic and clinical characteristics.Results: In the test sample, the NLP algorithm had very high sensitivity (98.6%; 95% CI, 95.0%-99.8%) and specificity (100%; 95% CI, 93.9%-100%) for identifying pulmonary nodules. For attenuation, edge, and calcification, the NLP algorithm achieved similar accuracies, and it correctly identified the diameter of the largest nodule in 135 of 141 cases (95.7%; 95% CI, 91.0%-98.4%). In the larger cohort, the NLP found 217,771 reports with nodules among 717,304 chest CT reports (30.4%). From 2006 to 2016, the number of reports with nodules increased by 150%, and the mean size of the largest nodule gradually decreased from 11 to 8.9 mm. Radiologists documented the laterality and lobe (90%-95%) more often than the attenuation, calcification, and edge characteristics (11%-14%).Interpretation: The NLP algorithm identified pulmonary nodules and associated characteristics with high accuracy. In our community practice settings, the documentation of nodule characteristics is incomplete. Our results call for better documentation of nodule findings. The NLP algorithm can be used in population-based studies to identify pulmonary nodules, avoiding labor-intensive chart review. [ABSTRACT FROM AUTHOR]

Purpose: Coronavirus disease 2019 (COVID-19) is a novel, highly contagious infection occurring throughout the world. Real-time polymerase chain reaction (RT-PCR) and computed tomography (CT) scan play a pivotal role in diagnosis. Chest CT although sensitive enough, is less specific in diagnosing COVID-19. The purpose of our study was to compare the sensitivity and specificity of chest CT with real-time polymerase chain reaction (RT-PCR) as reference standard. Methods: RT-PCR and chest CT were performed in patients with suspected COVID-19 disease and diagnostic accuracy of both the modalities was compared. Sensitivity, specificity, positive predictive and negative predictive values of the chest CT were calculated with RT-PCR assay as the reference standard. Results: Out of 100 consecutive patients with suspected COVID-19 disease, RT-PCR assay was positive in 64% of patients and abnormal findings on chest CT were seen in 72% of patients. CT was 79.7% sensitive and 41.7% specific in diagnosing COVID-19 disease with positive predictive and negative predictive values of 70.8% and 53.6% respectively, with RT-PCR as gold standard. CT was more sensitive and less specific than RT-PCR in diagnosing COVID-19 disease (p-value 0.02, k=0.224). Conclusion: Appropriate diagnosis of COVID-19 should be made on the basis of clinical presentation, viral nucleotide testing, contact history, occupational/social exposure and RT-PCR assay. Chest CT should only be employed in case of patients with high clinical suspicion of COVID-19 disease with negative RT-PCR result. [ABSTRACT FROM AUTHOR]

Background: Computed tomography (CT) is a routine procedure for diagnosing using ionization radiation which has hazardous effects especially on sensitive organs. Objective: The aim of this study was to quantify the dose reduction effect of lead apron shielding on the testicular region during routine chest CT scans. Material and Methods: In this measurement study, the routine chest CT examinations were performed for 30 male patients with common lead aprons folded and positioned in testis regions. The patient's mean body mass index (BMI) was 26.2 ± 4.6 kg/m². To calculate the doses at testis region, three thermoluminescent dosimeters (TLD-100) were attached at the top surface of the apron as an indicator of the doses without shielding, and three TLDs under the apron for doses with shielding. The TLD readouts were compared using SPSS software (Wilcoxon test) version 16. Results: The radiation dose in the testicular regions was reduced from 0.46 ± 0.04 to 0.20 ± 0.04 mGy in the presence of lead apron shielding (p < 0.001), the reduction was equal to 56%. Furthermore, the heritable risk probability was obtained at 2.0 ×10-5 % and 4.6 ×10-5 % for the patients using the lead apron shield versus without shield, respectively. Conclusion: Applying common lead aprons as shielding in the testis regions of male patients undergoing chest CT scans can reduce the radiation doses significantly. Therefore, this shield can be recommended for routine chest CT examinations. [ABSTRACT FROM AUTHOR]

In this article, we report a patient referred to the clinic of Imam Khomeini Hospital in Sari, Mazandaran, northern Iran, with a 3‐month complaint of chronic cough and weight loss. According to the chest computed tomography scan, a cavity was detected in the upper lobe of the patient's left lung. The patient had no history of smoking or underlying diseases that predisposed him to cavitation, including tuberculosis. Then, bronchoscopy was performed for the patient, and bronchoalveolar lavage fluid was sent to the Iranian National Registry Center for lophomoniasis, and Lophomonas blattarum was detected in samples. Finally, the patient's symptoms were totally resolved by prescribing third‐daily metronidazole for 2 weeks. [ABSTRACT FROM AUTHOR]

Purpose: COVID-19 is a novel, severely contagious and progressive infection occurring worldwide. The diagnosis of the disease is based on real-time polymerase chain reaction (RT-PCR) and computed tomography (CT) scan, even though they are still controversial methods. Material and methods: We studied 54 patients with suspected COVID-19 and the two mentioned methods were compared with each other. Results: Sensitivity and specificity of the abnormal chest CT scan, ground-glass opacity (GGO), consolidation opacity, and both of GGO and consolidation were also surveyed based on RT-PCR. The results showed that RT-PCR assay was negative in 23 (42.6%) patients and positive in 31 (57.4%) cases. Also, the patients with an abnormal chest CT scan comprised 37 (68.5%). The sensitivity and specificity of abnormal CT scan were 78.6% and 42.3%, respectively, based on the RT-PCR method. Conclusions: Other techniques alongside CT scan and RT-PCR are advocated for accuracy of the COVID-19 diagnosis. [ABSTRACT FROM AUTHOR]

Aim: To observe the clinical course of symptomatic pregnant women diagnosed with or suspected of having COVID‐19. Methods: This study analyzed the clinical and laboratory results of 27 patients with real‐time polymerase chain reaction (RT‐PCR)‐confirmed COVID‐19 and 25 patients with a suspected COVID‐19 diagnosis based on their symptoms and chest computed tomography (CT) findings. The patients' coagulation parameters and acute‐phase reactants were evaluated both before and after treatment. The maternal and neonatal outcomes were also reviewed. Results: The mean duration of hospitalization was 6.1 ± 3 days. The gestational age of the patients ranged from 6w2d to 40w2d. Thirty‐five patients' CT scan findings suggested viral pneumonia. Four patients delivered vaginally, and 10 patients underwent a cesarean section during the study period. Four of the cesarean deliveries were indicated due to COVID‐19 hypoxemia‐related fetal distress. Four patients were admitted to the intensive care unit (ICU) after the cesarean section. Conclusion: Early hospitalization and medical treatment can alleviate symptoms, improve the clinical course and reduce the need for ICU in symptomatic pregnant patients with suspected or confirmed COVID‐19. Chest CT scans are a suitable option for suspected but unconfirmed COVID‐19 infection. [ABSTRACT FROM AUTHOR]

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Background: The recent outbreak by a novel coronavirus originated from Wuhan, China in 2019, and is progressively spreading to other countries. Timely diagnosis of the coronavirus disease 2019 (COVID-19) improves the survival of the patients and also prevents the transmission of the infection. In this study, we reviewed the applicable and available methods for the diagnosis of COVID-19. Methods: For the review, we systematically searched Web of Science, PubMed, and Iranian articles that were published about COVID-19 diagnostic methods with a combination of the key terms: laboratory, radiological, tests, coronavirus. Results: Although the current gold standard diagnostic test for this virus is real-time reverse-transcriptase polymerase chain reaction (RT-PCR), the occasional false-negative and the low sensitivity of the test should not be underestimated. A chest computed tomography (CT) scan is another diagnostic test for COVID-19, with higher sensitivity but low specificity. A combination of sensitive RT-PCR with a chest CT scan together with the clinical features are highly recommended for the proper diagnosis. Notably, there are some other sensitive and low-cost tests for evaluation of COVID-19 infection, but their validation should be approved. Conclusion: Since early and accurate diagnosis of the viral disease could improve the survival rate of the patients, and halt the transmission chain, it is not surprising that tremendous attempts should be made to reduce the limitations of the tests leading to the false-negative results and to find a rapid test for the diagnosis of COVID-19. [ABSTRACT FROM AUTHOR]

• Polymer composites effectively reduce the absorbed doses due to computed tomography. • Absorbed doses of fetus of a 24th weeks pregnant phantom was studied in chest imaging. • Poly hydroxyethyl methacrylate tungsten oxide reduces brain dose notably at 80 kVp. Given their desirable shielding properties, 5 polymer composite shields reinforced with tungsten were selected and their effects as gamma shields on fetal dose reduction were investigated. According to the results, the selected shields reduce the fetus brain, the fetus lungs, the fetus kidneys, and the total fetus dose almost 34.17%-41.19%, 20.47%-25.08%, 9.27%-12.13%, and 15.39%-18.69%, respectively, at tube voltage of 80 kVp. At the higher tube potentials, the values of dose reduction were smaller. Moreover, it was observed that polymers named PHEMA-WO 3 and RS-U-30 had an excellent shielding ability among the other studied composites. [ABSTRACT FROM AUTHOR]

Abstract: Introduction: Lipoid pneumonia is a clinical condition that may be initially asymptomatic or confused with an infectious or malignant lung disease. Objectives: We report four cases of this pathological condition. Methods: The first case concerned an 85‐year old woman with bilateral confluent pulmonary opacities, ground‐glass type. Diagnosis was based on the cytology of the bronchoalveolar lavage (BAL) fluid followed by its ultrastructural examination. The second case was a 47‐year‐old man with an isolated pulmonary nodule, which was surgically removed; the diagnosis of lipoid pneumonia was formulated on the basis of the histological and electron microscopy examination. The third case concerned a 73‐year‐old woman, with bilateral hypodense areas at the bases of the lungs where FDG PET/CT scan showed an increased uptake. Diagnosis was formulated by BAL cytology and electron microscopy examination. The fourth case was a 69‐year‐old man, who performed a virtual colonoscopy for diverticulosis putting in evidence a round mass (3 cm in diameter) with two small peripheral nodules, located in the pulmonary left lower lobe. The histopathological examination of transthoracic biopsy confirmed a lipoid pneumonia. Results and conclusion: In all four cases, it was put in evidence a prolonged use of a nasal decongestant containing mineral oils. In literature, the most cases described are characterized by a subclinical evolution and were presented as ground glass opacities which evolve, in the later phases, in an interstitial involvement or in a peripheral mass, simulating a lung tumour. [ABSTRACT FROM AUTHOR]

This study intended to assess the dose length product (DLP), effective cumulative radiation dose (E.D.), and additional cancer risk (ACR) due to a chest CT scan to detect or follow up the Covid-19 disease in four university-affiliated hospitals that used different imaging protocols. Indeed, this study aimed to examine the differences in decision-making between different imaging centers in choosing chest CT imaging protocols during the pandemic, and to assess whether a new diagnostic reference level (DRL) is needed in pandemic situations. This retrospective study assessed the E.D. of all chest imagings for Covid-19 for six months in four different hospitals in our country. Imaging parameters and DLP (mGy.cm) were recorded. The E.D.s and ACRs from chest CT scans were calculated using an online calculator. Thousand-six hundred patients were included in the study. The mean cumulative dose due to chest CT was 3.97 mSv which might cause 2.59 × 10−2 ACR. The mean cumulative E.D. in different hospitals was in the range of 1.96–9.51 mSv. The variety of mean E.D.s shows that different hospitals used different imaging protocols. Since there is no defined DRL in the pandemic, some centers use routine protocols, and others try to reduce the dose but insufficiently. In pandemics such as Covid-19, when CT scan is used for screening or follow-up, DLPs can be significantly lower than in normal situations. Therefore, international regularized organizations such as the international atomic energy agency (IAEA) or the international commission on radiological protection (IRCP) should provide new DRL ranges. • During Covid-19, CT scan has a significant role in screening and follow-up. • The mean cumulative dose (ED) of chest CT for Covid-19 patients was 3.969 mSv. • 3.969 mSv (range 1.96–9.51 mSv) might cause 2.59 × 10−2 additional cancer risk. • The variety of mean EDs shows different policies in determining imaging protocols. • In pandemics, DLPs can be set significantly lower than in normal situations. [ABSTRACT FROM AUTHOR]

Fast chest CT scans with high-pitch factors are effective to reduce motion artifacts, but the over-ranging effect may increase harmful radiation exposure to organs which are located near the outside of the imaging area. This becomes a particular problem during chest CT imaging when managing the radiation dose to the radio-sensitive thyroid, which is located around the upper end of the imaging area. The use of an X-ray shielding material can reduce the exposure dose to the thyroid. However, when the shielding is performed using metal foil, metal artifacts definitely appear, and they interfere with the CT image. To solve this problem, we developed a novel less-artifact thyroid shield in which fine bismuth oxide particles are embedded in low-density polyurethane (PU) foam. This study aims to present the usefulness of our X-ray shield through experimentation using a human body phantom. Three kinds of thyroid shields were used: a commercially-available lead foil as a reference, investigational clay products to evaluate the proper amount of the fine bismuth oxide particles, and bismuth PU shields which are proposed in this study. Furthermore, a bismuth PU shield with an added PU spacer was fabricated for the further suppression of the artifacts. Under clinical conditions, shielding ability and image quality were evaluated. Thyroid doses were measured using small-type OSL dosimeters, and the dose reduction rates were determined. In addition, the image qualities of the thyroid and lung regions were evaluated using a contrast-to-noise ratio (CNR) and an artifact index (AI). When the thyroid is outside the scanning region, thyroid exposure without the shield was caused by over-ranging X-rays and showed 11 mGy. When applying bismuth with an effective mass thickness of 0.12 g/cm2 to the bismuth PU shield, the thyroid exposure dose was reduced by half. In addition, we confirmed that if this shield enters the scanning region through accident, the AI would be less than 10. Also, when using our thyroid shield, the occurrence of metal artifacts was drastically suppressed. In conclusion, our thyroid shield can reduce the radiation exposure dose in half while maintaining acceptable image quality. This is a valuable tool in solving the issue of radiation exposure when performing fast chest CT scans. The shield has breathability and flexibility, and patients can apply the shield to their necks by themselves. • Caused by an over-ranging effect, the thyroid is exposed during fast chest CT. • To reduce exposure dose to the thyroid, the use of an X-ray shield is effective. • We fabricated a low-density thyroid shield using bismuth oxide particles. • Thyroid dose and image quality were evaluated using a human body phantom. • Our shield can achieve good dose reduction and acceptable image quality. [ABSTRACT FROM AUTHOR]

Objective: To identify characteristics in patients who undergo positive and negative bronchoscopy for a suspected airway foreign body (AFB). Methods: Review medical records between 2008 and 2012. Results: There were 145 patients who went to the operating room with the pre-bronchoscopy diagnosis of suspected AFB during the study period. There was an overall negative bronchoscopy rate of an average of 37%, with an annual range between 21% and 50%. The findings of history or suspicion of choking, asymmetric breath sounds, and wheezing were statistically more common in patients with an AFB. Chest roentograms (CXR) had a sensitivity and specificity of 62% and 57%. Twenty patients had a chest computed tomography (CT) scan, and 100% were clinically significant. Four CT scans were diagnostic of an AFB, and 16 patients avoided bronchoscopy after negative CT. Conclusions: In current clinical practice, it is difficult to identify patients with an AFB without performing bronchoscopy. This results in a significant number of negative bronchoscopes. Certain elements in the history and physical exam were more common in patients who were found to have an AFB. Our preliminary data suggest that chest CT scans may be useful to decrease the number of negative bronchoscopies. [ABSTRACT FROM AUTHOR]

To determine the place of bronchoscopy and upper GI endoscopy in the initial staging of head and neck squamous cell carcinoma (HNSCC). A 10-year retrospective study was conducted on a series of 838 patients. As part of initial staging of the tumor, all patients were examined by neck and chest CT scan, 487 patients were examined by bronchoscopy and 588 patients were examined by upper GI endoscopy. Esophageal cancer was detected in 4.25 % of cases and lung cancer in 6.35 % of cases. Chest CT scan was statistically superior to bronchoscopy to detect second lung cancers ( p < 0.05). On multivariate analysis, oral cancers ( p = 0.009) and multiple (synchronous) HNSCC ( p = 0.009) were associated with the presence of a second lung cancer. Systematic bronchoscopy (performed by a pulmonologist) might not to be indicated for initial staging of HNSCC, particularly in the presence of normal chest CT scan. In case of abnormal Chest CT scan, patients should be referred to a pulmonologist. However, as oral cancers and multiple (synchronous) HNSCCs were statistically associated with the presence of a second lung cancer in this study, bronchoscopy might be indicated in these cases in order to detect rare small proximal bronchic lesions which might be invisible on chest CT scan in these patients at risk. More, systematic upper GI endoscopy (performed by a gastroenterologist) for initial staging of HNSCC might also not to be indicated in a majority of cases. [ABSTRACT FROM AUTHOR]

The article presents a study related to the ultrasound diagnosis of pneumothorax via retrospective computed tomography mapping of intrapleural air. Topics discussed under study include use of clinical utility in the diagnosis of lung pathologies, measurement of volumes of each pneumothorax by a radiologist and use of logistic regression to determine the relationship between volume and location of intrapleural air at specified areas of the hemithorax. The study revealed positive results.

Background: Gas trapping quantified on chest CT scans has been proposed as a surrogate for small airway disease in COPD. We sought to determine if measurements using paired inspiratory and expiratory CT scans may be better able to separate gas trapping due to emphysema from gas trapping due to small airway disease. Methods: Smokers with and without COPD from the COPDGene Study underwent inspiratory and expiratory chest CT scans. Emphysema was quantified by the percent of lung with attenuation < -950HU on inspiratory CT. Four gas trapping measures were defined: (1) Exp-856, the percent of lung < -856HU on expiratory imaging; (2) E/I MLA, the ratio of expiratory to inspiratory mean lung attenuation; (3) RVC856-950, the difference between expiratory and inspiratory lung volumes with attenuation between -856 and -950 HU; and (4) Residuals from the regression of Exp-856 on percent emphysema. Results: In 8517 subjects with complete data, Exp-856 was highly correlated with emphysema. The measures based on paired inspiratory and expiratory CT scans were less strongly correlated with emphysema. Exp-856, E/I MLA and RVC856-950 were predictive of spirometry, exercise capacity and quality of life in all subjects and in subjects without emphysema. In subjects with severe emphysema, E/I MLA and RVC856-950 showed the highest correlations with clinical variables. Conclusions: Quantitative measures based on paired inspiratory and expiratory chest CT scans can be used as markers of small airway disease in smokers with and without COPD, but this will require that future studies acquire both inspiratory and expiratory CT scans. [ABSTRACT FROM AUTHOR]