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A 62-year-old woman came to our hospital with worsening cough and dyspnea over the preceding week, during which time she had been treated with azithromycin and prednisone for suspected pneumonia. She had no fever, chills, or sweats, but her cough had become productive of clear to blood-tinged phlegm during the interval. Medical history was significant for insulin-dependent diabetes mellitus and OSA. She had quit smoking 44 years earlier and had no history of lung disease. She was a bank teller residing in southeastern Minnesota and described no relevant inhalational or environmental exposures, drug use, aspiration, or travels preceding her illness. [ABSTRACT FROM AUTHOR]

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]

In treating acute hypoxemic respiratory failure (AHRF) caused by coronavirus disease 2019 (COVID-19), clinicians choose respiratory therapies such as low-flow nasal cannula oxygenation, high-flow nasal cannula oxygenation, or mechanical ventilation after assessment of the patient's condition. Chest computed tomography (CT) imaging contributes significantly to diagnosing COVID-19 pneumonia. However, the costs and potential harm to patients from radiation exposure need to be considered. This study was performed to predict the quantitative extent of COVID-19 acute lung injury using clinical indicators such as an oxygenation index and blood test results. We analyzed data from 192 patients with COVID-19 AHRF. Multiple logistic regression was used to determine correlations between the lung infiltration volume (LIV) and other pathophysiological or biochemical laboratory parameters. Among 13 clinical parameters, we identified the oxygen saturation/fraction of inspired oxygen ratio (SF ratio) and serum lactate dehydrogenase (LD) concentration as factors associated with the LIV. In the binary classification of an LIV of ≥20 % or not and with the borderline LD = 2.2 × [SF ratio]−182.4, the accuracy, precision, diagnostic odds ratio, and area under the summary receiver operating characteristic curve were 0.828, 0.818, 23.400, and 0.870, respectively. These data suggest that acute lung injury due to COVID-19 pneumonia can be estimated using the SF ratio and LD concentration without a CT scan. These findings may provide significant clinical benefit by allowing clinicians to predict acute lung injury levels using simple, minimally invasive assessment of oxygenation capacity and biochemical blood tests. [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]

BackgroundCoccidioidomycosis (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 methodsWe 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.ResultsUsing 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.ConclusionsCareful 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 Background Lophomonas blattarum is an emerging protozoan that mostly infects the lower respiratory tract and causes pulmonary lophomoniasis. Radiologic findings in patients with pulmonary lophomoniasis have yet to be studied. Thus, we conducted a registry-based clinical investigation to evaluate the radiologic findings of lophomoniasis. Methods In this cross-sectional study, 34 Lophomonas positive patients were enrolled. Demographic data, relevant characteristics, and radiologic findings of the patients were recorded and analyzed. Results Thirty-four (male = 18, female = 16) patients with an average age of 52.21 ± 20.48 years old were examined. Radiological findings such as Alveolar consolidation (26.5%), Ground glass opacity (5.9%), Centrilobular nodules (23.5%), Tree -in- bud (38.2%), Cavitation (23.5%), Pleural effusion (23.5%), Interstitial opacity (8.8%), Lymphadenopathy (23.5%), Bronchocele (5.9%), Bronchiectasis (29.4%), Nodules (8.8%) and Mass (11.8%) were obtained, that the frequency of all radiological findings was less than 50%. Conclusion In this study, the most common radiological findings in patients with lophomoniasis were tree-in-bud nodules, alveolar consolidation, bronchiectasis, and centrilobular nodules which were mostly seen in the right lung and its middle and lower lobes. Given that the radiologic findings of this disease are unknown, it can be considered in differential diagnosis.

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 Lophomonas blattarum is an emerging protozoan that mostly infects the lower respiratory tract and causes pulmonary lophomoniasis. Radiologic findings in patients with pulmonary lophomoniasis have yet to be studied. Thus, we conducted a registry-based clinical investigation to evaluate the radiologic findings of lophomoniasis. Methods In this cross-sectional study, 34 Lophomonas positive patients were enrolled. Demographic data, relevant characteristics, and radiologic findings of the patients were recorded and analyzed. Results Thirty-four (male=18, female=16) patients with an average age of 52.21±20.48 years old were examined. Radiological findings such as Alveolar consolidation (26.5%), Ground glass opacity (5.9%), Centrilobular nodules (23.5%), Tree -in- bud (38.2%), Cavitation (23.5%), Pleural effusion (23.5%), Interstitial opacity (8.8%), Lymphadenopathy (23.5%), Bronchocele (5.9%), Bronchiectasis (29.4%), Nodules (8.8%) and Mass (11.8%) were obtained, that the frequency of all radiological findings was less than 50%. Conclusion In this study, the most common radiological findings in patients with lophomoniasis were tree-in-bud nodules, alveolar consolidation, bronchiectasis, and centrilobular nodules which were mostly seen in the right lung and its middle and lower lobes. Given that the radiologic findings of this disease are unknown, it can be considered in differential diagnosis. [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]

We aimed to investigate the safety and efficacy of nirmatrelvir/ritonavir (Paxlovid) therapy for hemodialysis-dependent patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Thirteen hemodialysis patients infected with the Omicron variant of SARS-CoV-2 from April 3 to May 30, 2022, were recruited. Laboratory parameters and chest CT (computed tomography) imaging were analyzed. The treatment group included six patients who received 150 mg/100 mg of Paxlovid orally once daily for 5 days, whereas the control group included seven patients who received basic treatment. No serious adverse reactions or safety events were recorded. Four control patients progressed to moderate disease, and none in the treatment group showed progression of chest CT findings (P < 0.05). Paxlovid therapy tended toward early viral clearance and low viral load on Day 8. Moreover, 83.3% of the patients in the treatment group and 57.1% of the patients in the control group turned negative within 22 days. In the Paxlovid treatment group, we found significantly increased levels of lymphocytes (P=0.03) and eosinophils (P=0.02) and decreased levels of D-dimer on Day 8 compared with those on Day 1. Paxlovid therapy showed a potential therapeutic effect with good tolerance in hemodialysis patients. The optimal dose and effectiveness evaluation must be further investigated in a largeer cohort. [ABSTRACT FROM AUTHOR]

IntroductionThis 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 methodsIn 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.ResultsThe 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 conclusionThis 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.

Zhimei Zhao,1,&ast; Xiang Han,1,&ast; Yunhong You,1 Jiankang Zhang,2 Keke Nie,1 Youxin Ji1 1Department of Oncology, Affiliated Qingdao Central Hospital of Qingdao University, Qingdao Cancer Hospital, Qingdao City, People’s Republic of China; 2Department of Medicine, Qingdao Medical College, Qingdao University, Qingdao City, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Keke Nie; Youxin Ji, Department of Oncology, Affiliated Qingdao Central Hospital of Qingdao University, Qingdao Cancer Hospital, 127 Si Liu South Road, Shibei District, Qingdao City, 266042, People’s Republic of China, Tel + (86)532-6866-5078, Fax + (86)532-8486-3506, Email niekekeqd@163.com; mdji001@gmail.comBackground: We study the characteristics and outcomes in lung cancer patients with COVID-19 Omicron variant infection.Methods: Hospitalized lung cancer patients with advanced-stage disease and laboratory-confirmed COVID-19 Omicron infection were included. Pneumonitis involving at least 25% of lung parenchyma on CT scans, accompanied by symptoms and oxygen saturation below 93%, were criteria for enrollment. Pneumonitis severity was graded using CTCAE v5.0. Treatment included Paxlovid, prednisolone, anticoagulation, and ventilation. Initial data, radiographic findings, and outcomes were compared. Logistic regression was employed to determine risk factors for in-hospital mortality.Results: Fifteen patients (median age: 65 years; 80.0% males) were included. 73.3% improved and were discharged, 20.0% died, and 6.7% remained intubated. Initial symptoms included cough (100.0%), fever (73.3%), and shortness of breath (53.3%). Symptoms resolved in discharged patients. Median fever duration was 3.5 days, and respiratory symptom recovery took 26 days. Three patients died due to respiratory failure from Omicron pneumonia. Lower oxygen saturation, reduced lymphocyte/neutrophil ratio on day 7, and diffuse bilateral lung lesions were poor prognostic factors.Conclusion: This study underscores the importance of prompt intervention and early diagnosis for lung cancer patients infected with the COVID-19 Omicron variant. Lower oxygen saturation, decreased lymphocyte/neutrophil ratio on day 7, and diffuse lung lesions on CT scans were associated with worse outcomes. Clinicians should prioritize timely and comprehensive management to improve survival rates in this population.Keywords: COVID-19 omicronvariant, lung cancer, oxygen saturation, lymphocyte and neutrophils ratio, chest CT scan

Fathia Omer Salah,1 Abubeker Fedlu Abdela,1 Zeinab Mustafa Obeid,2 Leul Adane,1 Gashaw Arega2 1Department of Diagnostic Radiology, Addis Ababa University, Addis Ababa, Ethiopia; 2Department of Pediatric & Child Health, Addis Ababa University, Addis Ababa, EthiopiaCorrespondence: Fathia Omer Salah, Department of Diagnostic Radiology, Addis Ababa University, P.O.Box 62058, Addis Ababa, Ethiopia, Tel +251 921 912290, Email drfeti01@gmail.com; fathia.omer@aau.edu.etAbstract: In tuberculous patient, abnormal extrarenal production of 1.25-dihydroxyvitamin D3 by activated macrophages results in hypercalcemia. High calcium level associated with tuberculosis is frequent in adults with active pulmonary tuberculosis even though most patients are asymptomatic, while hypercalcemia in children due to disseminated tuberculosis is rare. Here, we described a case of a 5-year-old who presented with cough and right anterior chest swelling of two-month duration with an Erythrocyte Sedimentation Rate of 144mm/hour, and a high serum ionized calcium level of 1.46millimol/L. With the epidemiologically prevalence, clinical and radiological imaging findings the diagnosis of disseminated tuberculosis to lung, pleura, lymph node, liver and bone was made, and the child was started with the anti-tuberculosis treatment, hypercalcemia was attributed to the disseminated tuberculosis precipitated by high calcium meal intake and excessive sun exposure. Tuberculosis can be complicated with hypercalcemia; care must be taken in supplementing vitamin D and high calcium meals especially in high sun exposure geographic areas.Keywords: hypercalcemia, disseminated tuberculosis, ESR, chest CT scan

Purpose: To determine the reliability of an artificial intelligence, deep learning (AI/DL)-based method of chest computer tomography (CT) scan analysis to distinguish pulmonary sarcoidosis from negative lung cancer screening chest CT scans (Lung Imaging Reporting and Data System score 1, Lung-RADS score 1). Methods: Chest CT scans of pulmonary sarcoidosis were evaluated by a clinician experienced with sarcoidosis and a chest radiologist for clinical and radiologic evidence of sarcoidosis and exclusion of alternative or concomitant pulmonary diseases. The AI/DL based method used an ensemble network architecture combining Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs). The method was applied to 126 pulmonary sarcoidosis and 96 Lung-RADS score 1 CT scans. The analytic approach of training and validation of the AI/DL method used a fivefold cross-validation technique, where 4/5th of the available data set was used to train a diagnostic model and tested on the remaining 1/5th of the data set, and repeated 4 more times with non-overlapping validation/test data. The probability values were used to generate Receiver Operating Characteristic (ROC) curves to assess the model's discriminatory power. Results: The sensitivity, specificity, positive and negative predictive value of the AI/DL method for the 5 folds of the training/validation sets and the entire set of CT scans were all over 94% to distinguish pulmonary sarcoidosis from LUNG-RADS score 1 chest CT scans. The area under the curve for the corresponding ROC curves were all over 97%. Conclusion: This AL/DL model shows promise to distinguish sarcoidosis from alternative pulmonary conditions using minimal radiologic data. [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.

Objective: To investigate the applicability of DR Bedside chest radiography and chest computed tomography (CT) scanning for the imaging and clinical diagnosis of severe novel coronavirus pneumonia. Methods: Imaging and clinical data of 43 patients with novel coronavirus pneumonia who were admitted to Beijing Shijitan Hospital Affiliated to Capital Medical University from December 10, 2022 to January 10, 2023 were retrospectively analyzed. Joint diagnoses by multidisciplinary experts according to the clinical and laboratory diagnosis criteria confirmed that all the 43 enrolled patients were severely infected with novel coronavirus pneumonia. All 43 patients underwent digital DR Bedside chest radiography; of these, 6 patients underwent chest CT scanning as they had relatively mild symptoms. The time interval for chest X-ray reexamination was 1~5 days, with 1~4 reexaminations. The chest CT scan review interval was 1~4 days, with 2 reviews. The imaging findings of chest radiography and chest CT scanning were observed and analyzed. Results: Among 43 patients with severe novel coronavirus pneumonia, 25 cases showed the first digital DR Bedside chest radiographs showing plaques and solid shadows in both lungs, 6 cases of pleural effusion in both lungs, 18 cases of unilateral lung exudation and solid shadows, 4 cases of unilateral pleural effusion, 7 cases of cardiac enlargement combined with pulmonary edema, and 2 cases of suspected pulmonary tumor mass shadows. There were multiple ground glass shadows in both lungs in 6 patients who underwent chest CT scanning. Spot shadows, grid shadows, thickened interlobular septum, and thickened pulmonary vessels and subbronchus were identified in the lesion area. Double lung spot density increased in the chest radiographs; the shadow area expanded in 5 cases and pleural effusion increased in 2 cases. Reexamination of chest CT images showed that 4 cases of increased ground-glass shadow transformed into irregular patchy high CT value shadow, 1 case of new atelectasis and 1 case of new pleural effusion. Conclusion: Digital DR Bedside chest radiography and chest CT scanning are the primary imaging methods for the diagnosis of novel coronavirus pneumonia. In particular, the former plays an important auxiliary diagnostic role when chest CT scan cannot be performed in patients with severe disease, and can greatly assist in the later review and clinical evaluation of the disease during active treatment.

Introduction: The increased use of cross-sectional imaging frequently identifies a growing number of lung nodules that require follow-up imaging studies and physician consultations. We report here the frequency of finding a ground-glass nodule (GGN) or semisolid lung lesion (SSL) in the past decade within a large academic health system. Methods: A radiology system database review was performed on all outpatient adult chest computed tomography (CT) scans between 2013 and 2022. Radiology reports were searched for the terms “ground-glass nodule,” “subsolid,” and “semisolid” to identify reports with findings potentially concerning for an adenocarcinoma spectrum lesion. Results: A total of 175,715 chest CT scans were performed between 2013 and 2022, with a steadily increasing number every year from 10,817 in 2013 to 21,916 performed in the year 2022. Identification of GGN or SSL on any outpatient CT increased from 5.9% in 2013 to 9.2% in 2022, representing a total of 2019 GGN or SSL reported on CT scans in 2022. The percentage of CT scans with a GGN or SSL finding increased during the study period in men and women and across all age groups above 50 years old. Conclusions: The total number of CT scans performed and the percentage of chest CT scans with GGN or SSL has more than doubled between 2013 and 2022; currently, 9% of all chest CT scans report a GGN or SSL. Although not all GGN or SSL radiographic findings represent true adenocarcinoma spectrum lesions, they are a growing burden to patients and health systems, and better methods to risk stratify radiographic lesions are needed.

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]

The harm associated with imaging abnormalities related to lung cancer screening (LCS) is not well documented, especially outside the clinical trial and academic setting. What is the frequency of invasive procedures and complications associated with a community based LCS program, including procedures for false-positive and benign, but clinically important, incidental findings? We performed a single-center retrospective study of an LCS program at a nonuniversity teaching hospital from 2016 through 2019 to identify invasive procedures prompted by LCS results, including their indication and complications. Among 2,003 LCS participants, 58 patients (2.9%) received a diagnosis of lung cancer and 71 patients (3.5%) received a diagnosis of any malignancy. Invasive procedures were performed 160 times in 103 participants (5.1%), including 1.7% of those without malignancy. Eight invasive procedures (0.4% of participants), including four surgeries (12% of diagnostic lung resections), were performed for false-positive lung nodules. Only 1% of Lung Imaging Reporting and Data System category 4A nodules that proved benign were subject to an invasive procedure. Among those without malignancy, an invasive procedure was performed in eight participants for extrapulmonary false-positive findings (0.4%) and in 19 participants (0.9%) to evaluate incidental findings considered benign but clinically important. Procedures for the latter indication resulted in treatment, change in management, or diagnosis in 79% of individuals. Invasive procedures in those without malignancy resulted in three complications (0.15%). Seventy nonsurgical procedures (6% complication rate) and 48 thoracic surgeries (4% major complication rate) were performed in those with malignancy. The use of invasive procedures to resolve false-positive findings was uncommon in the clinical practice of a nonuniversity LCS program that adhered to a nodule management algorithm and used a multidisciplinary approach. Incidental findings considered benign but clinically important resulted in invasive procedure rates that were similar to those for false-positive findings and frequently had clinical value. [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]

Background & Objectives: Numerous studies have shown that the risk of death is higher in elderly patients with COVID-19. In Iran, due to the growth of the elderly population and the prevalence of underlying diseases, it is necessary to pay attention to this age group of patients. In this study, clinical, radiological, PCR, and laboratory data of elderly patients with COVID-19 were collected and analyzed in two groups of recovered and dead patients. Materials & Methods: This is a retrospective study of 196 consecutive elderly patients with COVID-19 hospitalized from March 21, 2020, to April 3, 2020, and their follow-up until April 23, 2021. Clinical characteristics, laboratory results, PCR, chest CT scans and Hounsfield Unit data were collected and analyzed in two groups of recovered and dead patients. Obtained Data were analyzed using SPSSv22.0 and MATLAB-R2017 software. Results: The results showed that there were no specific symptoms to distinguish the death group from the recovery group. Significant differences were observed between the two groups for red blood cell counts, hemoglobin, MCHC and MCV levels, bilirubin, aminotransferase levels, CRP, white blood cells, serum BNU, creatinine and PT coagulation index. The concentrations of VBG (HCO3) and VBG (PCO2) in the deceased patients suggest compensated respiratory alkalosis. CT sensitivity is 100% for patients in advanced and severe stages of the disease. Conclusion: The patients in the death group had more underlying diseases than the recovered group. COVID-19 patients are more likely to die when they have both diabetes and cardiovascular disease.

Mei-Lan Wang,1,&ast; Lu Hui Png,2,&ast; Jing Ma,1 Ken Lin,1 Mei-hua Sun,1 Yi-Jun Chen,3 Xian-Chao Tang,4 Xian-Yun Bi,1 Ying-Qin Gao,1 Tie-Song Zhang1 1Department of Otolaryngology, Head and Neck Surgery, Kunming Children’s Hospital, Kunming, People’s Republic of China; 2Department of Otorhinolaryngology – Head and Neck Surgery, Singapore General Hospital, Singapore, Singapore; 3Department of Otolaryngology, Head and Neck Surgery, Kunming Children’s Hospital, Kunming Medical University, Kunming, People’s Republic of China; 4Department of Radiology, Kunming Children’s Hospital, Kunming, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Lu Hui Png; Tie-Song Zhang, Email Luhpng@gmail.com; zhangtiesong@etyy.cnObjective: We 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.Keywords: airway foreign body, chest X-ray, chest CT scan, airway reconstruction, microlaryngobronchoscopy

Abstract 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.

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]

Introduction: hypersensitivity pneumonitis (extrinsic allergic alveolitis) is a complex syndrome with different intensity of clinical presentation and nature of origin. There is an acute, subacute and chronic form. Aim: we present a case of hypersensitivity pneumonitis in a 53-year-old woman admitted to the Clinic of Lung Diseases and Tuberculosis of the Clinical Center University of Sarajevo due to dyspnea and cough as well as chest CT scan verified diffuse ground glass opacities. Case report: dyspnea and cough persist after recovering from COVID-19 infection in the previous year. Diffuse areas of ground glass opacities and thickening of the interlobular septa were seen on the chest CT scan, which was unchanged compared to the CT scan performed during the COVID-19 infection. Atypical resection of the right 6th lung segment was pathohistologically proven to be subacute hypersensitivity pneumonitis. Prednisone treatment was started with a successive dose reduction, and the patient was also monitored radiologically. Results: the radiological regression of the previously described changes was confirmed six months after corticosteroid treatment onset. Conclusion: all changes in the lung parenchyma with slow radiological regression should be accurately diagnosed pathohistologically after lung biopsy. [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]

Early detection of lung cancer through management of pulmonary nodules (PNs) may reduce lung cancer mortality. We assessed the relationship between PNs and lung cancer. How common are PNs in the Medicare population? What is the rate of lung cancer after detection of PNs? What is the relative proportion of early-stage lung cancer diagnosed after reporting of PNs vs through low-dose CT (LDCT) scan screening? Using the Surveillance Epidemiology and End Results Program-Medicare database, we defined two cohorts: those in the 5% sample with ≥ 12 months of Medicare Parts A and B coverage from 2014 through 2019 (5% sample cohort) and those with a diagnosis of lung cancer from 2015 through 2017 with coverage for the prior 18-month period (lung cancer cohort). We defined PNs as chest CT scans with accompanying codes of 793.11 (International Classification of Diseases [ICD], Ninth Revision) or R91.1 (ICD, Tenth Revision) denoting a solitary PN. Patients in the lung cancer cohort were classified by whether they had undergone LDCT scan screening and whether they had a diagnosis of PN or neither (reference) within 18 months before diagnosis. We compared cancer stage and survival across groups. Of 627,547 patients in the 5% sample cohort, 5.0% demonstrated PNs over median of 5.0 years of follow-up. Cumulative 1- and 2-year lung cancer rates after initial PN diagnosis were 3.2% and 4.7%, respectively. Of 44,194 patients in the lung cancer cohort, 15.7%, 2.9%, and 81.4% were in the PN, LDCT scan, and reference groups, respectively. Of patients in the PN, LDCT scan, and reference groups, 58.1%, 50.3%, and 24.4% respectively, had disease of a localized stage. Among all patients with localized disease, 30.0% and 4.9% were in the PN and LDCT scan and groups, respectively. Three-year lung cancer-specific survival rates were 75.0%, 75.6%, and 49.4% for the PN, LDCT scan, and reference groups. Patients with lung cancer who received a diagnosis after identification of PNs tended to have localized disease. Of all patients with localized disease, almost one-third had PNs that were diagnosed previously, compared with 5% of patients who had undergone LDCT scan screening. PNs represent a relatively common presentation of potentially curable lung cancer. [ABSTRACT FROM AUTHOR]

The objective of our study was to determine organ doses to estimate the lifetime attributable risk (LAR) of cancer incidence related to chest tomography simulations for Radiotherapy Treatment Planning (RTTP) using patient-specific information. Patient data were used to calculate organ doses and effective dose. The effective dose (E) was calculated by two methods. First, to calculate effective dose in a standard phantom, the collected dosimetric parameters were used with the ImPACT CT Patient Dosimetry Calculator and E was calculated by applying related correction factors. Second, using the scanner-derived Dose Length Product, LARs were computed using the US National Academy of Sciences (BEIR VII) model for age- and sex-specific risks at each exposure. DLP, CTDIvol, and scan length were 507 ± 143 mGy.cm, 11 ± 4 mGy, and 47 ± 7 cm, respectively. The effective dose was 10 ± 3 mSv using ImPACT patient dosimetry calculator software and 9 ± 2 mSv using the scanner-derived Dose Length Product. The LAR of cancer incidence for all cancers, all solid cancers and leukemia were 65 ± 29, 62 ± 27, 7 ± 2 cases per 100,000 individuals, respectively. Radiation exposure from the usage of CT for radiotherapy treatment planning (RTTP) causes non-negligible increases in lifetime attributable risk. The results of this study can be used as a guide by physicians to implement strategies based on the As Low As Reasonably Achievable (ALARA) principle that lead to a reduction dose without sacrificing diagnostic information. [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.)

Asthma-COPD overlap (ACO) is a common clinical syndrome, yet there is no single objective definition. We hypothesized that immunoglobulin E (IgE) measurements could be used to refine the definition of ACO. In baseline plasma samples from 2870 participants in the COPD Genetic Epidemiology (COPDGene®) study, we measured total IgE levels and specific IgE levels to 6 common allergens. Compared to usual chronic obstructive pulmonary disease (COPD), participants with ACO (based on self-report of asthma) had higher total IgE levels (median 67.0 versus 42.2 IU/ml) and more frequently had at least one positive specific IgE (43.5% versus 24.5%). We previously used a strict definition of ACO in participants with COPD, based on self-report of a doctor's diagnosis of asthma before age 40. This strict ACO definition was refined by the presence of atopy, determined by total IgE > 100 IU/ml or at least one positive specific IgE, as was the broader definition of ACO based on self-reported asthma history. Participants with all 3 ACO definitions were younger (mean age 60.0-61.3 years), were more commonly African American (36.8%-44.2%), had a higher exacerbation frequency (1.0-1.2 in the past year), and had more airway wall thickening on quantitative analysis of chest computed tomography (CT) scans. Among participants with ACO, 37%-46% did not have atopy; these individuals had more emphysema on chest CT scan. Based on associations with exacerbations and CT airway disease, IgE did not clearly improve the clinical definition of ACO. However, IgE measurements could be used to subdivide individuals with atopic and non-atopic ACO, who might have different biologic mechanisms and potential treatments.

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]

Mohamed Farah Yusuf Mohamud, Mahad Sadik Mukhtar Mogadishu Somali-Turkish Training and Research Hospital, Mogadishu, SomaliaCorrespondence: Mohamed Farah Yusuf Mohamud, Mogadishu Somali-Turkish Training and Research Hospital, 30 Street, Alikamin, Wartanabada District, Mogadishu, Somalia, Tel +252615591689, Email m.qadar59@gmail.comBackground: 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.Keywords: septic pulmonary embolism, hemodialysis, chest CT scan, intensive care unit, emergency

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]

The novel Coronavirus, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) spread all over the world, causing a dramatic shift in circumstances that resulted in a massive pandemic, affecting the world's well-being and stability. It is an RNA virus that can infect both humans as well as animals. Diagnosis of the virus as soon as possible could contain and avoid a serious COVID-19 outbreak. Current pharmaceutical techniques and diagnostic methods tests such as Reverse Transcription-Polymerase Chain Reaction (RT-PCR) and Serology tests are time-consuming, expensive, and require a well-equipped laboratory for analysis, making them restrictive and inaccessible to everyone. Deep Learning has grown in popularity in recent years, and it now plays a crucial role in Image Classification, which also involves Medical Imaging. Using chest CT scans, this study explores the problem statement automation of differentiating COVID-19 contaminated individuals from healthy individuals. Convolutional Neural Networks (CNNs) can be trained to detect patterns in computed tomography scans (CT scans). Hence, different CNN models were used in the current study to identify variations in chest CT scans, with accuracies ranging from 91% to 98%. The Multiclass Classification method is used to build these architectures. This study also proposes a new approach for classifying CT images that use two binary classifications combined to work together, achieving 98.38% accuracy. All of these architectures' performances are compared using different classification metrics.