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We aimed to evaluate the performance of convolutional neural networks (CNNs) in the classification of coronavirus disease 2019 (COVID‐19) disease using normal, pneumonia, and COVID‐19 chest radiographs (CXRs). First, we collected 9194 CXRs from open datasets and 58 from the Korea University Anam Hospital (KUAH). The number of normal, pneumonia, and COVID‐19 CXRs were 4580, 3884, and 730, respectively. The CXRs obtained from the open dataset were randomly assigned to the training, tuning, and test sets in a 70:10:20 ratio. For external validation, the KUAH (20 normal, 20 pneumonia, and 18 COVID‐19) dataset, verified by radiologists using computed tomography, was used. Subsequently, transfer learning was conducted using DenseNet169, InceptionResNetV2, and Xception to identify COVID‐19 using open datasets (internal) and the KUAH dataset (external) with histogram matching. Gradient‐weighted class activation mapping was used for the visualization of abnormal patterns in CXRs. The average AUC and accuracy of the multiscale and mixed‐COVID‐19Net using three CNNs over five folds were (0.99 ± 0.01 and 92.94% ± 0.45%), (0.99 ± 0.01 and 93.12% ± 0.23%), and (0.99 ± 0.01 and 93.57% ± 0.29%), respectively, using the open datasets (internal). Furthermore, these values were (0.75 and 74.14%), (0.72 and 68.97%), and (0.77 and 68.97%), respectively, for the best model among the fivefold cross‐validation with the KUAH dataset (external) using domain adaptation. The various state‐of‐the‐art models trained on open datasets show satisfactory performance for clinical interpretation. Furthermore, the domain adaptation for external datasets was found to be important for detecting COVID‐19 as well as other diseases. [ABSTRACT FROM AUTHOR]

Surfactant treatment is a manner to reduce alveolar superficial tension and increase pulmonary compliance in premature neonates. Thus, we aimed to analyze the effect of exogenous surfactant treatment in combination with manual ventilation for preterm lambs. We used 15 ewes and their lambs (n = 16), prematurely born at 135 days. At birth, lambs were submitted to orotracheal intubation attached to a handheld resuscitation device and randomly allocated to: Control Group (n = 5; only manual ventilation), Single Surfactant Group (n = 5; manual ventilation coupled by intratracheal administration of 100 mg/kg surfactant) and Double Surfactant Group (n = 6; surfactant volume was divided into two doses (50 mg/kg + 50 mg/kg) administrated at birth and 30 min thereafter). A complete physical exam, arterial gas analysis, blood glucose, urea and creatinine concentration and chest radiographic assessment were performed at fixed times. All lambs had decreased body temperature until 20 min after birth. However, control and double surfactant groups reached a thermic plateau after 30 min. Regardless of the time-point, control lambs had higher heart rate in comparison to treated neonates, including bradycardia in Single Surfactant Group. Single instillation led to lower oxygenation degree, compared to the Double Surfactant Group, suggesting that surfactant treatment was not able to adequately spread within the alveoli. Lambs treated with surfactant had severe impairment of aerobic activity, leading to anaerobic metabolism. All groups had hypercapnia, which can be explained by inadequate respiratory pattern and pulmonary opacity (89% of the lambs had severe or moderate lung content). In conclusion, exogenous surfactant therapy in association with manual ventilation is ineffective in reverting pulmonary immaturity of the preterm lamb, leading to less vitality, hypoxemia, delayed pulmonary clearance and high mortality rate. • No data on the benefits of surfactant instillation to preterm lambs is available. • Intratracheal surfactant was done in a single volume or twice within 30 min. • Surfactant therapy led to less vitality, hypoxemia and delayed pulmonary clearance. • Surfactant therapy with manual ventilation does not prevent lamb mortality. [ABSTRACT FROM AUTHOR]

Objective: To describe the radiological features, diagnostic accuracy and features of imaging studies and their relation with clinical course of Coronavirus disease-2019 (COVID-19) pneumonia in pregnant women. Material and Methods: The clinical, laboratory and radiological features of symptomatic pregnant women suspected of COVID-19 were retrospectively reviewed. Chest radiography (CXR) and chest computed tomography (CT) findings of COVID-19 in pregnant women were identified. Results: Fifty-five of eighty-one pregnant women were included in the final analysis. The most common admission symptoms were dry cough (45.4%), fever (29.1%) and dyspnea (34.5%). Radiological imaging studies were performed in 34 (61.8%) patients. Fourteen (66.7%) of the laboratory-confirmed COVID-19 patients had parenchymal abnormalities on CXR, and most common abnormalities were airspace opacities (61.9%) and prominent bronchovascular shadows (28.6%). Seventeen (85.0%) of the patients had parenchymal abnormalities consistent with COVID-19 on their chest CT. Chest CT most commonly showed bilateral (88.2%), multilobe (100%) involvement; peripheral and central distribution (70.6%); patchy-shape (94.1%) and ground-glass opacity (94.1%). The sensitivity of CXR and chest CT was calculated as 66.7% and 83.3%, respectively. Preterm birth rate was 41.2% (n=7/17). Five (9.1%) of the 55 pregnant women admitted to the intensive care unit, three of those developed acute respiratory distress syndrome and one died. Conclusion: This study describes the main radiological features of symptomatic pregnant women infected with COVID-19. The refusal rate among pregnant women for the imaging modalities involving ionizing radiation was high but these had high sensitivity for COVID-19 diagnosis. The preterm birth and cesarean section rates were observed as remarkably increased. [ABSTRACT FROM AUTHOR]

Background:Mycoplasma pneumoniae (MP) not only was a common pathogen of respiratory tract infections, but also could trigger the exacerbation of asthmatic symptoms in children with or without asthma.Objective: This study aimed to identify possible risk factors associated with wheezing among children diagnosed with MP infection.Methods: A retrospective analysis of medical records of children aged 28 days to 18 years old who visited the Shanghai Children's Hospital between January 2019 and January 2020 was carried out, and all children were then classified into three groups: two wheezing groups (with or without MP infection) and a non-wheezing group with MP infection. Information including patient's demographics, clinical features, laboratory data, and radiography findings was extracted from the electronic medical record system. Chest radiographs were reviewed independently by two board-certified, blinded pediatric radiologists.Results: A total of 1,512 patients were included in our study, and 21.9% of them belonged to the wheezing group without MP infection. Among 1,181 patients with MP infection, 295 people (25.0%) suffered from wheezing, and males accounted for 61%. Through the multivariable logistic regression analyses, we found that six variables were positively associated with wheezing attacks in children with MP infection: male gender (likelihood ratio [LR] = 2.124, 95% confidence interval [CI]: 1.478–3.053), history of allergy (LR= 3.301, 95% CI: 2.206–4.941), history of wheezing (LR = 7.808, 95% CI: 5.276–11.557), autumn in reference to summer (LR = 2.414, 95% CI: 1.500–3.885), non-end-point infiltration in reference to consolidation or pleural effusion (LR = 1.982, 95% CI: 1.348–2.914), and infiltration scope (LR = 1.773, 95% CI: 1.293–2.432). However, the model showed that the probability of wheezing after MP infection decreased as age increased (LR = 0.257, 95% CI: 0.196–0.337). Moreover, the area under the curve (AUC) of the regression model was as high as 0.901 (0.847–0.955).Conclusion: The model integrated with factors including gender, age, season, radiological patterns, infiltration scope, and history of allergy performed well in predicting wheezing attack after MP infection in children.

Background: Serious bacterial infection rates in febrile infants < 60 days are about 8-11%. Less than 1% of febrile infants with no respiratory symptoms will have pneumonia however, chest radiography (CXR) rates remain between 30 and 60%. Rapid Respiratory Syncytial Virus (RSV) and influenza (flu) testing is common, however, there is not enough data to determine if febrile infants without any respiratory symptoms should be tested. The goal of this study is to determine the rate of positive CXR and RSV/flu results in febrile infants with no respiratory symptoms and no sick contacts.Methods: Well-appearing febrile infants between 7 and 60 days of age who presented to the pediatric emergency department (PED) from September 1st, 2015 through October 30th, 2017 were enrolled. Demographic data, respiratory symptoms, CXR findings and RSV/flu results were collected. SAS statistical software was used for analysis.Results: 129 infants met enrollment criteria. Of the 129 infants, 58 (45.0%) had no respiratory symptoms and no sick contacts. Of these 58, 36 (62.1%) received a CXR and none of them had any abnormal findings, 48 (82.8%) had RSV/flu testing, no patients tested positive for RSV and only one patient tested positive for flu. Costs of CXR and RSV/flu testing for this cohort was $19,788.Conclusion: The absence of positive CXRs in this patient population reinforces the current recommendations that CXR is not indicated. The low incidence of RSV/flu indicate that routine testing may not be necessary in this population especially outside of the flu season. Reduced testing could decrease overall costs to the healthcare system as well as radiation exposure to this population. [ABSTRACT FROM AUTHOR]

Objective Direct graphy is the most common imaging modality used in the evaluation of the cardiopulmonary system, especially in intensive care units. Since it is often necessary to make an urgent decision, it should be evaluated by the clinician without waiting for the report. In our study, we aimed to determine the level of knowledge about chest radiography evaluation in our current education system and to reveal the necessity of training programs for on this subject. Materıals and Methods In our study, 3 question-answer forms were prepared to be filled in for the evaluation of chest radiographs for 42 physicians, including anesthesia residents and non-anesthesiologists who came to educational rotation in the intensive care unit of our hospital. In the first form, general information and training on posteroanterior evaluation, in the second form, case-based PA graphy evaluation and technical evaluation, consisting of 12 cases and 7 fixed questions for each case, and in the third form, 10 question has been prepared for evaluate general PA and graphy information. Statistical analysis of the results was made. Statistical analysis of the results were performed. Results 95.2% of residents (n = 40) stated that they had received training in evaluating chest radiography. In our study, 80.1% (n = 34) of the residents received training on chest radiography before graduation. Two of the residents (4.8%) stated that they did not receive any training. When we look at the assistantship experience period and the correct assessment skill rates of chest radiography; It was observed that those with intensive care experience had better knowledge levels and were statistically significant (p <0.005). Conclusion In our study, it was revealed that most of the residents working in the intensive care unit received their chest radiography training before graduation from the medical school, and the need for training was found when both theoretical and technical competence levels were considered. We think that the completion of the deficiencies in theoretical and practical training on this subject will contribute significantly to clinical applications. [ABSTRACT FROM AUTHOR]

Rationale and Objectives: The clinical prognosis of outpatients with coronavirus disease 2019 (COVID-19) remains difficult to predict, with outcomes including asymptomatic, hospitalization, intubation, and death. Here we determined the prognostic value of an outpatient chest radiograph, together with an ensemble of deep learning algorithms predicting comorbidities and airspace disease to identify patients at a higher risk of hospitalization from COVID-19 infection.Materials and Methods: This retrospective study included outpatients with COVID-19 confirmed by reverse transcription-polymerase chain reaction testing who received an ambulatory chest radiography between March 17, 2020 and October 24, 2020. In this study, full admission was defined as hospitalization within 14 days of the COVID-19 test for > 2 days with supplemental oxygen. Univariate analysis and machine learning algorithms were used to evaluate the relationship between the deep learning model predictions and hospitalization for > 2 days.Results: The study included 413 patients, 222 men (54%), with a median age of 51 years (interquartile range, 39-62 years). Fifty-one patients (12.3%) required full admission. A boosted decision tree model produced the best prediction. Variables included patient age, frontal chest radiograph predictions of morbid obesity, congestive heart failure and cardiac arrhythmias, and radiographic opacity, with an internally validated area under the curve (AUC) of 0.837 (95% CI: 0.791-0.883) on a test cohort.Conclusion: Deep learning analysis of single frontal chest radiographs was used to generate combined comorbidity and pneumonia scores that predict the need for supplemental oxygen and hospitalization for > 2 days in patients with COVID-19 infection with an AUC of 0.837 (95% confidence interval: 0.791-0.883). Comorbidity scoring may prove useful in other clinical scenarios. [ABSTRACT FROM AUTHOR]

Our objective is to investigate the reliability and usefulness of anatomic point–based lung zone segmentation on chest radiographs (CXRs) as a reference standard framework and to evaluate the accuracy of automated point placement. Two hundred frontal CXRs were presented to two radiologists who identified five anatomic points: two at the lung apices, one at the top of the aortic arch, and two at the costophrenic angles. Of these 1000 anatomic points, 161 (16.1%) were obscured (mostly by pleural effusions). Observer variations were investigated. Eight anatomic zones then were automatically generated from the manually placed anatomic points, and a prototype algorithm was developed using the point-based lung zone segmentation to detect cardiomegaly and levels of diaphragm and pleural effusions. A trained U-Net neural network was used to automatically place these five points within 379 CXRs of an independent database. Intra- and inter-observer variation in mean distance between corresponding anatomic points was larger for obscured points (8.7 mm and 20 mm, respectively) than for visible points (4.3 mm and 7.6 mm, respectively). The computer algorithm using the point-based lung zone segmentation could diagnostically measure the cardiothoracic ratio and diaphragm position or pleural effusion. The mean distance between corresponding points placed by the radiologist and by the neural network was 6.2 mm. The network identified 95% of the radiologist-indicated points with only 3% of network-identified points being false-positives. In conclusion, a reliable anatomic point–based lung segmentation method for CXRs has been developed with expected utility for establishing reference standards for machine learning applications. [ABSTRACT FROM AUTHOR]

Artificial intelligence techniques are used on chest X-ray images for accurate detection of diseases and this paper aims to develop a process which is capable of diagnosing COVID-19 using deep learning methods on X-ray images. For this purpose, we used Mask R-CNN method to train and test on the dataset to classify between patients infected and non-infected with COVID-19. The dataset used here contains a large number of frontal views of X-ray images which are an essential resource for the algorithms used in the development of tools for the detection of COVID-19. Using 668 chest Xray images, the proposed model achieved an accuracy as high as 96.98%, specificity of 97.36% with the precision of 96.60%. The entire process is presented in detail. When a comparison table on the AIbased techniques is prepared, it is noticed that the Mask R-CNN technique on chest X-ray images provides better efficiency in the detection of COVID-19. The Mask R-CNN method is found to be accurate and robust in the detection of COVID-19 from chest X-ray images. [ABSTRACT FROM AUTHOR]

Background: Chest radiography (CXR) often is performed in the acute setting to help understand the extent of respiratory disease in patients with COVID-19, but a clearly defined role for negative chest radiograph results in assessing patients has not been described.Research Question: Is portable CXR an effective exclusionary test for future adverse clinical outcomes in patients suspected of having COVID-19?Study Design and Methods: Charts of consecutive patients suspected of having COVID-19 at five EDs in New York City between March 19, 2020, and April 23, 2020, were reviewed. Patients were categorized based on absence of findings on initial CXR. The primary outcomes were hospital admission, mechanical ventilation, ARDS, and mortality.Results: Three thousand two hundred forty-five adult patients, 474 (14.6%) with negative initial CXR results, were reviewed. Among all patients, negative initial CXR results were associated with a low probability of future adverse clinical outcomes, with negative likelihood ratios of 0.27 (95% CI, 0.23-0.31) for hospital admission, 0.24 (95% CI, 0.16-0.37) for mechanical ventilation, 0.19 (95% CI, 0.09-0.40) for ARDS, and 0.38 (95% CI, 0.29-0.51) for mortality. Among the subset of 955 patients younger than 65 years and with a duration of symptoms of at least 5 days, no patients with negative CXR results died, and the negative likelihood ratios were 0.17 (95% CI, 0.12-0.25) for hospital admission, 0.09 (95% CI, 0.02-0.36) for mechanical ventilation, and 0.09 (95% CI, 0.01-0.64) for ARDS.Interpretation: Initial CXR in adult patients suspected of having COVID-19 is a strong exclusionary test for hospital admission, mechanical ventilation, ARDS, and mortality. The value of CXR as an exclusionary test for adverse clinical outcomes is highest among young adults, patients with few comorbidities, and those with a prolonged duration of symptoms. [ABSTRACT FROM AUTHOR]

There is a paucity of studies on the correlation between chest radiograph and ultrasound (US) in children. Our objective was to study the correlation between bedside chest radiograph and ultrasound findings in 413 children with 1002 episodes of chest radiograph and US enrolled for a prospective, double-blinded observational study in a multidisciplinary paediatric intensive care unit. Weighted κ statistic for agreement was different for right and left lungs and varied from 50% for left pleural effusion to 98% for right pneumothorax. Pulmonary oedema, pneumothorax and pleural effusion were diagnosed by ultrasound alone in a significantly higher number of patients as compared to chest radiograph (P = 0.001). Chest ultrasound is therefore deemed more sensitive than chest radiograph in detection of pleural effusion, pulmonary oedema and pneumothorax. [ABSTRACT FROM AUTHOR]

Background: Chest radiography is universally accepted as the method of choice to confirm correct positioning of a nasogastric tube (NGT). Considering also that radiation exposure could increase with multiple insertions in a single patient, bedside abdominal ultrasound (BAU) may be a potentially useful alternative to chest radiography in the management of NGTs.Research Question: What is the accuracy of BAU in confirming the correct positioning of an NGT?Study Design and Methods: After a specific course consisting of 10 h of training, the authors studied, in a prospective multicenter cohort, the validity of BAU to confirm correct NGT placement. All patients were also evaluated by auscultation (whoosh test) and by chest radiography. Every involved operator was blind to each other. Interobserver agreement and accuracy analyses were calculated.Results: This study evaluated 606 consecutive inpatients with an indication for NGT insertion. Eighty patients were excluded for protocol violation or incomplete examinations and 526 were analyzed. BAU was positive, negative, and inconclusive in 415 (78.9%), 71 (13.5%), and 40 (7.6%), respectively. The agreement between BAU and chest radiography was excellent. Excluding inconclusive results, BAU had a sensitivity of 99.8% (99.3%-100%), a specificity of 91.0% (88.5%-93.6%), a positive predictive value of 98.3% (97.2%-99.5%), and a negative predictive value of 98.6% (97.6%-99.7%). The accuracy of BAU slightly changed according to the different assignments of the uncertain cases and was improved by the exclusion of patients with an altered level of consciousness.Interpretation: These results suggest that BAU has a good positive predictive value and may confirm the correct placement of NGTs when compared with chest radiography. However, considering its suboptimal specificity, caution is necessary before implementing this technique in clinical practice. [ABSTRACT FROM AUTHOR]

Background: A relative paucity of data exists regarding chest radiography (CXR) in diagnosis of coronavirus disease (COVID-19) compared to computed tomography. We address the use of a strict pattern of CXR findings for COVID-19 diagnosis, specifically during early onset of symptoms with respect to patient age. Methods: We performed a retrospective study of patients under investigation for COVID-19 who presented to the emergency department during theCOVID-19 outbreak of 2020 and had CXR within 1week of symptoms. Only reverse transcription polymerase chain reaction (RT-PCR)-positive patients were included. Two board-certified radiologists, blinded to RT-PCR results, assessed 60 CXRs in consensus and assigned 1 of 3 patterns: characteristic, atypical, or negative. Atypical patterns were subdivided into more suspicious or less suspicious for COVID-19. Results: Sixty patients were included: 30 patients aged 52 to 88 years and 30 patients aged 19 to 48 years. Ninety-three percent of the older group demonstrated an abnormal CXR andwere more likely to have characteristic and atypical-more suspicious findings in the firstweek after symptom onset than the younger group. The relationship between age and CXR findings was statistically significant (χ² [2, n=60]=15.70; P=0.00039). The relationship between negative and characteristic COVID-19 CXR findings between the 2 age cohorts was statistically significant with Fisher exact test resulting in a P value of 0.001. Conclusion: COVID-19 positive patients>50 years showearlier, characteristic patterns of statistically significant CXR changes than younger patients, suggesting that CXR is useful in the early diagnosis of infection. CXR can be useful in early diagnosis of COVID-19 in patients older than 50 years. [ABSTRACT FROM AUTHOR]

Much has been learned since the findings of Covid-19's imaging were published in early 2020. Many classification systems have been developed based on characteristic imaging findings to report imaging studies. As a result of increased performance in imaging and improved access to RT-PCR (Reverse Transcriptase-Polymerase Chain Reaction) testing, imaging is only indicated for patients with more severe disease or worsening breathing. Although the infection occurs in a spectrum ranging from asymptomatic to severe and sometimes fatal disease, acute lung injury is the most common. Imaging initially emerged with CT (Computed Tomography) as an alternative and subsequently played a more limited role based on specific indications, possibly as a superior test compared to RT-PCR. Various classification and reporting schemes have been developed for triage in cases where RT-PCR availability is limited and its performance is uncertain. Interobserver agreement for features with typical findings unique to Covid-19 and features that suggest an alternative diagnosis is high in a large number of studies. Some studies evaluating the degree of lung involvement on chest X-ray and CT have correlated with critical illness and the need for mechanical ventilation. In addition to pulmonary manifestations, cardiovascular complications such as thromboembolism and myocarditis have sometimes been attributed to Covid-19, which contributes to neurological and abdominal manifestations. Finally, artificial intelligence shows promise in both the diagnosis and prognosis of Covid-19 pneumonia in terms of both radiography and CT. [ABSTRACT FROM AUTHOR]

Adenovirus pneumonia is a common cause of community-acquired pneumonia in children and can mimic bacterial pneumonia, but there are few publications on its radiographic features. This study has evaluated the chest radiography findings of community-acquired adenovirus pneumonia in children. The frequency of radiological findings mimicking bacterial pneumonia was investigated. The clinical features of patients with adenovirus pneumonia possessing radiological findings mimicking bacterial pneumonia were also evaluated. The chest radiographs of patients diagnosed with adenovirus pneumonia were retrospectively reviewed. The chest radiographs were interpreted independently by a pediatric infectious disease specialist and a pediatric radiologist. Chest radiography findings mimicking bacterial pneumonia (bacterial-like) were specified as consolidation +/− pleural effusion. Other findings on chest radiography or a completely normal chest X-ray were specified as findings that were compatible with "typical viral pneumonia". A total of 1407 patients were positive for adenovirus with respiratory multiplex PCR. The 219 patients who met the study criteria were included in the study. Chest radiographs were normal in 58 (26.5 %) patients. The chest radiograph findings mimicked bacterial pneumonia in 41 (18.7 %) patients. Adenovirus pneumonia occurs predominantly in children aged five years and younger, as with other viral pneumonias. The radiographic findings in adenovirus pneumonia are predominantly those seen in viral pneumonia. Increasing age and positivity for only adenovirus without other viruses on respiratory multiplex PCR were associated with the chest radiograph being more likely to be "bacterial-like". Adenovirus may lead to lobar/segmental consolidation at a rate that is not very rare. • Although it is known that adenovirus pneumonia can radiologically mimic bacterial pneumonia, it is not known how often it does so. • About a quarter of the patients with adenovirus pneumonia had normal chest radiography and a fifth had findings similar to bacterial pneumonia. • The radiographic findings in adenovirus pneumonia are predominantly those seen in viral pneumonia, however, it may lead to lobar consolidation. [ABSTRACT FROM AUTHOR]

Background Chest radiography (CXR) is the main tool used to detect pulmonary nodules. Lateral views of CXR are less effective and the aim of our study was to develop a rotation angle recommendation model to obtain the best oblique CXR with significantly increased contrast between lesions and surrounding normal structures in order to enhance the detection rate for potential obscured lesions on traditional posterior and anterior (PA) CXR. Methods A total of 140 subjects receiving low‐dose lung computed tomography (CT) screening were enrolled from the health check‐up database. An additional 14 cases with lung lesions on chest CT were included. Demography was also reviewed. Gross, left and right cardiothoracic ratios (CTR) were measured. All CT images were transformed to CXR to detect the best rotation angles and produce different views of CXR. Contrast ratio was calculated in the transformed CXR from CT with lesions. Comparison of contrast ratio among oblique, posterior‐anterior and lateral views was performed. Results CXR shows smaller gross CTR and left CTR but larger heart width and thoracic width in men than in women. Correlation evaluation displays gross CTR, heart width and left CTR are positively correlated with age only for the women group. The most important factor for the best rotation angle is right CTR for left rotation angle and left CTR for right rotation angle. The contrast ratio of the lesion to surrounding structures is significantly better on the oblique views in the designed angles than that on the traditional views. Conclusion CXR oblique views in the assigned angle from the 10‐degree rotation angle recommendation are able to enhance contrast ratio between the possible obscured lesions and surrounding structures on CXR.

Background: Firefighting is a high-risk occupation. The firefighters can be involved in acute and chronic diseases. The study was conducted to investigate the acute symptoms of pulmonary problems, chest radiography, and pulmonary function testing among the professional firefighters of Tehran Firefighting Stations in active firefighting of the Plasco trade center disaster. Methods: A call was announced by the national Fars news agency to examine the firefighters in the Plasco trade center disaster. Results: A total of 56 firefighters completed the study design. They were male, commonly at a young age, and less than their 3rd decade. Upper respiratory tract symptoms were at a higher frequency than a lower airway tract; 98% of the subjects complained of respiratory symptoms. Chest abnormality was 24% and normal acute short-term spirometry was 87%. Acute occupational bronchitis was a prominent respiratory disease. Conclusion: Acute toxic inhalation respiratory diseases, including acute bronchitis, asthma-like disease, and laryngitis were found in our study. Medical monitoring is necessary for the detection of adverse health effects in the exposure, post-exposure, and long lifetime.

Background: Tuberculosis (TB) remains a burden globally, including Indonesia. The primary objective of this study is to reveal the chest radiography characteristic of drug-sensitive TB (DS-TB) and multi-drug resistant TB (MDR-TB) in the Indonesian national tuberculosis prevalence survey 2013–2014. The secondary objective is to explore the correlation and incidence rate of chest radiography lesion of DS-TB and MDR-TB cases. Methods: This is a cross-sectional retrospective analytical studies with national and regional coverage. Samples were selected by stratified multi-stage clustering sampling technique in a population aged ≥15 years old. The diagnosis of TB was based on culture and GeneXpert tests. Results: There were 147 DS-TB and 11 MDR-TB patients that were analyzed in this study. The nodule is the only type of lesions that distinguish MDR-TB and DS-TB. In multivariate analysis of DS-TB, there were 3 significant chest radiography lesions, i.e infiltrate, cavity and consolidation with odd-ratio (OR) of 14, 13, and 3, respectively. In MDR-TB, the only significant lesion is a nodule, with OR of 19. Conclusion: Nodule is the only type of lesions that distinguish MDR-TB and DS-TB. Infiltrate, cavity and consolidation were the types of chest radiography lesions on DS-TB, meanwhile, a nodule was the only significant lesion for MDR-TB.

Background: Acute chest syndrome is a major cause of pulmonary disease and mortality in sickle cell disease patients. Its diagnosis can be delayed due to differing imaging patterns between children and adults. Objective: The purpose of this study was to describe the pulmonary and extrapulmonary imaging findings in sickle cell disease patients with acute chest syndrome and determine differences in findings between adult and pediatric patients. Patients and Methods: This retrospective study analyzed the data of all sickle cell disease patients who were admitted with a diagnosis of acute chest syndrome to King Fahd Hospital of the University, Al Khobar, Saudi Arabia, between January and June 2015 (n = 150). After grouping the patients into adults and pediatrics, the pulmonary and extrapulmonary characteristics were identified and the digital radiography, computed tomography and laboratory findings were compared. Results: A total of 116 patients with 163 acute chest syndrome episodes met the inclusion criteria, of which 69 (60%) were adults. In both adult and pediatric patients, the most frequent pulmonary finding was consolidation of the lung parenchyma. The right lung was most frequently involved: the lower lobe in adult patients and the middle lobe in pediatric patients. In addition, pleural effusion was observed in both age groups. Extrapulmonary radiological findings, such as avascular necrosis and cardiomegaly, were significantly more common in adult patients than in pediatric patients (P < 0.05). Compared with adults, pediatric patients had significantly lower hemoglobin levels (P = 0.001) and oxygen tension fraction in arterial blood (P = 0.007). Conclusions: Pediatric and adult sickle cell disease patients with acute chest syndrome typically exhibited similar pulmonary characteristics, whereas extrapulmonary findings were more prominent in adult patients. Furthermore, low levels of hemoglobin and oxygen tension fraction were dependent predictors of acute chest syndrome.

Abstract Study objective The 2019–20 coronavirus pandemic is caused by the severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), which causes coronavirus disease 2019 (COVID‐19). This study was undertaken to identify and compare findings of chest radiography and computed tomography among patients with SARS‐CoV‐2 infection. Methods This retrospective study was undertaken at a tertiary care center. Eligible subjects included consecutive patients age 18 and over with documented SARS‐CoV‐2 infection between March and July 2020. The primary outcome measures were results of chest radiography and computed tomography among patients with documented SARS‐CoV‐2 infection. Results Among 724 subjects, most were admitted to a medical floor (46.4%; N = 324) or admitted to an ICU (10.9%; N = 76). A substantial number of subjects were intubated during the emergency department visit or inpatient hospitalization (15.3%; N = 109). The majority of patients received a chest radiograph (80%; N = 579). The most common findings were normal, bilateral infiltrates, ground‐glass opacities, or unilateral infiltrate. Among 128 patients who had both chest radiography and computed tomography, there was considerable disagreement between the 2 studies (52.3%; N = 67; 95% confidence interval: 43.7% to 61.0%).). The presence of bilateral infiltrates (infiltrates or ground‐glass opacities) was associated with clinical factors including older age, ambulance arrivals, more urgent triage levels, higher heart rate, and lower oxygen saturation. Bilateral infiltrates were associated with poorer outcomes, including higher rate of intubation, greater number of inpatient days, and higher rate of death. Conclusions Common radiographic findings of SARS‐CoV‐2 infection include infiltrates or ground‐glass opacities. There was considerable disagreement between chest radiography and computed tomography. Computed tomography was more accurate in defining the extent of involved lung parenchyma. The presence of bilateral infiltrates was associated with morbidity and mortality.

COVID-19 is a highly contagious disease that can cause severe pneumonia. Patients with pneumonia undergo chest X-rays (XR) to assess infiltrates that identify the infection. However, the radiographic characteristics of COVID-19 are similar to the other acute respiratory syndromes, hindering the imaging diagnosis. In this work, we proposed identifying quantitative/radiomic biomarkers for COVID-19 to support XR assessment of acute respiratory diseases. This retrospective study used different cohorts of 227 patients diagnosed with pneumonia; 49 of them had COVID-19. Automatically segmented images were characterized by 558 quantitative features, including gray-level histogram and matrices of co-occurrence, run-length, size zone, dependence, and neighboring gray-tone difference. Higher-order features were also calculated after applying square and wavelet transforms. Mann–Whitney U test assessed the diagnostic performance of the features, and the log-rank test assessed the prognostic value to predict Kaplan–Meier curves of overall and deterioration-free survival. Statistical analysis identified 51 independently validated radiomic features associated with COVID-19. Most of them were wavelet-transformed features; the highest performance was the small dependence matrix feature of "low gray-level emphasis" (area under the curve of 0.87, sensitivity of 0.85, p < 0.001 ). Six features presented short-term prognostic value to predict overall and deterioration-free survival. The features of histogram "mean absolute deviation" and size zone matrix "non-uniformity" yielded the highest differences on Kaplan–Meier curves with a hazard ratio of 3.20 ( p < 0.05 ). The radiomic markers showed potential as quantitative measures correlated with the etiologic agent of acute infectious diseases and to stratify short-term risk of COVID-19 patients. [ABSTRACT FROM AUTHOR]

BACKGROUND: The study aims to determine whether shifting to professional emergency department (ED) teams leads to a higher rate of radiologic workup. METHODS: We retrospectively analyzed a total of 2,000 patients presenting to the ED of a tertiary teaching hospital in two time periods: group 1 (G1) comprised 1,000 consecutive patients enrolled from December 21, 2012 to January 5, 2013 (all patients were examined by an internal medicine specialist); group 2 (G2) comprised 1,000 consecutive patients enrolled from December 21, 2018 to January 3, 2019 (all patients were examined by an emergency physician). RESULTS: The chest X-ray (CXR) was performed in 40.6% of all patients. There was no difference in the frequency of CXR (38.9% in G1 vs. 42.3% in G2, P=0.152). More CXRs were performed in G2 patients older than 65 years, in female patients older than 65 years, in patients presenting during the evening and night shifts or off-hours, in patients with a history of malignancy, in patients with gastrointestinal bleeding, and in patients with bradycardia, but fewer in patients presenting with arrhythmia. No difference in the rates of pathological CXR was found (47.3% in G1 vs. 52.2% in G2, P=0.186). Compared with G2, higher sensitivity and specificity were obtained for the binary logistic regression model predicting pathological findings in G1. CONCLUSIONS: Shifting to professional ED teams does not increase radiologic workup. By implementing deliberate usage of ultrasound, some self-governing procedures, case-oriented investigations, and center-specific recommendations, unnecessary radiologic workup can be avoided. Professional ED teams could lead to a higher standard of emergency care. [ABSTRACT FROM AUTHOR]

• Subjective estimation of radiograph image quality is time consuming. • CNNs were trained to classify diagnostic image quality of chest radiographs. • AI can automate image quality control and offer instant feedback in chest radiography. To automate diagnostic chest radiograph imaging quality control (lung inclusion at all four edges, patient rotation, and correct inspiration) using convolutional neural network models. The data comprised of 2589 postero-anterior chest radiographs imaged in a standing position, which were divided into train, validation, and test sets. We increased the number of images for the inclusion by cropping appropriate images, and for the inclusion and the rotation by flipping the images horizontally. The image histograms were equalized, and the images were resized to a 512 × 512 resolution. We trained six convolutional neural networks models to detect the image quality features using manual image annotations as training targets. Additionally, we studied the inter-observer variability of the image annotation. The convolutional neural networks' areas under the receiver operating characteristic curve were >0.88 for the inclusions, and >0.70 and >0.79 for the rotation and the inspiration, respectively. The inter-observer agreement between two human annotators for the assessed image-quality features were: 92%, 90%, 82%, and 88% for the inclusion at patient's left, patient's right, cranial, and caudal edges, and 78% and 89% for the rotation and inspiration, respectively. Higher inter-observer agreement was related to a smaller variance in the network confidence. The developed models provide automated tools for the quality control in a radiological department. Additionally, the convolutional neural networks could be used to obtain immediate feedback of the chest radiograph image quality, which could serve as an educational instrument. [ABSTRACT FROM AUTHOR]

Here we present a case of a patient with breathlessness and cough admitted to the COVID ward. Chest radiography demonstrates findings consistent with lobar collapse, giving rise to the 'Luftsichel sign'. This sign has been described in the literature and highlights the importance of recognition and prompt further investigation. [ABSTRACT FROM AUTHOR]

[West J Emerg Med. 2013;14(6):643-644.]

Background: In December 2019, pneumonia cases of unknown cause were announced in Wuhan, China. The causative agent of pneumonia was identified as coronavirus 2 (SARS-CoV-2), and the disease was named coronavirus disease 2019 (COVID-19). Purpose: To evaluate the usefulness of computed thoracic tomography (CT) and postero anterior (PA) thoracic radiography in patients with COVID-19. Material and Methods: Between March and June 2020, the patients who arrived at our hospital with suspicion of COVID-19 were retrospectively analyzed. Thorax CT findings of the 281 patients (142 females and 139 males; age range 3–91 years) with positive PCR tests were evaluated. Lesions in the lung parenchyma were examined according to their number, localization, and distribution. PA chest radiograms were classified into two groups, positive and negative for the lung parenchymal lesions. Results: Of the total 281 patients with PCR-positive COVID-19, CT examinations were normal in 107 (38.1%), and positive CT findings for pneumonia were found in 174 patients (61.9%). Bilateral involvement was observed in 100 (57.5%) of the 174 patients with positive CT findings, and unilateral involvement was observed in 74 (42.5%) of them. According to the localization of the lesions, peripheral subpleural distribution occurred in 160 of the 174 patients (91.9). The most common lesion was the ground glass opacities (GGO). In 77 of 281 PCR-positive patients (27.4), pulmonary lesions were found on PA chest radiograms. Conclusion: The presence of bilateral posterior subpleural GGO, nodule, and consolidation in thoracic CT are significant in terms of COVID-19 pneumonia. [ABSTRACT FROM AUTHOR]

Introduction: To extra validate and evaluate the reproducibility of a commercial deep convolutional neural network (DCNN) algorithm for pulmonary nodules on chest radiographs (CRs) and to compare its performance with radiologists. Methods: This retrospective study enrolled 434 CRs (normal to abnormal ratio, 246:188) from 378 patients that visited a tertiary hospital. DCNN performance was compared with two radiology residents and two thoracic radiologists. Abnormality assessment (using the area under the receiver operating chjmirocteristics (AUROC)) and nodule detection (using jackknife alternative free‐response ROC (JAFROC)) were compared among three groups (DCNN only, radiologist without DCNN and radiologist with DCNN). A subset of 56 paired cases, having two CRs taken within a 7‐day period, were assessed for intraobserver reproducibility using the intraclass correlation coefficient. Independent chjmirocteristics of pulmonary nodules detected by DCNN were assessed by multiple logistic regression analysis. Results: The AUROC for abnormality detection for the three groups were 0.87, 0.93 and 0.96, respectively (P < 0.05), whereas the JAFROC analysis of nodule detection was 0.926, 0.929 and 0.964. Reproducibility for the three groups was 0.80, 0.67 and 0.80, which shows an increase in radiologists using DCNN (P < 0.05). Nodules detected by DCNN were more solid, round‐shaped and well marginated, not masked and laterally located (P < 0.05). Conclusions: Extra validation results of DCNN showed high ROC results and there was a significant improvement in the performance when radiologists used DCNN. Reproducibility by DCNN alone showed good agreement, and there was an improvement from moderate to good agreement for radiologists using DCNN. [ABSTRACT FROM AUTHOR]

Introduction: Acute heart failure (AHF) is one of the leading causes of hospital admissions and is characterized by systemic and pulmonary congestion, which often precedes the overt clinical signs and symptoms. Echocardiography in the management of chronic HF is well described; however, there are less evidence regarding echocardiography and lung ultrasound (LUS) in the acute setting. Areas covered: We have summarized current evidence regarding the use of echocardiography and LUS for assessing congestion in patients with AHF. We discuss the value and reliability of handheld/pocketsize ultrasound devices in AHF. Expert opinion: Echocardiography is an essential tool for the diagnostic work up in patients with AHF. No individual parameter reliably detects congestion, thus the physician must integrate several measurements from the right and left heart. Novel methods and advances in cardiac imaging and clinical chemistry make it possible to detect congestion at an early stage. LUS is particularly helpful in assessing congestion, and it has demonstrated diagnostic, therapeutic, and prognostic value in AHF. LUS is relatively easy to learn and allows for quick assessment of the presence of pulmonary congestion and pleural effusion. We recommend integration of LUS for routine management of patients with AHF. [ABSTRACT FROM AUTHOR]

Background: Screening for lung cancer has used chest radiography (CR), low dose computed tomography (LDCT) and sputum cytology (SC). Estimates of the lead time (LT), i.e., the time interval from detection of lung cancer by screening to the development of symptoms, have been derived from longitudinal studies of populations at risk, tumor doubling time (DT), the ratio between its prevalence at the first round of screening and its annual incidence during follow-up, and by probability modeling derived from the results of screening trials.Objective: To review and update the estimates of LT of lung cancer.Methods: A non-systematic search of the literature for estimates of LT and screening trials. Search of the reference sections of the retrieved papers for additional relevant studies. Calculation of LTs derived from these studies.Results: LT since detection by CR was 0.8-1.1 years if derived from longitudinal studies; 0.6-2.1 years if derived from prevalence / incidence ratios; 0.2 years if derived from the average tumor DT; and 0.2-1.0 if derived from probability modeling. LT since detection by LDCT was 1.1-3.5 if derived from prevalence / incidence ratios; 3.9 if derived from DT; and 0.9 if derived from probability modeling. LT since detection of squamous cell cancer by SC in persons with normal CR was 1.3-1.5 if derived from prevalence/incidence ratios; and 2.1 years if derived from the DT of squamous cell cancer.Conclusions: Most estimates of the LT yield values of 0.2-1.5 years for detection by CR; of 0.9-3.5 years for detection by LDCT; and about 2 years or less for detection of squamous cell cancer by SC in persons with normal CR. The heterogeneity of the screening trials and methods of derivation may account for the variability of LT estimates. [ABSTRACT FROM AUTHOR]

Background: The propagation of remote "telemedicine" has allowed intensivists (and other medical professions) to expand their ability to provide critical care medicine services to intensive care units (ICUs). The physical exam is a pertinent skill that all providers learn early in their medical careers. Key components of the physical exam can help a clinician narrow the differential diagnosis. Even with modern monitoring devices and high-powered imaging, it is hard to replicate the physical exam on a critical care patient from a tele-medicine center. Case presentation: An experienced intensivist working in a telemedicine (Tele-ICU) center reviewed the daily chest radiograph on a patient with a complex prolonged ICU course. The radiograph was immediately recognized as being concerning for an acute case of pneumomediastinum in a patient with recent tracheostomy manipulation. However, the intensivist was unable to corroborate his suspicions with a good physical exam as the differential diagnosis list was explored. Conclusions: Acute pneumomediastinum is a severe disease process arising from numerous etiologies that can be life threatening. This disease process can often times be diagnosed from plain chest radiography alone. However remote telemedicine patient care should never supersede a direct bedside physical exam. Every good clinician knows that the fundamental physical exam truly is fundamental. [ABSTRACT FROM AUTHOR]

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Background The thoracic ultrasound (TUS) is a monitoring tool that has gained worldwide popularity in various scenarios, offering the opportunity for dynamic, bedside evaluations. Recent studies indicate that the use of TUS enables the diagnosis of pathologies resulting from blunt chest trauma (BCT), yielding favorable outcomes. This study aimed to compare the utility of TUS versus chest radiography (CXR) in diagnosing pulmonary pathologies resulting from closed-chest traumas. Methodology A prospective cross-sectional study was conducted with a sample of 58 patients diagnosed with BCT who sought emergency care at the "Dr. Luis Razetti" University Hospital in Barcelona, Venezuela, from November 2023 to January 2024. Results Of the patients, 75.9% (n = 44) were male, with an average age of 37.8 years (standard deviation = 18.4 years). Injuries were reported in 8.6% (n = 5) of the patients, including 60% (n = 3) pneumothorax and 40% (n = 2) hemothorax. Ultrasound results coincided with CXR in 94.8% (n = 55) of the cases, with a Cohen's kappa coefficient of 0.9 (95% confidence interval (CI) = 0.642-1.0). TUS demonstrated higher sensitivity than CXR (100% vs. 60%) for detecting hemothorax and pneumothorax in patients with BCT, with an area under the receiver operating characteristic curve of 0.991 (95% CI = 0.968-1.013). Conclusions BCT predominantly occurred in young males, resulting primarily in pneumothorax and hemothorax lesions, detectable with higher sensitivity through TUS compared to CXR. The use of TUS should be considered an essential component of the initial assessment for individuals with BCT., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2024, Uzcategui-Gutierrez et al.)

Aim: Pleural effusion (PE) is a common chest radiography (CXR) finding in patients with advanced cardiac disease. The pathophysiology and clinical value of PE in this setting are incompletely defined. We aimed to assess the haemodynamic correlates and prognostic impact of PE in patients with severe aortic stenosis (AS)., Methods and Results: We studied 471 patients (mean age 74 ± 10 years) with severe AS (indexed aortic valve area 0.42 ± 0.12 cm 2 /m 2 , left ventricular ejection fraction 58 ± 12%) undergoing right heart catheterization and upright CXR prior to aortic valve replacement (AVR). Two radiologist independently evaluated all CXR for the presence of bilateral PE, unilateral, or no PE, blinded to any other data. There were 49 (10%) patients with bilateral PE, 32 (7%) patients with unilateral PE, and 390 (83%) patients with no PE. Patients with bilateral PE had the highest mean right atrial pressure, mean pulmonary artery wedge pressure (mPAWP), and pulmonary vascular resistance, and had the lowest stroke volume index while those with unilateral PE had intermediate values. In the multivariate analysis, mPAWP was an independent predictor of any PE and bilateral PE. After a median (interquartile range) post-AVR follow-up of 1361 (957-1878) days mortality was highest in patients with bilateral PE (2.7 times higher than in patients without PE), whereas patients with unilateral PE had similar mortality as those without PE., Conclusions: In severe AS patients, the presence of PE, particularly bilateral PE, is a marker of a poor haemodynamic constellation. Bilateral PE is associated with a substantially increased post-AVR mortality., (© 2024 The Authors. ESC Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology.)

We developed a new model for predicting bone mineral density on chest radiographs and externally validated it using images captured at facilities other than the development environment. The model performed well and showed potential for clinical use., Purpose: In this study, we performed external validation (EV) of a developed deep learning model for predicting bone mineral density (BMD) of femoral neck on chest radiographs to verify the usefulness of this model in clinical practice., Methods: This study included patients who visited any of the collaborating facilities from 2010 to 2020 and underwent chest radiography and dual-energy X-ray absorptiometry (DXA) at the femoral neck in the year before and after their visit. A total of 50,114 chest radiographs were obtained, and BMD was measured using DXA. We developed the model with 47,150 images from 17 facilities and performed EV with 2914 images from three other facilities (EV dataset). We trained the deep learning model via ensemble learning based on chest radiographs, age, and sex to predict BMD using regression. The outcomes were the correlation of the predicted BMD and measured BMD with diagnoses of osteoporosis and osteopenia using the T-score estimated from the predicted BMD., Results: The mean BMD was 0.64±0.14 g/cm 2 in the EV dataset. The BMD predicted by the model averaged 0.61±0.08 g/cm 2 , with a correlation coefficient of 0.68 (p<0.01) when compared with the BMD measured using DXA. The accuracy, sensitivity, and specificity of the model were 79.0%, 96.6%, and 34.1% for T-score < -1 and 79.7%, 77.1%, and 80.4% for T-score ≤ -2.5, respectively., Conclusion: Our model, which was externally validated using data obtained at facilities other than the development environment, predicted BMD of femoral neck on chest radiographs. The model performed well and showed potential for clinical use., (© 2024. International Osteoporosis Foundation and Bone Health and Osteoporosis Foundation.)

Introduction: Physical measurements of expiratory flow volume and speed can be obtained using spirometry. These measurements have been used for the diagnosis and risk assessment of chronic obstructive pulmonary disease and play a crucial role in delivering early care. However, spirometry is not performed frequently in routine clinical practice, thereby hindering the early detection of pulmonary function impairment. Chest radiographs (CXRs), though acquired frequently, are not used to measure pulmonary functional information. This study aimed to evaluate whether spirometry parameters can be estimated accurately from single frontal CXR without image findings using deep learning., Methods: Forced vital capacity (FVC), forced expiratory volume in 1 s (FEV 1 ), and FEV 1 /FVC as spirometry measurements as well as the corresponding chest radiographs of 11,837 participants were used in this study. The data were randomly allocated to the training, validation, and evaluation datasets at an 8:1:1 ratio. A deep learning network was pretrained using ImageNet. The input and output information were CXRs and spirometry test values, respectively. The training and evaluation of the deep learning network were performed separately for each parameter. The mean absolute error rate (MAPE) and Pearson's correlation coefficient ( r ) were used as the evaluation indices., Results: The MAPEs between the spirometry measurements and AI estimates for FVC, FEV 1 and FEV 1 /FVC were 7.59% ( r  = 0.910), 9.06% ( r  = 0.879) and 5.21% ( r  = 0.522), respectively. A strong positive correlation was observed between the measured and predicted indices of FVC and FEV 1 . The average accuracy of >90% was obtained in each estimation of spirometry indices. Bland-Altman analysis revealed good agreement between the estimated and measured values for FVC and FEV 1 ., Discussion: Frontal CXRs contain information related to pulmonary function, and AI estimation performed using frontal CXRs without image findings could accurately estimate spirometry values. The network proposed for estimating pulmonary function in this study could serve as a recommendation for performing spirometry or as an alternative method, suggesting its utility., Competing Interests: HF was employed by Konica Minolta, Inc. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Yoshida, Kai, Futamura, Oochi, Kondo, Sato and Kasai.)

Introduction: Differences in patient size often provide challenges for radiographers, particularly when choosing the optimum acquisition parameters to obtain radiographs with acceptable image quality (IQ) for diagnosis. This study aimed to assess the effect of body part thickness on IQ in terms of low-contrast detail (LCD) detection and radiation dose when undertaking adult chest radiography (CXR)., Methods: This investigation made use of a contrast detail (CD) phantom. Polymethyl methacrylate (PMMA) was utilised to approximate varied body part thicknesses (9, 11, 15 and 17 cm) simulating underweight, standard, overweight and obese patients, respectively. Different tube potentials were tested against a fixed 180 cm source to image distance (SID) and automatic exposure control (AEC). IQ was analysed using bespoke software thus providing an image quality figure inverse (IQF inv ) value which represents LCD detectability. Dose area product (DAP) was utilised to represent the radiation dose., Results: IQF inv values decreased statistically (P = 0.0001) with increasing phantom size across all tube potentials studied. The highest IQF inv values were obtained at 80 kVp for all phantom thicknesses (2.29, 2.02, 1.8 and 1.65, respectively). Radiation dose increased statistically (P = 0.0001) again with increasing phantom thicknesses., Conclusion: Our findings demonstrate that lower tube potentials provide the highest IQF inv scores for various body part thicknesses. This is not consistent with professional practice because radiographers frequently raise the tube potential with increased part thickness. Higher tube potentials did result in radiation dose reductions. Establishing a balance between dose and IQ, which must be acceptable for diagnosis, can prevent the patient from receiving unnecessary additional radiation dose., (© 2023 The Authors. Journal of Medical Radiation Sciences published by John Wiley & Sons Australia, Ltd on behalf of Australian Society of Medical Imaging and Radiation Therapy and New Zealand Institute of Medical Radiation Technology.)

Objectives: To document the pattern of chest radiographic findings in coronavirus disease 2019 (COVID-19) patients with moderate to severe disease. Design: Retrospective cross-sectional study. Setting: The study site was Komfo Anokye Teaching Hospital (KATH) located at Bantama in Kumasi, the capital town of the Ashanti Region. It is the second largest hospital in the country and the major referral site for Ashanti region and the northern part of the country. The hospital hosts a highly infectious isolation unit (HIIU) for COVID-19 patients with moderate to severe infections and receives referred cases from the region and within the hospital. Participants: The study involved 27 patients admitted to the HIIU at KATH with COVID-19 infection who underwent chest X-ray as part of their investigations. Results: The study enrolled 12 males and 15 females. The common comorbidities were hypertension and diabetes. Chest x-ray findings in most of the patients (81.5%) revealed ground-glass opacities while a few of them (18.5%) had lung consolidations without ground-glass opacities. For those with ground-glass opacities, eight (29.6%) had superimposed consolidation. All the participants had positive chest x-ray findings. Conclusion: The chest x-ray findings in the 27 COVID-19 positive patients with moderate to severe disease on admission at the KATH HIIU enrolled in this study showed significant pulmonary abnormalities. The predominant pulmonary abnormalities were bilateral peripheral ground-glass opacities with the lower lung zones being mostly affected. [ABSTRACT FROM AUTHOR]

Background: Foreign body (FB) in the pediatric airway is a prevailing and crucial emergency with presenting symptoms often overlapping with other common pediatric conditions. There are limited number of large cohort studies in an Asian population which demonstrate the diversity of symptoms, investigations which will aid in obtaining the diagnosis, and management. Using this large cohort, we aim to evaluate the type and location, clinical presentations and outcomes of medical management related to pediatric airway FB in an Asian society.Methods: This is a retrospective study of all airway FB treated in Kunming Children's Hospital, China from February 2016 to June 2019. Six hundred and thirty-two clinical and operative records of all airway FB were retrieved and reviewed from the hospital's central electronic medical records. A total of 617 patients were included in our study.Results: The age ranged from 4 months to 12 years (mean = 1.74 years). The duration of symptoms ranged from 1 h to 605 days, with the diagnosis established at an average 9.16 days. Almost all had multiple symptoms, most commonly cough (98.5%) followed by noisy breathing (98.2%). Majority of the FBs (95.5%) were organic and the rest inorganic. Of the organic FBs, peanut was the most common (31.6%), followed by walnut (13.3%) and sunflower seeds (9.2%). Comparatively, 80.8% of the organic FBs were retrieved incomplete while 85.7% of the inorganic FBs were completely intact. Multiple FBs were noted in 43.3% of the patients, with 2.4% of them in different locations.Conclusions: Airway FB can be easily missed with resultant delay in diagnosis. In an Asian population, walnut and sunflower/pumpkin seeds feature more prominently compared to Western populations. Sunflower seed FBs tend to present earlier and are found intact in the trachea. Rigid bronchoscopy is the most common technique used to remove such FBs and pulmonary-related complications post-operatively, though rare, are the most common adverse outcomes. Preventive strategies targeting the appropriate age group and this type of FB may be useful in an Asian population.

[West J Emerg Med. 2011;12(4):579–580.]

Early detection and diagnosis are critical factors to control the COVID-19 spreading. A number of deep learning-based methodologies have been recently proposed for COVID-19 screening in CT scans as a tool to automate and help with the diagnosis. These approaches, however, suffer from at least one of the following problems: (i) they treat each CT scan slice independently and (ii) the methods are trained and tested with sets of images from the same dataset. Treating the slices independently means that the same patient may appear in the training and test sets at the same time which may produce misleading results. It also raises the question of whether the scans from the same patient should be evaluated as a group or not. Moreover, using a single dataset raises concerns about the generalization of the methods. Different datasets tend to present images of varying quality which may come from different types of CT machines reflecting the conditions of the countries and cities from where they come from. In order to address these two problems, in this work, we propose an Efficient Deep Learning Technique for the screening of COVID-19 with a voting-based approach. In this approach, the images from a given patient are classified as group in a voting system. The approach is tested in the two biggest datasets of COVID-19 CT analysis with a patient-based split. A cross dataset study is also presented to assess the robustness of the models in a more realistic scenario in which data comes from different distributions. The cross-dataset analysis has shown that the generalization power of deep learning models is far from acceptable for the task since accuracy drops from 87.68% to 56.16% on the best evaluation scenario. These results highlighted that the methods that aim at COVID-19 detection in CT-images have to improve significantly to be considered as a clinical option and larger and more diverse datasets are needed to evaluate the methods in a realistic scenario.

Background and Objectives: Scant data regarding early post-COVID-19 effects are available, especially in younger people. Therefore, the objective of this study was to explore the early clinical impacts of post-COVID-19 pneumonia, comparing severe and non-severe patients. Materials and Methods: A cross-sectional study was conducted in adult patients admitted with COVID-19 pneumonia from April to May 2021. Demographic data, symptoms and signs, quality of life, Hospital Anxiety and Depression Scale (HADS), chest radiograph (CXR), pulmonary function tests (spirometry, impulse oscillometry), fractional exhaled nitric oxide (FeNO), and exercise capacity were assessed one month after hospital discharge. Twenty-five healthy control subjects that were age- and gender-matched were recruited for comparisons. Results: One hundred and five patients, with a mean age of 35.6 ± 15.8 years and 54 (51.4%) males, participated and were categorized into the non-severe pneumonia (N = 68) and severe pneumonia groups (N = 37). At a one-month follow-up visit (the time from the onset of the disease symptoms = 45.4 ± 5.9 days), the severe group had more cough, fatigue, and skin rash with higher dyspnea scale, more residual CXR lesions, and lower quality of life scores. Forced vital capacity (FVC) was lower in the severe group (88.3% of predicted value) and non-severe group (94.6% of predicted value) than in the healthy controls (p = 0.001). The six-minute walk distance was significantly lower in the non-severe group, at 79.2 m, and in the severe group, at 103.8 m, than in the healthy control subjects (p < 0.001). Conclusions: Adult patients with COVID-19, especially those with clinically severe pneumonia, still had residual symptoms and chest radiographic abnormalities, together with poorer quality of life and lower exercise capacity, one month after hospital discharge.

Background and Objectives: There is currently no method that can be used for a precise evaluation of pacemaker leads using X-ray images, which could be a valuable add-on in the follow-up of patients. The aim of this paper was to create a simple method to measure selected points and lines using the chest radiography of patients with cardiac pacemakers. Materials and Methods: The study included 99 patients after permanent pacemaker implantation (72.0 ± 12.9 y; 58 W). The newly created method was used to evaluate the course of the leads based on an X-ray of the chest in an AP (posterior–anterior) projection (standing up) with optimization. The chest X-ray was applied to the original measurement grid, which was determined by specific anatomical points. For the purpose of this paper, a number of measurable parameters have been proposed. Results: The technical quality of the images was very good (4.50 ± 0.72). There were no gender-specific differences: women 4.46 ± 0.75/men 4.56 ± 0.67; p = 0.5183. The quality of the imaging of the leads was also good (3.72 ± 0.83), and no statistical differences were found between the genders. After verifying the technical quality of the X-ray images, the tract of the leads was measured. The only significant difference was found in parameter E—this value describing the so-called “death bend”, which was significantly lower in women (3.98 ± 1.35) vs. men (4.58 ± 1.49): p = 0.039. Conclusions: The presented method permitted the leads of a cardiac pacemaker to be precisely described with good clinical validity using chest radiography.