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Unilateral proximal interruption of pulmonary artery with ipsilateral occurrence of lung fibrosis is a very rare entity. This case report is about a 27 year old male who had complaints of progressive dysponea since 1 year. He had past history of recurrent lower respiratory tract infections. On auscultation, velcro crackles are heard on right side. Pulmonary function test showed restrictive pattern. Chest Radiography, High Resolution Computed Tomography and CT Pulmonary angiography were performed.

Coronavirus disease 2019 (COVID-19) is caused by a infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).1 It started in Wuhan, China, in December 2019, after which quickly spread to many other countries around the world. Chest radiography (CXR) and computed tomography (CT) play key roles in managment and diagnosis of COVID-19. In this case series we are presenting three patients with predominant left-sided changes caused by COVID-19 infection. [ABSTRACT FROM AUTHOR]

Rationale and Objectives To evaluate the performance of a computer-aided detection (CAD) system with bone suppression imaging when applied to unselected consecutive chest radiographs (CXRs) with computed tomography (CT) correlation. Materials and Methods This study included 586 consecutive patients with standard or portable CXRs who had a chest CT scan on the same day. Among the 586 CXRs, 438 had various abnormalities, including 46 CXRs with 66 lung nodules, and 148 CXRs had no significant abnormalities. A commercially available CAD system was applied to all 586 CXRs. True nodules and false positives (FPs) marked on CXRs by the CAD system were evaluated based on the corresponding chest CT findings. Results The CAD system marked 47 of 66 (71%) lung nodules in this consecutive series of CXRs. The mean FP rate per image was 1.3 across all 586 CXRs, with 1.5 FPs per image on the 438 abnormal CXRs and 0.8 FPs per image on the 148 normal CXRs. A total of 41% of the 752 FP marks were related to non-nodule pathologic findings. Conclusions A currently available CAD system marked 71% of radiologist-identified lung nodules in a large consecutive series of CXRs, and 41% of “false” marks were caused by pathologic findings. [ABSTRACT FROM AUTHOR]

Objective: To describe variations in emergency department (ED) quality measures and determine the association between ED costs and outcomes for 3 pediatric conditions: asthma, gastroenteritis, and simple febrile seizure. Study design: This cross-sectional analysis of ED visits used the Pediatric Health Information System database. Children aged ≤18 years who were evaluated in an ED between July 2009 and June 2011 and had a discharge diagnosis of asthma, gastroenteritis, or simple febrile seizure were included. Two quality of care metrics were evaluated for each target condition, and Spearman correlation was applied to evaluate the relationship between ED costs (reflecting overall resource utilization) and admission and revisit rates among institutions. Results: More than 250 000 ED visits at 21 member hospitals were analyzed. Among children with asthma, the median rate of chest radiography utilization was 35.1% (IQR, 31.3%-41.7%), and that of corticosteroid administration was 82.6% (IQR, 78.5%-86.5%). For children with gastroenteritis, the median rate of ondansetron administration was 52% (IQR, 43.2%-57.0%), and that of intravenous fluid administration was 18.1% (IQR, 15.3%-21.3%). Among children with febrile seizures, the median rate of computed tomography utilization was 3.1% (IQR, 2.7%-4.3%), and that of lumbar puncture was 4.0% (IQR, 2.3%-5.6%). Increased costs were not associated with lower admission rate or 3-day ED revisit rate for the 3 conditions. Conclusion: We observed variation in quality measures for patients presenting to pediatric EDs with common conditions. Higher costs were not associated with lower hospitalization or ED revisit rates. [Copyright &y& Elsevier]

Major challenges in current computer-aided detection (CADe) schemes for nodule detection in chest radiographs (CXRs) are to detect nodules that overlap with ribs and/or clavicles and to reduce the frequent false positives (FPs) caused by ribs. Detection of such nodules by a CADe scheme is very important, because radiologists are likely to miss such subtle nodules. Our purpose in this study was to develop a CADe scheme with improved sensitivity and specificity by use of “virtual dual-energy” (VDE) CXRs where ribs and clavicles are suppressed with massive-training artificial neural networks (MTANNs). To reduce rib-induced FPs and detect nodules overlapping with ribs, we incorporated the VDE technology in our CADe scheme. The VDE technology suppressed rib and clavicle opacities in CXRs while maintaining soft-tissue opacity by use of the MTANN technique that had been trained with real dual-energy imaging. Our scheme detected nodule candidates on VDE images by use of a morphologic filtering technique. Sixty morphologic and gray-level-based features were extracted from each candidate from both original and VDE CXRs. A nonlinear support vector classifier was employed for classification of the nodule candidates. A publicly available database containing 140 nodules in 140 CXRs and 93 normal CXRs was used for testing our CADe scheme. All nodules were confirmed by computed tomography examinations, and the average size of the nodules was 17.8 mm. Thirty percent (42/140) of the nodules were rated “extremely subtle” or “very subtle” by a radiologist. The original scheme without VDE technology achieved a sensitivity of 78.6% (110/140) with 5 (1165/233) FPs per image. By use of the VDE technology, more nodules overlapping with ribs or clavicles were detected and the sensitivity was improved substantially to 85.0% (119/140) at the same FP rate in a leave-one-out cross-validation test, whereas the FP rate was reduced to 2.5 (583/233) per image at the same sensitivity level as the original CADe scheme obtained (Difference between the specificities of the original and the VDE-based CADe schemes was statistically significant). In particular, the sensitivity of our VDE-based CADe scheme for subtle nodules (66.7% = 28/42) was statistically significantly higher than that of the original CADe scheme (57.1% = 24/42). Therefore, by use of VDE technology, the sensitivity and specificity of our CADe scheme for detection of nodules, especially subtle nodules, in CXRs were improved substantially. [ABSTRACT FROM PUBLISHER]

Background: Correlation between pathology and imaging of the new SARS-Cov-2 disease (COVID-19) is scarce. This study aimed to characterize SARS-Cov-2 pneumonia on imaging of patients submitted to minimally invasive autopsy (MIA)., Methods: This unicentric retrospective observational study included 46 consecutive patients with confirmed COVID-19 who underwent MIA. All clinical chest images were reviewed and classified for the presence and grade of viral pneumonia, as well as disease evolution. On CT, phenotypes were described as consistent with mild, moderate, or severe viral pneumonia, with or without radiological signs of organizing pneumonia (OP). In severe pneumonia, CT could also be classified as diffuse progressive OP or radiological diffuse alveolar damage (DAD). Specific features on CT were noted, including fibroproliferative signs that could indicate potential or initial fibrosis., Results: MIA showed a heterogeneous panel of alterations, with a high prevalence of OP and acute fibrinous and organizing pneumonia (AFOP). Also, signs of interstitial fibrosis corresponded to the most prevalent pathological feature. Initial chest radiography (CXR) findings were mainly consistent with moderate or severe viral pneumonia. Most patients showed stability or improvement (reduction of opacities) on imaging. CTs were performed on 15 patients. Consolidations were found in most patients, frequently showing features consistent with an OP phenotype. Fibroproliferative changes were also prevalent on CT., Conclusions: In this study, SARS-Cov-2 pneumonia showed heterogeneous radiological and pathological patterns. Signs of organization and potential or initial fibrosis were prevalent on both imaging and pathology. Imaging phenotyping may help to predict post-infection fibrosing interstitial pneumonitis in COVID-19., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://atm.amegroups.com/article/view/10.21037/atm-21-4354/coif). The authors have no conflicts of interest to declare., (2022 Annals of Translational Medicine. All rights reserved.)

There is a plethora of cardiovascular devices used for therapy and monitoring, and newer devices are being introduced constantly. As a result of advancement of medical technology and rapid development of such technology to address unmet needs across cardiovascular care, multiple conditions which were previously treated surgically or with medications now benefit from trans-catheter device-based evaluation and management. Moreover, innovation to existing technology has transformed the structural design of many traditional cardiovascular devices, making them safer and enabling easier deployment within the chest (catheter-based versus surgical). A post-procedure chest radiography (CXR) is often the first routine imaging test ordered in these patients. A CXR is a relatively inexpensive and noninvasive imaging tool, which can be obtained at the patient's bedside if needed. Commonly implanted cardiovascular devices can be quite easily checked for appropriate positioning on routine CXRs. Potential complications associated with mal-positioning of such devices may be life-threatening. Such complications often manifest early on CXRs and may not be readily apparent on clinical examination. Prompt recognition of such abnormal radiographic appearances is critical for timely diagnosis and effective management. Clinicians need to be familiar with new devices in order to assess proper placement and identify complications related to mal-positioning. This pictorial essay aims to describe the radiologic appearances of contemporary cardiovascular devices, review indications for their usage and potential complications, and discuss magnetic resonance imaging (MRI) compatibility., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/cdt-20-617). The authors have no conflicts of interest to declare., (2020 Cardiovascular Diagnosis and Therapy. All rights reserved.)

Background: The study objective was to determine whether unlabeled datasets can be used to further train and improve the accuracy of a deep learning system (DLS) for the detection of tuberculosis (TB) on chest radiographs (CXRs) using a two-stage semi-supervised approach., Methods: A total of 111,622 CXRs from the National Institute of Health ChestX-ray14 database were collected. A cardiothoracic radiologist reviewed a subset of 11,000 CXRs and dichotomously labeled each for the presence or absence of potential TB findings; these interpretations were used to train a deep convolutional neural network (DCNN) to identify CXRs with possible TB (Phase I). The best performing algorithm was then used to label the remaining database consisting of 100,622 radiographs; subsequently, these newly-labeled images were used to train a second DCNN (phase II). The best-performing algorithm from phase II (TBNet) was then tested against CXRs obtained from 3 separate sites (2 from the USA, 1 from China) with clinically confirmed cases of TB. Receiver operating characteristic (ROC) curves were generated with area under the curve (AUC) calculated., Results: The phase I algorithm trained using 11,000 expert-labelled radiographs achieved an AUC of 0.88. The phase II algorithm trained on images labeled by the phase I algorithm achieved an AUC of 0.91 testing against a TB dataset obtained from Shenzhen, China and Montgomery County, USA. The algorithm generalized well to radiographs obtained from a tertiary care hospital, achieving an AUC of 0.87; TBNet's sensitivity, specificity, positive predictive value, and negative predictive value were 85%, 76%, 0.64, and 0.9, respectively. When TBNet was used to arbitrate discrepancies between 2 radiologists, the overall sensitivity reached 94% and negative predictive value reached 0.96, demonstrating a synergistic effect between the algorithm's output and radiologists' interpretations., Conclusions: Using semi-supervised learning, we trained a deep learning algorithm that detected TB at a high accuracy and demonstrated value as a CAD tool by identifying relevant CXR findings, especially in cases that were misinterpreted by radiologists. When dataset labels are noisy or absent, the described methods can significantly reduce the required amount of curated data to build clinically-relevant deep learning models, which will play an important role in the era of precision medicine., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/jtd.2019.08.34). The series “Role of Precision Imaging in Thoracic Disease” was commissioned by the editorial office without any funding or sponsorship. The authors have no other conflicts of interest to declare., (2020 Journal of Thoracic Disease. All rights reserved.)

Purpose: Studies suggest that "on-demand" radiography is equivalent to daily routine with regard to adverse events. In these studies, provider behavior is controlled. Pragmatic implementation has not been studied., Materials and Methods: This was a quasi-experimental, pre-post intervention study. Medical directors of two intervention ICUs requested pCXRs be ordered on an on-demand basis at one time point, without controlling or monitoring behavior or providing follow-up., Results: A total of 11,994 patient days over 18months were included. Combined characteristics: Age: 56.7, 66% male, 96% survival, APACHE II 14 (IQR: 11-19), mechanical ventilation (MV) (occurrences)/patient admission: mean 0.7 (SD: 0.6; range: 0-5), duration (hours) of MV: 21.7 (IQR: 9.8-81.4) and ICU LOS (days): 2.8 (IQR: 1.8-5.6). Average pCXR rate/patient/day before was 0.93 (95% CI: 0.89-0.96), and 0.73 (95% CI: 0.69-0.77) after. Controlling for severity, daily pCXR rate decreased by 21.7% (p<0.001), then increased by about 3%/month (p=0.044). There was no change in APACHE II, mortality, and occurrences or duration of MV, unplanned re-intubations, ICU LOS., Conclusions: In critically ill adults, pCXR reduction can be achieved in cardiothoracic and trauma/surgical patients with a pragmatic intervention, without adversely affecting patient care, outside a controlled study., (Copyright © 2017 Elsevier Inc. All rights reserved.)