scholarly journals The Source of the Problem

2019 ◽  
Vol 18 (1) ◽  
pp. 45-46
Author(s):  
Peter Moffitt ◽  
◽  
Adam Williamson ◽  
Peter Stenhouse ◽  
◽  
...  
Keyword(s):  
Sinus Rhythm ◽  
Endotracheal Tube ◽  
X Ray ◽  
Portable Chest ◽  
Chest X Ray ◽  
St Elevation ◽  
Cardiac Silhouette

The portable chest x-ray (Figure 1) shows a widened cardiac silhouette. An endotracheal tube is in situ, indicating the patient is now intubated. The ECG (Figure 2) shows sinus rhythm with widespread mixed convex and concave ST elevation, most notable in V4, V5 and the lateral leads. There is a suggestion of PR depression in the inferior leads.

Double Cardiac Silhouette on Lateral Chest X-Ray Graphy

2011 ◽  
Vol 29 (2) ◽  
pp. E52-E53 ◽  
Author(s):  
Ozcan Basaran ◽  
Ahmet Guler ◽  
Can Y. Karabay ◽  
Soe M. Aung ◽  
Arzu Kalayci ◽  
...  
Keyword(s):  
X Ray ◽  
Chest X Ray ◽  
Lateral Chest ◽  
Cardiac Silhouette

Amiodarone – induced pulmonary nodules mimiking metastatic lung disease – investigation by somatostatin radio peptide scaning

2005 ◽  
Vol 4 (2) ◽  
pp. 63-65
Author(s):  
Veronica Varney ◽  
◽  
Mary Warren ◽  
M Palmer ◽  
◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Sinus Rhythm ◽  
Pulmonary Nodules ◽  
Alcoholic Cardiomyopathy ◽  
X Ray ◽  
The Past ◽  
Previous Diagnosis ◽  
Metastatic Lung ◽  
Chest X Ray ◽  
200Mg Daily

A 61 year old former paramedic presented to A&E complaining of palpitations. He was found to be in atrial fibrillation, which reverted spontaneously to sinus rhythm. A chest x-ray taken at that time showed multiple pulmonary nodules consistent with metastatic malignancy (Figure 1). In the past he had been treated with amiodarone 200mg daily for 6 years following a previous diagnosis of atrial fibrillation, which had been attributed to alcoholic cardiomyopathy. He had discontinued the drug 8 months earlier, after selfdiagnosing hypotension and bradycardia. A previous chest X-ray, taken before starting amiodarone, was normal.

Abstract P18: Report on the Treatment Process and Impact of Mechanical Thrombectomy Before and After Coronavirus Disease in a Newly Opened Hospital of South Korea

Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Jin EUN ◽  
Hae-Kwan Park
Keyword(s):  
Emergency Treatment ◽  
Treatment Process ◽  
Mechanical Thrombectomy ◽  
X Ray ◽  
X Ray Imaging ◽  
New Process ◽  
Before And After ◽  
Portable Chest ◽  
Chest X Ray ◽  
Adequate Management

Introduction: The difficulty neurointernvetionists face in keeping “Time is brain” in the middle of the COVID-19 pandemic are inevitable. Our health system began shutting down entire hospital for two weeks after a transport agent was diagnosed with COVID-19. It took an additional two weeks to establish the process of emergency treatment. We intend to introduce our protocols and report on their progress so far. Post-COVID-19 Protocol (Figure 1) Methods: A total of 52 patients underwent mechanical thrombectomy at Eunpyeong St. Mary’s Hospital before the Covid-19 outbreak. For 18 patients who underwent mechanical thrombectomy through a new process after COVID-19, door-to-image time, door-to-puncture time, and TICI grade were compared. Results: For the treatment of all patients, portable chest x-ray imaging was performed, but the door-to-initial-brain-image time (min) was 15.5 vs. 15 (before COVID-19 vs. after COVID-19) (p=0.265). Door-to-needle-time (min) showed a delay of 9 minutes, from 144.5 to 153.5, but it was not statistically significant (p=0.299). Up to 95.2% of patients before COVID-19 achieved TICI grade 2b or higher, and 100% of patients after COVID-19 have achieved TICI grade 2b or 3. (Table 1) Conclusions: Overall, there was a slight increase in the door-to-needle time, but clear protocols and guidelines for management and collaboration with the clinical workforce have been able to reduce delays and ensure timely and adequate management. When referring to the protocol implemented while preparing for infectious diseases, it will be a reference not only for COVID-19, but also for other diseases that may occur in the future.

scholarly journals Anatomy-based transmission factors for technique optimization in portable chest x-ray

2015 ◽  
Author(s):  
Christopher L. Liptak ◽  
Deborah Tovey ◽  
William P. Segars ◽  
Frank D. Dong ◽  
Xiang Li
Keyword(s):  
X Ray ◽  
Portable Chest ◽  
Technique Optimization ◽  
Chest X Ray ◽  
Transmission Factors

Diagnostic value of the portable chest x-ray technic in pulmonary edema

1978 ◽  
Vol 135 (4) ◽  
pp. 604-606 ◽  
Author(s):  
Paul R. Liebman ◽  
Ervin Philips ◽  
Richard Weisel ◽  
Jameel Ali ◽  
Herbert B. Hechtman
Keyword(s):  
Pulmonary Edema ◽  
Diagnostic Value ◽  
X Ray ◽  
Portable Chest ◽  
Chest X Ray

scholarly journals Idiopathic Chylopericardium in a Young Adult: Diagnosis and Management

2021 ◽  
Vol 2021 ◽  
pp. 1-3
Author(s):  
João Pedro E. Sant’Ana ◽  
Amanda O. Vicente ◽  
Amanda S. Pereira ◽  
Pedro V. Bertozzi ◽  
Rodrigo A. S. Sardenberg
Keyword(s):  
Chest Pain ◽  
Pleural Effusion ◽  
Chest Ct ◽  
Pericardial Window ◽  
X Ray ◽  
Large Pericardial Effusion ◽  
Chest X Ray ◽  
Cardiac Silhouette ◽  
The Right ◽  
Precipitating Factor

Primary idiopathic chylopericardium (PIC) is an uncommon cardiologic disorder; it is defined as accumulation of lymph in the pericardial sac without any know precipitating factor. A 25-year-old presented with dyspnea and chest pain for over two months. The patient underwent a chest X-ray, which revealed an enlargement of cardiac silhouette and signs of cardiac tamponade. Chest CT was performed, revealing large pericardial effusion and small pleural effusion on the right hemithorax. The patient was referred to the ICU and underwent a pericardial window through VATS, which revealed 500 ml of a milky fluid.

scholarly journals Deep-learning convolutional neural networks with transfer learning accurately classify COVID-19 lung infection on portable chest radiographs

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e10309
Author(s):  
Shreeja Kikkisetti ◽  
Jocelyn Zhu ◽  
Beiyi Shen ◽  
Haifang Li ◽  
Tim Q. Duong
Keyword(s):  
Deep Learning ◽  
Transfer Learning ◽  
Bacterial Pneumonia ◽  
Lung Infection ◽  
Accurate Diagnosis ◽  
Viral Pneumonia ◽  
X Ray ◽  
Portable Chest ◽  
Chest X Ray ◽  
Lung Infections

Portable chest X-ray (pCXR) has become an indispensable tool in the management of Coronavirus Disease 2019 (COVID-19) lung infection. This study employed deep-learning convolutional neural networks to classify COVID-19 lung infections on pCXR from normal and related lung infections to potentially enable more timely and accurate diagnosis. This retrospect study employed deep-learning convolutional neural network (CNN) with transfer learning to classify based on pCXRs COVID-19 pneumonia (N = 455) on pCXR from normal (N = 532), bacterial pneumonia (N = 492), and non-COVID viral pneumonia (N = 552). The data was randomly split into 75% training and 25% testing, randomly. A five-fold cross-validation was used for the testing set separately. Performance was evaluated using receiver-operating curve analysis. Comparison was made with CNN operated on the whole pCXR and segmented lungs. CNN accurately classified COVID-19 pCXR from those of normal, bacterial pneumonia, and non-COVID-19 viral pneumonia patients in a multiclass model. The overall sensitivity, specificity, accuracy, and AUC were 0.79, 0.93, and 0.79, 0.85 respectively (whole pCXR), and were 0.91, 0.93, 0.88, and 0.89 (CXR of segmented lung). The performance was generally better using segmented lungs. Heatmaps showed that CNN accurately localized areas of hazy appearance, ground glass opacity and/or consolidation on the pCXR. Deep-learning convolutional neural network with transfer learning accurately classifies COVID-19 on portable chest X-ray against normal, bacterial pneumonia or non-COVID viral pneumonia. This approach has the potential to help radiologists and frontline physicians by providing more timely and accurate diagnosis.

Measurement of Endotracheal Tube Positioning on Chest X-Ray Using Object Detection

2021 ◽  
Author(s):  
Robert J. Harris ◽  
Scott G. Baginski ◽  
Yulia Bronstein ◽  
Shwan Kim ◽  
Jerry Lohr ◽  
...  
Keyword(s):  
Object Detection ◽  
Endotracheal Tube ◽  
X Ray ◽  
Chest X Ray
Sign in / Sign up

Export Citation Format

Share Document