PA/Lateral Chest X-Ray is Equivalent to Cine-Fluoroscopy for the Detection of Conductor Externalization in Defibrillation Leads

2014 ◽  
Vol 38 (1) ◽  
pp. 77-83
Author(s):  
CHRISTIAN STEINBERG ◽  
JEAN-FRANÇOIS SARRAZIN ◽  
FRANÇOIS PHILIPPON ◽  
JEAN CHAMPAGNE ◽  
FRANCK MOLIN ◽  
...  
Keyword(s):  
X Ray ◽  
Chest X Ray ◽  
Lateral Chest ◽  
Defibrillation Leads

Pa/Lateral Chest X-Ray Is Non-Inferior to Fluoroscopy for the Detection of Insulation Defects in Riata Defibrillation Leads

2013 ◽  
Vol 29 (10) ◽  
pp. S360
Author(s):  
C. Steinberg ◽  
J. Sarrazin ◽  
J. Champagne ◽  
F. Philippon ◽  
F. Molin ◽  
...  
Keyword(s):  
X Ray ◽  
Chest X Ray ◽  
Lateral Chest ◽  
Defibrillation 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

Diagnosis of vertebral fractures on lateral chest X-ray: Intraobserver agreement of semi-quantitative vertebral fracture assessment

2014 ◽  
Vol 83 (12) ◽  
pp. 2177-2180 ◽  
Author(s):  
H.C. van der Jagt-Willems ◽  
B.C. van Munster ◽  
M. Leeflang ◽  
E. Beuerle ◽  
C.R. Tulner ◽  
...  
Keyword(s):  
Vertebral Fracture ◽  
Vertebral Fractures ◽  
Vertebral Fracture Assessment ◽  
Intraobserver Agreement ◽  
X Ray ◽  
Chest X Ray ◽  
Fracture Assessment ◽  
Lateral Chest

scholarly journals Aggravation and deliberation over lung herniation

2019 ◽  
Vol 12 (5) ◽  
pp. e229225
Author(s):  
Michelle N Lee ◽  
Luke T Surry ◽  
David M Ferraro
Keyword(s):  
Influenza A ◽  
Surgical Repair ◽  
Caucasian Woman ◽  
Pleuritic Chest Pain ◽  
X Ray ◽  
Lung Herniation ◽  
Left Posterior ◽  
History Of ◽  
Chest X Ray ◽  
Lateral Chest

A Caucasian woman aged 58 years with history of asthma and surgically repaired congenital diaphragmatic hernia presented to the emergency department (ED) with persistent cough, pleuritic chest pain, shortness of breath, in spite of recent treatment for influenza A virus. On physical examination, a large bulge was protruding from her left posterior thorax. She was found to have a large abnormal radiographic lucency on lateral chest X-ray posterior to the thoracic cavity, confirmed with chest CT to represent a large lung herniation in between the left seventh and eighth ribs. The patient was evaluated by a thoracic surgeon and offered surgical repair but ultimately decided on conservative management which to date has been ineffective.

scholarly journals Comparative effectiveness of a mnemonic-use approach vs. self-study to interpret a lateral chest X-ray

2017 ◽  
Vol 41 (4) ◽  
pp. 518-521 ◽  
Author(s):  
Michael Thompson ◽  
Dallin Johansen ◽  
Russell Stoner ◽  
Allison Jarstad ◽  
Robert Sorrells ◽  
...  
Keyword(s):  
Medical Students ◽  
Imaging Study ◽  
Lateral View ◽  
Frontal View ◽  
Chest Film ◽  
X Ray ◽  
Self Study ◽  
Lateral Film ◽  
Chest X Ray ◽  
Lateral Chest

The chest X-ray is the most commonly performed medical imaging study; however, the lateral chest film intimidates many physicians and medical students. The lateral view is more difficult to interpret than the frontal view but provides important information that is either not visible or not as evident on frontal view, and inability to read it may lead to missed diagnoses and more expensive imaging. The objective of this study was to assess a novel mnemonic-based approach to teaching medical students to proficiently read a lateral film using a prospective pilot study. A clinical faculty radiologist taught two groups of second-year medical students to read a lateral chest X-ray. One group learned a novel mnemonic-based method (MUM), and the other cohort performed directed web-based self-study (STMM). Each cohort was given a pre- and postassessment, and their performance was analyzed. A total of n = 29 students participated with n = 14 being taught the mnemonic method. The MUM group significantly ( P = 0.001) improved their score vs. the STMM group This study demonstrates students can quickly and effectively learn to read a lateral chest film using this novel mnemonic.

scholarly journals Lateral Chest X-Ray for Physicians

2005 ◽  
Vol 98 (7) ◽  
pp. 310-312 ◽  
Author(s):  
Khalid A Gaber ◽  
Clive R McGavin ◽  
Irving P Wells
Keyword(s):  
X Ray ◽  
Chest X Ray ◽  
Lateral Chest

765 High Prevalence of Riata Insulation Defects Detected by Systematic PA/Lateral Chest-X Ray - A Single Center Experience

2012 ◽  
Vol 28 (5) ◽  
pp. S393-S394
Author(s):  
C. Steinberg ◽  
J. Sarrazin ◽  
M. Bouchard ◽  
F. Philippon ◽  
G. O'Hara ◽  
...  
Keyword(s):  
Single Center ◽  
X Ray ◽  
Single Center Experience ◽  
High Prevalence ◽  
Chest X Ray ◽  
Lateral Chest

Dual-Ray Net: Automatic Diagnosis of Thoracic Diseases Using Frontal and Lateral Chest X-rays

2020 ◽  
Vol 10 (2) ◽  
pp. 348-355
Author(s):  
Xin Huang ◽  
Yu Fang ◽  
Mingming Lu ◽  
Fengqi Yan ◽  
Jun Yang ◽  
...  
Keyword(s):  
Chest Radiography ◽  
Feature Fusion ◽  
Small Data ◽  
Data Sets ◽  
X Rays ◽  
X Ray ◽  
Comparison Results ◽  
Chest Disease ◽  
Chest X Ray ◽  
Lateral Chest

Computer-aided diagnosis (CAD) is an important work which can improve the working efficiency of physicians. With the availability of large-scale data sets, several methods have been proposed to classify pathology on chest X-ray images. However, most methods report performance based on a frontal chest radiograph, ignoring the effect of the lateral chest radiography on the diagnosis. This paper puts forward a kind of model, Dual-Ray Net, of a deep convolutional neural network which can deal with the front and lateral chest radiography at the same time by referring the method of using lateral chest radiography to assist diagnose during the diagnosis used by radiologists. Firstly, we evaluated the performance of parameter migration to small data after pre-training for large datasets. The data sets for pre-training are chest X-ray 14 and ImageNet respectively. The results showed that pre-training with chest X-ray 14 performed better than with the generic dataset ImageNet. Secondly, We evaluated the performance of the Frontal and lateral chest radiographs in different modes of input model for the diagnosis of assisted chest disease. Finally, by comparing different feature fusion methods of addition and concatenation, we found that the fusion effect of concatenation is better, which average AUC reached 0.778. The comparison results show that whether it is a public or a non-public dataset, our Dual-Ray Net (concatenation) architecture shows improved performance in recognizing findings in CXR images when compared to applying separate baseline frontal and lateral classes.

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