scholarly journals On the Replica of US Pulmonary Artifacts by Means of Physical Models

Diagnostics ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 1666
Author(s):  
Marcello Demi
Keyword(s):  
Visual Inspection ◽  
Lung Ultrasound ◽  
Diagnostic Value ◽  
Experimental Results ◽  
Physical Models ◽  
Ultrasound Images ◽  
Pulmonary Disorder ◽  
Visual Characteristics ◽  
Artifact Formation ◽  
B Lines

Currently, the diagnostic value of the artefactual information provided by lung ultrasound images is widely recognized by physicians. In particular, the existence of a correlation between the visual characteristics of the vertical artifacts, which arise from the pleura line, and the genesis (pneumogenic or cardiogenic) of a pulmonary disorder is commonly accepted. Physicians distinguish vertical artifacts from vertical artifacts which extend to the bottom of the screen (B-lines) and common vertical artifacts from well-structured artifacts (modulated B-lines). However, the link between these visual characteristics and the causes which determine them is still unclear. Moreover, the distinction between short and long artifacts and the distinction between common and structured artifacts are not on/off, and their classification can be critical. In order to derive further information from the visual inspection of the vertical artifacts, the mechanisms which control the artifact formation must be identified. In this paper, the link between the visual characteristics of the vertical artifacts (the observed effect) and the distribution of the aerated spaces at the pleural level (the cause) is addressed. Plausible mechanisms are suggested and illustrated through experimental results.

scholarly journals Diagnostic value of 12-zone lung ultrasound protocol for diagnosing COVID-19-associated pneumonia in outpatients

2021 ◽  
Vol 21 (87) ◽  
pp. 271-276
Author(s):  
Dzmitry Haurylenka ◽  
◽  
Victar Damantsevich ◽  
Andrey Filustsin ◽  
Anna Damantsevich ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Quantitative Assessment ◽  
Lung Ultrasound ◽  
Area Under The Curve ◽  
Diagnostic Value ◽  
Outpatient Setting ◽  
Diagnostic Significance ◽  
Decisive Importance ◽  
Sensitivity Specificity ◽  
B Lines

Introduction: In the SARS-CoV-2 pandemic, lung ultrasound can be of decisive importance for planning further treatment approach in patients with infection. There is still no clear priority for the choice of lung ultrasound protocol in an outpatient setting. Aim: The objective of the study was to evaluate the applicability of 12-zone protocol lung ultrasound for the diagnosis of COVID- 19 associated pneumonia in outpatients. Materials and methods: We examined 39 outpatients meeting the diagnostic criteria of COVID-19 infection (17 men and 22 women) aged 31–75 years (median 49 years). All patients underwent lung ultrasound immediately after chest computed tomography performed by a blinded specialist. Correlation analysis of the results of a quantitative assessment of the detected signs, assessment of the diagnostic significance of lung ultrasound for identifying signs of pneumonia were performed. Results: Pneumonia was diagnosed by computed tomography in 25 (64%; 95% CI 47–79) out of 39 patients. At the same time, ultrasound signs of interstitial abnormalities were detected in 31 patients. Multiple (narrow) B-lines, confluent (wide) B-lines, as well as areas of subpleural consolidation and “white lung” were the most common lung ultrasound abnormalities. When evaluating the method, the optimal sensitivity/ specificity ratio was obtained for a value of ≥2 points, the area under the curve = 0.970 (95% CI 0.858–0.999; p <0.0001). The score of lung ultrasound significantly correlated with computed tomography quantitative assessment (r = 0.928, p <0.001). Conclusion: Despite some limitations, lung ultrasound can be extremely useful in primary care settings, also in the case of a significant number of admitted patients, to detect features of COVID-19 associated pneumonia.

scholarly journals Development of a convolutional neural network to differentiate among the etiology of similar appearing pathological B lines on lung ultrasound: a deep learning study

BMJ Open ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. e045120
Author(s):  
Robert Arntfield ◽  
Blake VanBerlo ◽  
Thamer Alaifan ◽  
Nathan Phelps ◽  
Matthew White ◽  
...  
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Convolutional Neural Network ◽  
Lung Ultrasound ◽  
Low Cost ◽  
Characteristic Curve ◽  
Ultrasound Images ◽  
Diagnostic Specificity ◽  
Multicentre Research ◽  
B Lines

ObjectivesLung ultrasound (LUS) is a portable, low-cost respiratory imaging tool but is challenged by user dependence and lack of diagnostic specificity. It is unknown whether the advantages of LUS implementation could be paired with deep learning (DL) techniques to match or exceed human-level, diagnostic specificity among similar appearing, pathological LUS images.DesignA convolutional neural network (CNN) was trained on LUS images with B lines of different aetiologies. CNN diagnostic performance, as validated using a 10% data holdback set, was compared with surveyed LUS-competent physicians.SettingTwo tertiary Canadian hospitals.Participants612 LUS videos (121 381 frames) of B lines from 243 distinct patients with either (1) COVID-19 (COVID), non-COVID acute respiratory distress syndrome (NCOVID) or (3) hydrostatic pulmonary edema (HPE).ResultsThe trained CNN performance on the independent dataset showed an ability to discriminate between COVID (area under the receiver operating characteristic curve (AUC) 1.0), NCOVID (AUC 0.934) and HPE (AUC 1.0) pathologies. This was significantly better than physician ability (AUCs of 0.697, 0.704, 0.967 for the COVID, NCOVID and HPE classes, respectively), p<0.01.ConclusionsA DL model can distinguish similar appearing LUS pathology, including COVID-19, that cannot be distinguished by humans. The performance gap between humans and the model suggests that subvisible biomarkers within ultrasound images could exist and multicentre research is merited.

scholarly journals Development of a deep learning classifier to accurately distinguish COVID-19 from look-a-like pathology on lung ultrasound

2020 ◽  
Author(s):  
Robert Arntfield ◽  
Blake VanBerlo ◽  
Thamer Alaifan ◽  
Nathan Phelps ◽  
Matt White ◽  
...  
Keyword(s):  
Deep Learning ◽  
Lung Ultrasound ◽  
Low Cost ◽  
Ultrasound Images ◽  
Diagnostic Specificity ◽  
Imaging Tool ◽  
Learning Classifier ◽  
Learning Techniques ◽  
Deep Learning Model ◽  
B Lines

AbstractObjectivesLung ultrasound (LUS) is a portable, low cost respiratory imaging tool but is challenged by user dependence and lack of diagnostic specificity. It is unknown whether the advantages of LUS implementation could be paired with deep learning techniques to match or exceed human-level, diagnostic specificity among similar appearing, pathological LUS images.DesignA convolutional neural network was trained on LUS images with B lines of different etiologies. CNN diagnostic performance, as validated using a 10% data holdback set was compared to surveyed LUS-competent physicians.SettingTwo tertiary Canadian hospitals.Participants600 LUS videos (121,381 frames) of B lines from 243 distinct patients with either 1) COVID-19, Non-COVID acute respiratory distress syndrome (NCOVID) and 3) Hydrostatic pulmonary edema (HPE).ResultsThe trained CNN performance on the independent dataset showed an ability to discriminate between COVID (AUC 1.0), NCOVID (AUC 0.934) and HPE (AUC 1.0) pathologies. This was significantly better than physician ability (AUCs of 0.697, 0.704, 0.967 for the COVID, NCOVID and HPE classes, respectively), p < 0.01.ConclusionsA deep learning model can distinguish similar appearing LUS pathology, including COVID-19, that cannot be distinguished by humans. The performance gap between humans and the model suggests that subvisible biomarkers within ultrasound images could exist and multi-center research is merited.

Clinical Applicability of Lung Ultrasound Methods in the Emergency Department to Detect Pulmonary Congestion on Computed Tomography

2019 ◽  
Author(s):  
Kristina Cecilia Miger ◽  
Andreas Fabricius-Bjerre ◽  
Christian Peter Maschmann ◽  
Jesper Wamberg ◽  
Mathilde Marie Winkler Wille ◽  
...  
Keyword(s):  
Heart Failure ◽  
Emergency Department ◽  
Pleural Effusion ◽  
Lung Ultrasound ◽  
Decompensated Heart Failure ◽  
Diagnostic Value ◽  
Chest Ct ◽  
Chronic Obstructive ◽  
Pulmonary Congestion ◽  
B Lines

Abstract Background B-lines on lung ultrasound are seen in decompensated heart failure, but their diagnostic value in consecutive patients in the acute setting is not clear. Chest CT is the superior method to evaluate interstitial lung disease, but no studies have compared lung ultrasound directly to congestion on chest CT. Purpose To examine whether congestion on lung ultrasound equals congestion on a low-dose chest CT as the gold standard. Materials and Methods In a single-center, prospective observational study we included consecutive patients ≥ 50 years of age in the emergency department. Patients were concurrently examined by lung ultrasound and chest CT. Congestion on lung ultrasound was examined in three ways: I) the total number of B-lines, II) ≥ 3 B-lines bilaterally, III) ≥ 3 B-lines bilaterally and/or bilateral pleural effusion. Congestion on CT was assessed by two specialists blinded to all other data. Results We included 117 patients, 27 % of whom had a history of heart failure and 52 % chronic obstructive pulmonary disease. Lung ultrasound and CT were performed within a median time of 79.0 minutes. Congestion on CT was detected in 32 patients (27 %). Method I had an optimal cut-point of 7 B-lines with a sensitivity of 72 % and a specificity of 81 % for congestion. Method II had 44 % sensitivity, and 94 % specificity. Method III had a sensitivity of 88 % and a specificity of 85 %. Conclusion Pulmonary congestion in consecutive dyspneic patients ≥ 50 years of age is better diagnosed if lung ultrasound evaluates both B-lines and pleural effusion instead of B-lines alone.

scholarly journals The Role of Lung Ultrasound in Diagnosing COVID-19-Related Multisystemic Inflammatory Disease: A Preliminary Experience

2022 ◽  
Vol 11 (1) ◽  
pp. 234
Author(s):  
Anna Maria Musolino ◽  
Elena Boccuzzi ◽  
Danilo Buonsenso ◽  
Maria Chiara Supino ◽  
Maria Alessia Mesturino ◽  
...  
Keyword(s):  
Pleural Effusion ◽  
Inflammatory Disease ◽  
Lung Ultrasound ◽  
Point Of Care ◽  
Ultrasound Images ◽  
Systemic Inflammatory Disease ◽  
Areas Of Interest ◽  
Inflammatory Syndrome ◽  
B Lines

Background: To date, there are no data regarding the systematic application of Point-of-Care Lung Ultrasound (PoC-LUS) in children with Multisystem Inflammatory Syndrome in Children (MIS-C). The main aim of this study is to show the role of Point-of-Care Lung Ultrasound as an additional aid in the diagnosis of COVID-19-related Multisystem Inflammatory Syndrome in Children (MIS-C). Methods: Between April 2020 and April 2021, patients aged 0–18 years referred to our emergency department for fever, and later hospitalized without a specific diagnosis, underwent PoC-LUS. Ultrasound images of patients with a final diagnosis of MIS-C were retrospectively evaluated. Results: Ten patients were enrolled. All were described to have pleural irregularities and B-lines. In particular: 8/10 children presented with isolated B-lines in at least half of the lung areas of interest; 8/10 presented with multiple B-lines and 3/8 had them in at least 50% of lung areas; 5/10 had a white lung appearance in at least one lung area and 1/5 had them in half of the areas of interest. Pleural effusion was described in 9/10. Conclusions: During the ongoing COVID-19 pandemic, we suggest performing PoC-LUS in febrile patients with high levels of inflammatory indices and clinical suspicion of MIS-C, or without a certain diagnosis; the finding of many B-lines and pleural effusion would support the diagnosis of a systemic inflammatory disease.

scholarly journals Ability of non-physicians to perform and interpret lung ultrasound: A systematic review

2019 ◽  
Vol 18 (6) ◽  
pp. 474-483 ◽  
Author(s):  
Varsha Swamy ◽  
Philip Brainin ◽  
Tor Biering-Sørensen ◽  
Elke Platz
Keyword(s):  
Heart Failure ◽  
Systematic Review ◽  
Lung Ultrasound ◽  
Point Of Care ◽  
Ultrasound Images ◽  
Pulmonary Congestion ◽  
Pleural Effusions ◽  
Brief Training ◽  
Online Databases ◽  
B Lines

Background: Lung ultrasound is a useful tool in the assessment of pulmonary congestion in heart failure that is typically performed and interpreted by physicians at the point-of-care. Aims: To investigate the ability of nurses, students, and paramedics to accurately identify B-lines and pleural effusions for the detection of pulmonary congestion in heart failure and to examine the training necessary. Methods and results: We conducted a systematic review and searched online databases for studies that investigated the ability of nurses, students, and paramedics to perform lung ultrasound and detect B-lines and pleural effusions. Of 979 studies identified, 14 met our inclusion criteria: five in nurses, eight in students, and one in paramedics. After 0–12 h of didactic training and 58–62 practice lung ultrasound examinations, nurses were able to identify B-lines and pleural effusions with a sensitivity of 79–98% and a specificity of 70–99%. In image adequacy studies, medical students with 2–9 h of training were able to acquire adequate images for B-lines and pleural effusions in 50–100%. Only one eligible study investigated paramedic-performed lung ultrasound which did not support the ability of paramedics to adequately acquire and interpret lung ultrasound images after 2 h of training. Conclusions: Our findings suggest that nurses and students can accurately acquire and interpret lung ultrasound images after a brief training period in a majority of cases. The examination of heart failure patients with lung ultrasound by non-clinicians appears feasible and warrants further investigation.

scholarly journals Use of lung ultrasound in neonates during the COVID-19 pandemic

2020 ◽  
Vol 53 (6) ◽  
pp. 401-404
Author(s):  
Marcia Wang Matsuoka ◽  
Silvia Maria Sucena da Rocha ◽  
Maria Augusta Bento Cicaroni Gibelli ◽  
Carla Marques Nicolau ◽  
Werther Brunow de Carvalho ◽  
...  
Keyword(s):  
Respiratory Symptoms ◽  
Distress Syndrome ◽  
Lung Ultrasound ◽  
Ultrasound Examination ◽  
Neonatal Period ◽  
Ultrasound Images ◽  
Normal Pattern ◽  
Pleural Thickening ◽  
Pleural Line ◽  
B Lines

Abstract In the current pandemic, caused by infection with severe acute respiratory syndrome coronavirus 2, ultrasound has played a fundamental role in patients who develop the resulting disease, designated coronavirus disease 2019 (COVID-19). In this study we present ultrasound images of the lungs of neonates with a suspected or confirmed diagnosis of COVID-19, distinguishing between the changes related to COVID-19 and those unrelated to the disease. Ultrasound examinations were performed by a pediatric sonographer. A total of 27 neonates were evaluated. Among those who presented no respiratory symptoms, some tested negative for COVID-19 and others tested positive. All of those who were pulmonary symptomatic, negative for COVID-19 presented transient tachypnea of the newborn and respiratory distress syndrome. Lung ultrasound images obtained in COVID-19-negative neonates showed, in some cases, a normal pattern (with A lines, few B lines, a thin, linear pleural line, and no pleural effusion), whereas in others showed coalescent B lines and areas of opacity. In two of the COVID-19-positive neonates, lung ultrasound examination showed several coalescent B lines, pleural thickening, and areas of opacity. Lung ultrasound in the neonatal period appears to be applicable within the context of the current pandemic, allowing efficient evaluation of COVID-19-related changes in neonates, as well as of pathologies inherent to the neonatal period.

scholarly journals Diagnostic Value of Fluorescence Methods, Visual Inspection and Photographic Visual Examination in Initial Caries Lesion: A Systematic Review and Meta-Analysis

2021 ◽  
Vol 9 (3) ◽  
pp. 30
Author(s):  
Mai Thi Giang Thanh ◽  
Ngo Van Toan ◽  
Do Thi Thanh Toan ◽  
Nguyen Phu Thang ◽  
Ngoc Quang Dong ◽  
...  
Keyword(s):  
Systematic Review ◽  
Quality Assessment ◽  
Visual Inspection ◽  
Early Stage ◽  
Meta Analysis ◽  
Diagnostic Value ◽  
Caries Detection ◽  
Permanent Teeth ◽  
Visual Examination ◽  
Initial Caries

This systematic review and meta-analysis aimed to investigate the efficacy of fluorescence-based methods, visual inspections, and photographic visual examinations in initial caries detection. A literature search was undertaken in the PubMed and Cochrane databases. Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines were followed, and eligible articles published from 1 January 2009 to 30 October 2019 were included if they met the following criteria: they (1) assessed the accuracy of methods of detecting initial tooth caries lesions on occlusal, proximal, or smooth surfaces in both primary and permanent teeth (in clinical); (2) used a reference standard; (3) reported data regarding the sample size, prevalence of initial tooth caries, and accuracy of the methods. Data collection and extraction, quality assessment, and data analysis were conducted according to Cochrane standards Quality Assessment of Diagnostic Accuracy Studies-2. Statistical analyses were performed using Review Manager 5.3 and STATA 14.0. A total of 12 eligible articles were included in the meta-analysis. The results showed that the sensitivity and specificity of fluorescence-based methods were 80% and 80%, respectively; visual inspection was measured at 80% and 75%, respectively; photographic visual examination was measured at 67% and 79%, respectively. We found that the visual method and the fluorescence method were reliable for laboratory use to detect early-stage caries with equivalent accuracy.

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