False negative chest X-Rays in patients affected by COVID-19 pneumonia and corresponding chest CT findings

Cellina, Michaela; Orsi, Marcello; Toluian, Tahereh; Pittino, Carlo Valenti; Oliva, Giancarlo

doi:10.1016/j.radi.2020.04.017

Cited by 36 publications

(39 citation statements)

References 14 publications

(15 reference statements)

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“…29 argue that since Covid-19 appearances may be subtle, high image quality is required from mobile X-ray units. Such challenges have been further reported in a series of publications highlighting patients who had normal CXR appearances and who went on to subsequently have ground glass opacifications demonstrated on CT. 8 , 30 …”

Section: Discussionmentioning

confidence: 99%

“… 7 Management of patients with known or suspected Covid-19 includes Medical Imaging (radiography and computed tomography (CT)). 8 As reported by Stogiannos and colleagues 9 practice varies widely within different countries, mainly due to differences in the access of resources (testing, imaging equipment, specialist staff and protective equipment).…”

Section: Introductionmentioning

confidence: 97%

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Modifications to mobile chest radiography technique during the COVID-19 pandemic – implications of X-raying through side room windows

England

Littler

Romani³

et al. 2021

Radiography

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Introduction Modifications to common radiographic techniques have resulted from the challenges presented by the COVID-19 pandemic. Reports exist regarding the potential benefits of undertaking mobile radiography through side room windows. The aim of this study was to evaluate the impact on image quality and exposure factors when undertaking such examinations. Methods A phantom based study was undertaken using a digital X-ray room. Control acquisitions, using a commercially available image quality test tool, were performed using standard mobile chest radiography acquisition factors. Image quality (physical and visual), incidence surface air kerma (ISAK), Exposure Index (EI) and Deviation Index (DI) were recorded. Image quality and radiation dose were further assessed for two additional (experimental) scenarios, where a side room window was located immediately adjacent to the exit port of the light beam diaphragm. The goal of experimental scenario one was to modify exposure factors to maintain the control ISAK. The goal of experimental scenario two was to modify exposure factors to maintain the control EI and DI. Dose and image quality data were compared between the three scenarios. Results To maintain the pre-window (control) ISAK (76 μGy), tube output needed a three-fold increase (90 kV/4 mAs versus 90 kV/11.25 mAs). To maintain EI/DI a more modest increase in tube output was required (90 kV/8 mAs/ISAK 54 μGy). Physical and visual assessments of spatial resolution and signal-to-noise ratio were indifferent between the three scenarios. There was a slight statistically significant reduction in contrast-to-noise ratio when imaging through the glass window (2.3 versus 1.4 and 1.2; P = 0.005). Conclusion Undertaking mobile X-ray examinations through side room windows is potentially feasible but does require an increase in tube output and is likely to be limited by minor reductions in image quality. Implications for practice Mobile examinations performed through side room windows should only be used in limited circumstances and future clinical evaluation of this technique is warranted.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 97%

Modifications to mobile chest radiography technique during the COVID-19 pandemic – implications of X-raying through side room windows

England

Littler

Romani³

et al. 2021

Radiography

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“…The radiological expert is required to analyze chest X-ray for finding the COVID-19 imaging patterns. However, it is a time-consuming and error-prone task (Cellina et al 2020 ). Therefore, the automatic analysis of chest x-ray is required.…”

Section: Introductionmentioning

confidence: 99%

Rapid COVID-19 diagnosis using ensemble deep transfer learning models from chest radiographic images

Gianchandani

Jaiswal

Singh

et al. 2020

J Ambient Intell Human Comput

104

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The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes novel coronavirus disease (COVID-19) outbreak in more than 200 countries around the world. The early diagnosis of infected patients is needed to discontinue this outbreak. The diagnosis of coronavirus infection from radiography images is the fastest method. In this paper, two different ensemble deep transfer learning models have been designed for COVID-19 diagnosis utilizing the chest X-rays. Both models have utilized pre-trained models for better performance. They are able to differentiate COVID-19, viral pneumonia, and bacterial pneumonia. Both models have been developed to improve the generalization capability of the classifier for binary and multi-class problems. The proposed models have been tested on two well-known datasets. Experimental results reveal that the proposed framework outperforms the existing techniques in terms of sensitivity, specificity, and accuracy.

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“…Dans le secteur de la radiologie, la crise sanitaire li ee au Coronavirus Disease 2019 (COVID-19) a entrain e diff erents bouleversements: r eorganisation des services d'imagerie, [1][2][3][4][5][6] recommandations pour l'interpr etation des images radiologiques 7,8 mais egalement une adaptation rapide des centres de formation initiale. 9,10 Cette crise sanitaire a impos e la mise en place rapide d'une continuit e p edagogique a distance concernant les enseignements mais egalement le suivi des stages cliniques.…”

Section: Introductionunclassified

Évaluation d'un dispositif de continuité pédagogique à distance mis en place auprès d’étudiants MERM pendant le confinement sanitaire lié au COVID-19

Zorn

Feffer²,

Bauer³

et al. 2020

Journal of Medical Imaging and Radiation Sciences

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Introduction: The specific context related to the COVID-19 pandemic necessitated the implementation of distance learning continuity for students. In France, teachers and radiography students in initial training, not specially prepared for this, had to adapt. An evaluation of the system was proposed to the students. Materials and methods: An anonymous online questionnaire with 4 main sections (pedagogy, communication, learning and concerns) was sent to 91 students at the end of the semester. Results: 91 responses were received. The slideshows with sound or presented during a virtual class are appreciated by the students. Online quizzes are ideal for learning/reviewing. For assessments, individual assignments and online questionnaires are appreciated. Teacher/ student interaction via e-mail or video conferencing was considered satisfactory by the large majority of students. Student-student interactions via social networks, for course explanations or document exchange, are very suitable. The majority of students felt they were working a lot and much more compared to face-to-face teaching. Less than half of the students worked more than 20 h per week. Their motivation varied widely. Organizational habits were disrupted, but the autonomy granted was appreciated. The students were mainly concerned about the health of their loved ones and not about their own health. Discussion: The use of distance education tools requires teacher commitment and technical skills. The frequency of communication by e-mail and/or videoconference between members of the teaching team and students must be adapted to the situation. Exchanges by email allow for traceability, while videoconferencing allows direct interaction and a way out of isolation. Autonomy, appreciated by the students, was nevertheless combined with a strong variation in motivation; the anxiety-provoking period in which pedagogical continuity was built up may explain this contradictory observation. Conclusion: The results obtained largely confirm the data in the literature. The experience gained through this survey should lead teachers to continue their reflection by test/integrating and evaluating distance education systems, while continuing face-to-face activities.

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False negative chest X-Rays in patients affected by COVID-19 pneumonia and corresponding chest CT findings

Cited by 36 publications

References 14 publications

Modifications to mobile chest radiography technique during the COVID-19 pandemic – implications of X-raying through side room windows

Modifications to mobile chest radiography technique during the COVID-19 pandemic – implications of X-raying through side room windows

Rapid COVID-19 diagnosis using ensemble deep transfer learning models from chest radiographic images

Évaluation d'un dispositif de continuité pédagogique à distance mis en place auprès d’étudiants MERM pendant le confinement sanitaire lié au COVID-19

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