COVID-19 pneumonia—ultrasound, radiographic, and computed tomography findings: a comprehensive pictorial essay

Cellina, Michaela; Martinenghi, C; Marino, Pietro; Oliva, Giancarlo

doi:10.1007/s10140-021-01905-6

Cited by 9 publications

(5 citation statements)

References 31 publications

(63 reference statements)

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“…A traditional division of lung lesions, according to its anatomical location in one of the five lung lobes, was found to be useful for predicting patient outcomes at the time of presenting to the emergency department 30 . However, the MBrixia score allows for quantification of the overall lesion burden, and it is advantageous in COVID-19 pneumonia, since studies using higher-resolution imaging, such as CT imaging, have reported COVID-19 lesions in lobar segments—as opposed to entire lung lobes 31 , 32 . Furthermore, when comparing the Brixia score with the MBrixia score, as shown in Supplementary Fig.…”

Section: Discussionmentioning

confidence: 99%

Chest x-ray imaging score is associated with severity of COVID-19 pneumonia: the MBrixia score

Jensen

Costa

Nørgaard

et al. 2022

Sci Rep

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Spatial resolution in existing chest x-ray (CXR)-based scoring systems for coronavirus disease 2019 (COVID-19) pneumonia is low, and should be increased for better representation of anatomy, and severity of lung involvement. An existing CXR-based system, the Brixia score, was modified to increase the spatial resolution, creating the MBrixia score. The MBrixia score is the sum, of a rule-based quantification of CXR severity on a scale of 0 to 3 in 12 anatomical zones in the lungs. The MBrixia score was applied to CXR images from COVID-19 patients at a single tertiary hospital in the period May 4th–June 5th, 2020. The relationship between MBrixia score, and level of respiratory support at the time of performed CXR imaging was investigated. 37 hospitalized COVID-19 patients with 290 CXRs were identified, 22 (59.5%) were admitted to the intensive care unit and 10 (27%) died during follow-up. In a Poisson regression using all 290 MBrixia scored CXRs, a higher MBrixia score was associated with a higher level of respiratory support at the time of performed CXR. The MBrixia score could potentially be valuable as a quantitative surrogate measurement of COVID-19 pneumonia severity, and future studies should investigate the score’s validity and capabilities of predicting clinical outcomes.

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Section: Discussionmentioning

confidence: 99%

Chest x-ray imaging score is associated with severity of COVID-19 pneumonia: the MBrixia score

Jensen

Costa

Nørgaard

et al. 2022

Sci Rep

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“…Increased bronchovascular markings indicate thickening of the bronchial wall due to inflammation that damages the bronchial wall and is relatively uncommon in COVID-19 patients. 16 The findings on air bronchograms in previous studies were diverse. According to a literature review by Lamoro et al (2020), air bronchogram was found with a highly variable frequency in various studies, ranging from 8% to 80% of study subjects.…”

Section: Chest X-ray Characteristicsmentioning

confidence: 99%

The Comparison Of Chest X-Ray Changes Between Post-Covid-19-Infection Patients With Mild-Moderate Severity And Severe-Critical Severity At Ugm Academic Hospital

Nadira Adristi Amaradinka,

Siswanto,

Henda Ageng Rasena

et al. 2023

IJRI

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Introduction: Post-COVID-19 syndrome can be seen from the radiological findings on the chest X-ray (CXR). However, limited studies compared CXR changes in post-COVID-19 patients based on their severity. Methods: Thirty-three post-hospitalized COVID-19 patients who came to the Long COVID Clinic at UGM Academic Hospital were divided into mild-moderate and severe-critical groups. The CXR were taken during hospital admission, in the 4th week, and in the 8th week. CXR images were assessed with the Brixia Score method. Results: The Brixia score in the mild-moderate group (n = 17) and severe-critical (n = 16) group showed a trend of change, which increased in the 4th week and decreased in the 8th week. However, there were no significant changes between the two groups during hospital admission, in the 4th week, and in the 8th week. The Brixia score during hospital admission and in the 8th-week follow-up in the mild-moderate group was significantly lower than that of the severe-critical group. Clinically, the mean Brixia score in the mild-moderate group ranges from mild pneumonia, while the severe-critical group ranges from moderate pneumonia. Conclusion: There is no significant resolution of the CXR until the 8th-week follow-up in post-COVID-19 infection patients with mild-moderate and severe-critical severity. However, the CXR during hospital admission and the 8th week is better in post-COVID-19 infection patients with mild-moderate severity. Keywords: chest X-ray, COVID-19, infectious disease, post-COVID-19 syndrome, severity,

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“…Sometimes the test results may not be available immediately and may cause a false negative result, due to the quality of the sample [ 31 ]. In such situations, various chest imaging modalities such as X-ray, CT, and Ultrasound (US) help to confirm COVID-19 suspects [ 32 ]. The combination of AI techniques with various imaging modalities can assist to increase the efficiency of COVID-19 detection worldwide [ 32 ].…”

Section: Ai Techniques For Covid-19 Detectionmentioning

confidence: 99%

“…In such situations, various chest imaging modalities such as X-ray, CT, and Ultrasound (US) help to confirm COVID-19 suspects [ 32 ]. The combination of AI techniques with various imaging modalities can assist to increase the efficiency of COVID-19 detection worldwide [ 32 ].…”

Section: Ai Techniques For Covid-19 Detectionmentioning

confidence: 99%

Role of Artificial Intelligence in COVID-19 Detection

Gudigar

Raghavendra

Nayak

et al. 2021

Sensors

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The global pandemic of coronavirus disease (COVID-19) has caused millions of deaths and affected the livelihood of many more people. Early and rapid detection of COVID-19 is a challenging task for the medical community, but it is also crucial in stopping the spread of the SARS-CoV-2 virus. Prior substantiation of artificial intelligence (AI) in various fields of science has encouraged researchers to further address this problem. Various medical imaging modalities including X-ray, computed tomography (CT) and ultrasound (US) using AI techniques have greatly helped to curb the COVID-19 outbreak by assisting with early diagnosis. We carried out a systematic review on state-of-the-art AI techniques applied with X-ray, CT, and US images to detect COVID-19. In this paper, we discuss approaches used by various authors and the significance of these research efforts, the potential challenges, and future trends related to the implementation of an AI system for disease detection during the COVID-19 pandemic.

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COVID-19 pneumonia—ultrasound, radiographic, and computed tomography findings: a comprehensive pictorial essay

Cited by 9 publications

References 31 publications

Chest x-ray imaging score is associated with severity of COVID-19 pneumonia: the MBrixia score

Chest x-ray imaging score is associated with severity of COVID-19 pneumonia: the MBrixia score

The Comparison Of Chest X-Ray Changes Between Post-Covid-19-Infection Patients With Mild-Moderate Severity And Severe-Critical Severity At Ugm Academic Hospital

Role of Artificial Intelligence in COVID-19 Detection

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