Accuracy of Chest CT for Differentiating COVID-19 from COVID-19 Mimics

Sähn, Marwin-Jonathan; Yüksel, Can; Keil, Sebastian; Zeisberger, Marcel P.; Post, Manuel; Kleines, Michael; Brokmann, Jörg Christian; Hübel, Christian; Kuhl, Christiane K.; Isfort, Peter; Schulze-Hagen, Maximilian

doi:10.1055/a-1388-7950

Cited by 5 publications

(5 citation statements)

References 29 publications

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“…Although there are studies that may suggest otherwise [8], it is generally expected that accurate diagnosis rates will improve with increased professional experience. However, professional experience alone is not enough for the radiological evaluation to be accurate.…”

Section: Discussionmentioning

confidence: 99%

“…Notably, during the evaluation, junior residents showed a tendency to diagnose COVID-19, a condition they frequently encountered in daily practice. Another study conducted among radiology physicians (specialists and residents) in the early period of COVID-19 showed that radiologists, even without knowing the patient's clinic, were able to distinguish the diagnosis of COVID-19 with thoracic CT from other viral agents, independent of their professional experience [8]. As professional experience increases, so does self-confidence in decisions [5].…”

Section: Discussionmentioning

confidence: 99%

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Toraks bilgisayarlı tomografisinin yorumlanmasında acil tıp asistanlarının başarısı ve tanı koymadaki özgüvenleri

OSKAY

2023

Pam Tıp Derg

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Purpose: Interpration of thoracic computed tomography (CT) scans by emergency department (ED) physicians is important especially in crowded EDs. The aim of this study is to assess the proficiency and confidence of ED physicians with varying levels of experience in interpreting thoracic CT. Materials and methods: A total of 25 pathological and 5 normal thoracic CT images were interpreted by 32 ED residents, initially without clinical information, then with. After each session the participants were asked to score their confidence on a scale of 1 to 10. At the end of the study, the results were compared between seniors and junior residents. Results: The median age of the participants was 29 years (24–34). Twenty (62.5%) of the residents were junior residents. There were no significant differences between the two resident groups in terms of accurate diagnosis rates, regardless of the clinical information (p=0.307 and p=0.061). The physicians’ certainty of their own diagnosis mostly does not seem to be statistically different in these diagnoses. The seniors are more confident in the diagnosis of the CT scans they evaluated without clinical information (p=0.004), while when the clinical information is added, the confidence of the junior physicians also increase (p=0.087). Conclusion: Both senior and junior emergency medical residents are able to interpret thoracic CT images with a high degree of accuracy, both for COVID-19 and for other emergency diagnoses. Senior physicians could confidently diagnose CT images solely by visual inspection, whereas junior residents display similar confidence when clinical information is available.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Toraks bilgisayarlı tomografisinin yorumlanmasında acil tıp asistanlarının başarısı ve tanı koymadaki özgüvenleri

OSKAY

2023

Pam Tıp Derg

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“…Datenitems aus dieser initialen Datenerhebung im Netzwerk bereit. Hierzu wurden internationale und nationale Standards wie CO-RADS [ 14 ], COV-RADS [ 15 ], die Empfehlung der Arbeitsgruppe Thorax der Deutschen Röntgengesellschaft [ 16 ] und weitere aufgegriffen sowie auch neue radiologische Befundungsstandards abgestimmt. RACOON erlaubt hochqualitative strukturierte Auswertungen multimodaler Datensätze im multizentrischen Setting.…”

Section: Die Fünf Komponenten Der Num-forschungsdateninfrastrukturunclassified

Das Netzwerk Universitätsmedizin: Technisch-organisatorische Ansätze für Forschungsdatenplattformen

Heyder

2023

Bundesgesundheitsbl

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ZusammenfassungDas Netzwerk Universitätsmedizin (NUM) besteht aus den 36 Standorten der Universitätsmedizin in Deutschland. Der Auftrag ist die Koordinierung der universitätsmedizinischen COVID-19-Forschung auf nationaler Ebene. Dazu werden u. a. gemeinsame Infrastrukturen für die Sammlung, Haltung und Nutzung medizinischer Forschungsdaten benötigt. Diese standen beim Start des NUM-Projekts im April 2020 nicht im erforderlichen Rahmen zur Verfügung. Medizinische Forschungsdaten sind extrem heterogen und gehen weit über „Real World Data“ (Daten aus dem Versorgungsalltag) hinaus. Eine universelle Lösung dafür gab es nicht, deshalb hat das NUM fünf Forschungsinfrastrukturen für unterschiedliche Datenarten, unterschiedliche Wege der Datengewinnung und unterschiedliche Datenentstehungssettings aufgebaut. Um die Bildung neuer Datensilos zu verhindern, arbeiten alle fünf Infrastrukturen auf Basis der FAIR-Prinzipien, nach denen Daten auffindbar (findable), zugänglich (accessible), interoperabel (interoperable) und wiederverwendbar (reusable) sein sollen. Zudem implementiert das NUM einen übergreifenden Steuerungsrahmen (Governance Framework), um die Weiterentwicklung dieser fünf Infrastrukturen zentral zu steuern. Der Artikel beschreibt den aktuellen Stand der Infrastrukturentwicklung im NUM und mögliche Perspektiven. Ein starker Fokus wird dabei auf die technisch-organisatorischen Grundlagen gerichtet.

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“…1. Until now, these findings have been considered well understood and present in the vast majority of patients with confirmed SARS-CoV-2 pneumonia [6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Possible Alterations of Imaging Patterns in Computed Tomography for Delta-VOC of SARS-CoV-2

Yüksel

Sähn

Kleines

et al. 2022

Rofo

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Background So far, typical findings for COVID-19 in computed tomography (CT) have been described as bilateral, multifocal ground glass opacities (GGOs) and consolidations, as well as intralobular and interlobular septal thickening. On the contrary, round consolidations with the halo sign are considered uncommon and are typically found in fungal infections, such as invasive pulmonary aspergillosis. The authors recently observed several patients with COVID-19 pneumonia presenting with round, multifocal consolidations accompanied by a halo sign. As this may indicate alterations of CT morphology based on the virus variant, the aim of this study was to investigate this matter in more detail. Methods 161 CT scans of patients with confirmed SARS-CoV-2 infection (RT-PCR within 2 days of CT) examined between January 2021 and September 15, 2021 were included. Follow-up examinations, patients with invasive ventilation at the time of CT, and patients with insufficient virus typing for variants of concern (VOC) were excluded. CT scans were assessed for vertical and axial distribution of pulmonary patterns, degree of involvement, uni- vs. bilaterality, reticulations, and other common findings. The mean density of representative lesions was assessed in Hounsfield units. Results were compared using Mann-Whitney U-tests, Studentʼs t-rests, descriptive statistics, and Fisher’s exact tests. Results 75 patients did not meet the inclusion criteria. Therefore, 86/161 CT scans of unique patients were analyzed. PCR VOC testing confirmed manifestation of the Delta-VOC SARS-CoV-2 in 22 patients, 39 patients with Alpha-VOC and the remaining 25 patients with Non-VOC SARS-CoV-2 infections. Three patients with the Delta-VOC demonstrated multiple pulmonary masses or nodules with surrounding halo sign, whereas no patients with either Alpha-VOC (p = 0.043) or non-VOC (p = 0.095) demonstrated these findings. All three patients were admitted to normal wards and had no suspicion of a pulmonary co-infection. Patients with Delta-VOC were less likely to have ground glass opacities compared to Alpha-VOC (7/22 or 31.8 % vs. 4/39 or 10.3 %; p < 0.001), whereas a significant difference has not been observed between Delta-VOC and non-VOC (5/25 or 20 %; p = 0.348). The mean representative density of lesions did not show significant differences between the studied cohorts. Conclusion In this study 3 out of 22 patients (13.6 %) with Delta-VOC presented with bilateral round pulmonary masses or nodules with surrounding halo signs, which has not been established as a notable imaging pattern in COVID-19 pneumonia yet. Compared to the other cohorts, a lesser percentage of patients with Delta-VOC presented with ground glass opacities. Based on these results Delta-VOC might cause a divergence in CT-morphologic phenotype. Key Points: Citation Format

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Accuracy of Chest CT for Differentiating COVID-19 from COVID-19 Mimics

Cited by 5 publications

References 29 publications

Toraks bilgisayarlı tomografisinin yorumlanmasında acil tıp asistanlarının başarısı ve tanı koymadaki özgüvenleri

Toraks bilgisayarlı tomografisinin yorumlanmasında acil tıp asistanlarının başarısı ve tanı koymadaki özgüvenleri

Das Netzwerk Universitätsmedizin: Technisch-organisatorische Ansätze für Forschungsdatenplattformen

Possible Alterations of Imaging Patterns in Computed Tomography for Delta-VOC of SARS-CoV-2

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