Diagnostic Performance of Chest CT for SARS-CoV-2 Infection in                     Individuals with or without COVID-19 Symptoms

Smet, Kristof De; Smet, Dieter De; Ryckaert, Thomas; Laridon, E; Heremans, Birgit; Vandenbulcke, Ruben; Demedts, Ingel K.; Bouckaert, Bernard; Gryspeerdt, Stefaan; Martens, Guy

doi:10.1148/radiol.2020202708

Cited by 94 publications

(112 citation statements)

References 19 publications

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“…Risk of bias with respect to reference test was rated high in three studies ( 23 , 26 , 27 ) because repeated RT-PCR testing was not used in all patients with a negative initial RT-PCR result and persistent clinical suspicion of COVID-19. Risk of bias with respect to reference test was rated unclear in one study ( 21 ), because it was not clear whether all patients with an initial negative RT-PCR result and a persistent clinical suspicion of COVID-19 underwent repeated RT-PCR testing. In one study ( 20 ), there was potential risk of bias with regard to flow and timing, because the time interval between CT and RT-PCR testing was not reported.…”

Section: Resultsmentioning

confidence: 99%

Diagnostic Performance of CO-RADS and the RSNA Classification System in Evaluating COVID-19 at Chest CT: A Meta-Analysis

Kwee

Adams

Kwee

2021

Radiology: Cardiothoracic Imaging

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Section: Resultsmentioning

confidence: 99%

Diagnostic Performance of CO-RADS and the RSNA Classification System in Evaluating COVID-19 at Chest CT: A Meta-Analysis

Kwee

Adams

Kwee

2021

Radiology: Cardiothoracic Imaging

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“… 15 In addition, two recently published studies investigating the diagnostic accuracy of CO-RADS in RT-PCR confirmed cohorts confirmed its good performance in symptomatic individuals, thereby further supporting its application for triage. 23,24 Moreover, the readers were not blinded to the presence of clinical diagnosis of COVID-19 in the included patients, which may have artificially increased the interobserver agreement of the two systems due to the introduced bias. This, however, is also representative of a real-life clinical scenario during an epidemiologically severe situation where high pretest prevalence of COVID-19 is estimated and supporting clinical information is almost always available to the reporting clinicians, which was the case in a recent study evaluating the agreement of the RSNA COVID-19 chest CT classification scheme.…”

Section: Discussionmentioning

confidence: 99%

A head-to-head comparison of the intra- and interobserver agreement of COVID-RADS and CO-RADS grading systems in a population with high estimated prevalence of COVID-19

et al. 2020

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Objective: To evaluate the inter- and intraobserver agreement of COVID-RADS and CO-RADS reporting systems among differently experienced radiologists in a population with high estimated prevalence of COVID-19. Methods and materials: Chest CT scans of patients with clinically-epidemiologically diagnosed COVID-19 were retrieved from an open-source MosMedData dataset, randomised, and independently assigned COVID-RADS and CO-RADS grades by an abdominal radiology fellow, thoracic imaging fellow and a consultant cardiothoracic radiologist. The inter- and intraobserver agreement of the two systems were assessed using the Fleiss’ and Cohen’s κ coefficients, respectively. Results: A total of 200 studies were included in the analysis. Both systems demonstrated moderate interobserver agreement, with κ values of 0.51 (95% CI: 0.46–0.56) and 0.55 (95% CI: 0.50–0.59) for COVID-RADS and CO-RADS, respectively. When COVID-RADS and CO-RADS grades were dichotomised at cut-off values of 2B and four to evaluate the agreement between grades representing different levels of clinical suspicion for COVID-19, the interobserver agreement became substantial with κ values of 0.74 (95% CI: 0.66–0.82) for COVID-RADS and 0.73 (95% CI: 0.65–0.81) for CO-RADS. The median intraobserver agreement was considerably higher for CO-RADS reaching 0.81 (95% CI: 0.43–0.76) compared with 0.60 (95% CI: 0.43–0.76) of COVID-RADS. Conclusions: COVID-RADS and CO-RADS showed comparable interobserver agreement, which was moderate when grades were compared head-to-head and substantial when grades were dichotomised to better reflect the underlying levels of suspicion for COVID-19. The median intraobserver agreement of CO-RADS was, however, considerably higher compared with COVID-RADS. Advances in knowledge: This paper provides a comprehensive review of the newlyintroduced COVID-19 chest CT reporting systems, which will help radiologists of allsub-specialties and experience levels make an informed decision on which system touse in their own practice.

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“…Another novel application of 3D printing technique is to assist management with the recent coronavirus disease 2019 (COVID-19) pandemic which results in a shortage of medical supplies, in particular, the personal protective equipment (PPE) [ 85 , 86 , 87 , 88 ], given the primary presentation of respiratory symptoms by COVID-19 [ 89 , 90 , 91 , 92 , 93 ], although it is also associated with cardiovascular disease [ 94 , 95 , 96 , 97 ]. 3D printing is playing an important role in providing medical devices including PPE when we are still fighting against the COVID-19 as shown in some reports documenting an overview of 3D printing applications and challenges in the COVID-19 [ 87 , 98 ].…”

Section: Clinical Applications Of 3d Printing In Cardiovascular DImentioning

confidence: 99%

Clinical Applications of Patient-Specific 3D Printed Models in Cardiovascular Disease: Current Status and Future Directions

Sun

2020

Biomolecules

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Three-dimensional (3D) printing has been increasingly used in medicine with applications in many different fields ranging from orthopaedics and tumours to cardiovascular disease. Realistic 3D models can be printed with different materials to replicate anatomical structures and pathologies with high accuracy. 3D printed models generated from medical imaging data acquired with computed tomography, magnetic resonance imaging or ultrasound augment the understanding of complex anatomy and pathology, assist preoperative planning and simulate surgical or interventional procedures to achieve precision medicine for improvement of treatment outcomes, train young or junior doctors to gain their confidence in patient management and provide medical education to medical students or healthcare professionals as an effective training tool. This article provides an overview of patient-specific 3D printed models with a focus on the applications in cardiovascular disease including: 3D printed models in congenital heart disease, coronary artery disease, pulmonary embolism, aortic aneurysm and aortic dissection, and aortic valvular disease. Clinical value of the patient-specific 3D printed models in these areas is presented based on the current literature, while limitations and future research in 3D printing including bioprinting of cardiovascular disease are highlighted.

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Diagnostic Performance of Chest CT for SARS-CoV-2 Infection in Individuals with or without COVID-19 Symptoms

Cited by 94 publications

References 19 publications

Diagnostic Performance of CO-RADS and the RSNA Classification System in Evaluating COVID-19 at Chest CT: A Meta-Analysis

Diagnostic Performance of CO-RADS and the RSNA Classification System in Evaluating COVID-19 at Chest CT: A Meta-Analysis

A head-to-head comparison of the intra- and interobserver agreement of COVID-RADS and CO-RADS grading systems in a population with high estimated prevalence of COVID-19

Clinical Applications of Patient-Specific 3D Printed Models in Cardiovascular Disease: Current Status and Future Directions

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