Study of Thoracic CT in COVID-19: The STOIC Project

Revel, Marie-Pierre; Boussouar, Samia; Margerie-Mellon, Constance de; Saab, Inès; Lapotre, Thibaut; Mompoint, D.; Chassagnon, Guillaume; Milon, Audrey; Léderlin, Mathieu; Bennani, Souhail; Molière, Sébastien; Debray, Marie‐Pierre; Bompard, Florian; Dangeard, Séverine; Hani, Chahinez; Ohana, Mickaël; Bommart, Sébastien; Jalaber, Carole; Hajjam, Mostafa El; Petit, Isabelle; Fournier, Laure; Khalil, Antoine; Brillet, Pierre-Yves; Bellin, Marie‐France; Redheuil, Alban; Rocher, Laurence; Bousson, V.; Rousset, Pascal; Grégory, Jules; Deux, Jean‐François; Dion, Élisabeth; Valeyre, Dominique; Porcher, Raphaël; Jilet, Léa; Abdoul, Hendy

doi:10.1148/radiol.2021210384

Cited by 40 publications

(14 citation statements)

References 30 publications

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“…The accuracy of a COVID-19 diagnosis was 81% independent of the radiologist's experience. Similar findings regarding the absence of the impact of experience on a COVID-19 diagnosis have also been demonstrated by Revel et al ( 32 ).…”

Section: Discussionsupporting

confidence: 87%

Image quality assessment in low-dose COVID-19 chest CT examinations

et al. 2023

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Background Low-dose thoracic protocols were developed massively during the COVID-19 outbreak. Purpose To study the impact on image quality (IQ) and the diagnosis reliability of COVID-19 low-dose chest computed tomography (CT) protocols. Material and Methods COVID-19 low-dose protocols were implemented on third- and second-generation CT scanners considering two body mass index (BMI) subgroups (<25 kg/m2 and >25 kg/m2). Contrast-to-noise ratios (CNR) were compared with a Catphan phantom. Next, two radiologists retrospectively assessed IQ for 243 CT patients using a 5-point Linkert scale for general IQ and diagnostic criteria. Kappa score and Wilcoxon rank sum tests were used to compare IQ score and CTDIvol between radiologists, protocols, and scanner models. Results In vitro analysis of Catphan inserts showed in majority significantly decreased CNR for the low dose versus standard acquisition protocols on both CT scanners. However, in vivo, there was no impact on the diagnosis: sensitivity and specificity were ≥0.8 for all protocols and CT scanners. The third-generation scanner involved a significantly lower dose compared to the second-generation scanner (CTDIvol of 1.8 vs. 2.6 mGy for BMI <25 kg/m2 and 3.3 vs. 4.6 mGy for BMI >25 kg/m2). Still, the third-generation scanner showed a significantly higher IQ with the low-dose protocol compared to the second-generation scanner (30.9 vs. 28.1 for BMI <25 kg/m2 and 29.9 vs. 27.8 for BMI >25 kg/m2). Finally, the two radiologists had good global inter-reader agreement (kappa ≥0.6) for general IQ. Conclusion Low-dose protocols provided sufficient IQ independently of BMI subgroups and CT models without any impact on diagnosis reliability.

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Section: Discussionsupporting

confidence: 87%

Image quality assessment in low-dose COVID-19 chest CT examinations

et al. 2023

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“…1 b), we additionally obtained non-contrast chest CTs from 805 patients with COVID-19 infections admitted to Renmin Hospital of Wuhan University, Hubei General Hospital (D1). Another cohort used for the study was the STOIC2021-COVID-19 AI Challenge dataset (D2), 23 containing non-contrast chest CTs from 1917 patients suspected of being infected with COVID-19 during the first wave of the pandemic in France. The third cohort used for the study was the Stony Brook University COVID-19 Positive Cases dataset (D3), 24 which contains non-contrast chest CTs from 169 patients who tested positive for COVID-19.…”

Section: Methodsmentioning

confidence: 99%

Deep-learning-based hepatic fat assessment (DeHFt) on non-contrast chest CT and its association with disease severity in COVID-19 infections: A multi-site retrospective study

et al. 2022

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“…During the early period of the outbreak, the reported sensitivity of chest CT was 97% based on positive NAAT ( 49 ) and 98% of patients had evidence of abnormal CT compatible with viral pneumonia at baseline, while the sensitivity of NAAT was 71% ( 50 ). In another study ( 51 ), when using predefined criteria (positive or negative for COVID-19), CT interpretation performance was not influenced by reader experience and enabled a correct diagnosis of COVID-19 pneumonia with an overall accuracy of 80%.…”

Section: Imaging Of Covid-19 Pneumoniamentioning

confidence: 96%

Current and Emerging Knowledge in COVID-19

Jeong

Park

et al. 2023

Radiology

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COVID-19 has emerged as a pandemic leading to a global public health crisis of unprecedented morbidity. A comprehensive insight into the imaging of COVID-19 has enabled early diagnosis, stratification of disease severity, and identification of potential sequelae. The evolution of COVID-19 can be divided into early infectious, pulmonary, and hyperinflammatory phases. Clinical features, imaging features, and management are different among the three phases. In the early stage, peripheral ground-glass opacities are predominant CT findings, and therapy directly targeting SARS-CoV-2 is effective. In the later stage, organizing pneumonia or diffuse alveolar damage pattern are predominant CT findings and anti-inflammatory therapies are more beneficial. The risk of severe disease or hospitalization is lower in breakthrough or Omicron variant infection compared with nonimmunized or Delta variant infections. The protection rates of the fourth dose of mRNA vaccination were 34% and 67% against overall infection and hospitalizations for severe illness, respectively. After acute COVID-19 pneumonia, most residual CT abnormalities gradually decreased in extent, but they may remain as linear or multifocal reticular or cystic lesions. Advanced insights into the pathophysiologic and imaging features of COVID-19 along with vaccine benefits have improved patient care, but emerging knowledge of post–COVID-19 condition, or long COVID, also presents radiology with new challenges. © RSNA, 2023 Supplemental material is available for this article.

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Study of Thoracic CT in COVID-19: The STOIC Project

Abstract: provided the 3D image viewer web application and Orange Healthcare data storage resources.

Cited by 40 publications

References 30 publications

Image quality assessment in low-dose COVID-19 chest CT examinations

Image quality assessment in low-dose COVID-19 chest CT examinations

Deep-learning-based hepatic fat assessment (DeHFt) on non-contrast chest CT and its association with disease severity in COVID-19 infections: A multi-site retrospective study

Current and Emerging Knowledge in COVID-19

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