Coronavirus disease 2019 (COVID-19) imaging reporting and data system (COVID-RADS) and common lexicon: a proposal based on the imaging data of 37 studies
Autor: | Sana Salehi, Aidin Abedi, Sudheer Balakrishnan, Ali Gholamrezanezhad |
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Jazyk: | angličtina |
Rok vydání: | 2020 |
Předmět: |
medicine.medical_specialty
Coronavirus disease 2019 (COVID-19) Pneumonia Viral Physical examination Lexicon 030218 nuclear medicine & medical imaging Terminology 03 medical and health sciences Betacoronavirus 0302 clinical medicine Documentation medicine Data Systems Humans Radiology Nuclear Medicine and imaging Medical physics Pandemics Physical Examination Neuroradiology Modality (human–computer interaction) medicine.diagnostic_test business.industry SARS-CoV-2 COVID-19 Interventional radiology General Medicine Radiology Nuclear Medicine and imaging 030220 oncology & carcinogenesis Radiology business Coronavirus Infections Tomography X-Ray Computed |
Zdroj: | European Radiology |
ISSN: | 1432-1084 0938-7994 |
DOI: | 10.1007/s00330-020-06863-0 |
Popis: | In the vast majority of the laboratory-confirmed coronavirus disease 2019 (COVID-19) patients, computed tomography (CT) examinations yield a typical pattern and the sensitivity of this modality has been reported to be 97% in a large-scale study. Structured reporting systems simplify the interpretation and reporting of imaging examinations, serve as a framework for consistent generation of recommendations, and improve the quality of patient care. To compose a comprehensive lexicon for description of the imaging findings and propose a grading system and structured reporting format for CT findings in COVID-19. We updated our published systematic review on imaging findings in COVID-19 to include 37 published studies pertaining to diagnostic features of COVID-19 in chest CT. Using the reported imaging findings of 3647 patients, we summarized the typical chest CT findings, atypical features, and temporal changes of COVID-19 in chest CT. Subsequently, we extracted a list of descriptive terms and mapped it to the terminology that is commonly used in imaging literature. We composed a comprehensive lexicon that can be used for documentation and reporting of typical and atypical CT imaging findings in COVID-19 patients. Using the same data, we propose a grading system with five COVID-RADS categories. Each COVID-RADS grade corresponds to a low, moderate, or high level of suspicion for pulmonary involvement of COVID-19. The proposed COVID-RADS and common lexicon would improve the communication of findings to other healthcare providers, thus facilitating the diagnosis and management of COVID-19 patients. • Chest CT has high sensitivity in diagnosing the coronavirus disease 2019 (COVID-19). • Structured reporting systems simplify the interpretation and reporting of imaging examinations, serve as a framework for consistent generation of recommendations, and improve the quality of patient care. • The proposed COVID-RADS and common lexicon would improve the communication of findings to other healthcare providers, thus facilitating the diagnosis and management of COVID-19 patients. |
Databáze: | OpenAIRE |
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