Journal article
Imaging of COVID-19 pneumonia: Patterns, pathogenesis, and advances
British journal of radiology, Vol.93(1113), pp.20200538-20200538
01/01/2020
DOI: 10.1259/bjr.20200538
PMCID: PMC7465853
PMID: 32758014
Abstract
COVID-19 pneumonia is a newly recognized lung infection. Initially, CT imaging was demonstrated to be one of the most sensitive tests for the detection of infection. Currently, with broader availability of polymerase chain reaction for disease diagnosis, CT is mainly used for the identification of complications and other defined clinical indications in hospitalized patients. Nonetheless, radiologists are interpreting lung imaging in unsuspected patients as well as in suspected patients with imaging obtained to rule out other relevant clinical indications. The knowledge of pathological findings is also crucial for imagers to better interpret various imaging findings. Identification of the imaging findings that are commonly seen with the disease is important to diagnose and suggest confirmatory testing in unsuspected cases. Proper precautionary measures will be important in such unsuspected patients to prevent further spread. In addition to understanding the imaging findings for the diagnosis of the disease, it is important to understand the growing set of tools provided by artificial intelligence. The goal of this review is to highlight common imaging findings using illustrative examples, describe the evolution of disease over time, discuss differences in imaging appearance of adult and pediatric patients and review the available literature on quantitative CT for COVID-19. We briefly address the known pathological findings of the COVID-19 lung disease that may help better understand the imaging appearance, and we provide a demonstration of novel display methodologies and artificial intelligence applications serving to support clinical observations.
Details
- Title: Subtitle
- Imaging of COVID-19 pneumonia: Patterns, pathogenesis, and advances
- Creators
- Prashant Nagpal - Roy J. and Lucille A. Carver College of MedicineSabarish Narayanasamy - Roy J. and Lucille A. Carver College of MedicineAditi Vidholia - Roy J. and Lucille A. Carver College of MedicineJunfeng Guo - University of IowaKyung Min Shin - Kyungpook National UniversityChang Hyun Lee - Seoul National University HospitalEric A. Hoffman - University of Iowa
- Resource Type
- Journal article
- Publication Details
- British journal of radiology, Vol.93(1113), pp.20200538-20200538
- DOI
- 10.1259/bjr.20200538
- PMID
- 32758014
- PMCID
- PMC7465853
- NLM abbreviation
- Br J Radiol
- ISSN
- 0007-1285
- eISSN
- 1748-880X
- Publisher
- British Inst Radiology
- Number of pages
- 12
- Grant note
- R01-HL-130883 / NIH; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA
- Language
- English
- Date published
- 01/01/2020
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Radiology; Internal Medicine
- Record Identifier
- 9984318706602771
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