Journal article
QIBA guidance: Computed tomography imaging for COVID-19 quantitative imaging applications
Clinical imaging, Vol.77, pp.151-157
09/2021
DOI: 10.1016/j.clinimag.2021.02.017
PMCID: PMC7906537
PMID: 33684789
Abstract
As the COVID-19 pandemic impacts global populations, computed tomography (CT) lung imaging is being used in many countries to help manage patient care as well as to rapidly identify potentially useful quantitative COVID-19 CT imaging biomarkers. Quantitative COVID-19 CT imaging applications, typically based on computer vision modeling and artificial intelligence algorithms, include the potential for better methods to assess COVID-19 extent and severity, assist with differential diagnosis of COVID-19 versus other respiratory conditions, and predict disease trajectory. To help accelerate the development of robust quantitative imaging algorithms and tools, it is critical that CT imaging is obtained following best practices of the quantitative lung CT imaging community. Toward this end, the Radiological Society of North America's (RSNA) Quantitative Imaging Biomarkers Alliance (QIBA) CT Lung Density Profile Committee and CT Small Lung Nodule Profile Committee developed a set of best practices to guide clinical sites using quantitative imaging solutions and to accelerate the international development of quantitative CT algorithms for COVID-19. This guidance document provides quantitative CT lung imaging recommendations for COVID-19 CT imaging, including recommended CT image acquisition settings for contemporary CT scanners. Additional best practice guidance is provided on scientific publication reporting of quantitative CT imaging methods and the importance of contributing COVID-19 CT imaging datasets to open science research databases.
•Collecting CT data for quantitative COVID-19 research requires careful control of image acquisition settings.•Elevated pitch scans will improve imaging of patients with respiratory conditions.•It is important to keep respiratory level and CT image acquisition settings consistent over time.•Publication methods sections need to support image acquisition reproducibility.•Open COVID-19 CT imaging databases will accelerate the development of improved quantitative biomarkers.
Details
- Title: Subtitle
- QIBA guidance: Computed tomography imaging for COVID-19 quantitative imaging applications
- Creators
- Ricardo S AvilaSean B Fain - University of Wisconsin–MadisonChuck Hatt - University of Michigan–Ann ArborSamuel G Armato - University of ChicagoJames L Mulshine - Rush UniversityDavid Gierada - Washington University, United States of AmericaMario Silva - University of ParmaDavid A Lynch - National Jewish HealthEric A Hoffman - University of IowaFrank N Ranallo - University of Wisconsin SystemJohn R Mayo - University of British ColumbiaDavid Yankelevitz - Mount Sinai Health SystemRaul San Jose Estepar - Brigham and Women's HospitalRaja Subramaniam - Mount Sinai Health SystemClaudia I Henschke - Mount Sinai Health SystemAlex Guimaraes - Oregon Health & Science UniversityDaniel C Sullivan - Duke University
- Resource Type
- Journal article
- Publication Details
- Clinical imaging, Vol.77, pp.151-157
- Publisher
- Elsevier Inc
- DOI
- 10.1016/j.clinimag.2021.02.017
- PMID
- 33684789
- PMCID
- PMC7906537
- ISSN
- 0899-7071
- eISSN
- 1873-4499
- Language
- English
- Date published
- 09/2021
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Radiology; Electrical and Computer Engineering; Health and Human Physiology; Internal Medicine
- Record Identifier
- 9984274957102771
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