Cardiovascular magnetic resonance for evaluation of cardiac involvement in COVID-19: recommendations by the Society for Cardiovascular Magnetic Resonance.
Vanessa M FerreiraSven PleinTimothy C WongQian TaoZahra Raisi-EstabraghSupriya S JainYuchi HanVineeta OjhaDavid A BluemkeKate HannemanJonathan WeinsaftMahesh K VidulaNtobeko A B NtusiJeanette Schulz-MengerJiwon KimPublished in: Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance (2023)
Coronavirus disease 2019 (COVID-19) is an ongoing global pandemic that has affected nearly 600 million people to date across the world. While COVID-19 is primarily a respiratory illness, cardiac injury is also known to occur. Cardiovascular magnetic resonance (CMR) imaging is uniquely capable of characterizing myocardial tissue properties in-vivo, enabling insights into the pattern and degree of cardiac injury. The reported prevalence of myocardial involvement identified by CMR in the context of COVID-19 infection among previously hospitalized patients ranges from 26 to 60%. Variations in the reported prevalence of myocardial involvement may result from differing patient populations (e.g. differences in severity of illness) and the varying intervals between acute infection and CMR evaluation. Standardized methodologies in image acquisition, analysis, interpretation, and reporting of CMR abnormalities across would likely improve concordance between studies. This consensus document by the Society for Cardiovascular Magnetic Resonance (SCMR) provides recommendations on CMR imaging and reporting metrics towards the goal of improved standardization and uniform data acquisition and analytic approaches when performing CMR in patients with COVID-19 infection.
Keyphrases
- coronavirus disease
- magnetic resonance
- left ventricular
- sars cov
- respiratory syndrome coronavirus
- contrast enhanced
- high resolution
- clinical practice
- risk factors
- adverse drug
- liver failure
- case report
- heart failure
- machine learning
- emergency department
- mass spectrometry
- electronic health record
- big data
- atrial fibrillation
- artificial intelligence
- fluorescence imaging