4D flow cardiovascular magnetic resonance consensus statement

Petter Dyverfeldt1,2, Malenka Bissell3, Alex J Barker4

  • 1Division of Cardiovascular Medicine, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden. petter.dyverfeldt@liu.se.

Insights

Four-dimensional (4D) flow cardiovascular magnetic resonance (CMR) provides comprehensive access to complex heart and great vessel blood flow. This advanced imaging technique offers clinical advantages but requires further validation for specific flow parameters.

Area of Science:

  • Cardiovascular imaging
  • Biomedical engineering
  • Medical physics

Background:

  • Cardiovascular blood flow is complex, being time-varying and multidirectional.
  • Previous methods limited comprehensive analysis of these flows.
  • Four-dimensional (4D) flow cardiovascular magnetic resonance (CMR) has emerged as a powerful tool for detailed cardiovascular flow assessment.

Purpose of the Study:

  • To provide a consensus understanding of 4D Flow CMR acquisition and analysis methods.
  • To highlight potential clinical applications for the heart and great vessels.
  • To identify areas for future research and development in 4D Flow CMR.

Main Methods:

  • Consensus paper developed by physicists, physicians, and biomedical engineers active in 4D Flow CMR.
  • Review of acquisition parameters, spatial and temporal resolution, and acquisition times.
  • Discussion of retrospective flow calculation from a single acquisition volume.

Main Results:

  • 4D Flow CMR enables comprehensive, accurate, retrospective calculation of flow in any plane.
  • Clinical advantages include straightforward single acquisition volume placement.
  • Derived parameters like wall shear stress and turbulent kinetic energy require further validation for clinical use.

Conclusions:

  • 4D Flow CMR offers significant clinical advantages for assessing cardiovascular dynamics.
  • Further research is needed to validate advanced flow parameters for routine clinical adoption.
  • Standardized implementation and data handling are crucial for multicenter studies and widespread use.