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Automated Quantitative Stress Perfusion in a Clinical Routine

Kristopher D Knott1, Juliano Lara Fernandes2, James C Moon1

  • 1Barts Heart Centre, The Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases Unit, St Bartholomew's Hospital, West Smithfield, 2nd Floor, King George V Block, London EC1A 7BE, UK.

Magnetic Resonance Imaging Clinics of North America
|July 8, 2019
PubMed

Insights

Cardiovascular magnetic resonance (CMR) perfusion imaging accurately quantifies ischemia in coronary artery disease (CAD). Automated methods enable rapid, pixel-based myocardial blood flow mapping for clinical decisions.

Area of Science:

  • Cardiovascular imaging
  • Medical diagnostics

Background:

  • Cardiovascular magnetic resonance (CMR) perfusion imaging is a key noninvasive tool for assessing ischemia in patients with coronary artery disease (CAD).
  • While qualitative and semiquantitative CMR methods demonstrate high accuracy for diagnosing flow-obstructing lesions, quantitative assessment of ischemic burden is crucial for treatment decisions.

Purpose of the Study:

  • To highlight the evolution and clinical utility of quantitative CMR perfusion techniques.
  • To emphasize the role of automated methods in improving workflow and generating myocardial blood flow maps.

Main Methods:

  • Quantitative cardiovascular magnetic resonance (CMR) perfusion imaging.
  • Comparison with positron emission tomography (PET) and microsphere evaluation.
  • Development and implementation of automated methods for pixel-based myocardial blood flow mapping.

Main Results:

  • Quantitative CMR perfusion techniques have achieved accuracy comparable to established methods like PET and microsphere evaluation.
  • Automated methods significantly accelerate workflow and facilitate the generation of detailed myocardial blood flow maps.

Conclusions:

  • Quantitative CMR perfusion imaging is a highly accurate method for assessing ischemic burden in CAD.
  • Automated quantitative techniques are enhancing the clinical applicability of CMR perfusion imaging for patient management.

Keywords:
AutomationCardiovascular magnetic resonanceIschemiaMR imagingMyocardial perfusionQuantificationStress

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