Magnetic resonance multitasking for motion-resolved quantitative cardiovascular imaging

Quantitative cardiovascular magnetic resonance (CMR) imaging can be used to characterize fibrosis, oedema, ischaemia, inflammation and other disease conditions. However, the need to reduce artefacts arising from body motion through a combination of electrocardiography (ECG) control, respiration control and contrast-weighting selection makes CMR exams lengthy. Here, we show that physiological motions and other dynamic processes can be conceptualized as multiple time dimensions that can be resolved via low-rank tensor imaging, allowing for motion-resolved quantitative imaging with up to four time dimensions. This continuous-acquisition approach, which we name CMR multitasking, captures—rather than avoids—motion, relaxation and other dynamics to efficiently perform quantitative CMR without the use of ECG triggering or breath holds. We demonstrate that CMR multitasking allows for T1 mapping, T1/T2 mapping and time-resolved T1 mapping of myocardial perfusion without ECG information and/or under free-breathing conditions. CMR multitasking may provide a foundation for the development of setup-free CMR imaging for the quantitative evaluation of cardiovascular health. A continuous-acquisition method for reducing artefacts caused by the beating heart and other body motions in cardiovascular magnetic resonance imaging reduces the reliance on electrocardiography triggering and breath holds.

• Publication year

  2018

• Venue

  Nature Biomedical Engineering

• Publication date

  2018-03-09

• Fields of study

  Medicine, Computer Science, Engineering

• Identifiers
  DOI 10.1038/s41551-018-0217-yPMID 30237910PMCID 6141200
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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