Hyperpolarized C urea myocardial first- pass perfusion imaging using velocity- selective excitation

نویسندگان

  • Maximilian Fuetterer
  • Julia Busch
  • Sophie M. Peereboom
  • Constantin von Deuster
  • Lukas Wissmann
  • Miriam Lipiski
  • Thea Fleischmann
  • Nikola Cesarovic
  • Christian T. Stoeck
  • Sebastian Kozerke
چکیده

Background: A velocity-selective binomial excitation scheme for myocardial first-pass perfusion measurements with hyperpolarized C substrates, which preserves bolus magnetization inside the blood pool, is presented. The proposed method is evaluated against gadolinium-enhanced H measurements in-vivo. Methods: The proposed excitation with an echo-planar imaging readout was implemented on a clinical CMR system. Dynamic myocardial stress perfusion images were acquired in six healthy pigs after bolus injection of hyperpolarized C urea with the velocity-selective vs. conventional excitation, as well as standard H gadoliniumenhanced images. Signal-to-noise, contrast-to-noise (CNR) and homogeneity of semi-quantitative perfusion measures were compared between methods based on first-pass signal-intensity time curves extracted from a midventricular slice. Diagnostic feasibility is demonstrated in a case of septal infarction. Results: Velocity-selective excitation provides over three-fold reduction in blood pool signal with a two-fold increase in myocardial CNR. Extracted first-pass perfusion curves reveal a significantly reduced variability of semiquantitative first-pass perfusion measures (12–20%) for velocity-selective excitation compared to conventional excitation (28–93%), comparable to that of reference H gadolinium data (9–15%). Overall image quality appears comparable between the velocity-selective hyperpolarized and gadolinium-enhanced imaging. Conclusion: The feasibility of hyperpolarized C first-pass perfusion CMR has been demonstrated in swine. Comparison with reference H gadolinium data revealed sufficient data quality and indicates the potential of hyperpolarized perfusion imaging for human applications.

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تاریخ انتشار 2017