Magnetic resonance perfusion imaging using compressed sensing

Abstract. Perfusion analysis is an important experimental technique used for diagnostics and evaluation of therapy response. Analysis based on magnetic resonance (MR) helps in identifying the state and dynamic behaviour of oncological and cardiovascular diseases and enables bettertreatment. MR perfusion analysis is done by means of estimating parameters describing tissue properties from the acquired signal. Accurate quantification of the parameters driving complex perfusion models requires low signal to noise ratio and high spatial and temporal resolution. Recent studies show that the quantification methods based on advanced pharmacokinetic models and blind deconvolution have reached their limits. The goal of the project is to utilize knowledge from the field of compressed sensing to develop novel methods of MR acquisition and reconstruction taking into account the specifics of perfusion analysis. This will lead to significant improvements in the accuracy of perfusion parameter estimation, thus contributing to lifting today’s technical barriers and understanding better the nature of diseases.

Goals. The aim of the project is to develop new methods for perfusion imaging based on magnetic resonance and using compressed sensing. The methods enable a more accurate estimation of the perfusion parameters of tissues and they consequently increase the efficiency of diagnosis and treatment of cancer.

Keywords: Perfusion imaging; magnetic resonance; MRI; DCE-MRI; compressed sensing; compressive sampling; deconvolution

• Institute of Scientific Instruments, Czech Academy of Sciences, Brno
  Ing. Radovan Jiřík Ph.D.
  Ing. Lucie Grossová
  Ing. Jiří Kratochvíla
• Institute of Information Theory and Automation (UTIA), Czech Academy of Sciences, Prague
  RNDr. Michal Šorel, Ph.D.
  Ing. Filip Šroubek, Ph.D., DSc.
  Ing. Michal Bartoš, Ph.D.
• Faculty of Electrical Engineering and Communication, Brno University of Technology, Brno
  Doc. Mgr. Pavel Rajmic, Ph.D.
  Ing. Marie Daňková
  Ing. Michaela Novosadová

Funding