Method development for ultra-low-field magnetic resonance imaging and magnetoencephalography

Juhani Dabek

Research output: ThesisDoctoral ThesisCollection of Articles

Abstract

Ultra-low-field (ULF) magnetic resonance imaging (MRI) can be combined with magnetoencephalography (MEG) in a hybrid MEG-MRI device using superconducting quantum interference device (SQUID) sensors for measuring both MRI (structural imaging) and MEG (functional imaging) signals. The MEG-MRI device, which has an open structure, is situated in a magnetically shielded room to suppress magnetic field noise. The ULF-MRI device can be operated with relaxed safety considerations compared to conventional MRI because of the absence of very strong magnetic fields. MEG has grown into an important multichannel neuroimaging modality in the past 20 years with research and clinical applications. Low-field (LF) MRI, with field strength between that of ULF and conventional MRI, cannot accommodate MEG today but may grow in importance with the development of giant-magnetoresistive (GMR) mixed sensors. In this dissertation, methods for MRI and MEG have been developed, with an emphasis on ultra-low- and low-field applications. The necessary physical and signal-processing basis is reviewed, accompanied by new methodological improvements. The safety of low magnetic fields is investigated, modelling of the free induction decay (FID) signal underlying MRI is improved and the developed gradient-excitation-encoding method is tested by simulation. A new quantitative method for ULF-MRI device calibration and determination of, for example, sample water content is developed and validated. GMR mixed sensors are applied in LF MRI, resulting in a high signal-to-noise ratio and contrast-to-noise ratio. Eventually, a new method for power correlations between brainwaves is developed and tested on MEG data. The presented methods aim at improvements in the use of the two imaging modalities.
Translated title of the contributionMenetelmäkehitystä ultramatalien kenttien magneettikuvaukseen ja magnetoenkefalografiaan
Original languageEnglish
QualificationDoctor's degree
Awarding Institution
  • Aalto University
Supervisors/Advisors
  • Ilmoniemi, Risto, Supervising Professor
  • Ilmoniemi, Risto, Thesis Advisor
Publisher
Print ISBNs978-952-60-5629-6
Electronic ISBNs978-952-60-5630-2
Publication statusPublished - 2014
MoE publication typeG5 Doctoral dissertation (article)

Keywords

  • brain imaging
  • magnetic resonance imaging
  • MRI
  • ultra-low-field MRI
  • low-field MRI
  • magnetoencephalography
  • MEG
  • SQUID
  • GMR
  • mixed sensor

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