The doctoral dissertations of the former Helsinki University of Technology (TKK) and Aalto University Schools of Technology (CHEM, ELEC, ENG, SCI) published in electronic format are available in the electronic publications archive of Aalto University - Aaltodoc.
Aalto

Studying Functional Magnetic Resonance Imaging with Artificial Imaging Objects

Ville Renvall

Doctoral dissertation for the degree of Doctor of Science in Technology to be presented with due permission of the Faculty of Information and Natural Sciences for public examination and debate in Auditorium TU2 at the Aalto University School of Science and Technology (Espoo, Finland) on the 24th of March 2010 at 12 noon.

Overview in PDF format (ISBN 978-952-60-3081-4)   [2070 KB]
Dissertation is also available in print (ISBN 978-952-60-3080-7)

Abstract

Blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) is an indirect method for measuring information processing in the brain. The method has enabled mapping human brain function in an unprecedented variety of tasks and conditions, and with a spatial resolution of the order of 1 mm.

In this dissertation, artificial imaging objects, or phantoms, with adjustable signal intensity were used to simulate and investigate the generation of fMRI signals. The objective was to characterise, and devise means to characterise, fMRI signal components that arise from methodological reasons, impeding the correct physiological interpretation of the signals.

The first study involved building an fMRI phantom, where an electric current was applied to introduce magnetic field inhomogeneity within a magnetic resonance signal source. It was shown that the changes of field homogeneity and thus fMRI signal, largely corresponded to the human BOLD changes, even though the physical mechanisms were different.

The mechanical properties of phantoms and brain however differ. Thus it was important to look into the attributes of phantoms that would make the fMRI signal from the phantom similar to brain scanning data. The second study examined geometric distortions in the echo-planar imaging method—commonly employed in both fMRI and diffusion tensor imaging—using a purpose-built structural phantom. In the third study, another fMRI activation phantom was built. There the induction wires were located outside the source of the fMRI signal, and thus the partial volume effect limiting the usability of the first fMRI phantom was abated. The phantom was applied to induce artificial activations that could be utilized to deduce periods when simultaneously measured brain activations would yield deviant activation levels due to unphysiological causes.

In the last study, an fMRI phantom was used to show that transient fMRI signal components, often witnessed in brain activation data, could occur in the absence of corresponding physiological signal, resulting from the sole signal change.

This thesis consists of an overview and of the following 4 publications:

  1. Ville Renvall, Raimo Joensuu, and Riitta Hari. 2006. Functional phantom for fMRI: a feasibility study. Magnetic Resonance Imaging, volume 24, number 3, pages 315-320. © 2006 Elsevier Science. By permission.
  2. Seppo Mattila, Ville Renvall, Jaana Hiltunen, Douglas Kirven, Raimo Sepponen, Riitta Hari, and Antti Tarkiainen. 2007. Phantom-based evaluation of geometric distortions in functional magnetic resonance and diffusion tensor imaging. Magnetic Resonance in Medicine, volume 57, number 4, pages 754-763.
  3. Ville Renvall. 2009. Functional magnetic resonance imaging reference phantom. Magnetic Resonance Imaging, volume 27, number 5, pages 701-708. © 2009 Elsevier Science. By permission.
  4. Ville Renvall and Riitta Hari. 2009. Transients may occur in functional magnetic resonance imaging without physiological basis. Proceedings of the National Academy of Sciences of the United States of America, volume 106, number 48, pages 20510-20514. © 2009 by authors.

Keywords: functional magnetic resonance imaging, fMRI phantom, fMRI, BOLD, transient

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© 2010 Aalto University School of Science and Technology

Last update 2011-05-26