Adaptive functional magnetic resonance imaging

Functional MRI (fMRI) detects the signal associated with neuronal activation, and has been widely used to map brain functions. Locations of neuronal activation are localized and distributed throughout the brain, however, conventional encoding methods based on k-space acquisition have limited spatial selectivity. To improve it, we propose an adaptive fMRI method using non-Fourier, spatially selective RF encoding. This method follows a strategy of zooming into the locations of activation by progressively eliminating the regions that do not show any apparent activation. In this thesis, the conceptual design and implementation of adaptive fMRI are pursued under the hypothesis that the method may provide a more efficient means to localize functional activities with increased spatial or temporal resolution. The difference between functional detection and mapping is defined, and the multi- resolution approach for functional detection is examined using theoretical models simulating variations in both in-plane and through-plane resolution. We justify the multi-resolution approach experimentally using BOLD CNR as a quantitative measure and compare results to those obtained using theoretical models. We conclude that there is an optimal spatial resolution to obtain maximum detection; when the resolution matches the size of the functional activation. We demonstrated on a conventional 1.5-Tesla system that RF encoding provides a simple means for monitoring irregularly distributed slices throughout the brain without encoding the whole volume. We also show the potential for increased signal-to-noise ratio with Hadamard encoding as well as reduction of the in-flow effect with unique design of excitation pulses.

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Nuclear Engineering

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2000

Author dc:creator

• Yoo, Seung-Schik

Advisor dc:contributor.advisor

• Lawrence P. Panych.

• Nuclear Engineering.
• Harvard University--MIT Division of Health Sciences and Technology.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/70893

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/70893