All ETDs from UAB

Advisory Committee Chair

Donald B Twieg

Advisory Committee Members

Narasimha S Akella

Georg Deutsch

Allan C Dobbins

Alfred L Paige

Stanley J Reeves

Document Type

Dissertation

Date of Award

2010

Degree Name by School

Doctor of Philosophy (PhD) School of Engineering

Abstract

Fast imaging Magnetic Resonance Imaging (MRI) techniques such as Echo Planar Imaging (EPI) often suffer from artifacts such as signal dropouts, geometric distortions and susceptibility artifacts due to background gradients. Parameter Assessment by Retrieval from Signal Encoding (PARSE) was introduced as a single shot, inverse estimation technique that models the MRI process more accurately and estimates the initial transverse magnetization, M0 and its phase, the decay rate R2* and local frequency at each pixel. This technique is devoid of the aforementioned artifacts seen in EPI techniques. The goal of this work is to develop multi-shot parameter assessment by retrieval from signal encoding (MS-PARSE) techniques for higher resolution. In the first part, the MS-PARSE technique is implemented and tested using interleaved rosette shots. A modified progressive length conjugate gradient (PLCG) algorithm was developed to combine the multi-shot data and reconstruct high resolution parameter maps. Numerical simulations were carried out to assess the performance of the algorithm. The MS-PARSE sequence was programmed on a 4.7 T MRI scanner, the k- trajectory was calibrated and phantom data were collected. High resolution parameter maps were reconstructed. The R2* parameter maps from the experimental data were validated with reference values and are shown to correlate very well with `gold-standard' R2* measurement technique. The next part describes the extension of the MS-PARSE technique to parallel imaging. This paper describes the implementation of the PLCG algorithm to handle PARSE data from multiple coils and multiple shots. A multiple-coil data acquisition was simulated using a discrete numerical phantom with overlapping spatial sensitivity profiles. Numerical simulations were carried out to assess the performance of the algorithm under different noise conditions. The accuracy of the estimated parameters are compared with assigned reference values. We demonstrate that the technique can produce high-resolution multi-parameter maps from an acquisition lasting a few hundred milliseconds. The development of the above multi-shot PARSE techniques allows the generation of high spatial and temporal resolution multi-parameter maps. Upon validation, these techniques can potentially benefit functional MRI and a number of clinical MRI imaging applications.

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