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Understanding Error in Magnetic Resonance Fingerprinting

Kara, Danielle Christine
http://rave.ohiolink.edu/etdc/view?acc_num=case1521406087127691

Abstract Details

2018, Doctor of Philosophy, Case Western Reserve University, Physics.
The goal of this work was to understand and reduce the error in MRF parameter maps due to normal, thermal noise and correlated, aliasing noise. To achieve this goal, quality factors were introduced, which forecast the ability of MRF sequences to produce precise T1 and T2 parameter maps. Specifically, the variance in acquired parameter maps is inversely proportional to the derived quality factors. Due to their dependences on the MRF signal, quality factors were used to compare effects of MRF sequence design, including the flip angle distribution, TR distribution, number of total time steps (N), and use of preparation pulses on error in the resulting parameter maps, with the ultimate goal of reducing MRF error. In the presence of normal noise alone, rapidly varying flip angle distributions were ideal for minimizing parameter map error. Varying TR distributions were not found to be advantageous over constant TR, but the choice of the mean TR value was shown have a significant effect on parameter map precision, with the ideal choice depending on the underlying relaxation times. Quality factors for normal noise were found to have linear dependence on the total number of excitations for large N. Therefore, the precision of MRF experiments with large N reaches the expected statistical result for independent experiments: proportionality to 1/√N. The tested MRF experiments reached linearity in N after 1000 time steps. Because the efficiency of an MRF experiment is dependent on both σTi and the total sequence time, MRF efficiency is found to peak prior to N = 1000, after which it decreases toward constant. In the presence of dominant aliasing noise, smoothly varying flip angle distributions tend to outperform rapidly varying flip angle distributions. As in the case of normal noise alone, varying and constant TR distributions were comparable, but the choice of the mean value of TR was shown have a significant effect on T1 and T2 map precision. Like the quality factors for normal noise, the quality factors for aliasing noise are linearly dependent on the total number of time steps at large N, yielding σTi proportional to 1/√N and constant efficiency.
Robert Brown, PhD (Advisor)
Michael Martens, PhD (Committee Member)
Harsh Mathur, PhD (Committee Member)
Seiberlich Nicole, PhD (Committee Member)
183 p.
Biomedical Engineering; Physics
Magnetic Resonance Imaging, Quantitative MRI, Magnetic Resonance Fingerprinting, Aliasing Artifacts, Gaussian Noise, Quantification Error

Recommended Citations

Citations

  • Kara, D. C. (2018). Understanding Error in Magnetic Resonance Fingerprinting [Doctoral dissertation, Case Western Reserve University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=case1521406087127691

    APA Style (7th edition)

  • Kara, Danielle. Understanding Error in Magnetic Resonance Fingerprinting. 2018. Case Western Reserve University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=case1521406087127691.

    MLA Style (8th edition)

  • Kara, Danielle. "Understanding Error in Magnetic Resonance Fingerprinting." Doctoral dissertation, Case Western Reserve University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=case1521406087127691

    Chicago Manual of Style (17th edition)

case1521406087127691
610
© 2018, some rights reserved.Creative Commons License Understanding Error in Magnetic Resonance Fingerprinting by Danielle Christine Kara is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. Based on a work at etd.ohiolink.edu.
This open access ETD is published by Case Western Reserve University School of Graduate Studies and OhioLINK.