臺灣博碩士論文加值系統

在進行功能性磁振造影(functional MRI),所量測到的訊號可能會隨著機器的
不穩定或者是受試者的不自主運動,例如呼吸和心跳,導致相位訊號會隨著時間 而漂移。因為相位訊號漂移所產生的假影可以經由回溯性的方式進行校正,然而 此校正方式並無法將漂移的相位訊號有效地校正回來。透過收集 navigator echo 的 方式,我們可以有效的受到生理訊號(呼吸及心跳)干擾而隨時間漂移的相位訊 號進行校正。
在本篇論文中,我們使用動態偏離共振方法(dynamic off-resonance correction in k-space)來校正快速功能性核磁共振逆影像(magnetic resonance inverse imaging, InI)。因為快速功能性磁共振逆影像重組影像時,需利用一開始所取得的整個大腦 的影像(reference scan)來對整個加速的影像(accelerated scan)進行影像重組, 因此整個加速的影像所取的得相位訊號會隨著時間飄移,而導致在重組影像時的不 一致性。這裡我們假設透過動態偏離磁共振的方法來校正快速功能性核磁共逆影 像能減低訊號受到呼吸的干擾及穩定功能性磁振造影沿著時間所量到的訊號,並 且對血液動力學響應曲線(hemodynamic response curve)的峰值估計大為增加。

The phase of NMR signal can drift significantly over time in fMRI experiments due to systematic instability, head motion, or thoracic/pelvic cavity motion. Artifacts related to phase drift can be corrected by retrospective signal processing. However, time series images can be shifted or distorted seriously such that they cannot be recovered by these methods. Navigator echoes have been proposed to correct time-invariant artifacts related to phase drifting before MRI reconstruction. Respiration-induced phase drift can also be estimated and corrected dynamically by measuring navigator echoes in each acquisition in fMRI.
In this study, we use the “dynamic off-resonance in k-space” (DORK) method to correct the phase drift in magnetic resonance inverse imaging (InI), which is a method using minimally gradient encoded data and parallel detection to achieve massively accelerated fMRI. As the phase of each accelerated InI scan becomes farther away from the initial value, the discrepancy between the reference scan and the instantaneous accelerated InI acquisition becomes more severe. We hypothesize that DORK can significantly improve the InI reconstructions by reducing such data inconsistency. Empirical results show that DORK can reduce the InI fluctuation in the respiratory
frequencies, improve the stability of the fMRI time series, and increase the peak value of hemodynamic response estimates.

口試委員會審定書 .......................................................................................................... i
誌謝 ....................................................................................................................................... ii
中文摘要 ............................................................................................................................ iii
ABSTRACT ....................................................................................................................... iv CONTENTS ....................................................................................................................... vi
LIST OF FIGURES ......................................................................................................... vii
Chapter 1 Introduction .................................................................................................... 1
Chapter 2 Method............................................................................................................... 5
2.1 Participants and tasks........................................................................................ 5
2.2 Pulse sequence and Data acquisition.............................................................. 6
2.3 DORK correction …………….................................................................................. 9
2.4 InI reconstructions, hemodynamic response estimation, and performance
quantification ............................................................................................................. 12
Chapter 3 Results........................................................................................................................ 14
3.1 The validity of DORK……………………………………………………….................... 14
3.2 The spatial distribution of tSNR............................................................................. 17
3.3 Hemodynamic response after GLM with DORK ............................................. 19
Chapter 4 Discussion ..................................................................................................23
REFERENCE ..................................................................................................................27

Belliveau, J. W., Kennedy, D. N., Jr., M., R.C. , Buchbinder, B. R., Weisskoff, R. M., Cohen, M. S., . . . Rosen, B. R. (1991). Functional mapping of the human visual cortex by magnetic resonance imaging. Science, 254, 716-719.
C.Noll, D., & WalterSchneider. (1994). THEORY, SIMULATION, AND COMPENSATION OF PHYSIOLOGICAL MOTION ARTIFACTS IN FUNCTIONAL MRI. IEEE.
DC, N., CR, G., AL, V., JL, O. B., & WF, E. (1998). Evaluation of respiratory artifact correction techniques in multishot spiral func- tional MRI using receiver operator characteristic analyses. MRM, 40, 633-639.
GH, G., & S, L. (1998). Self-navigated spiral fMRI: interleaved versus single-
shot. MRM, 39, 361-368.
Glover, G. H., Li, T.-Q., & Ress, D. (2000). Image-Based Method for Retrospective Correction of Physiological Motion Effects in fMRI: RETROICOR. MRM, 44, 162-167.
Hu, X., Le, T. H., Parish, T., & Erhard, P. (1995). Retrospective Estimation and Correction of Physiological Fluctuation in Functional MRI. MRM, 34, 201-212.
Kruger, G., & Glover, G. H. (2001). Physiological noise in oxygenation-sensitive magnetic resonance imaging. . MRM, 46, 631-637.
Lin, F.-H., Tsai, K. W.-K., Chu, Y.-H., Witzel, T., Nummenmaa, A., Raij, T., . . . Belliveau, J. W. (2012). Ultrafast inverse imaging techniques for fMRI. NeuroImage, 62, 699-705.
Lin, F. H., Wald, L. L., Ahlfors, S. P., Hamalainen, M.S., K., K.K., & Belliveau, J. W. (2006). Dynamic magnetic resonance inverse imaging of human brain function. MRM, 56(787-802).
Mansfield, P. (1977). Multi-Planar Image-Formation Using Nmr Spin Echoes. . Journal of Physics C-Solid State Physics, 10, L55-L58.
Moortele, P.-F. V. d., Pfeuffer, J., Glover, G. H., Ugurbil, K., & Hu, X. (2002). Respiration-Induced B0 Fluctuations and Their Spatial Distribution in the Human Brain at 7 Tesla. MRM, 47, 888-895.
Pfeuffer, J., Moortele, P.-F. V. d., Ugurbil, K., Hu, X., & Glover, G. H. (2002). Correction of Physiologically Induced Global Off- Resonance Effects in Dynamic Echo-Planar and Spiral Functional Imaging. MRM, 47, 344-353.
Raj, D., Paley, D. P., Anderson, A. W., Kennan, R. P., & Gore, a. J. C. (2000). A model for susceptibility artefacts from respiration in functional echo-planar magnetic resonance imaging. Phys. Med. Biol., 45(2000), 3809-3820.
Restom, K., Behzadi, Y., & Liua, T. T. (2006). Physiological noise reduction for arterial spin labeling functional MRI. NeuroImage, 31, 1104 -1115.
Särkkä, S., Solin, A., Nummenmaa, A., Vehtari, A., Auranen, T., Vanni, S., & Lin, F.-H. (2012). Dynamic retrospective filtering of physiological noise in BOLD fMRI: DRIFTER. NeuroImage, 60, 1517-1527.
Triantafyllou, C., Hoge, T. R. D., Krueger, G., Wiggins, C. J., Potthast, A., Wiggins, G. C., & Walda, L. L. (2005). Comparison of physiological noise at 1.5 T, 3 T and 7 T and optimization of fMRI acquisition parameters. NeuroImage, 26, 243-250.
X, H., & SG, K. (1994). Reduction of signal fluctuation in functional MRI using
navigator echoes. MRM, 31, 495-503.
Zanche, N. D., Barmet, C., Nordmeyer-Massner, J. A., & Pruessmann, K. P. (2008). NMR Probes for Measuring Magnetic Fields and Field
Dynamics in MR Systems. MRM, 60, 176-186.