跳到主要內容

臺灣博碩士論文加值系統

(34.226.244.254) 您好!臺灣時間:2021/08/01 02:34
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

我願授權國圖
: 
twitterline
研究生:卓冠宏
研究生(外文):Kuan-Hung Cho
論文名稱:高夾角解析度擴散磁振造影之技術研究與發展:擴散加權值評估與取樣效率改進
論文名稱(外文):The Investigation and Development of High Angular Resolution Diffusion Imaging: The Evaluation of Diffusion Weighting and Improvement of Sampling Efficiency
指導教授:陳志宏陳志宏引用關係
學位類別:博士
校院名稱:國立臺灣大學
系所名稱:電機工程學研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2009
畢業學年度:97
語文別:英文
論文頁數:108
中文關鍵詞:高角解析度擴散造影q球造影角度解析度準確度半球取樣交叉項
外文關鍵詞:high angular resolution diffusion imagingq-ball imagingangular resolutionaccuracyhemi-spherical encoding schemecross-term correction
相關次數:
  • 被引用被引用:0
  • 點閱點閱:220
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
在過去十年中,擴散磁振造影技術藉由其計算在大腦不同功能區之間的神經纖維連結的能力,已在神經科學以及臨床研究上成為一個相當重要的工具。而相較於傳統的擴散磁振造影技術,高角解析度擴散影像技術更提供了複雜的神經纖維結構,如白質神經纖維的交叉等。然而,到目前為止,由於高角解析度擴散影像的冗長取像時間,加上大多數臨床研究者對於此技術相關知識的缺乏,造成其並未在臨床研究上被廣汎的使用。因此,本論文的主要目的是讓臨床研究者易於了解高角解析度擴散造影技術並進而使用之。

首先,我們藉由假體實驗評估了高角解析度擴散造影在計算複雜神經纖維方向的準確度以及其角度解析度。藉由闡述高角解析度擴散造影與序列參數之間的相關性,我們能幫助心理學家或臨床學家知道如何根據他們的需要來設定參數以得到好的結果。我們的結果顯示伴隨著較高的信雜比或是較低的擴散權值,高角解析度擴散造影解出的神經纖維方向有較高的準確度。而其角度解析度也隨著q值的增加而變好。而q值的選取決定於高角解析度擴散造影的準確性以及角度解析度。

另外,我們提出半球取樣的方法來縮短高角解析度擴散造影的取像時間。藉由擴散權值交叉項的修正,我們可以同時縮短時間並且得到準確得神經纖維方向估計。我們的結果顯示在使用半球取樣且沒修正擴散權值交叉項的情況下,神經纖維方向的估算有了明顯的誤差,而這誤差在經由修正擴散權值交叉項之後也的確變小。本論文提供了高角解析度擴散造影參數最佳化的決策並縮短了一半的取像時間,對於高角解析度擴散造影技術在未來臨床或是心理學上的研究有相當大的助益。
In past decade, the diffusion MRI has become an important approach to predict complex neural fiber connectivity between different brain regions in neuroscience and clinical fields. Comparing with conventional diffusion MRI techniques, high angular resolution diffusion imaging (HARDI) techniques provide the capability of resolving complex neural fiber architectures, such as intravoxel fiber crossing of white matter tracts. However, so far the HARDI techniques have not been extensively used in clinical application due to excessive scan time and the lack of the knowledge on such techniques for clinicians. Therefore, the main object of this dissertation is to facilitate the application of HARDI for clinicians.

First, we evaluated the q-related accuracy and angular resolution of estimating the complex fiber orientations for HARDI via phantom experiments. By illustrating the relationship between the inherent property of HARDI and the sequence parameters, we could help the psychologists or clinicians to understand how to get a better HARDI result or to set the parameters according to their demands. In our results, a more accurate estimation of fiber orientations was obtained when a higher SNR or lower q value was achieved. The angular resolution was also highly correspondent with the q value, i.e. a higher q value yielded a better angular resolution. It is a trade-off between the accuracy and the angular resolution to optimize the q value.

Second, a hemi-spherical encoding scheme was proposed based on the spherically symmetric property of diffusion signals. With correcting for the cross-term, we can get accurate fiber orientation estimate and halve the scan time of HARDI simultaneously. Our results showed an obvious estimation error when using a hemi-spherical encoding scheme without correcting for the cross-term in comparison with the cross-term-free results. This estimation error could be reduced after correcting for the cross-term. Conclusively, the application in clinical and psychological filed would benefit from our studies, which provide the optimization strategy of HARDI and halve the total scan time.
Cover 1
Acknowledgement 4
Chinese abstract 5
English abstract 6
Table of Contents 8
Lists of Figures 10
Lists of Tables 11
Chapter 1 Introduction 12
1.1 Background 12
1.1.1 Diffusion phenomenon and diffusion NMR 12
1.1.2 Diffusion MRI and its applications 21
1.2 Motivation and Purpose 28
1.3 Outline 28
Chapter 2 Evaluation of the accuracy and angular resolution of q-ball imaging 31
2.1 Introduction 31
2.2 Theory 34
2.2.1 QBI reconstruction 34
2.2.2 FWHM-nODF analysis 34
2.3 Materials and Methods 36
2.3.1 Phantom models 36
2.3.2 MR experiments 37
2.4 Results 40
2.4.1 Accuracy and angular resolution of QBI on phantom models 40
2.4.2 Angular resolution of QBI on healthy subject 41
2.5 Discussions 42
2.5.1 FWHM-nODF 42
2.5.2 Accuracy of QBI 42
2.5.3 QBI parameters for human study 44
2.5.4 Factors that might affect the accuracy of QBI 45
2.6 Conclusion 47
Chapter 3 Potential in reducing scan times of HARDI by accurate correction of the cross-term in a hemi-spherical encoding scheme 56
3.1 Introduction 56
3.2 Theory 59
3.3 Materials and Methods 61
3.3.1 MRI acquisition 61
3.3.2 Data analysis 62
3.4 Results 63
3.4.1 The actual b value in each directions 63
3.4.2 The fiber orientation estimation of the crossing phantom model 64
3.4.3 The fiber orientation estimation of the unidirectional phantom model 65
3.5 Discussion 65
3.6 Conclusion 70
Chapter 4 Discussion and Conclusion 80
4.1 Discussion 80
4.2 Conclusion 85
4.3 Future works 86
Reference 93
Publications 103
1.Stejskal, E.O. and J.E. Tanner, Spin Diffusion Measurements: Spin Echoes in the Presence of a Time-Dependent Field Gradient. J. Chem. Phys., 1965. 42(1): p. 288.
2.Torrey, H.C., Bloch Equations with Diffusion Terms. Physical Review, 1956. 104: p. 563-565.
3.Abragam, A., The principles of nuclear magnetism. 1961, Oxford :: Clarendon Press.
4.Bloch, F., The Principle of Nuclear Induction. Science, 1953. 118(3068): p. 425-430.
5.Ahn, C.B. and Z.H. Cho, A generalized formulation of diffusion effects in micron resolution nuclear magnetic resonance imaging. Med Phys, 1989. 16(1): p. 22-8.
6.Le Bihan, D., Magnetic resonance imaging of perfusion. Magn Reson Med, 1990. 14(2): p. 283-92.
7.Basser, P.J., J. Mattiello, and D. LeBihan, Estimation of the effective self-diffusion tensor from the NMR spin echo. J Magn Reson B, 1994. 103(3): p. 247-54.
8.Ljunggren, S., A simple graphical representation of fourier-based imaging methods. Journal of Magnetic Resonance (1969), 1983. 54(2): p. 338-343.
9.Twieg, D.B., The k-trajectory formulation of the NMR imaging process with applications in analysis and synthesis of imaging methods. Medical Physics, 1983. 10(5): p. 610-621.
10.Tanner, J.E., Use of the Stimulated Echo in NMR Diffusion Studies. J. Chem. Phys., 1970. 52(5): p. 2523-26.
11.Brihuega-Moreno, O., et al., Effects of, and corrections for, cross-term interactions in Q-space MRI. Magn Reson Med, 2004. 51(5): p. 1048-54.
12.Neeman, M., J.P. Freyer, and L.O. Sillerud, A simple method for obtaining cross-term-free images for diffusion anisotropy studies in NMR microimaging. Magn Reson Med, 1991. 21(1): p. 138-43.
13.Basser, P.J., J. Mattiello, and D. LeBihan, MR diffusion tensor spectroscopy and imaging. Biophys J, 1994. 66(1): p. 259-67.
14.Wiegell, M.R., H.B. Larsson, and V.J. Wedeen, Fiber crossing in human brain depicted with diffusion tensor MR imaging. Radiology, 2000. 217(3): p. 897-903.
15.Alexander, A.L., et al., Analysis of partial volume effects in diffusion-tensor MRI. Magn Reson Med, 2001. 45(5): p. 770-80.
16.Alexander, D.C., G.J. Barker, and S.R. Arridge, Detection and modeling of non-Gaussian apparent diffusion coefficient profiles in human brain data. Magn Reson Med, 2002. 48(2): p. 331-40.
17.Ozarslan, E. and T.H. Mareci, Generalized diffusion tensor imaging and analytical relationships between diffusion tensor imaging and high angular resolution diffusion imaging. Magn Reson Med, 2003. 50(5): p. 955-65.
18.Tournier, J.D., et al., Direct estimation of the fiber orientation density function from diffusion-weighted MRI data using spherical deconvolution. Neuroimage, 2004. 23(3): p. 1176-85.
19.Tuch, D.S., Q-ball imaging. Magn Reson Med, 2004. 52(6): p. 1358-72.
20.Anderson, A.W., Measurement of fiber orientation distributions using high angular resolution diffusion imaging. Magn Reson Med, 2005. 54(5): p. 1194-206.
21.Wedeen, V.J., et al., Mapping complex tissue architecture with diffusion spectrum magnetic resonance imaging. Magn Reson Med, 2005. 54(6): p. 1377-86.
22.Descoteaux, M., et al., Apparent diffusion coefficients from high angular resolution diffusion imaging: estimation and applications. Magn Reson Med, 2006. 56(2): p. 395-410.
23.Cory, D.G. and A.N. Garroway, Measurement of translational displacement probabilities by NMR: an indicator of compartmentation. Magn Reson Med, 1990. 14(3): p. 435-44.
24.Assaf, Y., et al., High b-value q-space analyzed diffusion-weighted MRI: application to multiple sclerosis. Magn Reson Med, 2002. 47(1): p. 115-26.
25.Assaf, Y. and Y. Cohen, Structural information in neuronal tissue as revealed by q-space diffusion NMR spectroscopy of metabolites in bovine optic nerve. NMR Biomed, 1999. 12(6): p. 335-44.
26.Callaghan, P.T., NMR imaging, NMR diffraction and applications of pulsed gradient spin echoes in porous media. Magn Reson Imaging, 1996. 14(7-8): p. 701-9.
27.Avram, L., Y. Assaf, and Y. Cohen, The effect of rotational angle and experimental parameters on the diffraction patterns and micro-structural information obtained from q-space diffusion NMR: implication for diffusion in white matter fibers. J Magn Reson, 2004. 169(1): p. 30-8.
28.King, M.D., et al., q-Space imaging of the brain. Magn Reson Med, 1994. 32(6): p. 707-13.
29.Lin, C.P., et al., Validation of diffusion spectrum magnetic resonance imaging with manganese-enhanced rat optic tracts and ex vivo phantoms. Neuroimage, 2003. 19(3): p. 482-95.
30.Tuch, D.S., et al., High angular resolution diffusion imaging of the human brain. Proc ISMRM 7th Ann Meeting, Philadelphia, 1999: p. 321.
31.Assaf, Y. and P.J. Basser, Composite hindered and restricted model of diffusion (CHARMED) MR imaging of the human brain. Neuroimage, 2005. 27(1): p. 48-58.
32.Zhan, W., et al., Circular spectrum mapping for intravoxel fiber structures based on high angular resolution apparent diffusion coefficients. Magn Reson Med, 2003. 49(6): p. 1077-88.
33.Perrin, M., et al., Validation of q-ball imaging with a diffusion fibre-crossing phantom on a clinical scanner. Philos Trans R Soc Lond B Biol Sci, 2005. 360(1457): p. 881-91.
34.Hess, C.P., et al., Q-ball reconstruction of multimodal fiber orientations using the spherical harmonic basis. Magn Reson Med, 2006. 56(1): p. 104-17.
35.Grannell, P.K. and P. Mansfield, Microscopy in vivo by nuclear magnetic resonance. Phys Med Biol, 1975. 20(3): p. 477-82.
36.Callaghan, P.T., Principles of nuclear magnetic resonance microscopy. 1991, New York :: Clarendon Press.
37.Conturo, T.E., et al., Tracking neuronal fiber pathways in the living human brain. Proc Natl Acad Sci U S A, 1999. 96(18): p. 10422-7.
38.Mori, S., et al., Three-dimensional tracking of axonal projections in the brain by magnetic resonance imaging. Ann Neurol, 1999. 45(2): p. 265-9.
39.Basser, P.J., et al., In vivo fiber tractography using DT-MRI data. Magn Reson Med, 2000. 44(4): p. 625-32.
40.Lin, C.P., et al., Validation of diffusion tensor magnetic resonance axonal fiber imaging with registered manganese-enhanced optic tracts. Neuroimage, 2001. 14(5): p. 1035-47.
41.Behrens, T.E., et al., Non-invasive mapping of connections between human thalamus and cortex using diffusion imaging. Nat Neurosci, 2003. 6(7): p. 750-7.
42.Frank, L.R., Anisotropy in high angular resolution diffusion-weighted MRI. Magn Reson Med, 2001. 45(6): p. 935-9.
43.Frank, L.R., Characterization of anisotropy in high angular resolution diffusion-weighted MRI. Magn Reson Med, 2002. 47(6): p. 1083-99.
44.Tuch, D.S., et al., High angular resolution diffusion imaging reveals intravoxel white matter fiber heterogeneity. Magn Reson Med, 2002. 48(4): p. 577-82.
45.Tuch, D.S., et al., Diffusion MRI of complex neural architecture. Neuron, 2003. 40(5): p. 885-95.
46.Campbell, J.S., et al., Flow-based fiber tracking with diffusion tensor and q-ball data: validation and comparison to principal diffusion direction techniques. Neuroimage, 2005. 27(4): p. 725-36.
47.Perrin, M., et al., Fiber tracking in q-ball fields using regularized particle trajectories. Inf Process Med Imaging, 2005. 19: p. 52-63.
48.von dem Hagen, E.A. and R.M. Henkelman, Orientational diffusion reflects fiber structure within a voxel. Magn Reson Med, 2002. 48(3): p. 454-9.
49.Assaf, Y., A. Mayk, and Y. Cohen, Displacement imaging of spinal cord using q-space diffusion-weighted MRI. Magn Reson Med, 2000. 44(5): p. 713-22.
50.Alexander, D.C. and G.J. Barker, Optimal imaging parameters for fiber-orientation estimation in diffusion MRI. Neuroimage, 2005. 27(2): p. 357-67.
51.Alexander, A.L., et al., A geometric analysis of diffusion tensor measurements of the human brain. Magn Reson Med, 2000. 44(2): p. 283-91.
52.Kim, S., et al., Dependence on diffusion time of apparent diffusion tensor of ex vivo calf tongue and heart. Magn Reson Med, 2005. 54(6): p. 1387-96.
53.Li, Y.C., et al., Optimal imaging parameters for minimum angular discrimination in diffusion spectrum imaging. Proc ISMRM 14th Ann Meeting, Seattle, USA, 2006: p. 644.
54.Callaghan, P.T., Principles of Nuclear Magnetic Resonance Microscopy. 1993.
55.Blees, M.H., The Effect of Finite Duration of Gradient Pulses on the Pulsed-Field-Gradient NMR Method for Studying Restricted Diffusion. Journal of Magnetic Resonance, Series A, 1994. 109(2): p. 203-209.
56.Jones, D.K., The effect of gradient sampling schemes on measures derived from diffusion tensor MRI: a Monte Carlo study. Magn Reson Med, 2004. 51(4): p. 807-15.
57.Parker, G.J., C.A. Wheeler-Kingshott, and G.J. Barker, Estimating distributed anatomical connectivity using fast marching methods and diffusion tensor imaging. IEEE Trans Med Imaging, 2002. 21(5): p. 505-12.
58.Lazar, M., et al., White matter tractography using diffusion tensor deflection. Hum Brain Mapp, 2003. 18(4): p. 306-21.
59.Parker, G.J., H.A. Haroon, and C.A. Wheeler-Kingshott, A framework for a streamline-based probabilistic index of connectivity (PICo) using a structural interpretation of MRI diffusion measurements. J Magn Reson Imaging, 2003. 18(2): p. 242-54.
60.Jansons, K.M. and D.C. Alexander, Persistent Angular Structure: new insights from diffusion MRI data. Dummy version. Inf Process Med Imaging, 2003. 18: p. 672-83.
61.Assaf, Y., et al., New modeling and experimental framework to characterize hindered and restricted water diffusion in brain white matter. Magn Reson Med, 2004. 52(5): p. 965-78.
62.Khachaturian, M.H., J.J. Wisco, and D.S. Tuch, Boosting the sampling efficiency of q-ball imaging using multiple wavevector fusion. Magn Reson Med, 2007. 57(2): p. 289-296.
63.Wu, Y.C. and A.L. Alexander, Hybrid diffusion imaging. Neuroimage, 2007. 36(3): p. 617-29.
64.Feinberg, D.A., T.G. Reese, and V.J. Wedeen, Simultaneous echo refocusing in EPI. Magn Reson Med, 2002. 48(1): p. 1-5.
65.Reese, T.G., et al., Halving Imaging Time of Whole Brain Diffusion Spectrum Imaging (DSI) Using Simultaneous Echo Refocusing (SER) EPI. Proc. Intl. Soc. Mag. Reson. Med., 2006. 14: p. 1044.
66.Neeman, M., J.P. Freyer, and L.O. Sillerud, Pulsed-gradient spin-echo diffusion studies in nmr imaging. Effects of the imaging gradients on the determination of diffusion coefficients. J Magn Reson, 1990. 90(2): p. 303-312.
67.Cho, K.H., et al., Evaluation of the accuracy and angular resolution of q-ball imaging. Neuroimage, 2008. 42(1): p. 262-71.
68.Jones, D.K., M.A. Horsfield, and A. Simmons, Optimal strategies for measuring diffusion in anisotropic systems by magnetic resonance imaging. Magn Reson Med, 1999. 42(3): p. 515-25.
69.Yeh, C.H., K.H. Cho, and C.P. Lin, Comparison Between Q-Ball Reconstructions Using Radial Basis Function and Spherical Harmonic Basis. Proc ISMRM 16th Ann Meeting, Toronto, Canada, 2008: p. 1864.
70.Sun, P.Z., J.G. Seland, and D. Cory, Background gradient suppression in pulsed gradient stimulated echo measurements. J Magn Reson, 2003. 161(2): p. 168-73.
71.Galvosas, P., F. Stallmach, and J. Karger, Background gradient suppression in stimulated echo NMR diffusion studies using magic pulsed field gradient ratios. J Magn Reson, 2004. 166(2): p. 164-73.
72.Sun, P.Z., S.A. Smith, and J. Zhou, Analysis of the magic asymmetric gradient stimulated echo sequence with shaped gradients. J Magn Reson, 2004. 171(2): p. 324-9.
73.Sun, P.Z., Improved diffusion measurement in heterogeneous systems using the magic asymmetric gradient stimulated echo (MAGSTE) technique. J Magn Reson, 2007. 187(2): p. 177-83.
74.Finsterbusch, J., Cross-term-compensated pulsed-gradient stimulated echo MR with asymmetric gradient pulse lengths. J Magn Reson, 2008. 193(1): p. 41-8.
75.Finsterbusch, J., Improved diffusion-weighting efficiency of pulsed gradient stimulated echo MR measurements with background gradient cross-term suppression. J Magn Reson, 2008. 191(2): p. 282-90.
76.Kuo, L.W., et al., Diffusion Spectrum Tractography in Patients with Brain Tumors. Proc ISMRM 13th Ann Meeting, Miami, USA, 2005: p. 1064.
77.Ying, L.L., et al., Determination of fiber orientation in MRI diffusion tensor imaging based on higher-order tensor decomposition. Conf Proc IEEE Eng Med Biol Soc, 2007. 2007: p. 2065-8.
78.Pajevic, S. and P.J. Basser, Parametric and non-parametric statistical analysis of DT-MRI data. J Magn Reson, 2003. 161(1): p. 1-14.
79.Nossin-Manor, R., R. Duvdevani, and Y. Cohen, Effect of experimental parameters on high b-value q-space MR images of excised rat spinal cord. Magn Reson Med, 2005. 54(1): p. 96-104.
80.Bar-Shir, A. and Y. Cohen, Crossing fibers, diffractions and nonhomogeneous magnetic field: correction of artifacts by bipolar gradient pulses. Magn Reson Imaging, 2008. 26(6): p. 801-8.
81.Calamante, F., et al., Correction for eddy current induced Bo shifts in diffusion-weighted echo-planar imaging. Magn Reson Med, 1999. 41(1): p. 95-102.
82.Jezzard, P., A.S. Barnett, and C. Pierpaoli, Characterization of and correction for eddy current artifacts in echo planar diffusion imaging. Magn Reson Med, 1998. 39(5): p. 801-12.
83.Maniega, S.M., M.E. Bastin, and P.A. Armitage, A quantitative comparison of two methods to correct eddy current-induced distortions in DT-MRI. Magn Reson Imaging, 2007. 25(3): p. 341-9.
84.Zhuang, J., et al., Correction of eddy-current distortions in diffusion tensor images using the known directions and strengths of diffusion gradients. J Magn Reson Imaging, 2006. 24(5): p. 1188-93.
85.Chen, B., H. Guo, and A.W. Song, Correction for direction-dependent distortions in diffusion tensor imaging using matched magnetic field maps. Neuroimage, 2006. 30(1): p. 121-9.
86.Reese, T.G., et al., Reduction of eddy-current-induced distortion in diffusion MRI using a twice-refocused spin echo. Magn Reson Med, 2003. 49(1): p. 177-82.
87.Aja-Fernandez, S., et al., Restoration of DWI data using a Rician LMMSE estimator. IEEE Trans Med Imaging, 2008. 27(10): p. 1389-403.
88.Wiest-Daessle, N., et al., Rician noise removal by non-Local Means filtering for low signal-to-noise ratio MRI: applications to DT-MRI. Med Image Comput Comput Assist Interv Int Conf Med Image Comput Comput Assist Interv, 2008. 11(Pt 2): p. 171-9.
89.Farrell, J.A., et al., Effects of signal-to-noise ratio on the accuracy and reproducibility of diffusion tensor imaging-derived fractional anisotropy, mean diffusivity, and principal eigenvector measurements at 1.5 T. J Magn Reson Imaging, 2007. 26(3): p. 756-67.
90.Basu, S., T. Fletcher, and R. Whitaker, Rician noise removal in diffusion tensor MRI. Med Image Comput Comput Assist Interv Int Conf Med Image Comput Comput Assist Interv, 2006. 9(Pt 1): p. 117-25.
91.Wirestam, R., et al., Denoising of complex MRI data by wavelet-domain filtering: application to high-b-value diffusion-weighted imaging. Magn Reson Med, 2006. 56(5): p. 1114-20.
92.Samsonov, A.A. and C.R. Johnson, Noise-adaptive nonlinear diffusion filtering of MR images with spatially varying noise levels. Magn Reson Med, 2004. 52(4): p. 798-806.
93.Descoteaux, M., High Angular Resolution Diffusion MRI: From Local Estimation to Segmentation and Tractography PhD Thesis, Universite de Nice-Sophia Antipolis, 2008.
94.Kuo, L.W., et al., Mossy fiber sprouting in pilocarpine-induced status epilepticus rat hippocampus: a correlative study of diffusion spectrum imaging and histology. Neuroimage, 2008. 41(3): p. 789-800.
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top