Diffusion tensor imaging with multiple diffusion-weighted gradient directions

被引:1
作者
Jiang, Shan [1 ]
Liu, Meixia [1 ]
Han, Tong [2 ]
Liu, Weihua [1 ]
机构
[1] Tianjin Univ, Sch Mech Engn, Tianjin 300072, Peoples R China
[2] Tianjin Huanhu Hosp, Med Image Evaluat Ctr, Tianjin 300060, Peoples R China
基金
中国国家自然科学基金;
关键词
diffusion tensor imaging; neural tissue; tensor matrix; multiple linear regression; condition number; SAMPLING SCHEMES; WILD BOOTSTRAP; B-MATRIX; MRI; PARAMETERS; ANISOTROPY; SPECTROSCOPY; ACCURACY; SYSTEMS; ECHO;
D O I
10.3969/j.issn.1673-5374.2011.01.011
中图分类号
Q2 [细胞生物学];
学科分类号
071009 ; 090102 ;
摘要
Diffusion tensor MRI (DT-MRI or DTI) is emerging as an important non-invasive technology for elucidating internal brain structures. It has recently been utilized to diagnose a series of diseases that affect the integrity of neural systems to provide a basis for neuroregenerative studies. Results from the present study suggested that neural tissue is reconstructed with multiple diffusion-weighted gradient directions DTI, which varies from traditional imaging methods that utilize 6 gradient directions. Simultaneously, the diffusion tensor matrix is obtained by multiple linear regressions from an equation of echo signal intensity. The condition number value and standard deviation of fractional anisotropy for each scheme can be used to evaluate image quality. Results demonstrated that increasing gradient direction to some extent resulted in improved effects. Therefore, the traditional 6 and 15 directions should not be considered optimal scan protocols for clinical DTI application. In a scheme with 20 directions, the condition number and standard deviation of fractional anisotropy of the encoding gradients matrix were significantly reduced, and resulted in more clearly and accurately displayed neural tissue. Results demonstrated that the scheme with 20 diffusion gradient directions provided better accuracy of structural renderings and could be an optimal scan protocol for clinical DTI application.
引用
收藏
页码:66 / 71
页数:6
相关论文
共 36 条
[1]  
ADLURU G, 2007, CONSTRAINED RECONSTR
[2]   AN IMPROVED NUCLEAR-MAGNETIC-RESONANCE DIFFUSION-COEFFICIENT IMAGING METHOD USING AN OPTIMIZED PULSE SEQUENCE [J].
AHN, CB ;
LEE, SY ;
NALCIOGLU, O ;
CHO, ZH .
MEDICAL PHYSICS, 1986, 13 (06) :789-793
[3]   Optimal imaging parameters for fiber-orientation estimation in diffusion MRI [J].
Alexander, DC ;
Barker, GJ .
NEUROIMAGE, 2005, 27 (02) :357-367
[4]   MR DIFFUSION TENSOR SPECTROSCOPY AND IMAGING [J].
BASSER, PJ ;
MATTIELLO, J ;
LEBIHAN, D .
BIOPHYSICAL JOURNAL, 1994, 66 (01) :259-267
[5]  
Basser PJ, 1996, J MAGN RESON SER B, V111, P209, DOI [10.1006/jmrb.1996.0086, 10.1016/j.jmr.2011.09.022]
[6]   ESTIMATION OF THE EFFECTIVE SELF-DIFFUSION TENSOR FROM THE NMR SPIN-ECHO [J].
BASSER, PJ ;
MATTIELLO, J ;
LEBIHAN, D .
JOURNAL OF MAGNETIC RESONANCE SERIES B, 1994, 103 (03) :247-254
[7]   Anisotropic noise propagation in diffusion tensor MRI sampling schemes [J].
Batchelor, PG ;
Atkinson, D ;
Hill, DLG ;
Calamante, F ;
Connelly, A .
MAGNETIC RESONANCE IN MEDICINE, 2003, 49 (06) :1143-1151
[8]   The basis of anisotropic water diffusion in the nervous system - a technical review [J].
Beaulieu, C .
NMR IN BIOMEDICINE, 2002, 15 (7-8) :435-455
[9]  
CAROLINE AS, 2009, HUMAN BRAIN MAPPING, V30, P3657
[10]   Variance of estimated DTI-derived parameters via first-order perturbation methods [J].
Chang, Lin-Ching ;
Koay, Cheng Guan ;
Pierpaoli, Carlo ;
Basser, Peter J. .
MAGNETIC RESONANCE IN MEDICINE, 2007, 57 (01) :141-149