DKI-(弥散峰度成像)ppt课件.ppt
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- DKI 弥散 峰度 成像 ppt 课件
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1、Diffusional Kurtosis Imaging DKI1Contents DWI(diffusion weighted imaging) DTI(diffusion tensor imaging)DKI(diffusion kurtosis imaging) 2DWI原理组织T1、T2驰豫时间、H1的密度、分子弥散运动利用扩散敏感梯度脉冲将水分子弥散效应扩大,来研究不同组织中水分子扩散运动的差异 3DWI评估弥散的参数 通过两个以上不同弥散敏感梯度值( b值)的弥散加权象,可计算出弥散敏感梯度方向上水分子的表观弥散系数(apparent diffusion coefficient A
2、DC) ADC=In(S低/S高)/(b高-b低)弥散敏感系数(b)值= =r22g2(-/3) b 值的取值范围为010 000s/mm2,较大的b 值具有较大的弥散权重,对水分子的弥散运动越敏感,并引起较大的信号下降,但b 值越大,图像信噪比也相应下降,如果b 值太小,易受T2 加权的影像,产生所谓的T2 透射效应(T2 shine through effect),一般来说用大b 值差的图像测得的ADC 值较准确,故侧ADC 值时宜选较高b 值和较大的b 值差4 均质介质中可以水分子的自由运动为各向同性,即在各个方向上的弥散强度大小一致,弥散张量D描述为球形,沿磁共振的三个主坐标的特征值为
3、 1=2=35defects of DTI Conventional DTI fails to fully utilize the MR diffusion measurements that are inherent to tissue microstructure. DTI computes apparent diffusivity based on the assumption that diffusion weighted (DW) MR signal has a monoexponential dependence on the diffusion factor (b-value).
4、 DTI implicitly assumes that water molecule diffusion occurs in a free and unrestricted environment with a Gaussian distribution of diffusion displacement. 6defects of DTI In biological tissue, complex cellular microstructures make water diffusion a highly hindered or restricted process. Non-monoexp
5、onential decays are experimentally observed in both white matter and gray matter. Moreover, the simplified description of the diffusion process in vivo by a 2nd-order 3D diffusivity tensor prevents DTI from being truly effective in characterizing relatively isotropic tissue such as GM. Even in WM, t
6、he DTI model can fail if the tissue contains substantial crossing or diverging fibers . 7defects of DTI As a result, DTI quantitation is b-value dependent and DTI fails to fully utilize the diffusion measurements that are inherent to tissue microstructure.8KurtosisKurtosis here refers to the excess
7、kurtosis that is the normalized and standardized fourth central moment of the water displacement distribution . It is a dimensionless measure that quantifies the deviation of the water diffusion displacement profile from the Gaussian distribution of unrestricted diffusion, providing a measure of the
8、 degree of diffusion hindrance or restriction.fourth central moment:四阶中心距,主要用来衡量随机分布变量的分布在均值附近的陡峭程度Since the deviation from Gaussian behavior is governed by the complexity of the tissue within which the water is diffusing, this excess diffusional kurtosis can be regarded as a measure of a tissues de
9、gree of structure.9Other advantages of DKIMean kurtosis (MK), the average apparent kurtosis along all diffusion gradient encoding directions, has been measured and demonstrated to offer an improved sensitivity in detecting developmental and pathological changes in neural tissues as compared to conve
10、ntional DTI .In addition, directional kurtosis analysis has been formulated to reveal directionally specific information, such as the water diffusion kurtoses along the direction parallel or perpendicular to the principle water diffusion direction as determined by the 2nd-order diffusion tensor10DKI
11、 provides a higher-order description of restricted water diffusion process by a 2nd-order 3D diffusivity tensor (DT as in conventional DTI) together with a 4th-order 3D kurtosis tensor (KT).11ConditionsThe method is based on the same type of pulse sequences employed for conventional diffusion-weight
12、ed imaging (DWI), but the required b values are somewhat larger than those usually used to measure diffusion coefficients. In the brain, b values of about 2000 s/mm2 are sufficient.At least 15 non-collinear and non-coplanar directions are required to construct KT.12DKI vs q-space imaging techniquesD
13、KI has a close relationship to q-space imaging techniques.q-space imaging methods have indeed recently been employed to estimate diffusional kurtosis.The principal difference between them is that q-space imaging seeks to estimate the full diffusion displacement probability distribution rather than j
14、ust the kurtosis.As a consequence,q-space imaging is more demanding in terms of imaging time and gradient strengths.Measuring the diffusional kurtosis requires only modest increases in b valuesAnd DKI is less demanding in terms of hardware requirements and postprocessing effort.13Kurtosis tensor (KT
15、) derived parametersMK(mean kurtosis):MK is a measure of the overall kurtosis. It does not have any directional specificity. MK 的大小取决于感兴趣区内组织的结构复杂程度,结构越复杂非正态分布水分子扩散受限越显著,MK 也即越大K (Axial kurtosis)and K(Radial kurtosis) :can be defined as the kurtosis parallel and perpendicular to the principle diffus
16、ion eigenvector (e1) K越大表明在该方向非正态分布水分子扩散受限越明显,反之则表明扩散受限越弱FAK (fractional anisotropy of kurtosis )Similar to FA in DTI, the anisotropy of directional kurtosis can be conveniently defined as FAK KA 越小即表示越趋于各向同性扩散; 若组织结构越紧密越规则,KA 越大14DKI parametric maps15DKI parametric maps Typical DKI-derived parametr
17、ic maps from a single slice of a) in vivo, b) formalin-fixed adult rat brains and c) a normal human subject (male, 44 years old). Axial diffusivity (/), radial diffusivity (), mean diffusivity (MD), axial kurtosis (K/), radial kurtosis (K ), mean kurtosis (MK), fractional anisotropy (FA), directiona
18、lly encoded colour FA (DEC-FA) and fractional anisotropy of kurtosis (FAK) maps are computed from DKI model.16DKI parametric maps For (a), raw DWIs were acquired by SE EPI with TR/TE=3000/30.3ms, /=5/17ms, slice thickness=1mm, FOV=3030mm2, data matrix=128128 (zero filled to 256256), NEX=4, 6 b-value
19、s (0.0, 0.5, 1.0, 1.5, 2.0 and 2.5ms/m2) and along 30 directions using 7T scanner17DKI parametric maps For (b), raw DWIs were acquired with the same parameters as those for in vivo except TE=34.3ms, =9ms and b-values of 0.0, 1.0, 2.0, 3.0, 4.0 and 5.0ms/m2. A larger b-value range was used in ex vivo
20、 experiment due to the generally lower diffusivities.18DKI parametric maps For (c), raw DWIs were acquired by SE EPI with TR/TE=2300/109ms, slice thickness=2mm, FOV=256256mm2, data matrix=128128, NEX=2, 6 b-values (0.0, 0.5, 1.0, 1.5, 2.0 and 2.5ms/m2) and along 30 directions using a 3T Siemens scan
21、ner 19DKI parametric maps Higher MK is found in WM, indicating a generally higher degree of diffusion complexity and restriction in the WM structures. It can be seen from the directional kurtosis maps that such high MK in WM is mainly contributed by K . This suggests the existence of heterogeneity a
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