DKI (弥散峰度成像) 英文PPT简介

DiffusionalKurtosisImagingDKIContentsDWI(diffusionweightedimaging)DTI(diffusiontensorimaging)DKI(diffusionkurtosisimaging)DWI原理MR图像的信号组织T1、T2驰豫时间、H1的密度、分子弥散运动DWI图像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DWI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（apparentdiffusioncoefficientADC）ADC=In(S低/S高)/(b高-b低)•弥散敏感系数(b)值==r2σ2g2(△-σ/3)b值的取值范围为0~10000s/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(T2shinethrougheffect)，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•ADC反映了水分子的扩散运动的能力,指水分子单位时间内扩散运动的范围，越高代表水分子扩散能力越强。•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λ1=λ2=λ3•在脑白质中由于髓鞘的阻挡，水分子的弥散被限制在与纤维走行一致的方向上，具有较高的各向异性，此时弥散张量可表示为椭球形，其特征值λ1λ2λ3，最大特征值对应的方向与经过该体素的纤维束走行平行defectsofDTI•ConventionalDTIfailstofullyutilizetheMRdiffusionmeasurementsthatareinherenttotissuemicrostructure.•DTIcomputesapparentdiffusivitybasedontheassumptionthatdiffusionweighted(DW)MRsignalhasamonoexponentialdependenceonthediffusionfactor(b-value).•DTIimplicitlyassumesthatwatermoleculediffusionoccursinafreeandunrestrictedenvironmentwithaGaussiandistributionofdiffusiondisplacement.defectsofDTI•Inbiologicaltissue,complexcellularmicrostructuresmakewaterdiffusionahighlyhinderedorrestrictedprocess.•Non-monoexponentialdecaysareexperimentallyobservedinbothwhitematterandgraymatter.•Moreover,thesimplifieddescriptionofthediffusionprocessinvivobya2nd-order3DdiffusivitytensorpreventsDTIfrombeingtrulyeffectiveincharacterizingrelativelyisotropictissuesuchasGM.EveninWM,theDTImodelcanfailifthetissuecontainssubstantialcrossingordivergingfibers.defectsofDTI•Asaresult,DTIquantitationisb-valuedependentandDTIfailstofullyutilizethediffusionmeasurementsthatareinherenttotissuemicrostructure.Kurtosis•Kurtosisherereferstotheexcesskurtosisthatisthenormalizedandstandardizedfourthcentralmomentofthewaterdisplacementdistribution.•ItisadimensionlessmeasurethatquantifiesthedeviationofthewaterdiffusiondisplacementprofilefromtheGaussiandistributionofunrestricteddiffusion,providingameasureofthedegreeofdiffusionhindranceorrestriction.•fourthcentralmoment: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•SincethedeviationfromGaussianbehaviorisgovernedbythecomplexityofthetissuewithinwhichthewaterisdiffusing,thisexcessdiffusionalkurtosiscanberegardedasameasureofatissue’sdegreeofstructure.OtheradvantagesofDKI•Meankurtosis(MK),theaverageapparentkurtosisalongalldiffusiongradientencodingdirections,hasbeenmeasuredanddemonstratedtoofferanimprovedsensitivityindetectingdevelopmentalandpathologicalchangesinneuraltissuesascomparedtoconventionalDTI.•Inaddition,directionalkurtosisanalysishasbeenformulatedtorevealdirectionallyspecificinformation,suchasthewaterdiffusionkurtosesalongthedirectionparallelorperpendiculartotheprinciplewaterdiffusiondirectionasdeterminedbythe2nd-orderdiffusiontensorDKIprovidesahigher-orderdescriptionofrestrictedwaterdiffusionprocessbya2nd-order3Ddiffusivitytensor(DTasinconventionalDTI)togetherwitha4th-order3Dkurtosistensor(KT).Conditions•Themethodisbasedonthesametypeofpulsesequencesemployedforconventionaldiffusion-weightedimaging(DWI),buttherequiredbvaluesaresomewhatlargerthanthoseusuallyusedtomeasurediffusioncoefficients.Inthebrain,bvaluesofabout2000s/mm2aresufficient.•Atleast15non-collinearandnon-coplanardirectionsarerequiredtoconstructKT.DKIvsq-spaceimagingtechniques•DKIhasacloserelationshiptoq-spaceimagingtechniques.•q-spaceimagingmethodshaveindeedrecentlybeenemployedtoestimatediffusionalkurtosis.•Theprincipaldifferencebetweenthemisthatq-spaceimagingseekstoestimatethefulldiffusiondisplacementprobabilitydistributionratherthanjustthekurtosis.•Asaconsequence,q-spaceimagingismoredemandingintermsofimagingtimeandgradientstrengths.•Measuringthediffusionalkurtosisrequiresonlymodestincreasesinbvalues•AndDKIislessdemandingintermsofhardwarerequirementsandpostprocessingeffort.Kurtosistensor(KT)derivedparameters•MK(meankurtosis):MKisameasureoftheoverallkurtosis.Itdoesnothaveanydirectionalspecificity.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∥(Axialkurtosis)andK⊥(Radialkurtosis):canbedefinedasthekurtosisparallelandperpendiculartotheprinciplediffusioneigenvector(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(fractionalanisotropyofkurtosis)SimilartoFAinDTI,theanisotropyofdirectionalkurtosiscanbeconvenientlydefinedasFAKKA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DKIparametricmapsDKIparametricmaps•TypicalDKI-derivedparametricmapsfromasinglesliceofa)invivo,b)formalin-fixedadultratbrainsandc)anormalhumansubject(male,44yearsold).•Axialdiffusivity(λ//),radialdiffusivity(λ⊥),meandiffusivity(MD),axialkurtosis(K//),radialkurtosis(K⊥),meankurtosis(MK),fractionalanisotropy(FA),directionallyencodedcolourFA(DEC-FA)andfractionalanisotropyofkurtosis(FAK)mapsarecomputedfromDKImodel.DKIparametricmaps•For(a),rawDWIswereacquiredbySEEPIwithTR/TE = 3000/30.3 ms,δ/Δ = 5/17 ms,slicethickness = 1 mm,FOV = 30 × 30 mm2,datamatrix = 128 × 128(zerofilledto256 × 256),NEX = 4,6b-values(0.0,0.5,1.0,1.5,2.0and2.5 ms/µm2)andalong30directionsusing7TscannerDKIparametricmaps•