DTI數(shù)據(jù)分析及應(yīng)用課件

DTI數(shù)據(jù)分析及應(yīng)用1整理pptPage2內(nèi)容提綱DTI的研究?jī)?nèi)容DTI數(shù)據(jù)處理流程DTIStudioFSL:FMRIB’sDiffusionToolbox2整理pptPage3擴(kuò)散張量成像的研究?jī)?nèi)容纖維跟蹤算法基于DTI的應(yīng)用研究3整理pptDxyxyDyyDyz=(v1v2v3)0λ20擴(kuò)散張量的數(shù)學(xué)描述D=

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v2DxzDyzDzz00λ3v34整理pptPage5確定性跟蹤算法跟蹤終止條件Morietal.,AnnNeurol,19995整理pptPage6確定性跟蹤結(jié)果Catanietal,Brain,2005粗大的白質(zhì)纖維束6整理pptUncertaintyPage7纖維走向的不確定性Jones,MRM,2003LinearityBootstrap方法7整理pptPage8概率跟蹤算法DirectionUncertaintyDTINoisePartialVolumeEffectsSlidefromTriNgo8整理pptPage9概率跟蹤的方法Non-parametric(modelfree)approachesBootstrapmethodHARDI:Q-ball,DSIParametricapproachesPriorknowledgeandmodels:BayesianframeworkProbabilitydensityfunction(PDF):local,globalHowtoestimatethedistributionoffiberorientationswithinavoxel?9整理pptPage10

概率跟蹤的思想Reference:Behrens,T.E.etal.Characterizationandpropagationofuncertaintyindiffusion-weightedMRimaging.MagnResonMed50,1077-88(2003).10整理pptPage11概率跟蹤結(jié)果Frimanetal,IEEETMI,200611整理pptPage12概率跟蹤的優(yōu)點(diǎn)：估計(jì)纖維走向的不確定性,一定程度上解決纖維交叉問題研究FA較低的灰質(zhì)腦區(qū)之間的解剖連接跟蹤結(jié)果對(duì)噪聲更穩(wěn)定定量描述空間任意兩個(gè)體素之間的連接概率概率跟蹤的缺點(diǎn)：需要采集較多梯度方向的DTI圖像計(jì)算量大，耗時(shí)12整理pptPage13Connectivity-basedclassificationof thalamicvoxelsproducesclustersBehrensetal,NatureNeuroscience,200313整理pptPage14ImprovementsonthediffusiontensormodelsinglefibremultiplefibresSlidefromSaadJbabdi14整理pptPage15確定性跟蹤常用軟件:DTIStudio,MedINRIA,3DSlicer等概率跟蹤常用軟件：FSL15整理pptPage16擴(kuò)散張量成像的研究?jī)?nèi)容纖維跟蹤算法基于DTI的應(yīng)用研究16整理pptPage17擴(kuò)散屬性測(cè)度以上三種情況的ADC=0.7x10-3mm2/s17整理pptPage1818整理pptPage1919整理pptPage2020整理pptPage21基于擴(kuò)散屬性測(cè)度的臨床研究基于全腦配準(zhǔn)的分析方法基于體素的統(tǒng)計(jì)分析（VBA）基于白質(zhì)骨架的空間統(tǒng)計(jì)分析（TBSS）基于感興趣區(qū)的分析方法手工畫感興趣區(qū)的方法基于纖維重建的定量分析21整理pptPage22Voxel-BasedAnalysis(VBA)VBMonFA(Ashburner,2000;Rugg-Gunn,2001)StrengthsFullyautomated&quickInvestigationwholebrainImplementationstepsPreprocessingNormalizationofFAimagesSmoothVoxelwisestatistics(e.g.controls–patients)IssuesAlignmentdifficult;smallestsystematicshiftsbetweengroupscanbeincorrectlyinterpretedasFAchangeNoobjectivewaytochoosesmoothingextent(6,8or10mm?)22整理pptPage2323整理pptPage2424整理pptPage2525整理pptPage2626整理pptPage2727整理pptPage2828整理pptPage2929整理pptPage3030整理ppt精神分裂癥患者的VBA分析

FA降低的腦區(qū)：????????cerebralpeduncle;frontalregions;inferiortemporalgyrus;medialparietallobes;hippocampalgyrus;Insula;rightanteriorcingulumbundle;rightcoronaradiata

Page31Haoetal.Neuroreport200631整理pptPage32Tract-BasedSpatialStatistics(TBSS)PartofFSLsoftware()OvercomethedrawbacksinVBAmethod,suchasalignmentissueandsmoothingissueFlowchart32整理pptPage33TBSSstepsindetail:preprocessing-createFAimagesfromyourdiffusionstudydatatbss_1_preproc-prepareyourFAdatainyourTBSSworkingdirectoryintherightformattbss_2_reg-applynonlinearregistrationofallFAimagesintostandardspacetbss_3_postreg-createthemeanFAimageandskeletoniseittbss_4_prestats-projectallsubjects'FAdataontothemeanFAskeletonstats(e.g.,randomise)-feedthe4DprojectedFAdataintoGLMmodellingandthresholdinginordertofindvoxelswhichcorrelatewithyourmodel.33整理pptPage34Docross-subjectvoxelwisestatsonskeleton-projectedFA34整理pptPage35Fig.TBSSresultsfrom15MSpatients.A,B:3DsurfacerenderingsofthemeanFAskeleton.C:YellowshowsthewhereFAcorrelatesnegativelywithEDSSdisabilityscore.D:Redasabove.InCandD,greenshowsthemeanFAskeleton,blueshowsthegroupmeanlesiondistribution,andthebackgroundimageistheMNI152.Smithetal.,NeuroImage,200635整理pptPage36Scholzetal.,NatureNeuroscience200936整理pptPage37TBSSdataacquisitionrequirement:

Voxelsizeshouldbelessthan3×3×3mm3.Atleastoneb=0shouldbeacquired;ideallyoneb=0imageforeveryeightdiffusion-weightedimages.b-valueshouldbeatleast800s/mm2.Atleastsix-gradientdirectionsmustbeacquired.itisbettertousemoreuniquesamplingdirections(withisotropicangulardensity18)thantoobtainrepeatsamplesofthesamesetofdirections.SNRinthediffusion-weightedimagesshouldbemaximized.AnexampleprotocolthatshouldleadtosufficientlyhighSNRishavingb=1,000smm–2,24diffusion-weightedimagesandSNRgreaterthan15intheb=0image.37整理pptPage38Thedatashouldnotbeupsampled(e.g.,throughunfilteredzero-paddingduringreconstruction)ifthisisdoneinsuchawayastointroduceringingintothedata.Ifmultiplerepeatsofb=0ordiffusion-weightedimagesaretobeacquired,theymustnotbeaveragedonthescanner(astheymustbecoregisteredbeforeaveraging,andanyriskofaveragingthecomplexdatashouldbeavoided).Fatsaturationshouldbeusedwheneverpossibletoremovesignalfromthescalp,whichcandisruptsignalinthebrainowingtochemicalshiftorghostingartifacts.Avitamincapsuleleft–rightmarker(oil,notwater)shouldbeattachedtotherightsideoftheheadtoavoidanyleft–rightambiguitiesduringdataconversionandanalysis.38整理pptPage39Computingequipment:Unix-basedcomputers.AppleMac(runningMacOSXversion10.4orhigher)andPCs(runningLinuxflavorsRedHat9,Enterprise,FC4,Suse9.0-9.3orDebian)HighRAMrequirements(particularlyiftensofsubjectsareusedinastudy),itislikelythatthecomputerwillneedtobe64bit.Thecomputershouldhaveatleasta1GHzCPUclock,1GBRAM,5GBs20GBfreeharddiskspace.Ifmultiplenetworkedcomputers(oracomputercluster)areavailable,theregistrationstepscanbeparallelized,greatlyreducingthetotalcomputationtime.39整理pptPage40白質(zhì)纖維束的定量分析FA:LeftCingulum(Red)>RightCingulum(Blue)ParameterizationprocessGongetal,HumanBrainMapping,200540整理pptPage41同正常人相比，早期盲人的視放射白質(zhì)擴(kuò)散異常，F(xiàn)A值顯著降低，ADC和λ23顯著升高。早期盲人大腦白質(zhì)擴(kuò)散異常研究Shuetal,HumanBrainMapping,200941整理pptPage42單張量模型的假設(shè)無法解決纖維交叉問題纖維跟蹤技術(shù)的準(zhǔn)確性缺乏嚴(yán)格的評(píng)價(jià)體系擴(kuò)散張量成像的局限性42整理pptPage43內(nèi)容提綱DTI的研究?jī)?nèi)容DTI數(shù)據(jù)處理流程DTIStudioFSL:FMRIB’sDiffusionToolbox43整理pptPage44數(shù)據(jù)處理的基本流程44整理pptPage45

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S5S6……45整理pptPage46PreprocessingDICOMdataconversionImagequalitycheckEddycurrentcorrection46整理pptPage47內(nèi)容提綱DTI的研究?jī)?nèi)容DTI數(shù)據(jù)處理流程DTIStudioFSL:FMRIB’sDiffusionToolbox47整理pptPage48DTIStudioDownload&InstallUserManualMailinglist48整理pptPage49LaunchingtheProgramandHardwareRequirementDtiStudio-latest-x86.exeforWindowssystemMorethan1GBRAMisrecommended49整理pptPage50MainFunctionsImageViewerDiffusionTensorCalculationFiberTrackingandEditing3DVisualizationImageROIDrawingandStatistics50整理pptPage51Howtodotensorcalculationandfibertracking?51整理pptPage52E:\work\Training\ExampleDataRawdata:MRIcroNdcm2nii.exe(.img,.hdr,.bvec,.bval)Eddycurrentcorrection:AIRTensor,FA,MDcalculation:DTIstudioFibertractography:DTIstudioROIselection52整理pptPage53第一步：對(duì)原始DICOM數(shù)據(jù)進(jìn)行格式轉(zhuǎn)換。利用MRIcroN軟件中的dcm2nii.exe工具，將DTI原始數(shù)據(jù)文件夾拖入，即可得到DTI掃描的梯度編碼文件.bval和.bvec，以及轉(zhuǎn)換后的NIFTI格式的圖像文件（OutputFormat選擇4DNIfTIhdr/img）。53整理pptPage54第二步：對(duì)DTI圖像進(jìn)行頭動(dòng)和渦流校正。打開DTIstudio,File->MRIView3D,選中上一步得到的4D.img文件，ImageParameters中選擇Image為Analyze，點(diǎn)擊OK，然后在Image面板ImageProcessing區(qū)域選擇AutomaticImageRegistration(AIR)，按圖3進(jìn)行設(shè)置，然后點(diǎn)擊OK，等圖像配準(zhǔn)完成后，在Image面板的OrthogonalViews區(qū)域的文件下拉框中看到Air_開頭的一系列文件，為校正后的DTI圖像文件，點(diǎn)擊Save，將Air_開頭的所有文件選中，選擇RawData，保存為一個(gè)4D的.dat文件。MRIView3D參數(shù)54整理pptPage55AIR的參數(shù)設(shè)置55整理pptPage56頭動(dòng)和渦流校正后的DTI圖像保存56整理pptPage57第三步：張量解算以及FA,ADC等擴(kuò)散指標(biāo)的計(jì)算。打開DTIstudio,File->DTIMapping,選擇PhilipsREC格式，Continue，按圖5進(jìn)行參數(shù)設(shè)置，Addafile中選中上一步保存的4D.dat文件，點(diǎn)擊OK，在DtiMap面板的Calculation區(qū)域選中Tensor,ColorMapetc.（計(jì)算ADC值選擇ADC-Map），根據(jù)圖像選擇噪聲水平，點(diǎn)擊OK，然后等DTIStudio算完后在Image面板的OrthogonalView區(qū)域可看到計(jì)算出來的各種擴(kuò)散屬性文件。對(duì)于想要保存的文件，如FA,EigenVector-0，ColorMap-0等可以分別進(jìn)行Save（.dat格式），便于下一次查看和使用。57整理pptPage58DtiMap面板進(jìn)行張量解算58整理pptPage59各種擴(kuò)散屬性的顯示59整理pptPage60第四步：纖維跟蹤及可視化。第一種方法：基于前面步驟，在DtiMap面板的FiberTracking區(qū)域點(diǎn)擊FiberTracking，然后進(jìn)行參數(shù)設(shè)置，點(diǎn)擊OK，就會(huì)進(jìn)行基于全腦體素（FA>0.2）的纖維重建；第二種方法：如果上一步已保存FA和EigenVector-0文件，可重新打開DTIStudio,File->Fiber-Tracking，選上FA-Map文件和PrincipleVector文件，并進(jìn)行參數(shù)設(shè)置，點(diǎn)擊OK，就會(huì)進(jìn)行基于全腦體素（FA>0.2）的纖維重建。通過任何一種方法，算完后右下角會(huì)出現(xiàn)Fiber面板，再此面板中可以對(duì)特定纖維束進(jìn)行顯示和編輯，并可以對(duì)纖維屬性進(jìn)行統(tǒng)計(jì)分析。60整理pptPage61纖維跟蹤方法261整理pptPage62纖維跟蹤的參數(shù)設(shè)置62整理pptPage63重建纖維束的可視化63整理pptPage6464整理pptPage65MajorwhitemattertractsReference:WakanaS,CaprihanA,PanzenboeckMM,etal.,Reproducibilityofquantitativetractographymethodsappliedtocerebralwhitematter.Neuroimage,2007,36(3):630-644.65整理pptPage66纖維屬性的統(tǒng)計(jì)分析66整理pptPage67NewModulesROIEditorR