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外文资料-- Glioma Tissue Modeling by Combing the Information of MRI and in vivo Multivoxel MRS.PDF

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外文资料-- Glioma Tissue Modeling by Combing the Information of MRI and in vivo Multivoxel MRS.PDF

GLIOMATISSUEMODELINGBYCOMBINGTHEINFORMATIONOFMRIANDINVIVOMULTIVOXELMRSWEIBEIDOU,AOYANDONG,PINGCHITSINGHUANATIONALLABORATORYFORINFORMATIONSCIENCEANDTECHNOLOGYDEPTOFELECTRONICENGINEERING,TSINGHUAUNIVERSITY,BEIJING,100084,PRCHINAEMAILDOUWBTSINGHUAEDUCNSHAOWULINEUROIMAGINGCENTEROFTIANTANHOSPITALCAPITALMEDICALUNIVERSITY,BEIJING,PRCHINAJEANMARCCONSTANSUNITD’IRM,EA3916,CHRUCAEN,FRANCEABSTRACTTHISPAPERPRESENTSAGLIOMAMODELIZATIONMETHODANDAREGRESSIONLIKEMODELTOCREATEAGRADUALLYGLIOMAIMAGEGLIOIMMULTIMODALSIGNAL,IMAGESOFMAGNETICRESONANCEIMAGINGMRIANDINVIVOMULTIVOXELMRSPECTROSCOPYMRSARECOMBINEDBYTHEREGRESSIONLIKEMODELWITHSPATIALRESOLUTIONREGISTRATIONTHISMODELINGMETHODCONSISTSOFFEATUREMODELSOFGLIOMASUCHASTHESIGNALINTENSITYOFMRIMAGEANDTHEMETABOLITECHANGESOFMRS,THECORRELATIONMODELNOTEDASMETABOLITESRATIOMETARANDTHECOMBINEDREGRESSIONLIKEMODELTHEESTIMATEDGLIOIMINCLUDESBOTHBRAINSTRUCTUREANDGLIOMAGRADEINFORMATIONANONLINEARMODELISPROPOSEDANDVALIDATEDINTHISPAPERTHETESTINGDATAISACQUIREDBYSIEMENSTRIOTIM3TANDSYNGOMRB15ATBEIJINGTIANTANHOSPITALOFCHINATHEMRSOFTHREEGLIOMAPATIENTS,TWOAFFECTEDBYASTROCYTOMAANDONEBYGLIOMA,ANDTHECHEMICALSHIFTIMAGINGCSIREFERENCET2IMAGESWERECONSIDEREDINOURVALIDATIONEXPERIMENTTHERESULTINGGLIOIMSARECOMPAREDWITHGROUNDTRUTHPROVIDEDBYNEURORADIOLOGISTSOFTIANTANANDVERIFIEDWITHTHEIRPATHOLOGYREPORTTHEYREPORTTHATOURMETHODANDMODELAREVERYEFFICIENTKEYWORDSMRSPECTROSCOPY;BRAIN;GLIOMA;CHEMICALSHIFTIMAGING;MRI;IMAGE;MODELING;COMBINATIONIINTRODUCTIONTODIAGNOSEBRAINTISSUEABNORMALITIES,LIKETUMOR,IT’SNECESSARYTOUSEMULTISPECTRALMAGNETICRESONANCEIMAGESMRIS,SUCHAST1WEIGHT,T2WEIGHT,GADOLINIUM,FLAIRETCINORDERTOFINDSOMEOFTUMOR’SPROPERTIESSUCHASSIZE,POSITION,SORT,ANDRELATIONSHIPWITHOTHERTISSUES,ETCBUTTHETUMORTYPEANDGRADEAREUSUALLYDIAGNOSEDFROMHISTOPATHOLOGICALEXAMINATIONOFASURGICALSPECIMENHOWEVER,HYDROGEN11HMAGNETICRESONANCESPECTROSCOPYMRSISANONINVASIVEMRTECHNIQUETHATPROVIDESBIOCHEMICALINFORMATIONOFMETABOLITESTHEMAJORBIOCHEMICALCHARACTERISTICSCANNONINVASIVELYPROVIDEUSEFULINFORMATIONONBRAINTUMORTYPEANDGRADE1INMANYSTUDIES,INVIVO1HMRSHASBEENPRESENTEDFORDETERMININGTHETYPEANDGRADEOFTUMORS123SINCEINVIVOMRSMEASUREMENTSANDANALYSISAREDEPENDENTONTHEACQUISITIONTECHNICALTHATCOMPROMISETHESPATIALRESOLUTIONANDACCURACYFORRESULTINGMETABOLITEVALUES4,METABOLICCHANGESWITHDISEASEISFREQUENTLYSUBTLEANDDIFFUSEFURTHERMORE,BYCHEMICALSHIFTIMAGINGCSITECHNIQUE,THEMETABOLITEIMAGESSOCALLEDMRSPECTROSCOPICIMAGINGMRSICANBECREATEDBYMULTIVOXELMRSINFORMATION,BUTITISNOTVISUALLYINTERPRETABLEINTHESENSEOFASTRUCTURALMRI4SOTHAT,FORTHETUMORTISSUECLASSIFICATION,ITISIMPORTANTTHATMRSIISCOMBINEDWITHMRITOESTIMATETHEVARIATIONOFMETABOLITESANDTOYIELDMUCHINFORMATIONREGARDINGTISSUEDURINGMORETHANADECADE,AUTOMATICBRAINTUMORCLASSIFICATIONBYMRSHASBEENDEVELOPED5,BUTTHEMORECLEARDEFINITIONOFBRAINTUMORTYPEANDGRADEMAYBEOBTAINEDBYCOMBINATIONOFMRSIANDMRI5ATECHNIQUETODIFFERENTIATEGLIOBLASTOMAFROMMETASTASISLESIONSBYUSINGMRIANDMRSDATAHASBEENPUBLISHEDIN6WANGETALDESCRIBEDACLASSIFICATIONOFBRAINTUMORSBYUSINGFEATURESSELECTIONANDFUZZYCONNECTEDNESSIN7,THESEFEATURESAREEXTRACTEDFROMMRIANDMRSDATATHEREARETWODIFFICULTIESFORCOMBINGMRSIDATAANDMRIDATAFIRSTLY,THESEDATAAREFROMDIFFERENTMODALITIES,SOTHEYARENOTINTHESAMESPATIALRESOLUTION,VERYLOWSPATIALRESOLUTIONINVOXELFORMRSIANDHIGHSPATIALRESOLUTIONINPIXELFORMRISECONDLY,ONEMRIMAGECORRESPONDSTOTHEDISTRIBUTIONOFALLTISSUES,ORTISSUESTRUCTUREBUTONEMRSIMAGEISAPROJECTIONIMAGEWHICHCORRESPONDSTOONEMETABOLITEORRATIOBETWEENSEVERALMETABOLITESSOTHEDIFFERENTMETABOLITEVALUESMAKEVARIATIONMRSIMAGES,JUSTLIKETHEMAPPINGOFMETABOLITEDISTRIBUTIONSBYMRSIPRESENTEDIN8THEQUESTIONFORAPPLICATIONISHOWTOCOMBINETHESEMRSIMAGESANDMRIMAGESTOGIVEANAUTOMATICTISSUECLASSIFICATIONRESULTTHEKEYPOINTOFTHECOMBINATIONISHOWTOMODELTHEMETABOLITEDISTRIBUTIONFROMMRS,WHICHCORRESPONDSTOINFORMATIONFROMMRIMAGESFORAUTOMATICDESCRIPTIONOFBRAINTUMORTYPEANDGRADE,WEPROPOSEAMODELIZATIONMETHODOFGLIOMATISSUESBYCOMBINGTHEINFORMATION,FROMMRIMAGESANDMULITIVOXELMRSDATAITCANCREATEAMRSWEIGHTEDMRIMAGEAUTOMATICALLYWHICHKEEPSTHEHIGHSPATIALRESOLUTIONLIKEMRIMAGEANDTHEGREYLEVELSCORRESPONDTOTHEDETERIORATIONOFBRAINTISSUESTHESECONDPARTOFTHISPAPERINTRODUCESTHEGLIOMATISSUEFEATURESBOTHINMRSVALUESANDINMRIMAGESTHECOMBINATIONMODELINGOFTHETWOTYPESOFINFORMATIONISPRESENTEDINTHETHIRDSECTIONANDITSVALIDATIONISSHOWNINTHEFOURTHSECTIONTHECONCLUSIONABOUTOURRESEARCHISGIVENATTHEENDOFTHISPAPERTHISWORKISFUNDEDBYTSINGHUANATIONALLABORATORYFORINFORMATIONSCIENCEANDTECHNOLOGY(TNLIST)CROSSDISCIPLINEFOUNDATION9781424447138/10/25002010IEEEIIFEATURESMODELOFGLIOMATISSUEFOLLOWINGTHERESEARCHOFDIAGNOSINGBRAINTUMORBYMRIMAGESANDMRS,WECANSUMMARIZETWOTYPESOFCHARACTERISTICSOFGLIOMA,ONEISTHESIGNALINTENSITYOFT1WEIGHTANDT2WEIGHTIMAGES,ANDTHEOTHERONEISTHECHEMICALSHIFTVALUESOFMETABOLITESPRESENTEDBYMRSDATAASIGNALINTENSITYCHARACTERISTICSOFMRIMAGESWEHAVEPROPOSEDSOMEFUZZYMODELINGMETHODSOFDIFFERENTTUMOROUSCEREBRALTISSUESONMRIMAGESBASEDONFUSIONOFTISSUEFEATURESIN91011TABLEIDESCRIBESTHECHARACTERISTICSOFBRAINTISSUESBYCREATINGAGRADUALITYOFSIGNALINTENSITYASAFUNCTIONOFDIFFERENTTISSUESANDSEQUENCESOFMRI10,WHERECSFISTHEABBREVIATIONOFCEREBRALSPINALFLUID,GMTHEABBREVIATIONOFGRAYMATTER,ANDWMWHITEMATTERINTABLEI,THE“SEQS”ISSHORTFORSEQUENCESOFMRI”THESYMBOL“”PRESENTSAHYPERSIGNAL;ITMEANSTHATTHESIGNALINTENSITYISVERYHIGHANDTHEIMAGEISVERYBRIGHTTHESYMBOL“”PRESENTSAHYPOSIGNAL,THEINTENSITYISVERYLOWANDTHEIMAGEISVERYDARKTHESYMBOL“”MEANSTHATTHESIGNALINTENSITYISHIGHERTHANHYPOSIGNAL,AND“”MEANSTHATITISDARKERTHANHYPERSIGNAL“”MEANSTHATTHESIGNALINTENSITYISLOWERTHANTHEHYPOSIGNAL,AND“”MEANSTHATITISBRIGHTERTHANTHEHYPERSIGNALANEXAMPLEOFT1WEIGHTEDIMAGENOTEDAST1,ANDT2WEIGHTEDIMAGENOTEDAST2ARESHOWNINFIG1TABLEISIGNALINTENSITYCHARACTERISTICSOFBRAINTISSUESONMRIMAGESSEQUENCESGRADUALITYOFSIGNALINTENSITYCSFGMWMGLIOMAEDEMANECROSIST1T2ABFIGURE1ORIGINALMRIIMAGESAT1IMAGE,BT2IMAGEBMETABOLITECHANGESFEATURESOFMRSTABLEIISCALARDESCRIPTIONOFMETABOLITEVALUESMETABOLITELEVELABSENTVERYLOWLITTLELOWLOWMEDIUMLITTLEHIGHHIGHVERYHIGHABBREVIATIONAVLLLLMLHHVHTHEREAREONLYSEVERALMETABOLITESWHICHCORRESPONDTOGLIOMAAMONGALARGENUMBEROFMETABOLITESOFHUMANBODYNACETYLASPARATENAA,CREATINECR,CHOLINECHO,MYOINOSITOLMI,LACTATELACANDFREELIPIDSLIPTHEVARIATIONOFTHESEMETABOLITESCANBEORDEREDINASCALARFORMASSHOWNINTABLEII,WHERETHESCALARORDERISABSENT,VERYLOW,LITTLELOW,LOW,MEDIUM,LITTLEHIGH,HIGH,VERYHIGH,WHICHCORRESPONDTOMETABOLITEVALUESFROM0TOMAXIMUMTHEMETABOLICCHANGESWITHBRAINTISSUESARESHOWNINTABLEIIIITISCONCLUDEDFROM121314TABLEIIIMETABOLITECHANGESFEATURESOFBRAINTISSUESONMRSMETABOLITEVARIATIONOFMETABOLITESCORRESPONDINGWITHBRAINTISSUESCSFGMWMGLIOMAEDEMANECROSISNAAVLVHHL/VLMACHOAMLHH/VHLHACRLHHM/LLLAMILMLHHLH/MALIPAVLLHLVHLACLHVLAH/LHLHHIIIMODELIZATIONBYCOMBININGMRSWITHMRITHEAIMOFTHISMODELIZATIONSTUDYISTOCREATEAGRADUALLYGLIOMAIMAGE,NOTEDASGLIOIM,WHICHINCLUDESBRAINSTRUCTUREANDGLIOMAGRADEINFORMATIONIFTHEGLIOMAGRADEINFORMATIONISCONSIDEREDASACORRELATIONFUNCTIONBETWEENMRSIGNALANDPATHOLOGICALCHANGESWEPROPOSEAREGRESSIONLIKEMODELTOESTIMATETHEGLIOIMFROMMRIMAGESNOTEDASMRIMANDMETABOLITECHANGESACORRELATIONMODELONEOFTHECORRELATIONFUNCTIONSISMETABOLITECHANGESCORRESPONDINGTOGLIOMABYCOMBININGTHEINFORMATIONINTABLEIANDTABLEIII,WECANREBUILDACONCLUSIONTABLEIVABOUTGLIOMACHARACTERISTICSWITHRELATIVEQUANTIZATIONOFMETABOLITESOFTABLEIIITHERELATIVEQUANTIZATIONISRATIOSBETWEENMETABOLITEVALUES,SUCHASTHERATIOOFCHOANDNAANOTEDASCHO/NAAINTABLEIV,ITISCALLEDMETABOLITESRATIOMETAR,ANDTABLEIVISCALLEDCORRELATIONMODELINTHISPAPERTABLEIVMETABOLITESRATIOCHARACTERISTICOFBRAINTISSUESMETABOLITEVARIATIONOFMETABOLITESCORRESPONDINGWITHBRAINTISSUESCSFGMWMGLIOMAEDEMANECROSISCHO/NAAAVLLVHHACHO/CRALLHHAMI/CRMLMHHALIP/CRAVLVLHMVHLAC/CRLHVLAHHHTHEMETARCHARACTERISTICSOFGLIOMA,EDEMAANDNECROSISAREENHANCEDANDTHENORMALTISSUESAREREDUCEDTHEYASSORTWITHSIGNALINTENSITYCHARACTERISTICSOFT2WEIGHTEDIMAGEDESCRIBEDINTABLEIBREGRESSIONLIKEMODELWITHSPATIALRESOLUTIONREGISTRATIONNORMALY,METARISAFUNCTIONOFVOXELDECIDEDBYCSISLICESHOWNINFIG2SOTHAT,ITISATWODIMENSIONALFUNCTIONNOTEDASMETARI,V,WHERE“I”ISINDEXOFMETABOLITEAND“V”ISTHEINDEXOFVOXELCORRESPONDEDWITHCSISLICEASTHESAMEREASON,GLIOIMCANBECREATEDASATHREEDIMENSIONALFUNCTION,NOTEDASGLIOIMV,P,G,WHERE“P”ISINDEXOFPIXELCORRESPONDEDWITHMRIM,AND“G”ISTHEGREYLEVELOFSELECTEDMRIMAGEANDCORRESPONDSTO“P”INFACT,MRIMISATWODIMENSIONALFUNCTIONNOTEDASMRIMP,G,WHEREANDG∈G,{}1,2,,,,,TTPDFLAIRGADODIFFUSIONPERFUSIONGCONSIDERTWOVARIABLES,MRIMANDGLIOIM,MRIMISACERTAINIMAGELIKET2,GLIOIMISANESTIMATEDIMAGETHECORRELATIONMODELMETARCANBECONSIDEREDASONERELATIONSHIPBETWEENTHEMSOTHEREGRESSIONLIKEMODELFORESTIMATINGGLIOIMFROMMRIMCANBECREATEDASEQUATION1IM,,,IM,GLIOVPGMETARIVMRPGΘ1WHERE“Θ”NOTESANECESSARYOPERATOR,AND“P”CORRESPONDSTO“V”IFALINEARREGRESSIVEISNECESSARY,EQUATION1CANBEREWRITTENAS2IM,,,IM,,GLIOVPGMETARIVMRPGMETARJV2WHERE“I”AND“J”INDICATEDIFFERENTMETABOLITESCNONLINEARREGRESSIONLIKEMODELTOAVOIDMOSAICEFFECTS,WEPROPOSEANONLINEARREGRESSIONLIKEMODELWITHSPATIALRESOLUTIONREGISTRATIONIN3IM,IM,,EXP,MRPGGLIOVPGMETARIVMETARJVT⎡⎤⎢⎥⎣⎦3WHERE“T”ISATIMECONSTANTCORRESPONDINGTOMRIMP,GACCORDINGTOTHECORRELATIONMODELOFTABLEIV,THELIP/CRANDLAC/CRARESPECIFICFEATURESWHICHAREDEPENDENTONTHETUMORGRADESOTHAT,INTHEMODELOFEQUATION2,WEHAVE{},/,/,//,/IJMETARCHONAACHOCRMICRLIPCRLACCR∈∈IJIJIJ∪,BECAUSETHEJOFMETARISTHEGRADEMARKER,ITTAKESANINTERCEPTIVEROLETOMAKEADIFFERENTGREYLEVELFROMOTHERVOXELSANDINDICATESAVARIABLEGRADEIVVALIDATIONANDRESULTAMATERIELTHREEGLIOMAPATIENTS,TWOAFFECTEDBYASTROCYTOMAANDONEBYGLIOMA,WERECONSIDEREDINOURVALIDATIONEXPERIMENTTHETESTINGDATAAREADATAPAIRCONSISTEDOFCSIRAWDATAANDTHEIRREFERENCEIMAGESTHESEDATAWEREACQUIREDWITHSTEAMSEQUENCEATBEIJINGTIANTANHOSPITALCHINA,BYSIEMENSMRTRIOTIM3TANDSYNGOMRB15THEMRSRAWDATAAREMEASUREDBYCSI_ST/90PROTOCOLWITHTR3000/TE72/TM6T2WEIGHTEDIMAGESAREMEASUREDBYT2_TSE_TRAPROTOCOLWITHTR4500/TE80TWOEXAMPLESOFTHESEDATAARESHOWNINFIG2THENONLINEARREGRESSIONLIKEMODEL3ISVALIDATEDBYOURTESTINGEXPERIMENTATIONMRIMOF3IST2WITH057057MM2PIXELSIZEAND5MMSLICETHICKNESSTHETIMECONSTANTTIN3ISINDICATEDBYHISTOGRAMPEAKOFCSIREFERENCEIMAGESINT2THEMETABOLITEVALUESARECALCULATEDBYTHUMRSV05DEVELOPEDBYOURRESEARCHGROUPANDPUBLISHEDIN15THECSISLICESNOTETHATTHEMRSVOXELSIZEIS141420MM3AB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