Parcellationofthethalamusbasedongraymattervolumecovarianceinhealthymales / 实用放射学杂志

ABSTRACT

Objective Toexplorethefeasibilityandaccuracyofsegmentationofthethalamusinhealthymaleswithgraymatter volumecovariance(GMVC)covariancepattern.Methods T1 3DstructuralMRIdatawerecollectedin103 maleparticipants [age from19to50y,mean＝(35.5±7.7)y,educationfrom6to16y,mean＝(10.5±2.3)y].AfterpreprocessedbyCAT12softwarewith standardprocedure (registration,segmentation,modulationandsmooth),thevoxelGwisebilateralthalamusgray mattervolume (GMV)andthewholebrain’svoxelGwiseGMVdatawereextractedtocalculatethecovariancematrixofallparticipants.ExtendedKGmeans clusteringalgorithm wasappliedtosegmentthalamusintosubGareas.RandomsubGsamplingandcrossingGvalidationtechniquewere usedtogenerate100subGdatasetsandverifythesimilarityindex.Cramers’V (CV)wascalculatedandtheKrelevanttothehighest meanofCV wasdeterminedastheoptimalnumberofsubGareasforthalamus.Results Theleftandrightthalamuswereoptimally segmentedinto11and13subGareasbyGMVcovariancepattern.BoththeleftandrightthalamuscomprisesAnteriorNuclear,ventral anteriornucleus,lateraldorsalnucleus,lateralposteriornucleus,ventrallateralnucleus,ventralposteriormedialnucleus,ventralposterior lateralnucleus,midlinenucleus,medialdorsalnucleusandpulvinar.Additionally,fortherightthalamus,anteriornucleargroupwas dividedinto2parts,dorsalpartandventralpart,andthemidlinenucleusintomedialpartandlateralpart.Thelateraldorsalandlateral posteriornucleusweremergedintolateralnucleargroup.Fortheleftthalamus,thelateralposteriornucleuswasfurtherdividedinto2 parts,anteriorpartandposteriorpart.Thesegmentationresultswerealmostalinewiththeanatomical14partitionofthalamus.Conclusion TheparcellationbasedonGMVCcovariancepatternisaneffectiveandreliabletoolforsegmentationofbraingraymatternucleus. Ourfindingsprovideexperimentbasisforthalamusfunctionalandstructuralstudyinthefutureandoptimaltreatmenttargetforneurosurgery anddeepbrainstimulustherapy.