AdvancesinExperimentalMedicine andBiology
Volume1093
EditorialBoard
IRUNR.COHEN, TheWeizmannInstituteofScience,Rehovot,Israel
ABELLAJTHA, N.S.KlineInstituteforPsychiatricResearch,Orangeburg, NY,USA
JOHND.LAMBRIS, UniversityofPennsylvania,Philadelphia,PA,USA
RODOLFOPAOLETTI, UniversityofMilan,Milan,Italy
NIMAREZAEI, TehranUniversityofMedicalSciences,Children’sMedical CenterHospital,Tehran,Iran
Moreinformationaboutthisseriesat http://www.springer.com/series/5584
GuoyanZheng • WeiTian • XiahaiZhuang
Editors
IntelligentOrthopaedics
ArtificialIntelligenceandSmart Image-guidedTechnologyfor Orthopaedics
Editor GuoyanZheng UniversityofBern Bern,Switzerland
XiahaiZhuang FudanUniversity Shanghai,China
WeiTian BeijingJishuitanHospital
PekingUniversity
Beijing,Beijing,China
ISSN0065-2598ISSN2214-8019(electronic) AdvancesinExperimentalMedicineandBiology
ISBN978-981-13-1395-0ISBN978-981-13-1396-7(eBook) https://doi.org/10.1007/978-981-13-1396-7
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©SpringerNatureSingaporePteLtd.2018
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1Computer-AidedOrthopaedicSurgery:State-of-the-Art andFuturePerspectives ..................................1 GuoyanZhengandLutz-P.Nolte
2Computer-AidedOrthopedicSurgery:IncrementalShift orParadigmChange? ....................................21 LeoJoskowiczandEricJ.Hazan
3CAMISSConceptandItsClinicalApplication ..............31 WeiTian,YajunLiu,MingxingFan,JingweiZhao,PeihaoJin, andChengZeng
4SurgicalNavigationinOrthopedics:WorkflowandSystem Review .................................................47 ChidozieH.Ewurum,YingyingGuo,SeangPagnha,ZhaoFeng, andXiongbiaoLuo
5Multi-objectModel-BasedMulti-atlasSegmentation ConstrainedGridCutforAutomaticSegmentationof LumbarVertebraefromCTImages .......................65 WeiminYu,WenyongLiu,LiwenTan,ShaoxiangZhang, andGuoyanZheng
6DeepLearning-BasedAutomaticSegmentationofthe ProximalFemurfromMRImages .........................73 GuodongZengandGuoyanZheng
7MuscleSegmentationforOrthopedicInterventions ..........81 NaokiKamiya
83X-Knee:ANovelTechnologyfor3DPreoperativePlanning andPostoperativeEvaluationofTKABasedon2DX-Rays ...93 GuoyanZheng,AlperAlcoltekin,BenediktThelen, andLutz-P.Nolte
9Atlas-Based3DIntensityVolumeReconstructionfrom2D LongLegStandingX-Rays:ApplicationtoHardandSoft TissuesinLowerExtremity ...............................105 WeiminYuandGuoyanZheng
103DUltrasoundforOrthopedicInterventions ................113 IlkerHacihaliloglu
11ANovelUltrasound-BasedLowerExtremityMotion TrackingSystem ........................................131 KenanNiu,VictorSluiter,JasperHomminga,AndréSprengers, andNicoVerdonschot
12Computer-AssistedPlanning,Simulation,andNavigation SystemforPeriacetabularOsteotomy .....................143 LiLiu,KlausSiebenrock,Lutz-P.Nolte,andGuoyanZheng
13BiomechanicalOptimization-BasedPlanning ofPeriacetabularOsteotomy .............................157 LiLiu,KlausSiebenrock,Lutz-P.Nolte,andGuoyanZheng
14BiomechanicalGuidanceSystemforPeriacetabular Osteotomy ..............................................169 MehranArmand,RobertGrupp,RyanMurphy,RachelHegman, RobertArmiger,RussellTaylor,BenjaminMcArthur, andJyriLepisto
15Gravity-AssistedNavigationSystemforTotal HipArthroplasty ........................................181 GuoyanZheng
163DVisualizationandAugmentedRealityforOrthopedics ....193 LongfeiMa,ZhenchengFan,GuochenNing,XinranZhang, andHongenLiao
17IntelligentHMIinOrthopedicNavigation .................207 GuangzhiWang,LiangLi,ShuweiXing,andHuiDing
18Patient-SpecificSurgicalGuidanceSystemforIntelligent Orthopaedics ...........................................225 ManuelaKunzandJohnF.Rudan
19IntelligentControlforHuman-RobotCooperation inOrthopedicsSurgery ..................................245 ShaolongKuang,YucunTang,AndiLin,ShumeiYu, andLiningSun
20MultilevelFuzzyControlBasedonForceInformation inRobot-AssistedDecompressiveLaminectomy ............263 XiaozhiQi,YuSun,XiaohangMa,YingHu,JianweiZhang, andWeiTian
21PotentialRiskofIntelligentTechnologiesinClinical Orthopedics ............................................281 YajunLiu
22ClinicalApplicationofNavigationintheSurgicalTreatment ofaPelvicRingInjuryandAcetabularFracture ............289 MasakiTakao,HidetoshiHamada,TakashiSakai, andNobuhikoSugano
23Patient-SpecificSurgicalGuideforTotalHipArthroplasty ...307 TakashiSakai
24ComputerNavigationinOrthopaedicTumourSurgery ......315 Kwok-ChuenWong,XiaohuiNiu,HairongXu,YuanLi, andShekharKumta
25Sensor-BasedSoftTissueBalancinginTotal KneeArthroplasty .......................................327 JimmyChow,TsunYeeLaw,andMartinRoche
26ImplantOrientationMeasurementAfterTHAUsing theEOSX-RayImageAcquisitionSystem ..................335 KunihikoTokunaga,MasashiOkamoto,andKenjiWatanabe
273DPrintinginSpineSurgery ..............................345 HongCai,ZhongjunLiu,FengWei,MiaoYu,NanfangXu, andZiheLi
Computer-AidedOrthopaedic Surgery:State-of-the-ArtandFuture Perspectives
GuoyanZhengandLutz-P.Nolte
Abstract
Introducedmorethantwodecadesago, computer-aidedorthopaedicsurgery(CAOS) hasemergedasanewandindependent area,duetotheimportanceoftreatment ofmusculoskeletaldiseasesinorthopaedics andtraumatology,increasingavailabilityof differentimagingmodalitiesandadvancesin analyticsandnavigationtools.Theaimof thischapteristopresentthebasicelements ofCAOSdevicesandtoreviewstate-of-theartexamplesofdifferentimagingmodalities usedtocreatethevirtualrepresentations, ofdifferentpositiontrackingdevicesfor navigationsystems,ofdifferentsurgical robots,ofdifferentmethodsforregistration andreferencing,andofCAOSmodulesthat havebeenrealizedfordifferentsurgicalprocedures.Futureperspectiveswillbeoutlined. Itisexpectedthattherecentadvancement onsmartinstrumentation,medicalrobotics, artificialintelligence,machinelearning,and deeplearningtechniques,incombinationwith bigdataanalytics,mayleadtosmartCAOS systemsandintelligentorthopaedicsinthe nearfuture.
G.Zheng( )·L.-P.Nolte InstituteforSurgicalTechnologyandBiomechanics, UniversityofBern,Bern,Switzerland e-mail: guoyan.zheng@istb.unibe.ch
©SpringerNatureSingaporePteLtd.2018
Keywords
Computer-aidedorthopaedicsurgery (CAOS)·Smartinstrumentation·Medical robotics·Artificialintelligence·Machine learning·Deeplearning·Bigdataanalytics· Intelligentorthopaedics
1.1Introduction
Thehumanmusculoskeletalsystemisanorgan systemthatincludesthebonesoftheskeletonand thecartilages,ligaments,andotherconnective tissuesthatbindtissuesandorganstogether.The mainfunctionsofthissystemaretoprovideform, support,stability,andmovementtothebody. Bones,besidessupportingtheweightofthebody, worktogetherwithmusclestomaintainbody positionandtoproducecontrolled,precisemovements.Musculoskeletaldiseaseisamongthe mostcommoncausesofseverelong-termdisabilityandpracticalpaininindustrializedsocieties [1].Theimpactandimportanceofmusculoskeletaldiseasesarecriticalnotonlyforindividual healthandmobilitybutalsoforsocialfunctioningandproductivityandeconomicgrowthona largerscale,reflectedbytheproclamationofthe BoneandJointDecade2000–2010[1].
G.Zhengetal.(eds.), IntelligentOrthopaedics,AdvancesinExperimentalMedicine andBiology1093, https://doi.org/10.1007/978-981-13-1396-7_1
Bothtraumatologyandorthopaedicsurgery aimatthetreatmentofmusculoskeletaltissues. Surgicalstepssuchastheplacementofanimplantcomponent,thereductionandfixationof afracture,ligamentreconstruction,osteotomy, tumourresection,andthecuttingordrillingof boneshouldideallybecarriedoutaspreciselyas possible.Notonlywilloptimalprecisionimprove thepost-operativeoutcomeofthetreatment,but itwillalsominimizetheriskfactorsforintraandpost-operativecomplications.Tothisend, alargenumberofpuremechanicalguideshave beendevelopedforvariousclinicalapplications. Thepuremechanicalguides,thougheasytouse andeasytohandle,donotrespecttheindividual patient’smorphology.Thus,theirgeneralbenefithasbeenquestioned(seeforexample[2]). Additionally,surgeonsoftenencounterthechallengeoflimitedvisibilityofthesurgicalsitus, whichmakesitdifficulttoachievetheintended procedureasaccuratelyasdesired.Moreover, therecenttrendtowardsincreasedminimally invasivesurgerymakesitmoreandmoreimportanttogainfeedbackaboutsurgicalactions thattakeplacesubcutaneously.JustasaGlobal PositioningSystem(GPS)-basedcarnavigation providesvisualinstructiontoadriverbydisplayingthelocationofthecaronamap,acomputeraidedorthopaedicsurgery(CAOS)moduleallowsthesurgeontogetreal-timefeedbackabout theperformedsurgicalactionsusinginformation conveyedthroughavirtualsceneofthesitus presentedonadisplaydevice[3, 4].Parallelto theCAOSmoduletopotentiallyimprovesurgical outcomeistheemploymentofsurgicalrobots thatactivelyorsemi-activelyparticipateinthe surgery[5].
Introducedmorethantwodecadesago[3–5], CAOShasemergedasanewandindependent areaandstandsforapproachesthatusecomputerenabledtrackingsystemsorroboticdevicesto improvevisibilitytothesurgicalfieldandincreaseapplicationaccuracyinavarietyofsurgicalprocedures.AlthoughCAOSmodulesuse numeroustechnicalmethodstorealizeindividual aspectsofaprocedure,theirbasicconceptual designisverysimilar.Theyallinvolvethreemajorcomponents:atherapeuticobject(TOinab-
breviation,whichisthetargetofthetreatment), avirtualobject(VOinabbreviation,whichis thevirtualrepresentationintheplanningand navigationcomputer),andaso-callednavigator thatlinksbothobjects.Forreasonsofsimplicity, theterm“CAOSsystem”willbeusedwithinthis articletorefertobothnavigationsystemsand roboticdevices.
ThecentralelementofeachCAOSsystemis thenavigator.Itisadevicethatestablishesa global,three-dimensional(3-D)coordinatesystem(COS)inwhichthetargetistobetreated andthecurrentlocationandorientationofthe utilizedendeffectors(EE)aremathematically described.Endeffectorsareusuallypassivesurgicalinstrumentsbutcanalsobesemi-activeor activedevices.Oneofthemainfunctionsof thenavigatoristoenablethetransmissionof positionalinformationbetweentheendeffectors, theTOandtheVO.Forroboticdevices,therobot itselfplaystheroleofthenavigator,whilefor surgicalnavigationapositiontrackingdeviceis used.
ForthepurposeofestablishmentofaCAOS systemthroughcoactionsofthesethreeentities, threekeyproceduralrequirementshavetobe fulfilled.Thefirstisthecalibrationoftheend effectors,whichmeanstodescribetheendeffectors’geometryandshapeinthecoordinate systemofthenavigator.Forthispurpose,itis requiredtoestablishphysicallyalocalcoordinate systemattheendeffectors.Whenanoptical trackerisused,thisisdoneviarigidattachmentofthreeormoreopticalmarkersontoeach endeffector.Thesecondisregistration,which aimstoprovideageometricaltransformation betweentheTOandtheVOinordertodisplay theendeffect’slocalizationwithrespecttothe virtualrepresentation,justlikethedisplayof thelocationofacarinamapinaGPS-based navigationsystem.Thegeometricaltransformationcouldberigidornon-rigid.Inliterature, awidevarietyofregistrationconceptsandassociatedalgorithmsexist(seethenextsection formoredetails).Thethirdkeyingredienttoa CAOSsystemisreferencing,whichisnecessary tocompensateforpossiblemotionofthenavigatorand/ortheTOduringthesurgicalactions
1Computer-AidedOrthopaedicSurgery:State-of-the-ArtandFuturePerspectives3
tobecontrolled.Thisisdonebyeitherattachingaso-calleddynamicreferencebases(DRB) holdingthreeormoreopticalmarkerstothe TOorimmobilizingtheTOwithrespecttothe navigator.
Therestofthechapterisorganizedasfollows. Section 1.2 willreviewthestate-of-the-artexamplesofbasicelementsofCAOSsystems.Section 1.3 willpresentclinicalfieldsofapplications.In Sect. 1.4,futureperspectiveswillbeoutlined, followedbyconclusioninSect. 1.5.
1.2BasicElementsofCAOS
Systems
1.2.1VirtualObject
TheVOineachCAOSsystemisdefinedasa sufficientlyrealisticrepresentationofthemusculoskeletalstructuresthatallowsthesurgeonto plantheintendedintervention,asexemplifiedin Fig. 1.1a Intra-operatively,italsoservesasthe “background”intowhichthemeasuredposition ofasurgicalinstrumentcanbevisualized(see Fig. 1.1b foranexample).Thoughmostofthe timeVOisderivedfromimagedataofthepatient,itcanalsobecreateddirectlyfromintraoperativedigitizationwithoutusinganymedical
imagedata.Belowdetailedexamplesofdifferent formsofVOswillbereviewed.
WhentheVOisderivedfrommedicalimage data,thesedatamaybeacquiredattwopointsin time:eitherpre-operativelyorintra-operatively. Twodecadesago,theVOsofmajorityCAOS systemswerederivedfrompre-operativelyacquiredCTscans,andafewgroupsalsotriedto usemagneticresonanceimaging(MRI)[6, 7].In comparisonwithMRI,CThasclearadvantages ofexcellentbone-softtissuecontrastandnogeometricaldistortiondespiteitsacquisitioninducingradiationexposuretothepatient.Soonafter theintroductionofthefirstCAOSsystems,the limitationsofpre-operativeVOswereobserved, whichledtotheintroductionofintra-operative imagingmodalities.Morespecifically,thebony morphologymayhavechangedbetweenthetime ofimageacquisitionandtheactualsurgicalprocedure.Asaconsequence,theVOmaynotnecessarilycorrespondtotheTOanymoreleading tounpredictableinaccuraciesduringnavigation orroboticprocedures.Thiseffectcanbeparticularlyadversefortraumatologyinthepresenceof unstablefractures.Toovercomethisproblemin thefieldofsurgicalnavigation,theuseofintraoperativeCTscanninghasbeenproposed[8],but theinfrastructuralchangesthatarerequiredfor therealizationofthisapproacharetremendous,
Fig.1.1 ExampleofCT-basednavigationalfeedback. ThesescreenshotsshowaCT-basedCAOSsystemduring pre-operativeplanning(a)andintra-operativenavigation
(b)ofpediclescrewplacement.(CourtesyofBrainlabAG, Munich,Germany)
Fig.1.2 Exampleoffluoroscopy-basednavigation.Thisscreenshotshowsthefluoroscopy-basednavigationfordistal lockingofanintramedullarynail.(CourtesyofBrainlabAG,Munich,Germany)
oftenrequiringconsiderablereconstructionofa hospital’sfacilities.Thishasmotivatedthedevelopmentofnavigationsystemsbasedonfluoroscopicimages[9–11].Theimageintensifieris awell-establisheddeviceduringorthopaedicand traumaproceduresbuthasthelimitationsthatthe imagesgeneratedwithafluoroscopeareusually distortedandthatone-dimensionalinformation getslostduetoimageprojection.Tousethese imagesasVOsthereforerequiresthecalibration ofthefluoroscopewhichaimstocomputetheimageprojectionmodelandtocompensateforthe imagedistortion[9–11].Theresultantsystems arethereforeknownas“fluoroscopy-basednavigationsystems”inliterature[9–11].Additional featureofferedbyafluoroscopy-basednavigation systemisthatmultipleimagesacquiredfrom differentpositionsareco-registeredtoacom-
moncoordinatesystemestablishedonthetarget structureviatheDRBtechnique.Suchasystem canthusprovidevisualfeedbackjustliketheuse ofmultiplefluoroscopesplacedatdifferentpositionsinconstantmodebutwithouttheassociated radiationexposure,whichisaclearadvantage (seeFig. 1.2 foranexample).Thistechnique isthereforealsoknownas“virtualfluoroscopy” [11].Despitethefactthatinsuchasystem,only two-dimensional(2-D)projectedimageswith lowcontrastareavailable,theadvantagesoffered byafluoroscopy-basednavigationsystempreponderateforanumberofclinicalapplications inorthopaedicsandtraumatology.
Inordertoaddressthe2-Dprojectionlimitationofafluoroscopy-basednavigationsystem, anewimagingdevicewasintroduced[12]that enablestheintra-operativegenerationof3-Dflu-
Fig.1.3 Navigationusingsurgeon-definedanatomyapproach.Thisvirtualmodelofapatient’skneeisgeneratedintra-operativelybydigitizingrelevantstructures.
oroscopicimagedata.Itconsistsofamotorized,isocentricC-armthatacquiresseriesof50–1002-Dprojectionsandreconstructsfromthem 13 × 13 × 13cm3 volumetricdatasetswhich arecomparabletoCTscans.Beinginitiallyadvocatedprimarilyforsurgeryattheextremities,this “fluoro-CT”hasbeenadoptedforusagewitha navigationsystemandhasbeenappliedtoseveral anatomicalareasalready[13, 14].Asamajor advantage,thedevicecombinestheavailability of3-Dimagingwiththeintra-operativedataacquisition.“Fluoro-CT”technologyisundercontinuousdevelopmentinvolvingsmallerandnonisocentricC-arms,“closed”C-arm,i.e.O-armTM design[15, 16],fasteracquisitionspeeds,larger fieldofview,andalsoflatpaneltechnology.
AlastcategoryofnavigationsystemsfunctionswithoutanyradiologicalimagesasVOs.Instead,thetrackingcapabilitiesofthesystemare
Althoughaveryabstractrepresentation,itprovidessufficientinformationtoenablenavigatedhightibialosteotomy
usedtoacquireagraphicalrepresentationofthe patient’sanatomybyintra-operativedigitization. Byslidingthetipofatrackedinstrumentonthe surfaceofasurgicalobject,thespatiallocationof pointsonthesurfacecanberecorded.Surfaces canthenbegeneratedfromtherecordedsparse pointcloudsandusedasthevirtualrepresentationofthesurgicalobject.Becausethismodelis generatedbytheoperator,thetechniqueisthereforeknownas“surgeon-definedanatomy”(SDA) (Fig. 1.3).Itisparticularlyusefulwhensoft tissuestructuressuchasligamentsorcartilage boundariesaretobeconsideredthataredifficult toidentifyonCTsorfluoroscopicimages[17]. Moreover,withSDA-basedsystems,somelandmarkscanbeacquiredevenwithoutthedirect accesstotheanatomy.Forinstance,thecentreof thefemoralhead,whichisanimportantlandmark duringtotalhipandkneereplacement,canbe
Fig.1.4 Anexampleofbonemorphing.Screenshots ofdifferentstagesofanintra-operativebonemorphing process.(a)Pointacquisition;(b)calculationofmorphed
model;and(c)verificationoffinalresult.(Courtesyof BrainlabAG,Munich,Germany) calculatedfromarecordedpassiverotationof thelegabouttheacetabulum.Itshouldbenoted thatthegeneratedrepresentationsareoftenrather abstractandnoteasytointerpretasexemplified inFig. 1.3.Thishasmotivatedthedevelopment oftheso-called“bonemorphing”techniques[18, 19],whichaimtoderiveapatient-specificmodel fromagenericstatisticalformsofthetarget anatomicalstructureandasetofsparsepoints thatareacquiredwiththeSDAtechnique[20]. Astheresult,arealisticvirtualmodelofthe targetstructurecanbepresentedandusedasa VOwithoutanyconventionalimageacquisition (Fig. 1.4).
1.2.2Registration
Positiondatathatisusedintra-operativelytodisplaythecurrenttoollocation(navigationsystem) ortoperformautomatedactionsaccordingtoa pre-operativeplan(robot)areexpressedinthe localcoordinatesystemoftheVO.Ingeneral, thiscoordinatesystemdiffersfromtheonein whichthenavigatoroperatesintra-operatively.In ordertobridgethisgap,themathematicalrelationshipsbetweenbothcoordinatespacesneed tobedetermined.Whenpre-operativeimages areusedasVOs,thisstepisperformedinteractivelybythesurgeonduringtheregistration,also knownasmatching.Awidevarietyofdifferent approacheshavebeendevelopedandrealized followingnumerousmethodologies[21].
EarlyCAOSsystemsimplementedpairedpointmatchingandsurfacematching[22].The operationalprocedureforpaired-pointmatching issimple.PairsofdistinctpointsaredefinedpreoperativelyintheVOandintra-operativelyinthe TO.ThepointsontheVOareusuallyidentified pre-operativelyusingthecomputermouse,while thecorrespondingpointsontheTOareusually doneintra-operativelywithatrackedprobe. Inthecaseofanavigationsystem,theprobe istrackedbythenavigator,andforarobotic surgery,itismountedontotherobot’sactuator [23].Althoughpaired-pointmatchingiseasyto solvemathematically,theaccuracyoftheresultantregistrationislow.Thisisduetothefactthat theaccuracyofpaired-pointmatchingdepends onanoptimalselectionoftheregistrationpoints andtheexactidentificationoftheassociated pairswhichiserrorprone.Oneobvioussolution tothisproblemistoimplantartificialobjectsto createeasilyandexactlyidentifiablefiducials foranaccuratepaired-pointmatching[23]. However,therequirementofimplantingthese objectsbeforetheinterventioncausesextra operationaswellasassociateddiscomfortand infectionriskforthepatient[24].Consequently, noneofthesemethodshavegainedwideclinical acceptance.Theotheralternativethathasbeen widelyadoptedinearlyCAOSsystemsisto complementthepaired-pointmatchingwith surfacematching[25, 26],whichdoesnotrequire implantinganyartificialobjectandonlyusesthe surfacesoftheVOasabasisforregistration.
Othermethodstocomputetheregistration transformationwithouttheneedforextensive pre-operativepreparationutilizeintra-operative imagingsuchascalibratedfluoroscopicimages orcalibratedultrasoundimages.Asdescribed above,alimitednumberoffluoroscopicimages (e.g.two)acquiredatdifferentpositionsarecalibratedandco-registeredtoacommoncoordinate systemestablishedonthetargetstructure.Asocalled“2-D-3-Dregistration”procedurecanthen beusedtofindthegeometricaltransformation betweenthecommoncoordinatesystemanda pre-operativelyacquired3-DCTdatasetbymaximizingasimilaritymeasurementbetweenthe2Dprojectiverepresentationsandtheassociated digitallyreconstructedradiographs(DRRs)that arecreatedbysimulatingX-rayprojections(see Fig. 1.5 foranexample).Intensity-basedaswell asfeature-basedapproacheshavebeenproposed before.Foracomprehensivereviewofdifferent2-D-3-Dregistrationtechniques,wereferto [21].
Anotheralternativeistheemploymentof intra-operativeultrasonography.Ifanultrasound probeistrackedbyanavigatorandits measurementsarecalibrated,itmayserveasa spatialdigitizerwithwhichpointsorlandmarks onthesurfacesofcertainsubcutaneousbony structuresmaybeacquired.Thisisdifferent fromthetouch-baseddigitizationdonewith
aconventionalprobewhichusuallyrequires aninvasiveexposureofthesurfacesofthe targetstructures.Twodifferenttrackedmode ultrasoundprobesareavailable.A(amplitude)modeultrasoundprobescanmeasurethe depthalongtheacousticaxisofthedevice. Placedonthepatient’sskin,theycanmeasure percutaneouslythedistancetotissueborders, andtheresultingpointcoordinatescanbe usedasinputstoanyfeature-basedregistration algorithm.Theapplicabilityofthistechniquehas beendemonstratedpreviouslybutwithcertain limitationswhichpreventitswideusage[27, 28]. Morespecifically,theaccuracyoftheA-mode ultrasoundprobe-baseddigitizationdependson howwelltheprobecanbeplacedperpendicularly tothesurfacesofthetargetbonystructures, whichisnotaneasytaskwhenthesubcutaneous softtissuesarethick.Moreover,thevelocityof soundduringtheprobecalibrationisusually differentfromthevelocityofsoundwhenthe probeisusedfordigitizationasthelatterdepends onthepropertiesofthetraversedtissues.Such avelocitydifferencewillleadtounpredictable inaccuracieswhentheprobeisusedtodigitize deeplylocatedstructures.Asaconsequence, thesuccessfulapplicationofthistechnique remainslimitedtoanarrowfieldofapplication. IncontrasttoanA-modeprobe,aB(brightness)modeultrasoundprobescansafan-shapedarea.
Fig.1.5 AnexampleofCT-fluoromatching.Screenshots ofdifferentstagesofaCT-fluoromatchingprocess.(a) PreregistrationforCT-fluoromatchingand(b)resultsof CT-fluoromatching.(CourtesyofBrainlabAG,Munich, Germany)
Itisthereforeabletodetectalsosurfacesthat areexaminedfromanobliquedirection,though theerrorscausedbythevelocitydifference stillpersist.Inordertoextracttherelevant informationfortheregistrationofpre-operative CTscans,theresulting,usuallynoisyimages needtobeprocessed[29].Asfortheintraoperativeprocessingoffluoroscopicimages,the useofB-modeultrasoundforregistrationisnot reliableineverycaseandconsequentlyremains thesubjectofCAOSresearch[30, 31].
ItisworthtopointoutthatiftheVOis generatedintra-operatively,registrationisaninherentprocess[21].Thisisduetothefactthat sincetheimagingdeviceistrackedduringdata acquisition,thepositionofanyacquiredimage isrecordedwithrespecttothelocalcoordinate systemestablishedontheTO.Therecordeddeviceposition,togetherwiththeadditionalimage calibrationprocess,automaticallyestablishesthe spatialrelationshipbetweentheVOandtheTO duringimageacquisition,whichisaclearadvantageovertheinteractiveregistrationinthecaseof pre-operativeimagesservingasVOs.Therefore, registrationisnotanissuewhenusingintraoperativeCT,2-D,3-DfluoroscopyorO-arm,or theSDAconcept.
Radermacheretal.[32]introducedanalternativewaytomatchpre-operativeplanning withtheintra-operativesituationusingindividual templates.Theprincipleofindividualizedtemplatesistocreatecustomizedtemplatesbased onpatient-specific3-Dbonemodelsthatare normallysegmentedfrompre-operative3-Ddata suchasCTorMRIscan.Onefeatureaboutthe individualtemplatesisthatsmallreferenceareas ofthebonestructuresareintegratedintothe templatesasthecontactfaces.Bythismeans,the plannedpositionandorientationofthetemplate inspatialrelationtothebonearestoredinastructuralwayandcanbereproducedintra-operatively byadjustingthecontactfacesofthetemplates untilanexactfittotheboneisachieved.By integratingholesand/orslots,individualizedtemplatesfunctionastoolguides,e.g.forthepreparationofpediclescrewholes[32]orascuttingjigsusedintotalkneeandhipreplacement surgery[33–35].
1.2.3Navigator
RegistrationclosesthegapbetweenVOandTO. Thenavigatorenablesthisconnectionbyprovidingaglobalcoordinatespace.Inaddition,itlinks thesurgicalendeffectors,withwhichaprocedure iscarriedout,totheTOthattheyactupon.From atheoreticalstandpoint,itistheonlyelementin whichsurgicalnavigationsystemsandsurgical roboticsystemsdiffer.
1.2.3.1Robots
ForthistypeofCAOStechnology,therobot itselfisthenavigator.Intra-operatively,ithasto beregisteredtotheVOinordertorealizethe planthatisdefinedinthepre-operativeimage dataset.Theendeffectorsofarobotareusually designedtocarryoutspecifictasksaspartofthe therapeutictreatment.Dependingonhowtheend effectorsofarobotactonthepatient,twodifferenttypesofrobotscanbefoundinliterature.The so-calledactiverobotsconductaspecifictask autonomouslywithoutadditionalsupportbythe surgeon.Suchasystemhasbeenappliedfortotal jointreplacement[5],buttheirclinicalbenefithas beenstronglyquestioned[36].Fortraumatology applications,theuseofactiverobotshasonly beenexploredinthelaboratorysetting[37, 38]. Onepossibleexplanationisthatthenatureof fracturetreatmentisanindividualizedprocess thatdoesnotincludemanystepsthatanactive robotcanrepetitivelycarryout.
Incontrasttoactiveroboticdevices,passiveor semi-activerobotsdonotcarryoutapartofthe interventionautonomouslybutratherguideorassistthesurgeoninpositioningthesurgicaltools. Atpresenttherearetworepresentativesofthis class,bothforboneresectionduringtotalknee arthroplasty(TKA).TheNaviosystem(BlueBelt TechnologiesInc.Pittsburgh,PA,USA)[39]is ahand-heldsemi-activerobotictechnologyfor boneshapingthatallowsasurgeontomovefreely inordertoresecttheboneaslongasthismotion stayswithinapre-operativelydefinedsafetyvolume.TheMakosystem[40]isapassiverobotic armsystemprovidingorientalandtactileguidance.BoththeNavioandtheMakosystemsrequireadditionaltrackingtechnologyasdescribed
inthenextsub-section.Duringthesurgicalprocedure,thesystemisunderthedirectsurgeon controlandgivesreal-timetactilefeedbacktothe surgeon.Othersemi-activerobotssuchasSpineAssist(MazorRoboticsLtd.,Israel)canbeseen asintelligentgaugesthatplace,forexample,cuttingjigsordrillingguidesautomatically[41, 42].
1.2.3.2Tracker
Thenavigatorofasurgicalnavigationsystemis aspatialpositiontrackingdevice.Itdetermines thelocationandorientationofobjectsandprovidesthesedataas3-Dcoordinatesor3-Drigid transformations.Althoughanumberoftrackingmethodsbasedonvariousphysicalmedia, e.g.acoustic,magnetic,optical,andmechanical methods,havebeenusedintheearlysurgical navigationsystems,mostoftoday’sproductsrely uponopticaltrackingofobjectsusingoperating room(OR)compatibleinfraredlightthatiseither activelyemittedorpassivelyreflectedfromthe trackedobjects.Totracksurgicalendeffectors withthistechnologythenrequiresthetoolstobe adaptedwithreferencebasesholdingeitherlightemittingdiodes(LED,active)orlight-reflecting spheresorplates(passive).Trackingpatterns withknowngeometrybymeansofvideoimages hasbeensuggested[43, 44]asaninexpensive alternativetoaninfrared-lightopticaltracker.
Opticaltrackingofsurgicalendeffectorsrequiresadirectlineofsightbetweenthetracker andtheobservedobjects.ThiscanbeacriticalissueintheORsetting.Theuseofelectromagnetic trackingsystemshasbeenproposedtoovercome thisproblem.Thistechnologyinvolvesahomogeneousmagneticfieldgeneratorthatisusually placedneartothesurgicalsitusandtheattachmentofreceivercoilstoeachoftheinstruments allowingmeasuringtheirpositionandorientation withinthemagneticfield.Thistechniquesenses positionsevenifobjectssuchasthesurgeon’s handareinbetweentheemittercoilandthe trackedinstrument.However,thehomogeneity ofthemagneticfieldcanbeeasilydisturbedby thepresenceofcertainmetallicobjectscausingmeasurementartefactsthatmaydecreasethe achievableaccuracyconsiderably[45, 46].There-
fore,magnetictrackinghasbeenemployedonly inveryfewcommercialnavigationsystemsand withlimitedsuccess.
Recentlyinertialmeasurementunit(IMU)basednavigationdeviceshaveattractedmore andmoreinterests[47–51].Thesedevicesattempttocombinetheaccuracyoflarge-console CAOSsystemswiththefamiliarityofconventionalalignmentmethodsandhavebeensuccessfullyappliedtoapplicationsincludingTKA [47, 48],pediclescrewplacement[49],andperiacetabularosteotomy(PAO)surgery[50, 51]. Withsuchdevices,theline-of-sightissuesin theopticalsurgicalnavigationsystemscanbe completelyeliminated.Technicallimitationsof suchdevicesinclude(a)relativelyloweraccuracy incomparisonwithopticaltrackingtechnique and(b)difficultyinmeasuringtranslations.
1.2.4Referencing
Intra-operatively,itisunavoidablethattherewill berelativemotionsbetweentheTOandthe navigatorduetosurgicalactions.Suchmotions needtobedetectedandcompensatedtosecure surgicalprecision.Forthispurpose,theoperated anatomyislinkedtothenavigator.Forrobotic surgerythisconnectionisestablishedasaphysicallinkage.Largeactiverobots,suchasthe earlymachinesusedfortotaljointreplacement, comewithaboneclampthattightlygripsthe treatedstructureorinvolveanadditionalmultilinkarm,whilesmalleractiveandsemi-active devicesaremounteddirectlyontothebone.For allothertrackertypes,bonemotionisdetermined bytheattachmentofaDRBtotheTO[52], whichisdesignedtohouseinfraredLEDs,reflectingmarkers,acousticsensors,orelectromagneticcoils,dependingontheemployedtracking technology.Figure 1.6 showsanexampleofa DRBforanactiveopticaltrackingsystemthat isattachedtothespinousprocessofalumbar vertebra.SincetheDRBisusedasanindicator toinformthetrackerpreciselyaboutmovements oftheoperatedbone,astablefixationthroughout theentiredurationoftheprocedureisessential.
Fig.1.6 Dynamicreferencebase.Adynamicreference baseallowsanavigationsystemtotracktheanatomical structurethatthesurgeonisoperatingon.Inthecaseof spinalsurgery,thisDRBisusuallyattachedtotheprocessusspinosuswiththehelpofaclampingmechanism.It isessentialthatitremainsrigidlyaffixedduringtheentire usageofthenavigationsystemonthatvertebra
1.3ClinicalFields ofApplications
Sincethemid-1990swhenfirstCAOSsystems weresuccessfullyutilizedfortheinsertionof pediclescrewsatthelumbarandthoracicspine andtotalhipreplacementprocedures[3, 4],a largenumberofmodulescoveringawiderange oftraumatologicalandorthopaedicapplications havebeendeveloped,validatedinthelaboratory andinclinicaltrials.Someofthemneededto beabandoned,becausetheanticipatedbenefit failedtobeachievedorthetechnologyproved tobeunreliableortoocomplextobeusedintraoperatively.Discussingalltheseapplications wouldgobeyondthefocusofthisarticle.Thus, herewefocusonareviewofthemostimportant applicationswiththemostoriginaltechnological approaches.
Whiletherewasclearlyonepioneering exampleofrobot-assistedorthopaedicsurgery–ROBODOC[5]–thefirstspinalnavigation systemswererealizedindependentlybyseveral researchgroups,almostinparallel[3, 4, 52–56]. Thesesystemsusedpre-operativeCTscansas theVO,relieduponpaired-pointandsurface matchingtechniquesforregistration,andwere basedonopticalorelectromagnetictrackers. Theirinitialclinicalsuccess[57–59]boosted thedevelopmentofnewCAOSsystemsand modules.Whilesomegroupstriedtousethe existingpediclescrewplacementsystemsfor otherclinicalapplications,othersaimedtoapply theunderlyingtechnicalprincipletonewclinical challengesbydevelopinghighlyspecialized navigationsystems[60, 61].Withtheadventof alternativeimagingmethodsforthegeneration ofVOs,theindicationfortheuseofoneorthe othermethodwasevaluatedmorecritically.For instance,itbecameevidentthatlumbarpedicle screwinsertioninthestandarddegenerativecase couldbecarriedoutwithfluoroscopy-based navigationsufficientlyaccurate,thusavoiding theneedforapre-operativeCT.
Asimilardevelopmenttookplacefortotal kneereplacement.Initially,thisprocedurewas supportedbyactive[36, 62]andsemi-activeor passive[39, 40]robots,aswellasnavigation systemsusingpre-operativeCTs[63],butwitha fewexceptions,theSDAapproach[64]istoday’s methodofchoice.
Fluoroscopy-basednavigationstillseemsto havealargepotentialtoexplorenewfieldsof application.Thetechnologyhasbeenmainly usedinspinalsurgery[65].Effortstoapplyit tototalhiparthroplasty(THA)[66]andthe treatmentoflong-bonefractures[67]havebeen commerciallylesssuccessful.Theintra-operative 3-DfluoroscopyorO-armhasbeenexplored intensively[13–16].Itisexpectedthatwith theadventoftheflatpaneltechnology,theuse offluoro-CTasavirtualobjectgeneratorwill significantlygrow[16].
Recently,computer-assistedsurgeryusingindividualtemplateshasgainedincreasingattention.Initiallydevelopedforpediclescrewfixation[32],suchatechniquehasbeensuccessfully
Fig.1.7 Patient-specificinstrumentationforpelvictumourresectionsurgery.Theseimagesshowthe applicationofpatient-specificinstrumentationfor pelvictumourtreatment.Implantandtemplate manufacturedbyMobelifeNV,Leuven,Belgium.
reintroducedtothemarketfortotalkneearthroplasty[33, 68, 69],hipresurfacing[34, 70],total hiparthroplasty[35],andpelvictumourresection [71, 72](seeFig. 1.7 foranexample).Itshould benotedthatmostoftheindividualtemplates areproducedusingadditivemanufacturingtechniques,whilemostoftheassociatedimplantsare producedconventionally.
1.4FuturePerspectives
Despiteitstoutedadvantages,suchasdecreased radiationexposuretothepatientandthesurgicalteamforcertainsurgicalproceduresand increasedaccuracyinmostsituations,surgical navigationhasyettogaingeneralacceptance amongorthopaedicsurgeons.Althoughissues relatedtotraining,technicaldifficulty,andlearningcurvearecommonlypresumedtobemajor barrierstotheacceptanceofsurgicalnavigation,
(a)Apre-operativeX-rayradiograph,(b)theimplant;(c)thepatient-specificguide;(d)apostoperativeX-rayradiograph.(CourtesyofProf. Dr.KSiebenrock,Inselspital,UniversityofBern, Switzerland)
arecentstudy[73]suggestedthatsurgeonsdid notselectthemasmajorweaknesses.Ithasbeen indicatedthatbarrierstoadoptionofsurgical navigationareneitherduetoadifficultlearning curvenortoalackoftrainingopportunities. Thebarrierstoadoptionofnavigationaremore intrinsictothetechnologyitself,includingintraoperativeglitches,unreliableaccuracy,frustrationwithintra-operativeregistration,andlineof-sightissues.Thesefindingssuggestthatsignificantimprovementsinthetechnologywillbe requiredtoimprovetheadoptionrateofsurgicalnavigation.Addressingtheseissuesfrom thefollowingperspectivesmayprovidesolutions inthecontinuingefforttoimplementsurgical navigationineverydayclinicalpractice.
• 2-Dor3-Dimagestitching.Long-bonefracturereductionandspinaldeformitycorrectionaretwotypicalclinicalapplicationsthat frequentlyusetheC-arminitsoperation.
Suchasurgeryusuallyinvolvescorrective manoeuverstoimprovethesagittalorcoronal profile.However,intra-operativeestimationof theamountofcorrectionisdifficult,especially inlongerinstrumentation.Mostly,anteroposterior(AP)andlateralfluoroscopicimagesare usedbuthavethedisadvantagetodepictonlya smallportionofthetargetstructureinasingle C-armimageduetothelimitedfieldofview ofaC-armmachine.Assuch,orthopaedic surgeonsnowadaysaremissinganeffective tooltoimagetheentireanatomicalstructure suchasthespineorlongbonesduringsurgery forassessingtheextentofcorrection.Althoughradiographsobtainedeitherbyusing alargefielddetectororbyimagestitching canbeusedtoimagetheentirestructure,they areusuallynotavailableforintra-operative interventions.Onealternativeistodevelop methodstostitchmultipleintra-operatively acquiredsmallfluoroscopicimagestobeable todisplaytheentirestructureatonce[74, 75].
Figure 1.8 showsanimagestitchingexample forspinalintervention.Thesameideacanbe extendedto3-Dimagingtocreateapanoramic conebeamcomputedtomography[76].Atthis moment,fastandeasy-to-use2-Dor3-Dimagestitchingsystemsarestillunderdevelopment,andasthetechnologyevolves,surgical benefitsandimprovedclinicaloutcomesare expected.
• Imagefusion.FusionofmultimodalitypreoperativeimagesuchasvariousMRIorCT datasetswithintra-operativeimageswould allowforvisualizationofcriticalstructures suchasnerverootsorvascularstructures duringsurgicalnavigation.Differentimaging modalitiesprovidecomplementaryinformationregardingbothanatomyandphysiology. Theevidencesupportingthiscomplementarity hasbeengainedoverthelastfewyears withincreasedinterestinthedevelopment ofplatformhardwareformultimodality imaging.Becausemultimodalityimagesby definitioncontaininformationobtainedusing differentimagingmethods,theyintroduce newdegreesoffreedom,raisingquestions beyondthoserelatedtoexploitingeachsingle modalityseparately.Processingmultimodality imagesisthenallaboutenablingmodalities tofullyinteractandinformeachother.It isimportanttochooseananalyticalmodel thatfaithfullyrepresentsthelinkbetween themodalitieswithoutimposingphantom connectionsorsuppressingexistingones. Henceitisimportanttobeasdatadriven aspossible.Inpractice,thismeansmaking thefewestassumptionsandusingthesimplest model,bothwithinandacrossmodalities. Examplemodelsincludelinearrelationships betweenunderlyinglatentvariables;useof model-independentpriorssuchassparsity,
Fig.1.8
Fig.1.9 Anexampleof statisticalshape model-based2-D-3-D reconstruction. Reconstructionofbone surfacefromtwocalibrated fluoroscopicimagesanda statisticalshapemodel usingdeformable registration
non-negativity,statisticalindependence,low rank,andsmoothness;orboth.Sucha principlehasbeensuccessfullyappliedto solvingchallengingproblemsinavariety ofapplications[77].Despitetheevident potentialbenefit,theknowledgeofhowto actuallyexploittheadditionaldiversitythat multimodalityimagesofferiscurrentlyat itspreliminarystageandremainsopenfor exploration.
• Statisticalshapeanddeformationanalysis. Statisticalshapeanddeformationanalysis [78]hasbeenshowntobeusefulforpredicting 3-Danatomicalshapeandstructuresfrom sparsepointsetsthatareacquiredwith theSDAtechnique.Suchatechniqueis heavilyemployedinso-called“image-free” navigationsystemsthatarecommercially availableinthemarket,mainlyforkneeand hipsurgery.However,withtheavailabilityof statisticalshapemodelsofotheranatomical regions,thetechniquecouldbeappliedtoany partoftheskeleton.Suchapproachesbear significantpotentialforfuturedevelopment ofcomputernavigationtechnologysince theyarenotatallboundtotheclassical pointer-basedacquisitionofbonyfeatures. Inprinciple,thereconstructionalgorithmscan betunedtoanytypeofpatient-specificinput, e.g.intra-operativelyacquiredfluoroscopic images[79]ortrackedultrasound[30], therebypotentiallyenablingnewminimally invasiveprocedures.Figure 1.9 showsan
exampleofbonesurfacereconstruction fromcalibratedfluoroscopicimagesanda statisticalshapemodel.Moreover,prediction fromstatisticalshapemodelsispossiblenot onlyforthegeometricshapeofanobject. Givenstatisticalshapeandintensitymodels, “syntheticCTscans”couldbepredictedfrom intra-operativelyrecordeddataafteratimeconsumingcomputation.Withmoreandmore computationsshiftedfromCPUstographics processingunits(GPUs),itisexpectedthat statisticalshapeanddeformationanalysisbasedtechniqueswillbeusedinmoreand moreCAOSsystems[80].
• Biomechanicalmodelling.Numericalmodels ofhumananatomicalstructuresmayhelp thesurgeonduringtheplanning,simulation, andintra-operativephaseswiththefinal goaltooptimizetheoutcomeoforthopaedic surgicalinterventions.Theterms“physical”or “biomechanical”areoftenused.Whilemost ofexistingbiomechanicalmodelsserveforthe basicunderstandingofphysicalphenomena, onlyafewhavebeenvalidatedforthe generalpredictionofconsequencesofsurgical interventions.
Thesituationforpatient-specificmodels isevenmorecomplex.Tobeusedinclinical practice,ideallytheexactknowledgeofthe underlyinggeometricaltissueconfiguration andassociatedmechanicalpropertiesaswell astheloadingregimeisrequiredasinput forappropriatemathematicalframeworks.
Inadditionthesemodelswillnotonlybe usedpre-operativelybutneedtofunction alsoinnearrealtimeintheoperating theatre.
Firstattemptshavebeenmadetoincorporatebiomechanicalsimulationandmodellingintothesurgicaldecision-makingprocessfororthopaedicinterventions.Forexample,alargespectrumofmedicaldevices existsforcorrectingdeformitiesassociated withspinaldisorders.Driscolletal.[81]developedadetailedvolumetricfiniteelement modelofthespinetosimulatesurgicalcorrectionofspinaldeformitiesandtoassess, compare,andoptimizespinaldevices.Anotherexamplewaspresentedin[82]where theauthorsshowedthatwithbiomechanical modellingtheinstrumentationconfiguration canbeoptimizedbasedonclinicalobjectives. Murphyetal.[83]presentedthedevelopment ofabiomechanicalguidancesystem(BGS) forperiacetabularosteotomy.TheBGSaims toprovidenotonlyreal-timefeedbackofthe jointrepositioningbutalsothesimulatedjoint contactpressures.
Anotherapproachisthecombineduse ofintra-operativesensingdeviceswith simplifiedbiomechanicalmodels.Crottet etal.[84]introducedadevicethatintraoperativelymeasureskneejointforcesand momentsandevaluateditsperformanceand surgicaladvantagesoncadavericspecimens usingakneejointloadingapparatus.Large variationamongspecimensreflectedthe difficultyofligamentreleaseandtheneed forintra-operativeforcemonitoring.A commercialversionofsuchadevice(eLIBRADynamicKneeBalancingSystem, SynvasiveTechnology,ElDoradoHills, CA,USA)becameavailableinrecentyears andisclinicallyused(see,e.g.[85]).Itis expectedthatincorporationofpatient-specific biomechanicalmodellingintoCAOSsystems withorwithouttheuseofintra-operative sensingdevicesmayeventuallyincreasethe qualityofsurgicaloutcomes[86].Research activitiesmustfocusonexistingtechnology
limitationsandmodelsofthemusculoskeletal apparatusthatarenotonlyanatomicallybut alsofunctionallycorrectandaccurate.
• Musculoskeletalimaging. Musculoskeletal imagingisdefinedastheimagingofbones, joints,andconnectedsofttissueswithan extensivearrayofmodalitiessuchasXrayradiography,CT,ultrasonography,and MRI.Forthepasttwodecades,rapidbut cumulativeadvancescanbeobservedin thisfield,notonlyforimprovingdiagnostic capabilitieswiththerecentadvancementon low-doseX-rayimaging,cartilageimaging, diffusiontensorimaging,MRarthrography, andhigh-resolutionultrasoundbutalsofor enablingimage-guidedinterventionswith theintroductionofreal-timeMRIorCT fluoroscopy,molecularimagingwithPET/CT, andopticalimagingintooperatingroom[87].
Onerecentadvancementthathasfound alotofclinicalapplicationsistheEOS2D/3-Dimagesystem(EOSimaging,Paris, France),whichwasintroducedtothemarketin2007.TheEOS2-D/3-Dimagingsystem[88]isbasedontheNobelPrize-winning workofFrenchphysicistGeorgesCharpak onmultiwireproportionalchamber,whichis placedbetweentheX-raysemergingfromthe radiographedobjectandthedistaldetectors. EachoftheemergingX-raysgeneratesasecondaryflowofphotonswithinthechamber, whichinturnstimulatethedistaldetectorsthat giverisetothedigitalimage.Thiselectronic avalancheeffectexplainswhyalowdoseof primaryX-raybeamissufficienttogenerate ahigh-quality2-Ddigitalradiograph,making itpossibletocoverafieldofviewof175cm by45cminasingleacquisitionofabout 20sduration[89].Withanorthogonallycolinked,verticallymovable,slot-scanningXraytube/detectorpairs,EOShasthebenefit thatitcantakeapairofcalibratedposteroanterior(PA)andlateral(LAT)imagessimultaneously[90].EOSallowstheacquisition ofimageswhilethepatientisinanupright, weight-bearing(standing,seated,orsquatting) positionandcanimagethefulllengthofthe
body,removingtheneedfordigitalstitching/manualjoiningofmultipleimages[91]. ThequalityandnatureoftheimagegeneratedbyEOSsystemarecomparableoreven betterthancomputedradiography(CR)and digitalradiography(DR)butwithmuchlower radiationdosage[90].ItwasreportedbyIllés etal.[90]thatabsorbedradiationdoseby variousorgansduringafull-bodyEOS2-D/3Dexaminationrequiredtoperformasurface 3-Dreconstructionwas800–1000timesless thantheamountofradiationduringatypical CTscanrequiredforavolumetric3-Dreconstruction.Whencomparedwithconventional ordigitalizedradiographs[92],EOSsystem allowsareductionoftheX-raydoseofan order80–90%.TheuniquefeatureofsimultaneouslycapturingapairofcalibratedPA andLATimagesofthepatientallowsafull 3-Dreconstructionofthesubject’sskeleton [90, 93, 94].Thisinturnprovidesover100 clinicalparametersforpre-andpost-operative surgicalplanning[90].Withaphantomstudy, Glaseretal.[95]assessedtheaccuracyofEOS 3-Dreconstructionbycomparingitwith3-D CT.Theyreportedameanshapereconstructionaccuracyof1.1±0.2mm(maximum4.7 mm)with95%confidenceintervalof1.7mm. Theyalsofoundthattherewasnosignificant differenceineachoftheiranalysedparameters (p>0.05)whenthephantomwasplacedin differentorientationsintheEOSmachine. Thereconstructionof3-Dbonemodelsallows analysisofsubject-specificmorphologyina weight-bearingsituationfordifferentapplicationstoalevelofaccuracywhichwasnot previouslypossible.Forexample,Lazennec etal.[96]usedtheEOSsystemtomeasure pelvisandacetabularcomponentorientations insittingandstandingpositions.FurtherapplicationsofEOSsysteminplanningtotal hiparthroplastyincludeaccurateevaluationof femoraloffset[97]androtationalalignment [98].Thelowdoseandbiplanarinformation oftheEOS2-D/3-Dimagingsystemintroduce keybenefitsincontemporaryradiologyand
opennumerousandimportantperspectivesin CAOSresearch.
Anothernoveltechnologyon2-D/3Dimagingwasintroducedin[99],which hadtheadvantageofbeingintegratedwith anyconventionalX-raymachine.Amean reconstructionparameterof1.06±0.20mm wasreported.Thistechnologyhasbeenused forconducting3-Dpre-operativeplanning andpost-operativetreatmentevaluationof TKAbasedononly2-Dlonglegstanding X-rayradiographs[100].
• Artificialintelligence,machinelearning,and deeplearning.Recentlyartificialintelligence andmachinelearning-basedmethodshave gainedincreasinginterestinmanydifferent fieldsincludingmusculoskeletalimagingand surgicalnavigation.Mostofthesemethodsare basedonensemblelearningprinciplesthatcan aggregatepredictionsofmultipleclassifiers anddemonstratesuperiorperformancein variouschallengingproblems[77, 101, 102]. Acrucialstepinthedesignofsuchsystems istheextractionofdiscriminantfeatures fromtheimages[103].Incontrast,many deeplearningalgorithmsthathavebeen proposedrecently,whicharebasedonmodels (networks)composedofmanylayersthat transforminputdata(e.g.images)tooutputs (e.g.segmentation),letcomputerslearnthe featuresthatoptimallyrepresentthedatafor theproblemathand.Themostsuccessful typeofmodelsforimageanalysistodateare convolutionalneuralnetworks(CNN)[104], whichcontainmanylayersthattransformtheir inputwithconvolutionfiltersofasmallextent. Deeplearning-basedmethodshavebeen successfullyusedtosolvemanychallenging problemsincomputer-aidedorthopaedic surgery[105–108].Figure 1.10 showsan exampleoftheapplicationofcascadedfully convolutionalnetworks(FCN)forautomatic segmentationoflumbarvertebraefromCT images[108].Itisexpectedthatmoreand moresolutionswillbedevelopedbasedon differenttypesofdeeplearningtechniques.
Fig.1.10 Aschematicviewofusingcascadedfullyconvolutionalnetworks(FCN),whichconsistsofalocalization netandasegmentationnetforautomaticsegmentationoflumbarvertebraefromCTimages
1.5Conclusions
Morethantwodecadeshavepassedsincethe firstrobotandnavigationsystemsforCAOSwere introduced.Todaythistechnologyhasemerged fromthelaboratoryandisbeingroutinelyused intheoperatingtheatreandmightbeaboutto becomestateoftheartforcertainorthopaedic procedures.
Stillweareatthebeginningofarapidprocess ofevolution.Existingtechniquesarebeingsystematicallyoptimized,andnewtechniqueswill constantlybeintegratedintoexistingsystems. HybridCAOSsystemsareunderdevelopment, whichwillallowthesurgeontouseanycombinationsoftheabove-describedconceptstoestablish virtualobjectinformation.Newgenerationsof mobileimagingsystems,inherentlyregistered, willsoonbeavailable.Howeverresearchfocusshouldparticularlybeonalternativetracking technologies,whichremovedrawbacksofthe currentlyavailableopticaltrackingandmagnetic devices.Thisinturnwillstimulatethedevelopmentoflessorevennon-invasiveregistration methodsandreferencingtools.Force-sensingdevicesandreal-timecomputationalmodelsmay allowestablishinganewgenerationofCAOS systemsbygoingbeyondpurekinematiccontrol ofthesurgicalactions.Forkeyholeprocedures thereisdistinctneedforsmartendeffectorsto complementthesurgeoninitsabilitytoperform asurgicalaction.Therecentadvancementon smartinstrumentation,medicalrobotics,artificial intelligence,machinelearning,anddeeplearning techniques,incombinationwithbigdataanalytics,mayleadtosmartCAOSsystemsand intelligentorthopaedicsinthenearfuture.
Acknowledgements Thischapterwasmodifiedfromthe paperpublishedbyourgroupin FrontiersinSurgery (ZhengandNolte2016;2:66).Therelatedcontentswere reusedwiththepermission.
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Computer-AidedOrthopedicSurgery: IncrementalShiftorParadigm Change?
LeoJoskowiczandEricJ.Hazan
Abstract
Computer-aidedorthopedicsurgery(CAOS) isnowabout25yearsold.Unlikeneurosurgery,computer-aidedsurgeryhasnot becomethestandardofcareinorthopedic surgery.Inthispaper,weprovidethetechnical andclinicalcontextraisedbythisobservation inanattempttoelucidatethereasonsfor thisstateofaffairs.Westartwithabrief outlineofthehistoryofCAOS,reviewthe mainCAOStechnologies,anddescribehow theyareevaluated.Wethenidentifysome ofthecurrentpublicationsinthefieldand presenttheopposingviewsontheirclinical impactandtheiracceptancebytheorthopedic communityworldwide.Wefocusontotal kneereplacementsurgeryasacasestudyand presentcurrentclinicalresultsandcontrasting opinionsonCAOStechnologies.Wethen discussthechallengesandopportunities forresearchinmedicalimageanalysisin CAOSandinmusculoskeletalradiology.We concludewithasuggestionthatwhileCAOS
L.Joskowicz( )
SchoolofComputerScienceandEngineering,The HebrewUniversityofJerusalem,Jerusalem,ISRAEL e-mail: josko@cs.huji.ac.il
E.J.Hazan
TraumatologyandEmergencyDepartments,Instituto NacionaldeRehabilitacion,MexicoCity,MEXICO
acceptancemaybemoremoderatethanthatof otherfieldsinsurgery,itstillhasaplaceinthe arsenalofusefultoolsavailabletoorthopedic surgeons.
Keywords
Computer-aidedorthopedicsurgery· Image-guidedsurgery·Medicalrobotics
2.1Introduction
Computer-basedtechnologies,includingboth softwareandhardware,areplayinganincreasinglylargerandmoreimportantroleindefining howsurgeryisperformedtoday.Orthopedic surgerywas,togetherwithneurosurgery, thefirstclinicalspecialtyforwhichimageguidednavigationandroboticsystemswere developed.Computer-aidedorthopedicsurgery (CAOS)isnowabout25yearsold.Duringthis time,awidevarietyofnovelandingenious systemshavebeenproposed,prototyped,and commercializedformostofthemainorthopedic surgeryprocedures,includingkneeandhip jointreplacement,cruciateligamentsurgery,
©SpringerNatureSingaporePteLtd.2018 G.Zhengetal.(eds.), IntelligentOrthopaedics,AdvancesinExperimentalMedicine andBiology1093, https://doi.org/10.1007/978-981-13-1396-7_2
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