Computational Biomechanics for Medicine: Towards Translation and Better Patient Outcomes PDF
Preview Computational Biomechanics for Medicine: Towards Translation and Better Patient Outcomes
Poul M. F. Nielsen · Martyn P. Nash · Xinshan Li · Karol Miller · Adam Wittek Editors Computational Biomechanics for Medicine Towards Translation and Better Patient Outcomes Computational Biomechanics for Medicine · · · Poul M. F. Nielsen Martyn P. Nash Xinshan Li · Karol Miller Adam Wittek Editors Computational Biomechanics for Medicine Towards Translation and Better Patient Outcomes Editors PoulM.F.Nielsen MartynP.Nash AucklandBioengineeringInstitute AucklandBioengineeringInstitute UniversityofAuckland UniversityofAuckland Auckland,NewZealand Auckland,NewZealand XinshanLi KarolMiller DepartmentofMechanicalEngineering IntelligentSystemsforMedicine UniversityofSheffield Laboratory Sheffield,UK TheUniversityofWesternAustralia Perth,WA,Australia AdamWittek IntelligentSystemsforMedicine Laboratory TheUniversityofWesternAustralia Perth,WA,Australia ISBN 978-3-031-09326-5 ISBN 978-3-031-09327-2 (eBook) https://doi.org/10.1007/978-3-031-09327-2 ©TheEditor(s)(ifapplicable)andTheAuthor(s),underexclusivelicensetoSpringerNature SwitzerlandAG2022 Thisworkissubjecttocopyright.AllrightsaresolelyandexclusivelylicensedbythePublisher,whether thewholeorpartofthematerialisconcerned,specificallytherightsoftranslation,reprinting,reuse ofillustrations,recitation,broadcasting,reproductiononmicrofilmsorinanyotherphysicalway,and transmissionorinformationstorageandretrieval,electronicadaptation,computersoftware,orbysimilar ordissimilarmethodologynowknownorhereafterdeveloped. Theuseofgeneraldescriptivenames,registerednames,trademarks,servicemarks,etc.inthispublication doesnotimply,evenintheabsenceofaspecificstatement,thatsuchnamesareexemptfromtherelevant protectivelawsandregulationsandthereforefreeforgeneraluse. Thepublisher,theauthors,andtheeditorsaresafetoassumethattheadviceandinformationinthisbook arebelievedtobetrueandaccurateatthedateofpublication.Neitherthepublishernortheauthorsor theeditorsgiveawarranty,expressedorimplied,withrespecttothematerialcontainedhereinorforany errorsoromissionsthatmayhavebeenmade.Thepublisherremainsneutralwithregardtojurisdictional claimsinpublishedmapsandinstitutionalaffiliations. ThisSpringerimprintispublishedbytheregisteredcompanySpringerNatureSwitzerlandAG Theregisteredcompanyaddressis:Gewerbestrasse11,6330Cham,Switzerland Preface Computationalbiomechanicsexploitsourknowledgeofphysicsandphysiological and biological processes, to enable quantitative predictions of outcomes resulting fromthecomplexinteractionsthatoccurinlivingsystems.Biomechanicalmodels increasinglyprovidevaluabletoolstoimprovethediagnosis,treatment,andmoni- toring of many diseases, as well as enhancing our understanding of how healthy bodiesfunction. The first volume in the Computational Biomechanics for Medicine book series waspublishedin2010.Sincethen,thebookhasbecomeanannualforumforspecial- istsincomputationalsciencestodescribetheirlatestresultsanddiscusstheappli- cationoftheirtechniques tocomputer-integrated medicine.Thetwelfthvolumein theComputationalBiomechanicsforMedicinebookseriescomprisesfifteenofthe latestdevelopmentsincontinuumbiomechanicsandpatient-specificcomputations, byresearchersfromNewZealand,Australia,Serbia,Denmark,France,theUnited Kingdom,Argentina,andtheUnitedStatesofAmerica.Topicscoveredinthisbook include: (cid:129) Tissuebiomechanics; (cid:129) Patient-specificmodelling; (cid:129) Vesselfluidmechanics; (cid:129) Biomedicalinstrumentation; (cid:129) Medicalimageanalysis. TheComputationalBiomechanicsforMedicinebookseriesprovidesthecommu- nity with the most up-to-date source of information for both researchers and practitioners. Auckland,NewZealand PoulM.F.Nielsen Auckland,NewZealand MartynP.Nash Perth,Australia KarolMiller Perth,Australia AdamWittek Sheffield,UK XinshanLi v Contents SolidMechanics TowardsAccurateMeasurementofAbdominalAorticAneurysm WallThicknessfromCTandMRI .................................. 3 AndyT.HuynhandKarolMiller Patient-SpecificFiniteElementModelingofAneurysmalDilatation AfterChronicTypeBAorticDissection .............................. 15 ShaojieZhang, JoanD.Laubrie, S.JamaleddinMousavi, SabrinaBenAhmed,andStéphaneAvril Characterizing the Biomechanics of an Endovascular InterventioninCerebralAneurysmsUsingKirchhoff–LoveShells ofNonuniformThickness .......................................... 39 NicolásMuzi,FrancescoCamussoni,LuisG.Moyano,andDanielMillán Imaging-Based Patient-Specific Biomechanical Evaluation of Atherosclerosis and Aneurysm: A Comparison Between Structural-Only, Fluid-Only and Fluid–Structure Interaction Analysis .......................................................... 53 JessicaBenitezMendieta, PhaniKumariParitala, JiaqiuWang, andZhiyongLi Automatic Framework for Patient-Specific Biomechanical ComputationsofOrganDeformation:AnEpilepsy(EEG)Case Study ............................................................. 75 SaimaSafdar,BenjaminZwick,GeorgeBourantas,GrandR.Joldes, SimonK.Warfield,DamonE.Hyde,AdamWittek,andKarolMiller GeneratingScolioticComputedTomographyVolumesfromFinite ElementSpineModels ............................................. 91 AustinTapp, MichaelPolanco, IsaacKumi, SebastianBawab, StacieRingleb, RumitKakar, CarlSt.Remy, JamesBennett, andMichelAudette vii viii Contents Morphological Variation in an Endothelial Cell Population: AVirtual-CellModel .............................................. 105 YiChungLim,MichaelCooling,SueMcGlashan,andDavidS.Long FluidMechanics EfficientandAccurateComputationofQuantitativeFlowRatio (QFR)forPhysiologicalAssessmentofCoronaryArteryStenosis fromaSingleAngiographicView ................................... 121 GeorgeC.Bourantas, GrigoriosTsigkas, KonstantinosKatsanos, FivosV.Bekiris,BenjaminF.Zwick,AdamWittek,KarolMiller, andPeriklisDavlouros Predicting Plaque Progression in Patient-Specific Carotid Bifurcation ....................................................... 133 TijanaDjukic,SmiljanaDjorovic,BrankoArsic,BrankoGakovic, IgorKoncar,andNenadFilipovic Imaging AssessingFibreReorientationinSoftTissueswithSimultaneous MuellerMatrixImagingandMechanicalTesting ..................... 145 AlexanderW.Dixon, AndrewJ.Taberner, MartynP.Nash, andPoulM.F.Nielsen A Direct Geometry Processing Cartilage Generation Method UsingSegmentedBoneModelsfromDatasetswithPoorCartilage Visibility .......................................................... 155 FaezehMoshfeghifar,MaxKragballeNielsen,JoséD.Tascón-Vidarte, SuneDarkner,andKennyErleben Development of an Open Source, Low-Cost Imaging System forContinuousLungMonitoring ................................... 171 SamuelRichardson, AndrewCreegan, AlexDixon, LlewellynSimJohns, HaribalanKumar, KellyBurrowes, PoulM.F.Nielsen,J.GeoffreyChase,andMerrynH.Tawhai Measuring Three-Dimensional Surface Deformations of Skin UsingaStereoscopicSystemandIntrinsicFeatures ................... 183 AmirHajiRassouliha, DebbieZhao, DongHoonChoi, EmilyJ.LamPoTang, AndrewJ.Taberner, MartynP.Nash, andPoulM.F.Nielsen Index ............................................................. 195 Solid Mechanics Towards Accurate Measurement of Abdominal Aortic Aneurysm Wall Thickness from CT and MRI AndyT.HuynhandKarolMiller Abstract AbdominalAorticAneurysm(AAA)isthefocaldilationorwideningof the infrarenal artery. It is a vascular disease commonly found in older adults with prevalenceincreasingsteadilywithage.Thediseaseisoftendiscoveredbyunrelated medicalexaminationsandscreeningsduetoitsasymptomaticnature.Peopleunaware oftheirconditionmayonlyfindoutafterthecatastrophiceventofarupturedAAA, where most patients will not survive if left untreated. The current clinical rupture riskindicatorforAAArepairisaAAAdiameterexceeding5.5cm.Therearemany limitationswiththeclinicalruptureriskindicatorduetoitsderivationcomingfrom population statistics and not patient-specific circumstances. Computation of AAA wall stress using three-dimensional (3D) reconstructions of patient CT scans have oftenbeenusedbyresearchersasapotentialpatient-specificruptureriskindicator. Apropertythathasagreatinfluenceonthestressdistributionandmagnitudeisthe aortic wall thickness. Unfortunately, there are no validated, non-invasive methods formeasuringaorticwallthicknessofpatientswithAAA.Researchershaveutilised eitherCTorMRIasinputintotheircustomwalldetectionalgorithms,however,there hasnotyetbeenastudywhichutilisesboth.Therefore,thisstudyaimstodevelopa non-invasive,andpatient-specificmethodofdetectingaorticwallthicknessutilising bothCTandMRIscans. · · · Keywords Abdominalaorticaneurysm Aorticwallthickness Measurement · · Patient-specific Computedtomography Magneticresonanceimaging B A.T.Huynh( )·K.Miller IntelligentSystemsforMedicineLaboratory,TheUniversityofWesternAustralia,Perth,WA, Australia e-mail:[email protected] K.Miller e-mail:[email protected] K.Miller HarvardMedicalSchool,Boston,MA,USA ©TheAuthor(s),underexclusivelicensetoSpringerNatureSwitzerlandAG2022 3 P.M.F.Nielsenetal.(eds.),ComputationalBiomechanicsforMedicine, https://doi.org/10.1007/978-3-031-09327-2_1 4 A.T.HuynhandK.Miller 1 Introduction AbdominalAorticAneurysm(AAA)isthefocaldilationorwideningoftheinfrarenal arteryandismostcommonlyfusiforminshape[1].Itisavasculardiseasecommonly foundinolderadultswithprevalenceincreasingsteadilywithage[2].Althoughthe prevalenceandincidenceofAAAhasdeclinedglobally,therehavebeenrisingAAA ratesinmanyregionalareasaroundtheworld,includingtheOceanicregion[2].In Australia, approximately 7% of elderly men aged 65 years and above suffer from AAA—equatingtoabout114,000Australianmen[3].Thishighlightstheneedfor improveddiseasesurveillanceandprevention. Duetotheasymptomaticnatureofthedisease,itisoftendiscoveredbyunrelated medicalexaminationsandscreening[1].Peopleunawareoftheirconditionmayonly find out after the catastrophic event of a ruptured AAA. The majority of patients witharupturedAAAwillnotsurviveifleftuntreated,havinganoverallmortality rateofapproximately80–90%[4].Unfortunately,evenwithimmediatesurgeryby experiencedvascularsurgeons,themortalityremainshighbetween41and55%[5]. Assuch,itiscrucialfordoctorstoidentifythelocationontheAAAvesselathighest riskofrupturingpriortothecatastrophicevent. Therearemanylimitationstothecurrentclinicalruptureriskindicatorduetoits derivationcomingfrompopulationstatisticsandnotpatient-specificcircumstances. Clinical rupture risk indicator for elective repair only factors the AAA diameter size(>5.5cmformenand>5cmforwomen),growthrate(>1cm/year)andsome patient symptoms [1]. This is insufficient as there are many other patient-specific factors such as age, smoking, atherosclerosis, hypertension, ethnicity, and family history[1].Furtherevidenceindicatesthat60%ofAAAsthatwererecommended forelectiverepairoftenremainedstable[6]and20%ofsmallAAAhaveruptured[7]. Researchiscurrentlybeingundertakentovisualiseandunderstandpatient-specific biomechanics of AAA. This novel approach aims to develop a non-invasive and patient-specificbiomechanicalruptureriskassessmentforAAA. ComputationofAAAwallstressusingthree-dimensional(3D)reconstructionsof patientCTscanshaveoftenbeenusedbyresearchersasapotentialruptureriskindi- cator[8–10].Althoughitwasrecentlydiscoveredthatneitherstressmagnitudenor stressdistributionalonehadanynoticeablerelationshipwithAAAsymptoms[11], wallstresscalculationsstillholdsgreatpracticalimportanceinresearch.Wallthick- nessisapropertythathasagreatinfluenceonthestressdistributionandmagnitude [8,12].Unfortunately,therearenovalidated,non-invasivemethodsformeasuring aortic wall thickness [13]. Additionally, the poor soft tissue contrast of CT scans alonelimitthevisibilityandmeasurementoftheaorticwall,resultinginamajority ofAAAruptureriskstudiesassumingauniformwallthickness[14].BioPARRisa softwaresystemusedforestimatingtherupturepotentialindex(RPI)forAAA[14]. ThesoftwareonlyrequiresthesegmentationoftheAAAandwallthicknessspecifi- cationasmanualuserinputswithallotherstepsbeingautomated.Unfortunately,the wallthicknessspecificationisappliedeitherbyassuminguniformwallthicknessor manually measuring wall thickness at sparse locations and using them to generate
The list of books you might like
