Patient specific, imaging-informed modeling of rhenium-186 nanoliposome delivery via convection-enhanced delivery in glioblastoma multiforme

Ryan T. Woodall, David A. Hormuth, Chengyue Wu, Michael R.A. Abdelmalik, William T. Phillips, Ande Bao, Thomas J.R. Hughes, Andrew J. Brenner, Thomas E. Yankeelov

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

Convection-enhanceddeliveryofrhenium-186(186Re)-nanoliposomesisapromisingapproachto provideprecisedeliveryoflargelocalizeddosesofradiationforpatientswithrecurrentglioblastoma multiforme.Currentapproachesfortreatmentplanningutilizingconvection-enhanceddeliveryare designedforsmallmoleculedrugsandnotforlargerparticlessuchas186Re-nanoliposomes.Toenable thetreatmentplanningfor186Re-nanoliposomesdelivery,wehavedevelopedacomputationalfluid dynamicsapproachtopredictthedistributionofnanoliposomesforindividualpatients.Inthiswork,we construct,calibrate,andvalidateafamilyofcomputationalfluiddynamicsmodelstopredictthespatiotemporaldistributionof186Re-nanoliposomeswithinthebrain,utilizingpatient-specificpre-operative magneticresonanceimaging(MRI)toassignmaterialpropertiesforanadvection-diffusiontransport model.Themodelfamilyiscalibratedtosinglephotonemissioncomputedtomography(SPECT) imagesacquiredduringandaftertheinfusionof186Re-nanoliposomesforfivepatientsenrolledina PhaseI/IItrial(NCTNumberNCT01906385),andisvalidatedusingaleave-one-outbootstrapping methodologyforpredictingthefinaldistributionoftheparticles.Aftercalibration,ourmodelsare capableofpredictingthemid-deliveryandfinalspatialdistributionof186Re-nanoliposomeswithaDice valueof0.69 ± 0.18andaconcordancecorrelationcoefficientof0.88 ± 0.12(mean ± 95%confidence interval),usingonlythepatient-specific,pre-operativeMRIdata,andcalibratedmodelparametersfrom priorpatients.Theseresultsdemonstrateaproof-of-conceptforapatient-specificmodelingframework, whichpredictsthespatialdistributionofnanoparticles.Furtherdevelopmentofthisapproachcould enableoptimizingcatheterplacementforfuturestudiesemployingconvection-enhanceddelivery.

Original languageEnglish (US)
Article number045012
JournalBiomedical Physics and Engineering Express
Volume7
Issue number4
DOIs
StatePublished - Jul 2021

Keywords

  • Computational fluid dynamics
  • Computational oncology
  • Convection-enhanced delivery
  • Glioblastoma multiforme
  • Radiation therapy

ASJC Scopus subject areas

  • General Nursing

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