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

doi:10.1088/2057-1976/ac02a6

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 journal › Article › peer-review

17 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 language	English (US)
Article number	045012
Journal	Biomedical Physics and Engineering Express
Volume	7
Issue number	4
DOIs	https://doi.org/10.1088/2057-1976/ac02a6
State	Published - Jul 2021

Keywords

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

ASJC Scopus subject areas

General Nursing

Access to Document

10.1088/2057-1976/ac02a6

Cite this

Woodall, R. T., Hormuth, D. A., Wu, C., Abdelmalik, M. R. A., Phillips, W. T., Bao, A., Hughes, T. J. R., Brenner, A. J., & Yankeelov, T. E. (2021). Patient specific, imaging-informed modeling of rhenium-186 nanoliposome delivery via convection-enhanced delivery in glioblastoma multiforme. Biomedical Physics and Engineering Express, 7(4), Article 045012. https://doi.org/10.1088/2057-1976/ac02a6

Woodall, RT, Hormuth, DA, Wu, C, Abdelmalik, MRA, Phillips, WT, Bao, A, Hughes, TJR, Brenner, AJ & Yankeelov, TE 2021, 'Patient specific, imaging-informed modeling of rhenium-186 nanoliposome delivery via convection-enhanced delivery in glioblastoma multiforme', Biomedical Physics and Engineering Express, vol. 7, no. 4, 045012. https://doi.org/10.1088/2057-1976/ac02a6

@article{4839abb3f1fc4650b242f0891605952a,

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

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.",

keywords = "Computational fluid dynamics, Computational oncology, Convection-enhanced delivery, Glioblastoma multiforme, Radiation therapy",

author = "Woodall, \{Ryan T.\} and Hormuth, \{David A.\} and Chengyue Wu and Abdelmalik, \{Michael R.A.\} and Phillips, \{William T.\} and Ande Bao and Hughes, \{Thomas J.R.\} and Brenner, \{Andrew J.\} and Yankeelov, \{Thomas E.\}",

note = "Publisher Copyright: {\textcopyright} 2021 IOP Publishing Ltd.",

year = "2021",

month = jul,

doi = "10.1088/2057-1976/ac02a6",

language = "English (US)",

volume = "7",

journal = "Biomedical Physics and Engineering Express",

issn = "2057-1976",

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T1 - Patient specific, imaging-informed modeling of rhenium-186 nanoliposome delivery via convection-enhanced delivery in glioblastoma multiforme

AU - Woodall, Ryan T.

AU - Hormuth, David A.

AU - Wu, Chengyue

AU - Abdelmalik, Michael R.A.

AU - Phillips, William T.

AU - Bao, Ande

AU - Hughes, Thomas J.R.

AU - Brenner, Andrew J.

AU - Yankeelov, Thomas E.

PY - 2021/7

Y1 - 2021/7

N2 - 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.

AB - 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.

KW - Computational fluid dynamics

KW - Computational oncology

KW - Convection-enhanced delivery

KW - Glioblastoma multiforme

KW - Radiation therapy

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UR - https://www.scopus.com/pages/publications/85107247901#tab=citedBy

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DO - 10.1088/2057-1976/ac02a6

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C2 - 34050041

AN - SCOPUS:85107247901

SN - 2057-1976

VL - 7

JO - Biomedical Physics and Engineering Express

JF - Biomedical Physics and Engineering Express

IS - 4

M1 - 045012

ER -

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

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