TY - JOUR
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.
N1 - Funding Information:
We thank the National Institutes of Health for funding through R01 CA235800, T32 EB007507, NCI 1R01 CA186193 and NCI 1U01CA253540, and 1U01 CA174706. We thank CPRIT for funding through RR160005. T.E.Y. is a CPRIT Scholar of Cancer Research. We thank the American Association of Physicists in Medicine for Research Seed Funding. We offer a sincere thank you to all the patients who volunteer to participate in our studies; your strength and courage are examples for all of us.
Publisher Copyright:
© 2021 IOP Publishing Ltd.
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
UR - http://www.scopus.com/inward/record.url?scp=85107247901&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85107247901&partnerID=8YFLogxK
U2 - 10.1088/2057-1976/ac02a6
DO - 10.1088/2057-1976/ac02a6
M3 - Article
C2 - 34050041
AN - SCOPUS:85107247901
VL - 7
JO - Biomedical Physics and Engineering Express
JF - Biomedical Physics and Engineering Express
SN - 2057-1976
IS - 4
M1 - 045012
ER -