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Sökning: L773:2197 7364 > Predicting [177Lu]L...

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FältnamnIndikatorerMetadata
00006242naa a2200481 4500
001oai:DiVA.org:uu-520032
003SwePub
008240112s2023 | |||||||||||000 ||eng|
0247 a https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-5200322 URI
0247 a https://doi.org/10.1186/s40658-023-00565-42 DOI
040 a (SwePub)uu
041 a engb eng
042 9 SwePub
072 7a ref2 swepub-contenttype
072 7a art2 swepub-publicationtype
1001 a Siebinga, Hinkeu Netherlands Canc Inst, Dept Pharm & Pharmacol, Plesmanlaan 121, NL-1066 CX Amsterdam, Netherlands.;Netherlands Canc Inst, Dept Nucl Med, Amsterdam, Netherlands.;Univ Utrecht, Grad Sch Life Sci, Utrecht, Netherlands.4 aut
2451 0a Predicting [177Lu]Lu-HA-DOTATATE kidney and tumor accumulation based on [68Ga]Ga-HA-DOTATATE diagnostic imaging using semi-physiological population pharmacokinetic modeling
264 1b Springer,c 2023
338 a electronic2 rdacarrier
520 a BackgroundPrediction of [177Lu]Lu-HA-DOTATATE kidney and tumor uptake based on diagnostic [68Ga]Ga-HA-DOTATATE imaging would be a crucial step for precision dosing of [177Lu]Lu-HA-DOTATATE. In this study, the population pharmacokinetic (PK) differences between [177Lu]Lu-HA-DOTATATE and [68Ga]Ga-HA-DOTATATE were assessed and subsequently [177Lu]Lu-HA-DOTATATE was predicted based on [68Ga]Ga-HA-DOTATATE imaging.MethodsA semi-physiological nonlinear mixed-effects model was developed for [68Ga]Ga-HA-DOTATATE and [177Lu]Lu-HA-DOTATATE, including six compartments (representing blood, spleen, kidney, tumor lesions, other somatostatin receptor expressing organs and a lumped rest compartment). Model parameters were fixed based on a previously developed physiologically based pharmacokinetic model for [68Ga]Ga-HA-DOTATATE. For [177Lu]Lu-HA-DOTATATE, PK parameters were based on literature values or estimated based on scan data (four time points post-injection) from nine patients. Finally, individual [177Lu]Lu-HA-DOTATATE uptake into tumors and kidneys was predicted based on individual [68Ga]Ga-HA-DOTATATE scan data using Bayesian estimates. Predictions were evaluated compared to observed data using a relative prediction error (RPE) for both area under the curve (AUC) and absorbed dose. Lastly, to assess the predictive value of diagnostic imaging to predict therapeutic exposure, individual prediction RPEs (using Bayesian estimation) were compared to those from population predictions (using the population model).ResultsPopulation uptake rate parameters for spleen, kidney and tumors differed by a 0.29-fold (15% relative standard error (RSE)), 0.49-fold (15% RSE) and 1.43-fold (14% RSE), respectively, for [177Lu]Lu-HA-DOTATATE compared to [68Ga]Ga-HA-DOTATATE. Model predictions adequately described observed data in kidney and tumors for both peptides (based on visual inspection of goodness-of-fit plots). Individual predictions of tumor uptake were better (RPE AUC –40 to 28%) compared to kidney predictions (RPE AUC –53 to 41%). Absorbed dose predictions were less predictive for both tumor and kidneys (RPE tumor and kidney –51 to 44% and –58 to 82%, respectively). For most patients, [177Lu]Lu-HA-DOTATATE tumor accumulation predictions based on individual PK parameters estimated from diagnostic imaging outperformed predictions based on population parameters.ConclusionOur semi-physiological PK model indicated clear differences in PK parameters for [68Ga]Ga-HA-DOTATATE and [177Lu]Lu-HA-DOTATATE. Diagnostic images provided additional information to individually predict [177Lu]Lu-HA-DOTATATE tumor uptake compared to using a population approach. In addition, individual predictions indicated that many aspects, apart from PK differences, play a part in predicting [177Lu]Lu-HA-DOTATATE distribution.
650 7a MEDICIN OCH HÄLSOVETENSKAPx Klinisk medicinx Radiologi och bildbehandling0 (SwePub)302082 hsv//swe
650 7a MEDICAL AND HEALTH SCIENCESx Clinical Medicinex Radiology, Nuclear Medicine and Medical Imaging0 (SwePub)302082 hsv//eng
650 7a MEDICIN OCH HÄLSOVETENSKAPx Klinisk medicinx Cancer och onkologi0 (SwePub)302032 hsv//swe
650 7a MEDICAL AND HEALTH SCIENCESx Clinical Medicinex Cancer and Oncology0 (SwePub)302032 hsv//eng
653 a [68Ga]Ga-HA-DOTATATE
653 a [177Lu]Lu-HA-DOTATATE
653 a Theranostics
653 a PRRT
653 a NLMEM
653 a Uptake prediction
653 a Precision medicine
7001 a de van der Veen, Berlinda J.u Netherlands Canc Inst, Dept Nucl Med, Amsterdam, Netherlands.4 aut
7001 a Beijnen, Jos H.u Netherlands Canc Inst, Dept Pharm & Pharmacol, Plesmanlaan 121, NL-1066 CX Amsterdam, Netherlands.4 aut
7001 a Stokkel, Marcel P. M.u Netherlands Canc Inst, Dept Nucl Med, Amsterdam, Netherlands.4 aut
7001 a Dorlo, Thomas P. C.,c PhD,d 1983-u Uppsala universitet,Institutionen för farmaci,Netherlands Canc Inst, Dept Pharm & Pharmacol, Plesmanlaan 121, NL-1066 CX Amsterdam, Netherlands4 aut0 (Swepub:uu)thodo249
7001 a Huitema, Alwin D. R.u Netherlands Canc Inst, Dept Pharm & Pharmacol, Plesmanlaan 121, NL-1066 CX Amsterdam, Netherlands.;Univ Utrecht, Univ Med Ctr Utrecht, Dept Clin Pharm, Utrecht, Netherlands.;Princess Maxima Ctr Pediat Oncol, Dept Pharmacol, Utrecht, Netherlands.4 aut
7001 a Hendrikx, Jeroen J. M. A.u Netherlands Canc Inst, Dept Pharm & Pharmacol, Plesmanlaan 121, NL-1066 CX Amsterdam, Netherlands.;Netherlands Canc Inst, Dept Nucl Med, Amsterdam, Netherlands.4 aut
7102 a Netherlands Canc Inst, Dept Pharm & Pharmacol, Plesmanlaan 121, NL-1066 CX Amsterdam, Netherlands.;Netherlands Canc Inst, Dept Nucl Med, Amsterdam, Netherlands.;Univ Utrecht, Grad Sch Life Sci, Utrecht, Netherlands.b Netherlands Canc Inst, Dept Nucl Med, Amsterdam, Netherlands.4 org
7730 t EJNMMI Physicsd : Springerg 10:1q 10:1x 2197-7364
8564 u https://doi.org/10.1186/s40658-023-00565-4y Fulltext
8564 u https://uu.diva-portal.org/smash/get/diva2:1827130/FULLTEXT01.pdfx primaryx Raw objecty fulltext:print
8564 8u https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-520032
8564 8u https://doi.org/10.1186/s40658-023-00565-4

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