Advertisement

The role of patient-based treatment planning in peptide receptor radionuclide therapy

  • Deni Hardiansyah
  • Christian Maass
  • Ali Asgar Attarwala
  • Berthold Müller
  • Peter Kletting
  • Felix M. Mottaghy
  • Gerhard Glatting
Original Article

Abstract

Background

Accurate treatment planning is recommended in peptide-receptor radionuclide therapy (PRRT) to minimize the toxicity to organs at risk while maximizing tumor cell sterilization. The aim of this study was to quantify the effect of different degrees of individualization on the prediction accuracy of individual therapeutic biodistributions in patients with neuroendocrine tumors (NETs).

Methods

A recently developed physiologically based pharmacokinetic (PBPK) model was fitted to the biokinetic data of 15 patients with NETs after pre-therapeutic injection of 111In-DTPAOC. Mathematical phantom patients (MPP) were defined using the assumed true (true MPP), mean (MPP 1A) and median (MPP 1B) parameter values of the patient group. Alterations of the degree of individualization were introduced to both mean and median patients by including patient-specific information as a priori knowledge: physical parameters and hematocrit (MPP 2A/2B). Successively, measurable individual biokinetic parameters were added: tumor volume V tu (MPP 3A/3B), glomerular filtration rate GFR (MPP 4A/4B), and tumor perfusion f tu (MPP 5A/5B). Furthermore, parameters of MPP 5A/5B and a simulated 68Ga-DOTATATE PET measurement 60 min p.i. were used together with the population values used as Bayesian parameters (MPP 6A/6B). Therapeutic biodistributions were simulated assuming an infusion of 90Y-DOTATATE (3.3 GBq) over 30 min to all MPPs. Time-integrated activity coefficients were predicted for all MPPs and compared to the true MPPs for each patient in tumor, kidneys, spleen, liver, remainder, and whole body to obtain the relative differences RD.

Results

The large RD values of MPP 1A [RDtumor = (625 ± 1266)%, RDkidneys = (11 ± 38)%], and MPP 1B [RDtumor = (197 ± 505)%, RDkidneys = (11 ± 39)%] demonstrate that individual treatment planning is needed due to large physiological differences between patients. Although addition of individual patient parameters reduced the deviations considerably [MPP 5A: RDtumor = (−2 ± 27)% and RDkidneys = (16 ± 43)%; MPP 5B: RDtumor = (2 ± 28)% and RDkidneys = (7 ± 40)%] errors were still large. For the kidneys, prediction accuracy was considerably improved by including the PET measurement [MPP 6A/MPP 6B: RDtumor = (−2 ± 22)% and RDkidneys = (−0.1 ± 0.5)%].

Conclusion

Individualized treatment planning is needed in the investigated patient group. The use of a PBPK model and the inclusion of patient specific data, e.g., weight, tumor volume, and glomerular filtration rate, do not suffice to predict the therapeutic biodistribution. Integrating all available a priori information in the PBPK model and using additionally PET data measured at one time point for tumor, kidneys, spleen, and liver could possibly be sufficient to perform an individualized treatment planning.

Keywords

PRRT PBPK modeling Treatment planning PET 

Notes

Acknowledgments

The authors gratefully acknowledge grants by “Direktorat Jendral Pendidikan Tinggi” (Directorate General of Higher Education DIKTI of Ministry for Research, Technology and Higher Education, Republic Indonesia. Grant Number: 2644/E4.4/K/2013) for DH, funding received for MITIGATE from the European Community’s Seventh Framework Programme (FP7/2007-20013) under grant agreement no 602306 and M2OLIE (Research Campus funded by the German Federal Ministry of Education and Research (BMBF) within the Framework “Forschungscampus: public–private partnership for Innovations”) and Perspektivförderung “Translationale Radiochemie und Radiopharmazie” (Land Baden–Württemberg) and by the “Bundesministerium für Bildung und Forschung” (Federal Ministry of Education and Research, BMBF 02NUK008F) and “Bundesamt für Strahlenschutz” (Federal Office for Radiation Protection, BfS 3608S04001) for the establishment of the endowed professorship “Medizinische Strahlenphysik/Strahlenschutz” (Medical Radiation Physics/Radiation Protection). The authors also gratefully acknowledge the “Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) for support (GL 236/11-1 and KL 2742/2-1).

Authors’ contributions

DH and GG conceived and designed the experiments.

DH performed the experiments.

DH, PK and GG analyzed the data.

FM and BM contributed reagents/materials/analysis tools.

DH, CM, AAA, BM, PK, FMM, GG contributed to the writing of the manuscript.

Compliance with ethical standards

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. Informed consent was obtained from all individual participants included in the study.

Competing interest

The authors declare that they have no competing interests.

Supplementary material

259_2015_3248_MOESM1_ESM.doc (262 kb)
Additional File 1 (DOC 262 kb)
259_2015_3248_MOESM2_ESM.xlsx (235 kb)
Additional File 2 (XLSX 234 kb)
259_2015_3248_MOESM3_ESM.doc (1.2 mb)
Additional File 3 (DOC 1276 kb)

References

  1. 1.
    de Jong M, Bakker WH, Krenning EP, Breeman WA, van der Pluijm ME, Bernard BF, et al. 90Yttrium and 111Indium labelling, receptor binding and biodistribution of [DOTA0, d-Phe1, Tyr3]octreotide, a promising somatostatin analogue for radionuclide therapy. Eur J Nucl Med. 1997;24:368–71.PubMedGoogle Scholar
  2. 2.
    Krenning EP, de Jong M, Kooij PP, Breeman WA, Bakker WH, de Herder WW, et al. Radiolabelled somatostatin analogue(s) for peptide receptor scintigraphy and radionuclide therapy. Ann Oncol. 1999;10 Suppl 2:S23–9.CrossRefPubMedGoogle Scholar
  3. 3.
    Otte A, Jermann E, Behe M, Goetze M, Bucher HC, Roser HW, et al. DOTATOC: a powerful new tool for receptor-mediated radionuclide therapy. Eur J Nucl Med. 1997;24:792–5.PubMedGoogle Scholar
  4. 4.
    Rolleman EJ, Melis M, Valkema R, Boerman OC, Krenning EP, de Jong M. Kidney protection during peptide receptor radionuclide therapy with somatostatin analogues. Eur J Nucl Med Mol Imaging. 2010;37:1018–31.CrossRefPubMedGoogle Scholar
  5. 5.
    Cremonesi M, Botta F, Di Dia A, Ferrari M, Bodei L, De Cicco C, et al. Dosimetry for treatment with radiolabelled somatostatin analogues. A review. Q J Nucl Med Mol Imaging. 2010;54:37–51.PubMedGoogle Scholar
  6. 6.
    Cremonesi M, Ferrari M, Di Dia A, Botta F, De Cicco C, Bodei L, et al. Recent issues on dosimetry and radiobiology for peptide receptor radionuclide therapy. Q J Nucl Med Mol Imaging. 2011;55:155–67.PubMedGoogle Scholar
  7. 7.
    Glatting G, Bardiès M, Lassmann M. Treatment planning in molecular radiotherapy. Z Med Phys. 2013;23:262–9.CrossRefPubMedGoogle Scholar
  8. 8.
    Kletting P, Bunjes D, Reske SN, Glatting G. Improving anti-CD45 antibody radioimmunotherapy using a physiologically based pharmacokinetic model. J Nucl Med. 2009;50:296–302.CrossRefPubMedGoogle Scholar
  9. 9.
    Thomas SR. Options for radionuclide therapy: from fixed activity to patient-specific treatment planning. Cancer Biother Radiopharm. 2002;17:71–82.CrossRefPubMedGoogle Scholar
  10. 10.
    Marincek N, Jorg AC, Brunner P, Schindler C, Koller MT, Rochlitz C, et al. Somatostatin-based radiotherapy with [90Y-DOTA]-TOC in neuroendocrine tumors: long-term outcome of a phase I dose escalation study. J Transl Med. 2013;11:17–27.CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Kletting P, Kull T, Bunjes D, Luster M, Reske SN, Glatting G. Optimal preloading in radioimmunotherapy with anti-CD45 antibody. Med Phys. 2011;38:2572–8.CrossRefPubMedGoogle Scholar
  12. 12.
    Lassmann M, Chiesa C, Flux G, Bardies M, Committee ED. EANM Dosimetry Committee guidance document: good practice of clinical dosimetry reporting. Eur J Nucl Med Mol Imaging. 2011;38:192–200.CrossRefPubMedGoogle Scholar
  13. 13.
    Strigari L, Konijnenberg M, Chiesa C, Bardies M, Du Y, Gleisner KS, et al. The evidence base for the use of internal dosimetry in the clinical practice of molecular radiotherapy. Eur J Nucl Med Mol Imaging. 2014;41:1976–88.CrossRefPubMedGoogle Scholar
  14. 14.
    Mansi L, Cuccurullo V. Diagnostic imaging in neuroendocrine tumors. J Nucl Med. 2014;55:1576–7.CrossRefPubMedGoogle Scholar
  15. 15.
    Kletting P, Kull T, Bunjes D, Mahren B, Luster M, Reske SN, et al. Radioimmunotherapy with anti-CD66 antibody: improving the biodistribution using a physiologically based pharmacokinetic model. J Nucl Med. 2010;51:484–91.CrossRefPubMedGoogle Scholar
  16. 16.
    Kletting P, Müller B, Erentok B, Schmaljohann J, Behrendt FF, Reske SN, et al. Differences in predicted and actually absorbed doses in peptide receptor radionuclide therapy. Med Phys. 2012;39:5708–17.CrossRefPubMedGoogle Scholar
  17. 17.
    Bradshaw-Pierce EL, Eckhardt SG, Gustafson DL. A physiologically based pharmacokinetic model of docetaxel disposition: from mouse to man. Clin Cancer Res. 2007;13:2768–76.CrossRefPubMedGoogle Scholar
  18. 18.
    Heatherington AC, Vicini P, Golde H. A pharmacokinetic/pharmacodynamic comparison of SAAM II and PC/WinNonlin modeling software. J Pharm Sci. 1998;87:1255–63.CrossRefPubMedGoogle Scholar
  19. 19.
    Cremonesi M, Ferrari M, Bodei L, Tosi G, Paganelli G. Dosimetry in peptide radionuclide receptor therapy: a review. J Nucl Med. 2006;47:1467–75.PubMedGoogle Scholar
  20. 20.
    Chalkia MT, Stefanoyiannis AP, Chatziioannou SN, Round WH, Efstathopoulos EP, Nikiforidis GC. Patient-specific dosimetry in peptide receptor radionuclide therapy: a clinical review. Australas Phys Eng Sci Med. 2015;38:7–22.CrossRefPubMedGoogle Scholar
  21. 21.
    Tsougos I, Loudos G, Georgoulias P, Theodorou K, Kappas C. Patient-specific internal radionuclide dosimetry. Nucl Med Commun. 2010;31:97–106.CrossRefPubMedGoogle Scholar
  22. 22.
    Garkavij M, Nickel M, Sjogreen-Gleisner K, Ljungberg M, Ohlsson T, Wingardh K, et al. 177Lu-[DOTA0, Tyr3] octreotate therapy in patients with disseminated neuroendocrine tumors: analysis of dosimetry with impact on future therapeutic strategy. Cancer. 2010;116:1084–92.CrossRefPubMedGoogle Scholar
  23. 23.
    Glatting G, Landmann M, Kull T, Wunderlich A, Blumstein NM, Buck AK, et al. Internal radionuclide therapy: the ULMDOS software for treatment planning. Med Phys. 2005;32:2399–405.CrossRefPubMedGoogle Scholar
  24. 24.
    Barrett PH, Bell BM, Cobelli C, Golde H, Schumitzky A, Vicini P, et al. SAAM II: simulation, analysis, and modeling software for tracer and pharmacokinetic studies. Metabolism. 1998;47:484–92.CrossRefPubMedGoogle Scholar
  25. 25.
    Snyder WS, Cook MJ, Nasset ES, Karhausen RS, Howells GP. Report of the task group on reference man. Ann ICRP. 1979;3:iii.Google Scholar
  26. 26.
    Durkee BY, Mudd SR, Roen CN, Clipson L, Newton MA, Weichert JP, et al. Reproducibility of tumor volume measurement at microCT colonography in living mice. Acad Radiol. 2008;15:334–41.CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    Miller TR, Grigsby PW. Measurement of tumor volume by PET to evaluate prognosis in patients with advanced cervical cancer treated by radiation therapy. Int J Radiat Oncol Biol Phys. 2002;53:353–9.CrossRefPubMedGoogle Scholar
  28. 28.
    Chase DM, Sill MW, Monk BJ, Chambers MD, Darcy KM, Han ES, et al. Changes in tumor blood flow as measured by Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) may predict activity of single agent bevacizumab in recurrent epithelial ovarian (EOC) and primary peritoneal cancer (PPC) patients: an exploratory analysis of a Gynecologic Oncology Group Phase II study. Gynecol Oncol. 2012;126:375–80.CrossRefPubMedGoogle Scholar
  29. 29.
    Sugawara Y, Murase K, Kikuchi K, Sakayama K, Miyazaki T, Kajihara M, et al. Measurement of tumor blood flow using dynamic contrast-enhanced magnetic resonance imaging and deconvolution analysis: a preliminary study in musculoskeletal tumors. J Comput Assist Tomogr. 2006;30:983–90.CrossRefPubMedGoogle Scholar
  30. 30.
    Edwards WB, Fields CG, Anderson CJ, Pajeau TS, Welch MJ, Fields GB. Generally applicable, convenient solid-phase synthesis and receptor affinities of octreotide analogs. J Med Chem. 1994;37:3749–57.CrossRefPubMedGoogle Scholar
  31. 31.
    Reubi JC, Schar JC, Waser B, Wenger S, Heppeler A, Schmitt JS, et al. Affinity profiles for human somatostatin receptor subtypes SST1-SST5 of somatostatin radiotracers selected for scintigraphic and radiotherapeutic use. Eur J Nucl Med. 2000;27:273–82.CrossRefPubMedGoogle Scholar
  32. 32.
    Svensson J, Berg G, Wangberg B, Larsson M, Forssell-Aronsson E, Bernhardt P. Renal function affects absorbed dose to the kidneys and haematological toxicity during 177Lu-DOTATATE treatment. Eur J Nucl Med Mol Imaging. 2015;42:947–55.CrossRefPubMedPubMedCentralGoogle Scholar
  33. 33.
    Bodei L, Kidd M, Paganelli G, Grana CM, Drozdov I, Cremonesi M, et al. Long-term tolerability of PRRT in 807 patients with neuroendocrine tumours: the value and limitations of clinical factors. Eur J Nucl Med Mol Imaging. 2015;42:5–19.CrossRefPubMedGoogle Scholar
  34. 34.
    Harris A, Kamishima T, Hao HY, Kato F, Omatsu T, Onodera Y, et al. Splenic volume measurements on computed tomography utilizing automatically contouring software and its relationship with age, gender, and anthropometric parameters. Eur J Radiol. 2010;75:e97–101.CrossRefPubMedGoogle Scholar
  35. 35.
    Johnson TN, Tucker GT, Tanner MS, Rostami-Hodjegan A. Changes in liver volume from birth to adulthood: a meta-analysis. Liver Transpl. 2005;11:1481–93.CrossRefPubMedGoogle Scholar
  36. 36.
    Leggett RW, Williams LR. A proposed blood circulation model for reference man. Health Phys. 1995;69:187–201.CrossRefPubMedGoogle Scholar
  37. 37.
    Thomas GD, Chappell MJ, Dykes PW, Ramsden DB, Godfrey KR, Ellis JR, et al. Effect of dose, molecular size, affinity, and protein binding on tumor uptake of antibody or ligand: a biomathematical model. Cancer Res. 1989;49:3290–6.PubMedGoogle Scholar
  38. 38.
    Vegt E, de Jong M, Wetzels JF, Masereeuw R, Melis M, Oyen WJ, et al. Renal toxicity of radiolabeled peptides and antibody fragments: mechanisms, impact on radionuclide therapy, and strategies for prevention. J Nucl Med. 2010;51:1049–58.CrossRefPubMedGoogle Scholar
  39. 39.
    Kroiss A, Putzer D, Decristoforo C, Uprimny C, Warwitz B, Nilica B, et al. 68Ga-DOTA-TOC uptake in neuroendocrine tumour and healthy tissue: differentiation of physiological uptake and pathological processes in PET/CT. Eur J Nucl Med Mol Imaging. 2013;40:514–23.CrossRefPubMedGoogle Scholar
  40. 40.
    Hänscheid H, Sweeney RA, Flentje M, Buck AK, Lohr M, Samnick S, et al. PET SUV correlates with radionuclide uptake in peptide receptor therapy in meningioma. Eur J Nucl Med Mol Imaging. 2012;39:1284–8.CrossRefPubMedGoogle Scholar
  41. 41.
    Lyra M, Lagopati N, Charalambatou P, Vamvakas I. Patient-specific dosimetry in radionuclide therapy. Radiat Prot Dosim. 2011;147:258–63.CrossRefGoogle Scholar
  42. 42.
    Walrand S, Barone R, Pauwels S, Jamar F. Experimental facts supporting a red marrow uptake due to radiometal transchelation in 90Y-DOTATOC therapy and relationship to the decrease of platelet counts. Eur J Nucl Med Mol Imaging. 2011;38:1270–80.CrossRefPubMedGoogle Scholar
  43. 43.
    Hindorf C, Glatting G, Chiesa C, Linden O, Flux G, Committee ED. EANM Dosimetry Committee guidelines for bone marrow and whole-body dosimetry. Eur J Nucl Med Mol Imaging. 2010;37:1238–50.CrossRefPubMedGoogle Scholar
  44. 44.
    Oomen SP, Hofland LJ, van Hagen PM, Lamberts SW, Touw IP. Somatostatin receptors in the haematopoietic system. Eur J Endocrinol. 2000;143 Suppl 1:S9–14.CrossRefPubMedGoogle Scholar
  45. 45.
    Peluso G, Mansi L. Immunity and somatostatin receptors. Minerva Endocrinol. 2001;26:111–7.PubMedGoogle Scholar
  46. 46.
    Forrer F, Krenning EP, Kooij PP, Bernard BF, Konijnenberg M, Bakker WH, et al. Bone marrow dosimetry in peptide receptor radionuclide therapy with [177Lu-DOTA(0), Tyr(3)]octreotate. Eur J Nucl Med Mol Imaging. 2009;36:1138–46.CrossRefPubMedPubMedCentralGoogle Scholar
  47. 47.
    Pereira JM, Stabin MG, Lima FR, Guimaraes MI, Forrester JW. Image quantification for radiation dose calculations—limitations and uncertainties. Health Phys. 2010;99:688–701.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Deni Hardiansyah
    • 1
    • 2
  • Christian Maass
    • 1
  • Ali Asgar Attarwala
    • 1
    • 2
  • Berthold Müller
    • 3
  • Peter Kletting
    • 4
  • Felix M. Mottaghy
    • 3
    • 5
  • Gerhard Glatting
    • 1
  1. 1.Medical Radiation Physics/Radiation Protection, Universitätsmedizin Mannheim, Medical Faculty MannheimHeidelberg UniversityMannheimGermany
  2. 2.Department of Radiation OncologyUniversitätsmedizin Mannheim, Medical Faculty Mannheim, Heidelberg UniversityMannheimGermany
  3. 3.Klinik für NuklearmedizinUniversity Hospital, RWTH Aachen UniversityAachenGermany
  4. 4.Klinik für NuklearmedizinUniversität UlmUlmGermany
  5. 5.Department of Nuclear MedicineMaastricht University Medical Center (MUMC+)MaastrichtThe Netherlands

Personalised recommendations