Estimation of [¹⁷⁷Lu]PSMA-617 tumor uptake based on voxel-wise 3D Monte Carlo tumor dosimetry in patients with metastasized castration resistant prostate cancer

Abstract

Objective Patients with advanced prostate cancer are suitable candidates for [¹⁷⁷Lu]PSMA-617 therapy. Integrated SPECT/CT systems have the potential to improve the accuracy of patient-specific tumor dosimetry. We present a novel patient-specific Monte Carlo based voxel-wise dosimetry approach to determine organ and total tumor doses (TTD).

Methods 13 patients with histologically confirmed metastasized castration-resistant prostate cancer were treated with a total of 18 cycles of [¹⁷⁷Lu]PSMA-617 therapy. In each patient, dosimetry was performed after the first cycle of [¹⁷⁷Lu]PSMA-617 therapy. Regions of interest were defined manually on the SPECT/CT images for the kidneys, spleen and all 295 PSMA-positive tumor lesions in the field of view. The absorbed dose to normal organs and to all tumor lesions were calculated by a three dimensional dosimetry method based on Monte Carlo Simulations.

Results The average dose values yielded the following results: 2.59 ± 0.63 Gy (1.67–3.92 Gy) for the kidneys, 0.79 ± 0.46 Gy (0.31–1.90 Gy) for the spleen and 11.00 ± 11.97 Gy (1.28–49.10 Gy) for all tracer-positive tumor lesions. A trend towards higher TTD was observed in patients with Gleason Scores > 8 compared to Gleason Scores ≤ 8 and in lymph node metastases compared to bone metastases. A significant correlation was determined between the serum-PSA level before RLT and the TTD (r = –0.57, p < 0.05), as well as between the TTD with the percentage change of serum-PSA levels before and after therapy was observed (r = –0.57, p < 0.05). Patients with higher total tumor volumes of PSMA-positive lesions demonstrated significantly lower kidney average dose values (r = –0.58, p < 0.05).

Conclusion The presented novel Monte Carlo based voxel-wise dosimetry calculates a patient specific whole-body dose distribution, thus taking into account individual anatomies and tissue compositions showing promising results for the estimation of radiation doses of normal organs and PSMA-positive tumor lesions.

Zusammenfassung

Ziel Patienten mit fortgeschrittenem Prostatakrebs sind geeignete Kandidaten für die [¹⁷⁷Lu]-PSMA-617-Therapie. SPECT/CT-Systeme haben das Potenzial, die patientenspezifische Tumordosimetrie zu verbessern. Wir stellen einen neuen patientenspezifischen, Monte-Carlo-basierten voxelweisen Dosimetrieansatz vor, um Organ- und totale Tumordosen (TTD) zu bestimmen.

Methodik 13 Patienten mit histologisch gesichertem metastasiertem kastrationsresistentem Prostatakrebs wurden mit insgesamt 18 Zyklen [¹⁷⁷Lu]-PSMA-617 behandelt. Bei jedem Patienten wurde eine Dosimetrie nach dem ersten Therapiezyklus durchgeführt. Volumes of interest (VOIs) wurden manuell auf den SPECT/CT-Bildern für die Nieren, die Milz und alle 295 PSMA-positiven Tumorläsionen im Untersuchungsgebiet definiert. Die absorbierte Dosis für Organe und alle Tumorläsionen wurden mittels einer 3-dimensionalen Monte-Carlo-basierten Simulation berechnet.

Ergebnisse Die mittleren Dosiswerte wurden wie folgt bestimmt: 2,59 ± 0,63 Gy (1,67–3,92 Gy) für die Nieren, 0,79 ± 0,46 Gy (0,31–1,90 Gy) für die Milz und 11,00 ± 11,97 Gy (1,28–49,10 Gy) für alle Tracer-positiven Tumorläsionen. Ein Trend zu höheren totalen Tumordosen wurde in Patienten mit Gleason-Scores > 8 im Vergleich zu Gleason-Scores ≤ 8 und in Patienten mit Lymphknotenmetastasen im Vergleich zu Knochenmetastasen beobachtet. Eine signifikante Korrelation wurde zwischen Serum-PSA-Werten vor Radioligandentherapie und der totalen Tumordosis ermittelt (r = –0,57; p < 0,05) sowie zwischen der totalen Tumordosis und der prozentualen Änderung der Serum-PSA-Werte vor und nach Therapie beobachtet (r = –0,57; p < 0,05). Patienten mit höherem totalem Tumorvolumen der PSMA-positiven Läsionen zeigten signifikant geringere mittlere Nierendosen (r = –0,58; p < 0,05).

Schlussfolgerung Die vorgestellte neuartige Monte-Carlo-basierte voxelweise Dosimetrie berechnet eine patientenspezifische Ganzkörper-Dosisverteilung, die individuelle Gewebezusammensetzungen berücksichtigt und vielversprechende Resultate für die Bestimmung der absorbierten Dosis von Organen und PSMA-positiven Tumorläsionen zeigt.

Key words

PSMA - dosimetry - prostate cancer - radioligand therapy

Schlüsselwörter

PSMA - Dosimetrie - Prostatakrebs - Radioligandentherapie

• References

• 1 Karantanos T, Corn PG, Thompson TC. Prostate cancer progression after androgen deprivation therapy: mechanisms of castrate resistance and novel therapeutic approaches. Oncogene 2013; 32 (49) 5501
• 2 Huggins C, Hodges CV. Studies on prostatic cancer: I. The effect of castration, of estrogen and of androgen injection on serum phosphatases in metastatic carcinoma of the prostate. J Urol 2002; 168 (01) 9-12
• 3 Harris WP, Mostaghel EA, Nelson PS. et al. Androgen deprivation therapy: progress in understanding mechanisms of resistance and optimizing androgen depletion. Nature Reviews Urology 2009; 6 (02) 76
• 4 Sridhar SS, Freedland SJ, Gleave ME. et al. Castration-resistant prostate cancer: from new pathophysiology to new treatment. Eur Urol 2014; 65 (02) 289-299
• 5 James ND, Sydes MR, Clarke NW. et al. Addition of docetaxel, zoledronic acid, or both to first-line long-term hormone therapy in prostate cancer (STAMPEDE): survival results from an adaptive, multiarm, multistage, platform randomised controlled trial. The Lancet 2016; 387: 1163-1177
• 6 Sweeney CJ, Chen YH, Carducci M. et al. Chemohormonal therapy in metastatic hormone-sensitive prostate cancer. New England Journal of Medicine 2015; 373 (08) 737-746
• 7 Yadav MP, Ballal S, Tripathi M. et al. 177 Lu-DKFZ-PSMA-617 therapy in metastatic castration resistant prostate cancer: safety, efficacy, and quality of life assessment. European journal of nuclear medicine and molecular imaging 2017; 44 (01) 81-91
• 8 Bräuer A, Grubert LS, Roll W. et al. 177Lu-PSMA-617 radioligand therapy and outcome in patients with metastasized castration-resistant prostate cancer. European journal of nuclear medicine and molecular imagin 2017; 44 (10) 1663-1670
• 9 Rahbar K, Ahmadzadehfar H, Kratochwil C. et al. German multicenter study investigating 177Lu-PSMA-617 radioligand therapy in advanced prostate cancer patients. Journal of Nuclear Medicine 2017; 58 (01) 85-90
• 10 Ahmadzadehfar H, Eppard E, Kürpig S. et al. Therapeutic response and side effects of repeated radioligand therapy with 177Lu-PSMA-DKFZ-617 of castrate-resistant metastatic prostate cancer. Oncotarget 2016; 7 (11) 12477
• 11 Maffioli L, Florimonte L, Costa D. et al. New radiopharmaceutical agents for the treatment of castration-resistant prostate cancer. QJ Nucl Med Mol Imaging 2015; 59 (04) 420-438
• 12 Delker A, Fendler WP, Kratochwil C. et al. Dosimetry for 177 Lu-DKFZ-PSMA-617: a new radiopharmaceutical for the treatment of metastatic prostate cancer. European journal of nuclear medicine and molecular imaging 2016; 43 (01) 42-51
• 13 Okamoto S, Thieme A, Allmann J. et al. Radiation dosimetry for 177Lu-PSMA I&T in metastatic castration-resistant prostate cancer: absorbed dose in normal organs and tumor lesions. Journal of Nuclear Medicine 2017; 58 (03) 445-450
• 14 Van Essen M, Krenning EP, De Jong M. et al. Peptide receptor radionuclide therapy with radiolabelled somatostatin analogues in patients with somatostatin receptor positive tumours. Acta Oncol 2007; 46 (06) 723-734
• 15 Kratochwil C, Giesel FL, Stefanova M. et al. PSMA-targeted radionuclide therapy of metastatic castration-resistant prostate cancer with 177Lu-labeled PSMA-617. J Nucl Med 2016; 57 (08) 1170-1176
• 16 Sanders J, Kuwert T, Hornegger J. et al. Quantitative SPECT/CT imaging of 177 Lu with in vivo validation in patients undergoing peptide receptor radionuclide therapy. Mol Imaging Biol. 2015; 17 (04) 585-593
• 17 Annkah JK, Rosenberg I, Hindocha N. et al. Assessment of the dosimetric accuracies of CATPhan 504 and CIRS 062 using kV-CBCT for performing direct calculations. Journal of Medical Physics/Association of Medical Physicists of India 2014; 39 (03) 133
• 18 Bhuiyan SM, Adhami RR, Khan JF. et al. A novel approach of fast and adaptive bidimensional empirical mode decomposition. 2008 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE; 2008
• 19 Kawrakow I, Mainegra-Hing E, Rogers D. et al. The EGSnrc code system: Monte Carlo simulation of electron and photon transport pp 2001–15. NCR Report 2013.
• 20 Berger MJ. Monte Carlo calculation of the penetration and diffusion of fast charged particles 1963.
• 21 Arce P, Lagares JI, Harkness L. et al. Gamos: A framework to do Geant4 simulations in different physics fields with an user-friendly interface. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 2014; 735: 304-313
• 22 Götz TI, Lang E, Schmidkonz C. et al Particle filter de-noising of voxel-specific time-activity-curves in personalized 177Lu therapy. Zeitschrift für Medizinische Physik 2019; 2020 May; 30 (02) 116-134
• 23 Zankl M, Panzer W, Drexler G. The calculation of dose from external photon exposures using reference human phantoms and Monte Carlo methods. Pt. 6. GSF-Forschungszentrum für Umwelt und Gesundheit GmbH 1991.
• 24 Götz TI, Ermer M, Salas-González D. et al. On the use of multi-dimensional scaling and electromagnetic tracking in high dose rate brachytherapy. Phys Med Biol 2017; 62 (20) 7959
• 25 Salas-González D, Górriz J, Ramírez J. et al. Parameterization of the distribution of white and grey matter in MRI using the α-stable distribution. Comput Biol Med 2013; 43 (05) 559-567
• 26 De Maesschalck R, Jouan-Rimbaud D, Massart DL. The mahalanobis distance. Chemometrics and intelligent laboratory systems 2000; 50 (01) 1-18
• 27 Penny KI. Appropriate critical values when testing for a single multivariate outlier by using the Mahalanobis distance. Journal of the Royal Statistical Society: Series C (Applied Statistics) 1996; 45 (01) 73-81
• 28 Götz TI, Schmidkonz C, Lang E. et al Factors affecting accuracy of S values and determination of time-integrated activity in clinical Lu-177 dosimetry. Annals of nuclear medicine 2019; Jul 33 (07) 521-531
• 29 Kolbert KS, Sgouros G, Scott AM. et al. Implementation and evaluation of patient-specific three-dimensional internal dosimetry. J Nucl Med. 1997; 38 (02) 301-307
• 30 Stabin MG, Sparks RB, Crowe E. OLINDA/EXM: the second-generation personal computer software for internal dose assessment in nuclear medicine. Journal of nuclear medicine 2005; 46 (06) 1023-1027
• 31 Violet J, Jackson P, Ferdinandus J. et al. Dosimetry of 177Lu-PSMA-617 in Metastatic Castration-Resistant Prostate Cancer: Correlations Between Pretherapeutic Imaging and Whole-Body Tumor Dosimetry with Treatment Outcomes. Journal of Nuclear Medicine 2019; 60 (04) 517-523
• 32 Kabasakal L, AbuQbeitah M, Aygün A. et al. Pre-therapeutic dosimetry of normal organs and tissues of 177 Lu-PSMA-617 prostate-specific membrane antigen (PSMA) inhibitor in patients with castration-resistant prostate cancer. Eur J Nucl Med Mol Imaging 2015; 42 (13) 1976-1983
• 33 Perner S, Hofer MD, Kim R. et al. Prostate-specific membrane antigen expression as a predictor of prostate cancer progression. Hum Pathol 2007; 38 (05) 696-701
• 34 Ahmadzadehfar H, Schlolaut S, Fimmers R. et al. Predictors of overall survival in metastatic castration-resistant prostate cancer patients receiving [177Lu] Lu-PSMA-617 radioligand therapy. Oncotarget 2017; 8 (61) 103108
• 35 Heidenreich A, Bastian PJ, Bellmunt J. et al. EAU guidelines on prostate cancer. Part II: treatment of advanced, relapsing, and castration-resistant prostate cancer. Eur Urol 2014; 65 (02) 467-479
• 36 Beauregard JM, Hofman MS, Kong G. et al. The tumour sink effect on the biodistribution of 68 Ga-DOTA-octreotate: implications for peptide receptor radionuclide therapy. Eur J Nucl Med Mol Imaging 2012; 39 (01) 50-56
• 37 Gaertner FC, Halabi K, Ahmadzadehfar H. et al. Uptake of PSMA-ligands in normal tissues is dependent on tumor load in patients with prostate cancer. Oncotarget 2017; 8 (33) 55094
• 38 Begum NJ, Thieme A, Eberhardt N. et al. The effect of total tumor volume on the biologically effective dose to tumor and kidneys for 177Lu-labeled PSMA peptides. Journal of Nuclear Medicine 2018; 59 (06) 929-933
• 39 Kletting P, Thieme A, Eberhardt N. et al. Modeling and predicting tumor response in radioligand therapy. Journal of Nuclear Medicine 2019; 60 (01) 65-70