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Research ArticleBasic Science Investigation

Mathematic Modeling of Tumor Growth During [177Lu]Lu-PSMA Therapy: Insights into Treatment Optimization

Nouran R.R. Zaid, Remco Bastiaannet, Rob Hobbs and George Sgouros
Journal of Nuclear Medicine January 2025, 66 (1) 84-90; DOI: https://doi.org/10.2967/jnumed.124.268457
Nouran R.R. Zaid
1Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland; and
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Remco Bastiaannet
1Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland; and
2Department of Radiology, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri
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Rob Hobbs
1Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland; and
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George Sgouros
1Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland; and
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Abstract

The treatment regimen for [177Lu]Lu-prostate-specific membrane antigen (PSMA) 617 therapy follows that of chemotherapy: 6 administrations of a fixed activity, each separated by 6 wk. Mathematic modeling can be used to test the hypothesis that the current treatment regimen for a radiopharmaceutical modality is suboptimal. Methods: A mathematic model was developed to describe tumor growth during [177Lu]Lu-PSMA therapy. The model examined alternative treatment schedules to maximize tumor mass reduction while still maintaining an acceptable biologically effective dose to kidneys. Median patients’ pharmacokinetics from literature reports were used to obtain the dose rate over time. The model incorporates the Gompertz tumor growth and linear quadratic models to describe the effect of radiation-induced cell kill on tumor growth. For a fixed total activity of 44.4 GBq of [177Lu]Lu-PSMA-617 and a 6-wk interval between cycles, the efficacy of the standard fractionation (6-cycle) treatment schedule was compared with different treatment regimens for a distribution of published tumor masses. A treatment schedule whereby 7.4 GBq are administered in the first cycle, and the remaining activity (37 GBq) in the second cycle (1-2-cycle treatment), was examined. Results: When tumor mass nadir was used as the optimization metric, a lower tumor burden (e.g., <4 g) was insensitive to the number of cycles; the 6-cycle treatment was equivalent to the 1-2-cycle treatment. For larger masses, fewer cycles yielded better results. For a 7-g tumor, the 5-cycle, 4-cycle, 3-cycle and 1-2-cycle schedules were 24%, 50%, 76%, and 84% more efficacious, respectively, than the 6-cycle schedule. The absorbed doses to kidneys, parotid glands, lacrimal glands, and red marrow were 23, 16, 70, and 1 Gy, respectively. In all fractionated schedules, the biologically effective dose to kidneys was within tolerance (<40 Gy). Conclusion: On the basis of model-derived simulations, treatment delivered in a 1-2-cycle schedule is recommended to achieve better outcomes for patients undergoing [177Lu]Lu-PSMA therapy.

  • radiobiological modeling
  • Gompertz tumor growth
  • treatment optimization
  • [177Lu]Lu-PSMA therapy
  • pharmacokinetics
  • © 2025 by the Society of Nuclear Medicine and Molecular Imaging.
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Journal of Nuclear Medicine: 66 (1)
Journal of Nuclear Medicine
Vol. 66, Issue 1
January 1, 2025
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Mathematic Modeling of Tumor Growth During [177Lu]Lu-PSMA Therapy: Insights into Treatment Optimization
Nouran R.R. Zaid, Remco Bastiaannet, Rob Hobbs, George Sgouros
Journal of Nuclear Medicine Jan 2025, 66 (1) 84-90; DOI: 10.2967/jnumed.124.268457

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Mathematic Modeling of Tumor Growth During [177Lu]Lu-PSMA Therapy: Insights into Treatment Optimization
Nouran R.R. Zaid, Remco Bastiaannet, Rob Hobbs, George Sgouros
Journal of Nuclear Medicine Jan 2025, 66 (1) 84-90; DOI: 10.2967/jnumed.124.268457
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Keywords

  • radiobiological modeling
  • Gompertz tumor growth
  • treatment optimization
  • [177Lu]Lu-PSMA therapy
  • pharmacokinetics
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