4.7 Article

A Hepatic Dose-Toxicity Model Opening the Way Toward Individualized Radioembolization Planning

Journal

JOURNAL OF NUCLEAR MEDICINE
Volume 55, Issue 8, Pages 1317-1322

Publisher

SOC NUCLEAR MEDICINE INC
DOI: 10.2967/jnumed.113.135301

Keywords

radioembolization; PET; dosimetry; normal tissue complication probability; Monte Carlo

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The 50% normal-tissue complication probability (NTCP) after lobar irradiation of the liver results in highly variable biologic effective doses depending on the modality used: a biologic effective dose for 50% (BED50) of 115, 93, and 250 Gy for external-beam radiotherapy, resin microsphere radioembolization, and glass microsphere radioembolization, respectively. This misunderstood property has made it difficult to predict the maximal tolerable dose as a function of microsphere activity and targeted liver volume. The evolution toward more selective catheterization techniques, resulting in more variable targeted volumes, makes it urgent to solve this issue. Methods: We computed by Monte Carlo simulations the microsphere distribution in the portal triads based on microsphere transport dynamics through a synthetically grown hepatic arterial tree. Afterward, the microscale dose distribution was computed using a dose deposition kernel. We showed that the equivalent uniform dose cannot handle microscale dosimetry and fails to solve the discordance between the BED50 values. Consequently, we developed a new radiobiologic model to compute the liver NTCP from the microscale dose distribution. Results: The new model explains all the observed BED50 values and provides a way to compute the hepatic dose-toxicity relationship as a function of microsphere activity and targeted liver volume. The NTCP obtained is in agreement with the data reported from clinical radioembolization studies. Conclusion: The results should encourage interventional radiologists to fine-tune the delivered dose to the liver as a function of the targeted volume. The present model could be used as the backbone of the treatment planning, allowing optimization of the absorbed dose to the tumors.

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