Abstract

Radionuclides conjugated to molecules that bind specifically to cancer cells are of great interest as a means to increase the specificity of radiotherapy. Currently, the methods to disseminate these targeted radiotherapeutics have been either systemic delivery or by bolus injection into the tumor or tumor resection cavity. Herein we model a potentially more efficient method of delivery, namely pressure-driven fluid flow, called convection-enhanced delivery (CED), where a device infuses the molecules in solution (or suspension) directly into the tissue of interest. In particular, we focus on the setting of primary brain cancer after debulking surgery, where the tissue margins surrounding the surgical resection cavity are infiltrated with tumor cells and the most frequent sites of tumor recurrence. We develop the combination of fluid flow, chemical kinetics, and radiation dose models needed to examine such protocols. We focus on Auger electrons emitting radionuclides (e.g. 67Ga, 77Br, 111In, 125I, 123I, 193mPt, 195mPt) whose short range makes them ideal for targeted therapy in this setting of small foci of tumor spread within normal tissue. By solving these model equations, we confirm that a CED protocol is promising in allowing sufficient absorbed dose to destroy cancer cells with minimal absorbed dose to normal cells at clinically feasible activity levels. We also show that Auger emitters are ideal for this purpose while the longer range alpha particle emitters fail to meet criteria for effective therapy (as neither would energetic beta particle emitters). The model is used with simplified assumptions on the geometry and homogeneity of brain tissue to allow semi-analytic solutions to be displayed, and with the purpose of a first examination of this new delivery protocol proposed for radionuclide therapy. However, we emphasize that it is immediately extensible to personalized therapy treatment planning as we have previously shown for conventional CED, at the price of requiring a fully numerical computerized approach.

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