Microdosimetry aspects of Diffusing Alpha-emitters Radiation Therapy

  Yevgeniya Korotinsky  ,  Lior Arazi  
Unit of Nuclear Engineering, Faculty of Engineering Sciences, Ben-Gurion University of the Negev

Diffusing Alpha-emitters Radiation Therapy (“DaRT”) is a new cancer treatment modality, which enables treating solid tumors by alpha particles. The treatment utilizes implantable seeds embedded with a low activity of radium-224. Each seed continuously emits the short-lived alpha-emitting daughters of radium-224, which spread over several mm around it, creating a kill region of high alpha-particle dose. DaRT is presently tested in clinical trials, starting with locally advanced and recurrent squamous cell carcinoma (SCC) of the skin and head and neck, with promising results with respect to both efficacy and safety. In order to become an accepted and effective tool for the treatment of cancer, DaRT must be amenable to quantitative planning and analysis. Gaining a better understanding of the radiobiological effects of particles on cells requires studies to correlate the induced biological damage with the physics of alpha-particle irradiation at the cellular and subcellular levels. This work aims to introduce the first steps taken towards establishing a numerical microdosimetric model that can serve as a basis for DaRT dosimetry; For a given macroscopic dose, alpha-particle source distribution and target size, the proposed model provides statistical distributions of the number of alpha -particle traversals and the specific energy deposited in the site which are later used as inputs for cell survival probability calculations. In spite of its rather simplistic definition, the current model constitutes a zero-order approximate framework that allows for gross estimates of the underlying physics in the microdosimetric domain. Together with well-defined extensions and future refinements of the model, these estimates can be implemented as inputs for further treatment planning algorithms, such as Tumor Control Probability (TCP), yielding first suggestions for the prescription dose.