  We present a novel application of Tensor Network methods in cancer treatment
as a potential tool to solve the dose optimization problem in radiotherapy. In
particular, the Intensity-Modulated Radiation Therapy (IMRT) technique - that
allows treating irregular and inhomogeneous tumors while reducing the radiation
toxicity on healthy organs - is based on the optimization of the radiation
beamlets intensities. The optimization aims to maximize the delivery of the
therapy dose to cancer while avoiding the organs at risk to prevent their
damage by the radiation. Here, we map the dose optimization problem into the
search of the ground state of an Ising-like Hamiltonian, describing a system of
long-range interacting qubits. Finally, we apply a Tree Tensor Network
algorithm to find the ground-state of the Hamiltonian. In particular, we
present an anatomical scenario exemplifying a prostate cancer treatment. A
similar approach can be applied to future hybrid classical-quantum algorithms,
paving the way for the use of quantum technologies in future medical
treatments.
