放射治疗
量子位元
哈密顿量(控制论)
计算机科学
张量(固有定义)
数学优化
量子
最优化问题
物理
医学
数学
算法
量子力学
放射科
纯数学
作者
Samuele Cavinato,Timo Felser,M. Fusella,M. Paiusco,Simone Montangero
标识
DOI:10.1088/1361-6560/ac01f2
摘要
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.
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