A new standard quadratic optimization approach to beam angle optimization for fixed-field intensity modulated radiation therapy

TL;DR

This paper introduces a novel quadratic optimization framework for beam angle selection in fixed-field IMRT, improving dose sparing of organs at risk by efficiently finding optimal beam configurations.

Contribution

It reformulates beam angle optimization as a standard quadratic optimization problem using linear constraints and reweighting l1-norm, enabling efficient and optimal solutions.

Findings

Successfully verified on digital phantom and patient data.

Achieved improved dose sparing on organs at risk.

Demonstrated efficiency of the convex optimization approach.

Abstract

Beam angle optimization (BAO) largely determines the performance of fixed-field intensity modulated radiation therapy (IMRT), and it is usually considered as non-convex optimization and an NP hard problem. In this work, BAO is reformulated into a highly efficient framework of standard quadratic optimization. The maximum of beamlet intensities for each incident field as the surrogate variable indicating whether one radiation field has been selected. By converting the function of maximum value in the objective into a set of linear constraints, the problem is solved as standard quadratic optimization via reweighting l1-norm scheme. The performance of the proposed BAO has been verified on a digital phantom and two patients. And the conclusion is drawn: the proposed convex optimization framework is able to find an optimal set of beam angles, leading to improved dose sparing on OARs in fixed-field IMRT.