ESTRO 2024 - Abstract Book

S3702

Physics - Dose prediction, optimisation and applications of photon and electron planning

ESTRO 2024

Purpose/Objective:

The selection of the collimator angle for linac-based stereotactic radiosurgery (SRS) of multiple brain metastases (BMs) is important to reduce the bridge dose in between the different lesions and minimize brain toxicities. Previous research on collimator angle optimization considered the geometrical projection of the PTV onto the beam-eye-view and aimed to select a collimator angle at each beam orientation which minimizes the exposed area by the multileaf collimator (MLC) between different lesions, independent of the dose distribution [1]. In this work, we developed an algorithm that simultaneously optimizes the dose distribution and the collimator angle for linac-based SRS of multiple BMs.

Material/Methods:

A column generation-based direct aperture optimization (CG-DAO) algorithm was implemented into our in-house research optimization platform. The algorithm workflow is schematically illustrated in Figure 1. Starting from an empty set of apertures, promising multileaf collimated apertures are iteratively determined for different beam orientations and different collimator angles by solving a so-called pricing problem [2], where the dose-influence matrices and the corresponding bixel gradients for apertures at non-zero collimator angles are approximated from the dose-influence matrix and bixel gradients at 0° using a rotation function. The resulting candidate apertures have an associated price, given by the sum of the gradient contributions of each of the bixels not covered by the MLC, and the aperture with the lowest price is added to the treatment plan at each iteration. After each iteration of the CG-DAO algorithm, the weights of all apertures in the plan are re-optimized and the apertures with zero weight are removed. The optimization stops when a user-defined number of apertures are generated.