Multi-Criteria Optimization for Image Guidance

TL;DR

This paper introduces a multi-criteria optimization framework to improve patient setup decisions in image-guided radiotherapy, balancing tumor coverage and organ protection amid daily variations.

Contribution

It presents a novel algorithm that integrates dosimetric constraints into patient positioning decisions, enhancing accuracy for deformable and moving targets.

Findings

The framework enables clinical decision-making for patient positioning.

Optimal patient setups can be derived considering dosimetric goals.

The approach accommodates daily anatomical changes.

Abstract

Purpose: To develop a multi-criteria optimization framework for image guided radiotherapy. Methods: An algorithm is proposed for a multi-criteria framework for the purpose of patient setup verification decision processes. Optimal patient setup shifts and rotations are not always straightforward, particularly for deformable or moving targets of the spine, abdomen, thorax, breast, head and neck and limbs. The algorithm relies upon dosimetric constraints and objectives to aid in the patient setup such that the patient is setup to maximize tumor dose coverage and minimize dose to organs at risk while allowing for daily clinical changes. A simple 1D model and a lung lesion are presented. Results: The algorithm delivers a multi-criteria optimization framework allowing for clinical decisions to accommodate patient target variation make setup decisions less straightforward. With dosimetric considerations, optimal patient positions can be derived. Conclusions: A multi-criteria framework is demonstrated to aid in the patient setup and determine the most appropriate daily position considering dosimetric goals.