Increased accuracy of planning tools for optimization of dynamic multileaf collimator delivery of radiotherapy through reformulated objective functions

Lovisa Engberg,Kjell Eriksson,Anders Forsgren

doi:10.1088/1361-6560/aac70a

Abstract

The purpose of this study is to examine in a clinical setting a novel formulation of objective functions for intensity-modulated radiotherapy treatment plan multicriteria optimization (MCO) that we suggested in a recent study. The proposed objective functions are extended with dynamic multileaf collimator (DMLC) delivery constraints from the literature, and a tailored interior point method is described to efficiently solve the resulting optimization formulation. In a numerical planning study involving three patient cases, DMLC plans Pareto optimal to the MCO formulation with the proposed objective functions are generated. Evaluated based on pre-defined plan quality indices, these DMLC plans are compared to conventionally generated DMLC plans. Comparable or superior plan quality is observed. Supported by these results, the proposed objective functions are argued to have a potential to streamline the planning process, since they are designed to overcome the methodological shortcomings associated with the conventional penalty-based objective functions assumed to cause the current need for time-consuming trial-and-error parameter tuning. In particular, the increased accuracy of the planning tools imposed by the proposed objective functions has the potential to make the planning process less complicated. These conclusions position the proposed formulation as an alternative to existing methods for automated planning.

Highlights

Optimization of intensity-modulated radiation therapy (IMRT) treatment plans using the widely used penalty-based objective functions results in plans of high quality in a majority of cases
A doseat-volume index here refers to the dose level at a given volume fraction in the dosevolume histograms (DVHs) of a region of interest (ROI), such as a planning target volume (PTV) or an organ at risk (OAR), corresponding to the minimum dose received by this fraction of the particular ROI
To examine the ability of the proposed objective functions to produce high-quality dynamic multileaf collimator (DMLC) plans, we have studied the plan quality indices obtained among DMLC plans Pareto optimal to (2.1)

Summary

Introduction

Optimization of intensity-modulated radiation therapy (IMRT) treatment plans using the widely used penalty-based objective functions results in plans of high quality in a majority of cases Appenzoller et al [2] suggest a method to predict achievable dosevolume histograms (DVHs) to be used as reference, and Fredriksson [10] describes a technique to reduce the dose delivered to healthy tissue subsequent to optimization. McIntosh and Purdie [13] and Shiraishi and Moore [20] present methods to predict an achievable dose distribution to possibly input in a subsequent automated plan reconstruction phase, and Wu et al [25] and Appenzoller et al [2] suggest methods to predict parts of or entire achievable DVHs to support the planner’s desicions on planning parameters. Gintz et al [11] describe and evaluate a clinically available computerization strategy to mimic a planning scheme that can handle a general patient case

Objectives

Methods

Results

Conclusion