Explicit optimization of plan quality measures in intensity-modulated radiation therapy treatment planning

TL;DR

This paper introduces a new convex optimization framework for IMRT treatment planning that explicitly optimizes DVH statistics, leading to better dose distribution control and plan quality compared to conventional penalty-based methods.

Contribution

The authors propose a novel planning objective based on mean-tail-dose, enabling explicit DVH statistic optimization and reducing computational costs in IMRT planning.

Findings

Proposed method improves DVH statistic optimization.

Plans show better dose distribution balance.

Computational efficiency is significantly enhanced.

Abstract

Conventional planning objectives in optimization of intensity-modulated radiotherapy treatment (IMRT) plans are designed to minimize the violation of dose-volume histogram (DVH) thresholds using penalty functions. Although successful in guiding the DVH curve towards these thresholds, conventional planning objectives offer limited control of the individual points on the DVH curve (doses-at-volume) used to evaluate plan quality. In this study, we abandon the usual penalty-function framework and propose planning objectives that more explicitly relate to DVH statistics. The proposed planning objectives are based on mean-tail-dose, resulting in convex optimization. We also demonstrate how to adapt a standard optimization method to the proposed formulation in order to obtain a substantial reduction in computational cost. We investigate the potential of the proposed planning objectives as tools for optimizing DVH statistics through juxtaposition with the conventional planning objectives on two patient cases. Sets of treatment plans with differently balanced planning objectives are generated using either the proposed or the conventional approach. Dominance in the sense of better distributed doses-at-volume is observed in plans optimized within the proposed framework, indicating that the DVH statistics are better optimized and more efficiently balanced using the proposed planning objectives.