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Deterministic direct aperture optimization using multiphase piecewise constant segmentation.

Dan Nguyen¹, Daniel O'Connor¹, Dan Ruan¹

¹Department of Radiation Oncology, University of Los Angeles California, Los Angeles, CA, USA.

Medical Physics

|August 24, 2017

Summary

This summary is machine-generated.

A new deterministic direct aperture optimization (DAO) method using Mumford-Shah segmentation offers faster computation and improved plan quality, especially for complex cases like head and neck cancer.

Keywords:

direct aperture optimization piecewise constant segmentation

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Area of Science:

Medical Physics
Radiation Oncology
Computational Optimization

Background:

Direct aperture optimization (DAO) aims to integrate machine constraints into inverse optimization, avoiding post-processing steps that can reduce plan quality.
Current commercial DAO methods often use stochastic or greedy approaches, limiting the search space for aperture solutions.

Purpose of the Study:

To develop and evaluate a novel deterministic direct aperture optimization (DAO) method.
This method integrates fluence map optimization with multiphase piecewise constant Mumford-Shah segmentation.

Main Methods:

A Mumford-Shah based DAO formulation was developed, incorporating dose fidelity and total variation terms.
A proximal-class, first-order primal-dual solver was implemented to efficiently solve the large-scale optimization problem.
The method was tested on three patient cases (glioblastoma, lung, head and neck) and compared against simulated annealing DAO (DAO_SA).

Main Results:

The novel DAO (DAO_MS) showed comparable dosimetry to DAO_SA for simpler cases (GBM, lung).
DAO_MS significantly improved organ-at-risk (OAR) sparing and PTV coverage for the complex head and neck case.
DAO_MS demonstrated superior high dose spillage and conformity for the head and neck plan, with 9.5- to 40-fold faster computation times.

Conclusions:

A novel deterministic DAO formulation combining FMO and Mumford-Shah segmentation was successfully developed and evaluated.
This unified framework offers efficient problem-solving.
DAO_MS provides comparable or superior results to commercial DAO_SA, particularly for complex treatment plans, with significant speed advantages.