Literature DB >> 25832076

Dose domain regularization of MLC leaf patterns for highly complex IMRT plans.

Dan Nguyen1, Daniel O'Connor2, Victoria Y Yu1, Dan Ruan1, Minsong Cao1, Daniel A Low1, Ke Sheng1.   

Abstract

PURPOSE: The advent of automated beam orientation and fluence optimization enables more complex intensity modulated radiation therapy (IMRT) planning using an increasing number of fields to exploit the expanded solution space. This has created a challenge in converting complex fluences to robust multileaf collimator (MLC) segments for delivery. A novel method to regularize the fluence map and simplify MLC segments is introduced to maximize delivery efficiency, accuracy, and plan quality.
METHODS: In this work, we implemented a novel approach to regularize optimized fluences in the dose domain. The treatment planning problem was formulated in an optimization framework to minimize the segmentation-induced dose distribution degradation subject to a total variation regularization to encourage piecewise smoothness in fluence maps. The optimization problem was solved using a first-order primal-dual algorithm known as the Chambolle-Pock algorithm. Plans for 2 GBM, 2 head and neck, and 2 lung patients were created using 20 automatically selected and optimized noncoplanar beams. The fluence was first regularized using Chambolle-Pock and then stratified into equal steps, and the MLC segments were calculated using a previously described level reducing method. Isolated apertures with sizes smaller than preset thresholds of 1-3 bixels, which are square units of an IMRT fluence map from MLC discretization, were removed from the MLC segments. Performance of the dose domain regularized (DDR) fluences was compared to direct stratification and direct MLC segmentation (DMS) of the fluences using level reduction without dose domain fluence regularization.
RESULTS: For all six cases, the DDR method increased the average planning target volume dose homogeneity (D95/D5) from 0.814 to 0.878 while maintaining equivalent dose to organs at risk (OARs). Regularized fluences were more robust to MLC sequencing, particularly to the stratification and small aperture removal. The maximum and mean aperture sizes using the DDR were consistently larger than those from DMS for all tested number of segments.
CONCLUSIONS: The fluence map to MLC segmentation conversion problem was formulated as a secondary optimization problem in the dose domain to minimize the smoothness-regularized dose discrepancy. The large scale optimization problem was solved using a primal-dual algorithm that transformed complicated fluences into maps that were more robust to the MLC segmentation and sequencing, affording fewer and larger segments with minimal degradation to dose distribution.

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Mesh:

Year:  2015        PMID: 25832076     DOI: 10.1118/1.4915286

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  14 in total

1.  A novel software and conceptual design of the hardware platform for intensity modulated radiation therapy.

Authors:  Dan Nguyen; Dan Ruan; Daniel O'Connor; Kaley Woods; Daniel A Low; Salime Boucher; Ke Sheng
Journal:  Med Phys       Date:  2016-02       Impact factor: 4.071

2.  VMAT optimization with dynamic collimator rotation.

Authors:  Qihui Lyu; Daniel O'Connor; Dan Ruan; Victoria Yu; Dan Nguyen; Ke Sheng
Journal:  Med Phys       Date:  2018-05-03       Impact factor: 4.071

3.  Many-isocenter optimization for robotic radiotherapy.

Authors:  Qihui Lyu; Ryan Neph; Victoria Y Yu; Dan Ruan; Salime Boucher; Ke Sheng
Journal:  Phys Med Biol       Date:  2020-02-10       Impact factor: 3.609

4.  Use of proximal operator graph solver for radiation therapy inverse treatment planning.

Authors:  Xinmin Liu; Charles Pelizzari; Andrew H Belcher; Zachary Grelewicz; Rodney D Wiersma
Journal:  Med Phys       Date:  2017-04       Impact factor: 4.071

5.  Deterministic direct aperture optimization using multiphase piecewise constant segmentation.

Authors:  Dan Nguyen; Daniel O'Connor; Dan Ruan; Ke Sheng
Journal:  Med Phys       Date:  2017-09-22       Impact factor: 4.071

6.  Using deep learning to predict beam-tunable Pareto optimal dose distribution for intensity-modulated radiation therapy.

Authors:  Gyanendra Bohara; Azar Sadeghnejad Barkousaraie; Steve Jiang; Dan Nguyen
Journal:  Med Phys       Date:  2020-08-02       Impact factor: 4.071

7.  A novel optimization framework for VMAT with dynamic gantry couch rotation.

Authors:  Qihui Lyu; Victoria Y Yu; Dan Ruan; Ryan Neph; Daniel O'Connor; Ke Sheng
Journal:  Phys Med Biol       Date:  2018-06-13       Impact factor: 3.609

8.  Fraction-variant beam orientation optimization for non-coplanar IMRT.

Authors:  Daniel O'Connor; Victoria Yu; Dan Nguyen; Dan Ruan; Ke Sheng
Journal:  Phys Med Biol       Date:  2018-02-15       Impact factor: 3.609

9.  Computerized triplet beam orientation optimization for MRI-guided Co-60 radiotherapy.

Authors:  Dan Nguyen; David Thomas; Minsong Cao; Daniel O'Connor; James Lamb; Ke Sheng
Journal:  Med Phys       Date:  2016-10       Impact factor: 4.071

10.  A comprehensive formulation for volumetric modulated arc therapy planning.

Authors:  Dan Nguyen; Qihui Lyu; Dan Ruan; Daniel O'Connor; Daniel A Low; Ke Sheng
Journal:  Med Phys       Date:  2016-07       Impact factor: 4.071

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