Literature DB >> 30153339

Inverse-planned deliverable 4D-IMRT for lung SBRT.

Mahdi Hamzeei1, Arezoo Modiri1, Narges Kazemzadeh1, Aaron Hagan1, Amit Sawant1.   

Abstract

PURPOSE: We present a particle swarm optimization (PSO)-based technique to create deliverable four-dimensional (4D = 3D + time) intensity-modulated radiation therapy (IMRT) plans for lung stereotactic body radiotherapy (SBRT). The 4D planning concept uses respiratory motion as an additional degree of freedom to achieve further sparing of organs at risk (OARs). The 4D-IMRT plan involves the delivery of an order of magnitude more IMRT apertures (~15,000-20,000), with potentially large interaperture variations in the delivered fluence, compared to conventional (i.e., 3D) IMRT. In order to deliver the 4D plan in an efficient manner, we present an optimization-based aperture sequencing technique.
METHOD: A graphic processing unit (GPU)-enabled PSO-based inverse planning engine, developed and integrated with a research version of the Eclipse (Varian, Palo Alto, CA) treatment planning system (TPS), was employed to create 4D-IMRT plans as follows. Four-dimensional computed tomography scans (4DCTs) and beam configurations from clinical treatment plans of seven lung cancer patients were retrospectively collected, and in each case, the PSO engine iteratively adjusted aperture monitor unit (MU) weights for all beam apertures across all respiratory phases to optimize OAR dose sparing while maintaining planning target volume (PTV) coverage. We calculated the transition times from each aperture to all other apertures for each beam, taking into account the maximum leaf velocity of the multileaf collimator (MLC), and developed a mixed integer optimization technique for aperture sequencing. The goal of sequencing was to maximize delivery efficiency (i.e., minimize the time required to deliver the dose map) by accounting for leaf velocity, aperture MUs, and duration of each respiratory phase. The efficiency of the proposed delivery method was compared with that of a greedy algorithm which chose only from neighboring apertures for the subsequent steps in the sequence.
RESULTS: 4D-IMRT-optimized plans achieved PTV coverage comparable to clinical plans while improving OAR sparing by an average of 39.7% for D max heart, 20.5% for D max esophagus, 25.6% for D max spinal cord, and 2.1% for V 13 lung (with D max standing for maximum dose and V 13 standing for volume receiving ≥ 13 Gy). Our mixed integer optimization-based aperture sequencing enabled the delivery to be performed in fewer cycles compared to the greedy method. This reduction was 89 ± 79 cycles corresponding to an improvement of 15.94 ± 8.01%, when considering respiratory cycle duration of 4 s, and 55 ± 33 cycles corresponding to an improvement of 15.14 ± 4.45%, when considering respiratory cycle duration of 6 s.
CONCLUSION: PSO-based 4D-IMRT represents an attractive technique to further improve OAR sparing in lung SBRT. Efficient delivery of a large number of sparse apertures (control points) introduces a challenge in 4D-IMRT treatment planning and delivery. Through judicious optimization of the aperture sequence across all phases, such delivery can be performed on a clinically feasible time scale.
© 2018 American Association of Physicists in Medicine.

Entities:  

Keywords:  4D-IMRT; aperture sequencing; lung SBRT; mixed integer programming; particle swarm optimization

Mesh:

Year:  2018        PMID: 30153339      PMCID: PMC6234081          DOI: 10.1002/mp.13157

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


  26 in total

1.  Improved leaf sequencing reduces segments or monitor units needed to deliver IMRT using multileaf collimators.

Authors:  M Langer; V Thai; L Papiez
Journal:  Med Phys       Date:  2001-12       Impact factor: 4.071

2.  Four-dimensional intensity-modulated radiation therapy planning for dynamic tracking using a direct aperture deformation (DAD) method.

Authors:  Minzhi Gui; Yuanming Feng; Byongyong Yi; Anil Arvind Dhople; Cedric Yu
Journal:  Med Phys       Date:  2010-05       Impact factor: 4.071

3.  Inverse planning for four-dimensional (4D) volumetric modulated arc therapy.

Authors:  Yunzhi Ma; Daniel Chang; Paul Keall; Yiaoqin Xie; Jae-yoon Park; Tae-suk Suh; Lei Xing
Journal:  Med Phys       Date:  2010-11       Impact factor: 4.071

4.  A multi-institutional study to assess adherence to lung stereotactic body radiotherapy planning goals.

Authors:  Andrew Woerner; John C Roeske; Matthew M Harkenrider; John Fan; Bulent Aydogan; Matthew Koshy; Robert Laureckas; Faisal Vali; Maria Campana; Murat Surucu
Journal:  Med Phys       Date:  2015-08       Impact factor: 4.071

5.  Determination of maximum leaf velocity and acceleration of a dynamic multileaf collimator: implications for 4D radiotherapy.

Authors:  K Wijesooriya; C Bartee; J V Siebers; S S Vedam; P J Keall
Journal:  Med Phys       Date:  2005-04       Impact factor: 4.071

6.  Temporo-spatial IMRT optimization: concepts, implementation and initial results.

Authors:  Alexei Trofimov; Eike Rietzel; Hsiao-Ming Lu; Benjamin Martin; Steve Jiang; George T Y Chen; Thomas Bortfeld
Journal:  Phys Med Biol       Date:  2005-05-25       Impact factor: 3.609

7.  The susceptibility of IMRT dose distributions to intrafraction organ motion: an investigation into smoothing filters derived from four dimensional computed tomography data.

Authors:  Catherine Coolens; Phil M Evans; Joao Seco; Steve Webb; Jane M Blackall; Eike Rietzel; George T Y Chen
Journal:  Med Phys       Date:  2006-08       Impact factor: 4.071

8.  Inverse 4D conformal planning for lung SBRT using particle swarm optimization.

Authors:  A Modiri; X Gu; A Hagan; R Bland; P Iyengar; R Timmerman; A Sawant
Journal:  Phys Med Biol       Date:  2016-08-01       Impact factor: 3.609

9.  Motion management with phase-adapted 4D-optimization.

Authors:  Omid Nohadani; Joao Seco; Thomas Bortfeld
Journal:  Phys Med Biol       Date:  2010-08-16       Impact factor: 3.609

10.  Four-dimensional IMRT treatment planning using a DMLC motion-tracking algorithm.

Authors:  Yelin Suh; Amit Sawant; Raghu Venkat; Paul J Keall
Journal:  Phys Med Biol       Date:  2009-05-28       Impact factor: 3.609

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