Evidence map›Paper›PMID 30153339›Full record

ArticleMedical physics2018

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

Mahdi Hamzeei, Arezoo Modiri, Narges Kazemzadeh, Aaron Hagan, Amit Sawant

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PubMed Full text at PMC Publisher
In one paragraph

Article in Medical physics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
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2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Mahdi HamzeeiSchool of Medicine, University of Maryland, 685 W Baltimore St., Baltimore, MD, 21201, USA.
Arezoo ModiriSchool of Medicine, University of Maryland, 685 W Baltimore St., Baltimore, MD, 21201, USA.
Narges KazemzadehSchool of Medicine, University of Maryland, 685 W Baltimore St., Baltimore, MD, 21201, USA.
Aaron HaganSchool of Medicine, University of Maryland, 685 W Baltimore St., Baltimore, MD, 21201, USA.
Amit SawantSchool of Medicine, University of Maryland, 685 W Baltimore St., Baltimore, MD, 21201, USA.

Funding

Personalized Motion Management for truly 4D Lung Stereotactic Body RadiotherapyR01CA169102 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI SAWANT, AMIT · 2013 to 2018
$2.8M
NCI NIH HHS R01 CA169102NIH HHS R01CA169102
6 · The paper itself

Abstract

purposeWe 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.

methodA 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.

results4D-IMRT-optimized plans achieved PTV coverage comparable to clinical plans while improving OAR sparing by an average of 39.7% for

conclusionPSO-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.

Indexed as

Four-Dimensional Computed TomographyRadiosurgeryHumansLung NeoplasmsMovementRadiotherapy DosageRadiotherapy Planning, Computer-AssistedRespirationRetrospective Studies4D-IMRTaperture sequencinglung SBRTmixed integer programmingparticle swarm optimization

Identifiers

PMID30153339
PMCPMC6234081

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.