Inverse‐planned deliverable 4D‐IMRT for lung SBRT

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...

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Bibliographic Details
Published in:Medical physics (Lancaster) 2018-11, Vol.45 (11), p.5145-5160
Main Authors: Hamzeei, Mahdi, Modiri, Arezoo, Kazemzadeh, Narges, Hagan, Aaron, Sawant, Amit
Format: Article
Language:English
Subjects:
4D‐IMRT
aperture sequencing
Four-Dimensional Computed Tomography
Humans
Lung Neoplasms - diagnostic imaging
Lung Neoplasms - physiopathology
Lung Neoplasms - radiotherapy
lung SBRT
mixed integer programming
Movement
particle swarm optimization
Radiosurgery
Radiotherapy Dosage
Radiotherapy Planning, Computer-Assisted - methods
Respiration
Retrospective Studies
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Summary: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 Dmax heart, 20.5% for Dmax esophagus, 25.6% for Dmax spinal cord, and 2.1% for V13 lung (with Dmax standing for maximum dose and V13 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
ISSN:0094-2405
2473-4209
DOI:10.1002/mp.13157