Target tracking using DMLC for volumetric modulated arc therapy: A simulation study

Sun, Baozhou; Rangaraj, D; Papież, Lech; Oddiraju, Swetha; Yang, Deshan; Li, H. Harold

doi:10.1118/1.3511516

Cited by 13 publications

(21 citation statements)

References 37 publications

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“…[2][3][4][5][6][7] Dynamic multileaf collimator (DMLC) tracking is a method to compensate for intrafraction target motion by real-time adaption of the MLC aperture to the targets movement. [8][9][10][11][12][13][14][15][16][17] Other methods of motion compensation, not covered in this study, include beam gating, moving the source, and couch tracking. The accuracy of DMLC tracking depends on the alignment between the leaves and the target motion, with motion perpendicular to the leaf travel being more challenging.…”

Section: Introductionmentioning

confidence: 99%

The impact of leaf width and plan complexity on DMLC tracking of prostate intensity modulated arc therapy

et al. 2013

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Purpose: Intensity modulated arc therapy (IMAT) is commonly used to treat prostate cancer. The purpose of this study was to evaluate the impact of leaf width and plan complexity on dynamic multileaf collimator (DMLC) tracking for prostate motion management during IMAT treatments. Methods: Prostate IMAT plans were delivered with either a high-definition MLC (HDMLC) or a Millennium MLC (M-MLC) (0.25 and 0.50 cm central leaf width, respectively), with and without DMLC tracking, to a dosimetric phantom that reproduced four prostate motion traces. The plan complexity was varied by applying leaf position constraints during plan optimization. A subset of the M-MLC plans was converted for delivery with the HDMLC, isolating the effect of the different leaf widths. The gamma index was used for evaluation. Tracking errors caused by target localization, leaf fitting, and leaf adjustment were analyzed. Results: The gamma pass rate was significantly improved with DMLC tracking compared to no tracking (p < 0.001). With DMLC tracking, the average gamma index pass rate was 98.6% (range 94.8%-100%) with the HDMLC and 98.1% (range 95.4%-99.7%) with the M-MLC, using 3%, 3 mm criteria and the planned dose as reference. The corresponding pass rates without tracking were 87.6% (range 76.2%-94.7%) and 91.1% (range 81.4%-97.6%), respectively. Decreased plan complexity improved the pass rate when static target measurements were used as reference, but not with the planned dose as reference. The main cause of tracking errors was leaf fitting errors, which were decreased by 42% by halving the leaf width. Conclusions: DMLC tracking successfully compensated for the prostate motion. The finer leaf width of the HDMLC improved the tracking accuracy compared to the M-MLC. The tracking improvement with limited plan complexity was small and not discernible when using the planned dose as reference.

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Section: Introductionmentioning

confidence: 99%

The impact of leaf width and plan complexity on DMLC tracking of prostate intensity modulated arc therapy

et al. 2013

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“…The tracking algorithm was based on the algorithm developed by Sawant et al for motion compensation30 and studies on modifications of beam parameters to generate a linac deliverable plan 31, 33, 34, 35. All machine parameters such as MLC leaf speed, gantry speed, and gantry acceleration were within limits (Table 1) after MLC leaf modification.…”

Section: Methodsmentioning

confidence: 99%

“…However, in actual delivery, there is a finite time before dose rate reaches the planned value 31, 32, 35. By acquiring delivery parameters (e.g., MLC leaf position errors) of 4D DCAT plans, we could evaluate the discrepancy between plans generated by simulation algorithm and the actual delivered ones.…”

Section: Methodsmentioning

confidence: 99%

“…Several studies implemented motion tracking with dynamic MLC treatment delivery for either Varian or Elekta linac and reported improved target dose coverage without significantly increasing the total treatment time 30, 31, 32, 33, 34, 35. Sawant et al developed lung tumor motion compensation method where target motion that is decomposed to the beam's eye view (BEV) is dependent on collimator, gantry, and couch angles 30.…”

Section: Introductionmentioning

confidence: 99%

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Effects of collimator angle, couch angle, and starting phase on motion‐tracking dynamic conformal arc therapy (4D DCAT)

Yao

Podgorsak

et al. 2017

J Applied Clin Med Phys

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PurposeThe aim of this study was to find an optimized configuration of collimator angle, couch angle, and starting tracking phase to improve the delivery performance in terms of MLC position errors, maximal MLC leaf speed, and total beam‐on time of DCAT plans with motion tracking (4D DCAT).Method and materialsNontracking conformal arc plans were first created based on a single phase (maximal exhalation phase) of a respiratory motion phantom with a spherical target. An ideal model was used to simulate the target motion in superior‐inferior (SI), anterior‐posterior (AP), and left‐right (LR) dimensions. The motion was decomposed to the MLC leaf position coordinates for motion compensation and generating 4D DCAT plans. The plans were studied with collimator angle ranged from 0° to 90°; couch angle ranged from 350°(−10°) to 10°; and starting tracking phases at maximal inhalation (θ=π/2) and exhalation (θ=0) phases. Plan performance score (PPS) evaluates the plan complexity including the variability in MLC leaf positions, degree of irregularity in field shape and area. PPS ranges from 0 to 1, where low PPS indicates a plan with high complexity. The 4D DCAT plans with the maximal and the minimal PPS were selected and delivered on a Varian TrueBeam linear accelerator. Gafchromic‐EBT3 dosimetry films were used to measure the dose delivered to the target in the phantom. Gamma analysis for film measurements with 90% passing rate threshold using 3%/3 mm criteria and trajectory log files were analyzed for plan delivery accuracy evaluation.ResultsThe maximal PPS of all the plans was 0.554, achieved with collimator angle at 87°, couch angle at 350°, and starting phase at maximal inhalation (θ=π/2). The maximal MLC leaf speed, MLC leaf errors, total leaf travel distance, and beam‐on time were 20 mm/s, 0.39 ± 0.16 mm, 1385 cm, and 157 s, respectively. The starting phase, whether at maximal inhalation or exhalation had a relatively small contribution to PPS (0.01 ± 0.05).ConclusionsBy selecting collimator angle, couch angle, and starting tracking phase, 4D DCAT plans with the maximal PPS demonstrated less MLC leaf position errors, lower maximal MLC leaf speed, and shorter beam‐on time which improved the performance of 4D motion‐tracking DCAT delivery.

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“…The MLC essentially allows the beam (or matrix of beamlets) to be shaped to the contour of the tumor by blocking parts of the beam with the leaves. Volumetric modulated arc therapy (VMAT) [18,20] involves continuous motion of the beam around the patient to track the tumor, has been developed in order to minimize beam on-time and reduce danger to the patient. In this paper we present a novel method for algorithmically computing the point or points in time that a tumor is most exposed, for the purpose of supporting IMRT (with multi-leaf collimator) treatments.…”

Section: Introductionmentioning

confidence: 99%

Radiation therapy simulation and optimization using kinetic polygon modeling

Allen

Daescu

2013

2013 IEEE 14th International Conference on Information Reuse &Amp; Integration (IRI)

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Intensity modulated radiotherapy (IMRT) is a treatment for various cancers that involves applying a beam of radiation to diseased tumor cells.Although effective at destroying cancerous tissue, physicians must take care to avoid healthy tissues during the treatment plan as these may also be damaged. To improve treatment, computational methods are often employed to allow treatment planners to track the target tumor and apply radiation when it is less obstructed by healthy organs and tissues and thus more exposed to the beam, maximizing the damage to the diseased cells while minimizing the harm to healthy cells. Internal organs and tissues are rarely static, so this optimal time frame can be challenging to pinpoint. In this paper we develop a novel algorithm and accompanying data structure to determine the point in time at which the tumor target is most exposed. By modeling the organs and tumor as a set of moving polygons in the beam's eye view and using a kinetic data structure to track the level of exposure of the tumor as organs in the treatment area move, healthy tissue can be protected and the tumor can be targeted with greater effectiveness and precision, thus improving the overall quality of treatment.

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Target tracking using DMLC for volumetric modulated arc therapy: A simulation study

Cited by 13 publications

References 37 publications

The impact of leaf width and plan complexity on DMLC tracking of prostate intensity modulated arc therapy

The impact of leaf width and plan complexity on DMLC tracking of prostate intensity modulated arc therapy

Effects of collimator angle, couch angle, and starting phase on motion‐tracking dynamic conformal arc therapy (4D DCAT)

Radiation therapy simulation and optimization using kinetic polygon modeling

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