Comparing Radiation Treatments Using Intensity-Modulated Beams, Multiple Arcs, and Single Arcs

Tang, Grace; Earl, M.; Luan, Shuang; Wang, Chao; Mohiuddin, Majid; Yu, C

doi:10.1016/j.ijrobp.2009.04.003

Cited by 44 publications

(41 citation statements)

References 12 publications

(14 reference statements)

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“…Volumetric‐modulated arc therapy (VMAT) offers equivalent or higher conformity to target volumes and faster delivery times compared to step and shoot or dynamic intensity‐modulated radiotherapy (IMRT) 1 , 2 . VMAT is a system for intensity‐modulated radiotherapy treatment delivery that achieves high dose conformality by optimizing the dose rate, gantry speed, and the leaf positions of the dynamic multileaf collimator.…”

Section: Introductionmentioning

confidence: 99%

Correlation of phantom‐based and log file patient‐specific QA with complexity scores for VMAT

Agnew

Irvine

McGarry

2014

J Applied Clin Med Phys

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The motivation for this study was to reduce physics workload relating to patient‐specific quality assurance (QA). VMAT plan delivery accuracy was determined from analysis of pre‐ and on‐treatment trajectory log files and phantom‐based ionization chamber array measurements. The correlation in this combination of measurements for patient‐specific QA was investigated. The relationship between delivery errors and plan complexity was investigated as a potential method to further reduce patient‐specific QA workload. Thirty VMAT plans from three treatment sites — prostate only, prostate and pelvic node (PPN), and head and neck (H&N) — were retrospectively analyzed in this work. The 2D fluence delivery reconstructed from pretreatment and on‐treatment trajectory log files was compared with the planned fluence using gamma analysis. Pretreatment dose delivery verification was also carried out using gamma analysis of ionization chamber array measurements compared with calculated doses. Pearson correlations were used to explore any relationship between trajectory log file (pretreatment and on‐treatment) and ionization chamber array gamma results (pretreatment). Plan complexity was assessed using the MU/ arc and the modulation complexity score (MCS), with Pearson correlations used to examine any relationships between complexity metrics and plan delivery accuracy. Trajectory log files were also used to further explore the accuracy of MLC and gantry positions. Pretreatment 1%/1 mm gamma passing rates for trajectory log file analysis were 99.1% (98.7%–99.2%), 99.3% (99.1%–99.5%), and 98.4% (97.3%–98.8%) (median (IQR)) for prostate, PPN, and H&N, respectively, and were significantly correlated to on‐treatment trajectory log file gamma results (normalR=0.989,p<0.001). Pretreatment ionization chamber array (2%/2 mm) gamma results were also significantly correlated with on‐treatment trajectory log file gamma results (normalR=0.623,p<0.001). Furthermore, all gamma results displayed a significant correlation with MCS (normalR>0.57,p<0.001), but not with MU/arc. Average MLC position and gantry angle errors were 0.001±0.002.15emmm and 0.025°±0.008° over all treatment sites and were not found to affect delivery accuracy. However, variability in MLC speed was found to be directly related to MLC position accuracy. The accuracy of VMAT plan delivery assessed using pretreatment trajectory log file fluence delivery and ionization chamber array measurements were strongly correlated with on‐treatment trajectory log file fluence delivery. The strong correlation between trajectory log file and phantom‐based gamma results demonstrates potential to reduce our current patient‐specific QA. Additionally, insight into MLC and gantry position accuracy through trajectory log file analysis and the strong correlation between gamma analysis results and the MCS could also provide further methodologies to both optimize the VMAT planning and QA process.PACS number: 87.53.Bn, 87.55.Kh, 87.55.Qr

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Section: Introductionmentioning

confidence: 99%

Correlation of phantom‐based and log file patient‐specific QA with complexity scores for VMAT

Agnew

Irvine

McGarry

2014

J Applied Clin Med Phys

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Section: Introductionmentioning

confidence: 99%

“…For VMAT however, the increase of available intensity levels, ( 10 , 14 ) achieved by superposition of several modulated arcs, allowed better dose conformality than in a single modulated arc. One of the studies ( 14 ) utilized two‐stage optimization process, where fluence maps optimization and their conversion into multileaf collimator (MLC) trajectories are separated. The other work utilized deliverable ( 15 – 18 ) optimization, where the fluence‐map‐to MLC trajectories conversion is incorporated into the optimization process, thereby explicitly accounting for MLC leaf position weights.…”

Section: Introductionmentioning

confidence: 99%

The effect of gantry spacing resolution on plan quality in a single modulated arc optimization

Mihaylov

Curran

Sternick

2011

J Applied Clin Med Phys

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Volumetric‐modulated arc technique (VMAT) is an efficient form of IMRT delivery. It is advantageous over conventional IMRT in terms of treatment delivery time. This study investigates the relation between the number of segments and plan quality in VMAT optimization for a single modulated arc. Five prostate, five lung, and five head‐and‐neck (HN) patient plans were studied retrospectively. For each case, four VMAT plans were generated. The plans differed only in the number of control points used in the optimization process. The control points were spaced 2°, 3°, 4°, and 6° apart, respectively. All of the optimization parameters were the same among the four schemes. The 2° spacing plan was used as a reference to which the other three plans were compared. The plan quality was assessed by comparison of dose indices (DIs) and generalized equivalent uniform doses (gEUDs) for targets and critical structures. All optimization schemes generated clinically acceptable plans. The differences between the majority of reference and compared DIs and gEUDs were within 3%. DIs and gEUDs which differed in excess of 3% corresponded to dose levels well below the organ tolerances. The DI and the gEUD differences increased with an increase in plan complexity from prostates to HNs. Optimization with gantry spacing resolution of 4° seems to be a very balanced alternative between plan quality and plan complexity.PACS number: 87.55.de

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“…This is not a failure of ROCO but rather a consequence of the difficulty of directly comparing two plans, a difficult and well-known problem. [29][30][31][32] As a result, it was sometimes necessary to reoptimize patients using lower organ dose constraints or a lower PTV max dose constraint. When ROCO is used as a standalone planning tool, without the intention of comparing to a reference plan, this step is not necessary, because the ROCO D 95 would be clinically acceptable.…”

Section: Iiib Clinical Plan Comparisonmentioning

confidence: 99%

Reduced order constrained optimization (ROCO): Clinical application to lung IMRT

et al. 2011

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Purpose: The authors use reduced-order constrained optimization (ROCO) to create clinically acceptable IMRT plans quickly and automatically for advanced lung cancer patients. Their new ROCO implementation works with the treatment planning system and full dose calculation used at Memorial Sloan-Kettering Cancer Center (MSKCC). The authors have implemented mean dose hard constraints, along with the point-dose and dose-volume constraints that the authors used for our previous work on the prostate. Methods: ROCO consists of three major steps. First, the space of treatment plans is sampled by solving a series of optimization problems using penalty-based quadratic objective functions. Next, an efficient basis for this space is found via principal component analysis (PCA); this reduces the dimensionality of the problem. Finally, a constrained optimization problem is solved over this basis to find a clinically acceptable IMRT plan. Dimensionality reduction makes constrained optimization computationally efficient. Results: The authors apply ROCO to 12 stage III non-small-cell lung cancer (NSCLC) cases, generating IMRT plans that meet all clinical constraints and are clinically acceptable, and demonstrate that they are competitive with the clinical treatment plans. The authors also test how many samples and PCA modes are necessary to achieve an adequate lung plan, demonstrate the importance of long-range dose calculation for ROCO, and evaluate the performance of nonspecific normal tissue ("rind") constraints in ROCO treatment planning for the lung. Finally, authors show that ROCO can save time for planners, and they estimate that in the clinic, planning using their approach would save a median of 105 min for the patients in the study. Conclusions: New challenges arise when applying ROCO to the lung site, which include the lack of a class solution, a larger treatment site, an increased number of parameters and beamlets, a variable number of beams and beam arrangement, and the customary use of rinds in clinical plans to avoid high-dose areas outside the PTV. In the authors previous work, use of an approximate dose calculation in the hard constraint optimization sometimes meant that clinical constraints were not met when evaluated with the full dose calculation. This difficulty has been removed in the current work by using the full dose calculation in the hard constraint optimization. The authors have demonstrated that ROCO offers a fast and automatic way to create IMRT plans for advanced NSCLC, which extends their previous application of ROCO to prostate cancer IMRT planning.

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Comparing Radiation Treatments Using Intensity-Modulated Beams, Multiple Arcs, and Single Arcs

Cited by 44 publications

References 12 publications

Correlation of phantom‐based and log file patient‐specific QA with complexity scores for VMAT

Correlation of phantom‐based and log file patient‐specific QA with complexity scores for VMAT

The effect of gantry spacing resolution on plan quality in a single modulated arc optimization

Reduced order constrained optimization (ROCO): Clinical application to lung IMRT

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