Validation of Dosimetric Leaf Gap (DLG) prior to its implementation in Treatment Planning System (TPS): TrueBeam™ millennium 120 leaf MLC

Impact of MLC error on dose distribution in SRS treatment of single-isocenter multiple brain metastases: comparison between DCAT and VMAT techniques

Background

Dynamic conformal arc therapy (DCAT) and volumetric modulated arc therapy (VMAT) can achieve near equal plan quality in single-isocenter multiple target stereotactic radiosurgery (SRS) for brain metastases. This study aimed to investigate the impact of multi-leaf collimator (MLC) errors during beam delivery on the dose distribution for each technique.

Materials and methods

A 10-mm diameter delineation of the three targets was employed on the computed tomography images of a head phantom, and the reference plans were created using the DCAT and VMAT. We simulated the systematic opened and closed MLC errors. 10 MLC error plans with different magnitudes of errors were created in each technique. We investigated the relationship between the magnitude of MLC errors and the change in dose-volume histogram parameters of the targets and normal brain tissue.

Results

The percentage change in the D98% (Gy) and D0.1% (Gy) of the target per millimeter of the MLC errors were 13.3% and 2.7% for the DCAT and 15.3% and 9.3% for the VMAT, respectively. The fluctuations of the maximum dose were very small for the DCAT compared to the VMAT. Changes in the V12Gy (cc) of the normal brain tissue were 47.1%/mm and 53.2%/mm for the DCAT and VMAT, respectively, which are comparable changes for both techniques.

Conclusions

Although the impact of MLC errors on the target coverage and the normal brain tissue is comparable for both techniques, the internal dose of the targets generated by the DCAT technique is robust to the MLC errors.

Assessment of the Sun Nuclear ArcCHECK to detect errors in 6MV FFF VMAT delivery of brain SABR using ROC analysis

Institutions use a range of different detector systems for patient-specific quality assurance (QA) measurements conducted to assure that the dose delivered by a patient's radiotherapy treatment plan matches the calculated dose distribution. However, the ability of different detectors to detect errors from different sources is often unreported. This study contains a systematic evaluation of Sun Nuclear's ArcCHECK in terms of the detectability of potential machine-related treatment errors. The five investigated sources of error were multileaf collimator (MLC) leaf positions, gantry angle, collimator angle, jaw positions, and dose output. The study encompassed the clinical treatment plans of 29 brain cancer patients who received stereotactic ablative radiotherapy (SABR). Six error magnitudes were investigated per source of error. In addition, the Eclipse AAA beam model dosimetric leaf gap (DLG) parameter was varied with four error magnitudes. Error detectability was determined based on the area under the receiver operating characteristic (ROC) curve (AUC). Detectability of DLG errors was good or excellent (AUC >0.8) at an error magnitude of at least ±0.4 mm, while MLC leaf position and gantry angle errors reached good or excellent detectability at error magnitudes of at least 1.0 mm and 0.6°, respectively. Ideal thresholds, that is, gamma passing rates, to maximize sensitivity and specificity ranged from 79.1% to 98.7%. The detectability of collimator angle, jaw position, and dose output errors was poor for all investigated error magnitudes, with an AUC between 0.5 and 0.6. The ArcCHECK device's ability to detect errors from treatment machine-related sources was evaluated, and ideal gamma passing rate thresholds were determined for each source of error. The ArcCHECK was able to detect errors in DLG value, MLC leaf positions, and gantry angle. The ArcCHECK was unable to detect the studied errors in collimator angle, jaw positions, and dose output.

Investigating the use of aperture shape controller in VMAT treatment deliveries

BACKGROUND

Aperture shape controller (ASC) is a recently introduced leaf sequencer that controls the complexity of multileaf collimator apertures in the Photon Optimizer algorithm of the Eclipse treatment planning system. The aim of this study is to determine if the ASC can reduce plan complexity and improve verification results, without compromising plan quality.

METHODS

Thirteen plans grouped into cohorts of head and neck/brain, breast/chest and pelvis were reoptimised using the same optimization as the non-ASC setting for low, moderate and high ASC settings. These plans were analyzed using plan quality indices such as the conformity index and homogeneity index in addition to dose-volume histogram based analysis on PTVs and organ at risks. Complexity assessments were performed using metrics such as average leaf pair opening, modulation complexity scores, relative monitor units (MU) and treatment time. Monitor unit per gantry angle variations were also analyzed. A third-party algorithm was also used to assess 3D dose distributions produced using the new leaf sequencer tool. Deliverability for the final multileaf collimator distribution was quantified using portal dose image prediction based gamma analysis.

RESULTS

Plan conformality assessments showed comparable results and no significant plan degradation for plans reoptimised using ASC. Reduction in overall MU distributions were seen in some cases using higher ASC however, no overall trends were observed. In general, treatment deliverability, assessed using gamma analysis did not improve drastically however MU per degree distribution in 1 case improved when reoptimised using ASC. Treatment MUs generally reduced when ASC settings were used whilst in 1 case an increase in the treatment time factor > 1.8 was observed. The third-party algorithm assessment showed an underestimation of dose calculations for all cohorts used in this study when a higher ASC setting is used.

CONCLUSIONS

The impact of using ASC in treatment plans was characterised in this study. Although plan complexity marginally improved when using higher ASC settings, no consensus could be reached based on metrics analyzed in this study. A reduction in MU distribution was observed with increasing ASC settings in most cases. This study recommends that ASC to be used as an additional tool only to test its suitability to reduce plan complexity.