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.

[1]  T. Kairn,et al.  Treatment plan complexity metrics for predicting IMRT pre-treatment quality assurance results , 2014, Australasian Physical & Engineering Sciences in Medicine.

[2]  Steve B. Jiang,et al.  Dependence of fluence errors in dynamic IMRT on leaf-positional errors varying with time and leaf number. , 2003, Medical physics.

[3]  Benedick A Fraass,et al.  Penalization of aperture complexity in inversely planned volumetric modulated arc therapy. , 2012, Medical physics.

[4]  E. Wong,et al.  Intensity-modulated arc therapy simplified. , 2002, International journal of radiation oncology, biology, physics.

[5]  C. Nelson,et al.  Commissioning results of an automated treatment planning verification system , 2014, Journal of applied clinical medical physics.

[6]  Jean M. Moran,et al.  Predicting deliverability of volumetric‐modulated arc therapy (VMAT) plans using aperture complexity analysis , 2016, Journal of applied clinical medical physics.

[7]  P Zygmanski,et al.  Method of identifying dynamic multileaf collimator irradiation that is highly sensitive to a systematic MLC calibration error. , 2001, Medical physics.

[8]  Georges Noël,et al.  Conformity index: a review. , 2006, International journal of radiation oncology, biology, physics.

[9]  Luca Cozzi,et al.  Volumetric-modulated arc radiotherapy for carcinomas of the anal canal: A treatment planning comparison with fixed field IMRT. , 2009, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[10]  Ravindra Shende,et al.  Validation of Dosimetric Leaf Gap (DLG) prior to its implementation in Treatment Planning System (TPS): TrueBeam™ millennium 120 leaf MLC. , 2017, Reports of practical oncology and radiotherapy : journal of Greatpoland Cancer Center in Poznan and Polish Society of Radiation Oncology.

[11]  Luca Cozzi,et al.  A treatment planning study comparing volumetric arc modulation with RapidArc and fixed field IMRT for cervix uteri radiotherapy. , 2008, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[12]  Tanya Kairn,et al.  Retrospective evaluation of dosimetric quality for prostate carcinomas treated with 3D conformal, intensity modulated and volumetric modulated arc radiotherapy , 2013, Journal of medical radiation sciences.

[13]  Tanya Kairn,et al.  Contribution : Photon optimizer ( PO ) vs progressive resolution optimizer ( PRO ) : a conformality-and complexity-based comparison for intensity-modulated arc therapy plans , 2017 .

[14]  Joseph O Deasy,et al.  Quantitative Analyses of Normal Tissue Effects in the Clinic (QUANTEC): an introduction to the scientific issues. , 2010, International journal of radiation oncology, biology, physics.

[15]  A. Ahnesjö Collapsed cone convolution of radiant energy for photon dose calculation in heterogeneous media. , 1989, Medical physics.

[16]  Monica W.K. Kan,et al.  The performance of the progressive resolution optimizer (PRO) for RapidArc planning in targets with low‐density media , 2013, Journal of applied clinical medical physics.

[17]  Satoshi Morita,et al.  Stereotactic ablative body radiation therapy for octogenarians with non-small cell lung cancer. , 2013, International journal of radiation oncology, biology, physics.

[18]  Tanya Kairn,et al.  The development of a Monte Carlo system to verify radiotherapy treatment dose calculations , 2009 .

[19]  Peter Dunscombe,et al.  Experimental validation of the Eclipse AAA algorithm , 2007, Journal of applied clinical medical physics.

[20]  Fan Jiang,et al.  Photon Optimizer (PO) prevails over Progressive Resolution Optimizer (PRO) for VMAT planning with or without knowledge‐based solution , 2017, Journal of applied clinical medical physics.

[21]  Andrea L McNiven,et al.  A new metric for assessing IMRT modulation complexity and plan deliverability. , 2010, Medical physics.