Experimental evaluation of a GPU-based Monte Carlo dose calculation algorithm in the Monaco treatment planning system

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Abstract

A new GPU-based Monte Carlo dose calculation algorithm (GPUMCD), developed by the vendor Elekta for the Monaco treatment planning system (TPS), is capable of modeling dose for both a standard linear accelerator and an Elekta MRI linear accelerator. We have experimentally evaluated this algorithm for a standard Elekta Agility linear accelerator. A beam model was developed in the Monaco TPS (research version 5.09.06) using the commissioned beam data for a 6 MV Agility linac. A heterogeneous phantom representing several scenarios — tumor-in-lung, lung, and bone-in-tissue — was designed and built. Dose calculations in Monaco were done using both the current clinical Monte Carlo algorithm, XVMC, and the new GPUMCD algorithm. Dose calculations in a Pinnacle TPS were also produced using the collapsed cone convolution (CCC) algorithm with heterogeneity correction. Calculations were compared with the measured doses using an ionization chamber (A1SL) and Gafchromic EBT3 films for Symbol, and Symbol field sizes. The percentage depth doses (PDDs) calculated by XVMC and GPUMCD in a homogeneous solid water phantom were within Symbol of film measurements and within 1% of ion chamber measurements. For the tumor-in-lung phantom, the calculated doses were within Symbol of film measurements for GPUMCD. For the lung phantom, doses calculated by all of the algorithms were within Symbol of film measurements, except for the Symbol field size where the CCC algorithm underestimated the depth dose by Symbol in a larger extent of the lung region. For the bone phantom, all of the algorithms were equivalent and calculated dose to within Symbol of film measurements, except at the interfaces. Both GPUMCD and XVMC showed interface effects, which were more pronounced for GPUMCD and were comparable to film measurements, whereas the CCC algorithm showed these effects poorly.

PACS number(s): 87.53.Bn, 87.55.dh, 87.55.km

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