Abstract
BackgroundA new implementation has been made on CloudMC, a cloud-based platform presented in a previous work, in order to provide services for radiotherapy treatment verification by means of Monte Carlo in a fast, easy and economical way. A description of the architecture of the application and the new developments implemented is presented together with the results of the tests carried out to validate its performance.MethodsCloudMC has been developed over Microsoft Azure cloud. It is based on a map/reduce implementation for Monte Carlo calculations distribution over a dynamic cluster of virtual machines in order to reduce calculation time. CloudMC has been updated with new methods to read and process the information related to radiotherapy treatment verification: CT image set, treatment plan, structures and dose distribution files in DICOM format. Some tests have been designed in order to determine, for the different tasks, the most suitable type of virtual machines from those available in Azure. Finally, the performance of Monte Carlo verification in CloudMC is studied through three real cases that involve different treatment techniques, linac models and Monte Carlo codes.ResultsConsidering computational and economic factors, D1_v2 and G1 virtual machines were selected as the default type for the Worker Roles and the Reducer Role respectively. Calculation times up to 33 min and costs of 16 € were achieved for the verification cases presented when a statistical uncertainty below 2% (2σ) was required. The costs were reduced to 3–6 € when uncertainty requirements are relaxed to 4%.ConclusionsAdvantages like high computational power, scalability, easy access and pay-per-usage model, make Monte Carlo cloud-based solutions, like the one presented in this work, an important step forward to solve the long-lived problem of truly introducing the Monte Carlo algorithms in the daily routine of the radiotherapy planning process.
Highlights
A new implementation has been made on CloudMC, a cloud-based platform presented in a previous work, in order to provide services for radiotherapy treatment verification by means of Monte Carlo in a fast, easy and economical way
In a previous work [19], we presented CloudMC, a cloud-based platform developed over Microsoft Azure® cloud
The outcome considered for the Worker Role test was the CPU time spent on the execution of the PenEasy MC program
Summary
A new implementation has been made on CloudMC, a cloud-based platform presented in a previous work, in order to provide services for radiotherapy treatment verification by means of Monte Carlo in a fast, easy and economical way. For PENELOPE code, PenEasy, a general-purpose main program [7], and PRIMO, an application for clinical linacs MC calculations with graphical user interface included [8], are available. Regardless of the code used, a huge number of simulated particles is necessary to achieve a precise solution because of the stochastic nature of the MC approach. These simulations are often computationally-expensive or time-consuming [9]. The main barrier to this solution is the high investment needed, as well as associated maintenance, upgrade and staff costs [11] Such costs make practically unfeasible the use of MC simulations in a routine clinical basis
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