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dc.contributor.authorZiegenhein, P
dc.contributor.authorKozin, IN
dc.contributor.authorKamerling, CP
dc.contributor.authorOelfke, U
dc.date.accessioned2017-03-24T14:36:03Z
dc.date.issued2017-06-07
dc.identifier.citationPhysics in medicine and biology, 2017, 62 (11), pp. 4375 - 4389
dc.identifier.issn0031-9155
dc.identifier.urihttps://repository.icr.ac.uk/handle/internal/507
dc.identifier.eissn1361-6560
dc.identifier.doi10.1088/1361-6560/aa5d4e
dc.description.abstractNear real-time application of Monte Carlo (MC) dose calculation in clinic and research is hindered by the long computational runtimes of established software. Currently, fast MC software solutions are available utilising accelerators such as graphical processing units (GPUs) or clusters based on central processing units (CPUs). Both platforms are expensive in terms of purchase costs and maintenance and, in case of the GPU, provide only limited scalability. In this work we propose a cloud-based MC solution, which offers high scalability of accurate photon dose calculations. The MC simulations run on a private virtual supercomputer that is formed in the cloud. Computational resources can be provisioned dynamically at low cost without upfront investment in expensive hardware. A client-server software solution has been developed which controls the simulations and transports data to and from the cloud efficiently and securely. The client application integrates seamlessly into a treatment planning system. It runs the MC simulation workflow automatically and securely exchanges simulation data with the server side application that controls the virtual supercomputer. Advanced encryption standards were used to add an additional security layer, which encrypts and decrypts patient data on-the-fly at the processor register level. We could show that our cloud-based MC framework enables near real-time dose computation. It delivers excellent linear scaling for high-resolution datasets with absolute runtimes of 1.1 seconds to 10.9 seconds for simulating a clinical prostate and liver case up to 1% statistical uncertainty. The computation runtimes include the transportation of data to and from the cloud as well as process scheduling and synchronisation overhead. Cloud-based MC simulations offer a fast, affordable and easily accessible alternative for near real-time accurate dose calculations to currently used GPU or cluster solutions.
dc.formatPrint-Electronic
dc.format.extent4375 - 4389
dc.languageeng
dc.language.isoeng
dc.publisherIOP Publishing Ltd
dc.rights.urihttps://creativecommons.org/licenses/by/4.0
dc.subjectHumans
dc.subjectLiver Neoplasms
dc.subjectProstatic Neoplasms
dc.subjectRadiotherapy Dosage
dc.subjectRadiotherapy Planning, Computer-Assisted
dc.subjectMonte Carlo Method
dc.subjectAlgorithms
dc.subjectPhotons
dc.subjectSoftware
dc.subjectMale
dc.titleTowards real-time photon Monte Carlo dose calculation in the cloud.
dc.typeJournal Article
rioxxterms.versionofrecord10.1088/1361-6560/aa5d4e
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by/4.0
rioxxterms.licenseref.startdate2017-06
rioxxterms.typeJournal Article/Review
dc.relation.isPartOfPhysics in medicine and biology
pubs.issue11
pubs.notesNo embargo
pubs.organisational-group/ICR
pubs.organisational-group/ICR/Primary Group
pubs.organisational-group/ICR/Primary Group/ICR Divisions
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging/Radiotherapy Physics Modelling
pubs.organisational-group/ICR/Primary Group/Royal Marsden Clinical Units
pubs.organisational-group/ICR
pubs.organisational-group/ICR/Primary Group
pubs.organisational-group/ICR/Primary Group/ICR Divisions
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging/Radiotherapy Physics Modelling
pubs.organisational-group/ICR/Primary Group/Royal Marsden Clinical Units
pubs.publication-statusPublished
pubs.volume62
pubs.embargo.termsNo embargo
icr.researchteamRadiotherapy Physics Modelling
dc.contributor.icrauthorKozin, Igor


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