Literature DB >> 21841211

Toward real-time Monte Carlo simulation using a commercial cloud computing infrastructure.

Henry Wang1, Yunzhi Ma, Guillem Pratx, Lei Xing.   

Abstract

Monte Carlo (MC) methods are the gold standard for modeling photon and electron transport in a heterogeneous medium; however, their computational cost prohibits their routine use in the clinic. Cloud computing, wherein computing resources are allocated on-demand from a third party, is a new approach for high performance computing and is implemented to perform ultra-fast MC calculation in radiation therapy. We deployed the EGS5 MC package in a commercial cloud environment. Launched from a single local computer with Internet access, a Python script allocates a remote virtual cluster. A handshaking protocol designates master and worker nodes. The EGS5 binaries and the simulation data are initially loaded onto the master node. The simulation is then distributed among independent worker nodes via the message passing interface, and the results aggregated on the local computer for display and data analysis. The described approach is evaluated for pencil beams and broad beams of high-energy electrons and photons. The output of cloud-based MC simulation is identical to that produced by single-threaded implementation. For 1 million electrons, a simulation that takes 2.58 h on a local computer can be executed in 3.3 min on the cloud with 100 nodes, a 47× speed-up. Simulation time scales inversely with the number of parallel nodes. The parallelization overhead is also negligible for large simulations. Cloud computing represents one of the most important recent advances in supercomputing technology and provides a promising platform for substantially improved MC simulation. In addition to the significant speed up, cloud computing builds a layer of abstraction for high performance parallel computing, which may change the way dose calculations are performed and radiation treatment plans are completed.

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Year:  2011        PMID: 21841211      PMCID: PMC3431188          DOI: 10.1088/0031-9155/56/17/N02

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  15 in total

1.  Monte Carlo methods for dose calculation and treatment planning: a revolution for radiotherapy.

Authors:  J J DeMarco; T D Solberg; I Chetty
Journal:  Adm Radiol J       Date:  1999-08

2.  Monte Carlo evaluation of RapidArc oropharynx treatment planning strategies for sparing of midline structures.

Authors:  K Bush; S Zavgorodni; I Gagne; R Townson; W Ansbacher; W Beckham
Journal:  Phys Med Biol       Date:  2010-07-29       Impact factor: 3.609

3.  Cloud computing.

Authors:  Alex Bateman; Matt Wood
Journal:  Bioinformatics       Date:  2009-05-12       Impact factor: 6.937

4.  Dosimetric validation of Acuros XB with Monte Carlo methods for photon dose calculations.

Authors:  K Bush; I M Gagne; S Zavgorodni; W Ansbacher; W Beckham
Journal:  Med Phys       Date:  2011-04       Impact factor: 4.071

5.  Replacement correction factors for plane-parallel ion chambers in electron beams.

Authors:  Lilie L W Wang; David W O Rogers
Journal:  Med Phys       Date:  2010-02       Impact factor: 4.071

6.  GPUMCD: A new GPU-oriented Monte Carlo dose calculation platform.

Authors:  Sami Hissoiny; Benoît Ozell; Hugo Bouchard; Philippe Després
Journal:  Med Phys       Date:  2011-02       Impact factor: 4.071

Review 7.  GPU computing in medical physics: a review.

Authors:  Guillem Pratx; Lei Xing
Journal:  Med Phys       Date:  2011-05       Impact factor: 4.071

8.  Patient-specific radiation dose and cancer risk estimation in CT: part I. development and validation of a Monte Carlo program.

Authors:  Xiang Li; Ehsan Samei; W Paul Segars; Gregory M Sturgeon; James G Colsher; Greta Toncheva; Terry T Yoshizumi; Donald P Frush
Journal:  Med Phys       Date:  2011-01       Impact factor: 4.071

Review 9.  Computational solutions to large-scale data management and analysis.

Authors:  Eric E Schadt; Michael D Linderman; Jon Sorenson; Lawrence Lee; Garry P Nolan
Journal:  Nat Rev Genet       Date:  2010-09       Impact factor: 53.242

10.  Monte Carlo modeling of a 6 and 18 MV Varian Clinac medical accelerator for in-field and out-of-field dose calculations: development and validation.

Authors:  Bryan Bednarz; X George Xu
Journal:  Phys Med Biol       Date:  2009-01-14       Impact factor: 3.609

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  8 in total

1.  Monte Carlo simulation of photon migration in a cloud computing environment with MapReduce.

Authors:  Guillem Pratx; Lei Xing
Journal:  J Biomed Opt       Date:  2011-12       Impact factor: 3.170

2.  Independent calculation of monitor units for VMAT and SPORT.

Authors:  Xin Chen; Karl Bush; Aiping Ding; Lei Xing
Journal:  Med Phys       Date:  2015-02       Impact factor: 4.071

Review 3.  Internet-based computer technology on radiotherapy.

Authors:  James C L Chow
Journal:  Rep Pract Oncol Radiother       Date:  2017-09-08

Review 4.  Towards the Interpretability of Machine Learning Predictions for Medical Applications Targeting Personalised Therapies: A Cancer Case Survey.

Authors:  Antonio Jesús Banegas-Luna; Jorge Peña-García; Adrian Iftene; Fiorella Guadagni; Patrizia Ferroni; Noemi Scarpato; Fabio Massimo Zanzotto; Andrés Bueno-Crespo; Horacio Pérez-Sánchez
Journal:  Int J Mol Sci       Date:  2021-04-22       Impact factor: 5.923

5.  Monte Carlo verification of radiotherapy treatments with CloudMC.

Authors:  Hector Miras; Rubén Jiménez; Álvaro Perales; José Antonio Terrón; Alejandro Bertolet; Antonio Ortiz; José Macías
Journal:  Radiat Oncol       Date:  2018-06-27       Impact factor: 3.481

6.  A Novel GPU-based Fast Monte Carlo Photon Dose Calculating Method for Accurate Radiotherapy Treatment Planning.

Authors:  Karbalaee M; Shahbazi-Gahrouei D; Tavakoli M B
Journal:  J Biomed Phys Eng       Date:  2020-06-01

7.  HealtheDataLab - a cloud computing solution for data science and advanced analytics in healthcare with application to predicting multi-center pediatric readmissions.

Authors:  Louis Ehwerhemuepha; Gary Gasperino; Nathaniel Bischoff; Sharief Taraman; Anthony Chang; William Feaster
Journal:  BMC Med Inform Decis Mak       Date:  2020-06-19       Impact factor: 2.796

8.  Scalable and accessible personalized photodynamic therapy optimization with FullMonte and PDT-SPACE.

Authors:  Shuran Wang; Xiao Ying Dai; Shengxiang Ji; Tina Saeidi; Fynn Schwiegelshohn; Abdul-Amir Yassine; Lothar Lilge; Vaughn Betz
Journal:  J Biomed Opt       Date:  2022-04       Impact factor: 3.758

  8 in total

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