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Report of the AAPM Task Group No. 105: Issues associated with clinical implementation of Monte Carlo-based photon and electron external beam treatment planning

Overview of attention for article published in Medical Physics, November 2007
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (64th percentile)
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

Mentioned by

patent
1 patent

Citations

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367 Dimensions

Readers on

mendeley
457 Mendeley
Title
Report of the AAPM Task Group No. 105: Issues associated with clinical implementation of Monte Carlo-based photon and electron external beam treatment planning
Published in
Medical Physics, November 2007
DOI 10.1118/1.2795842
Pubmed ID
Authors

Indrin J. Chetty, Bruce Curran, Joanna E. Cygler, John J. DeMarco, Gary Ezzell, Bruce A. Faddegon, Iwan Kawrakow, Paul J. Keall, Helen Liu, C.-M. Charlie Ma, D. W. O. Rogers, Jan Seuntjens, Daryoush Sheikh-Bagheri, Jeffrey V. Siebers

Abstract

The Monte Carlo (MC) method has been shown through many research studies to calculate accurate dose distributions for clinical radiotherapy, particularly in heterogeneous patient tissues where the effects of electron transport cannot be accurately handled with conventional, deterministic dose algorithms. Despite its proven accuracy and the potential for improved dose distributions to influence treatment outcomes, the long calculation times previously associated with MC simulation rendered this method impractical for routine clinical treatment planning. However, the development of faster codes optimized for radiotherapy calculations and improvements in computer processor technology have substantially reduced calculation times to, in some instances, within minutes on a single processor. These advances have motivated several major treatment planning system vendors to embark upon the path of MC techniques. Several commercial vendors have already released or are currently in the process of releasing MC algorithms for photon and/or electron beam treatment planning. Consequently, the accessibility and use of MC treatment planning algorithms may well become widespread in the radiotherapy community. With MC simulation, dose is computed stochastically using first principles; this method is therefore quite different from conventional dose algorithms. Issues such as statistical uncertainties, the use of variance reduction techniques, theability to account for geometric details in the accelerator treatment head simulation, and other features, are all unique components of a MC treatment planning algorithm. Successful implementation by the clinical physicist of such a system will require an understanding of the basic principles of MC techniques. The purpose of this report, while providing education and review on the use of MC simulation in radiotherapy planning, is to set out, for both users and developers, the salient issues associated with clinical implementation and experimental verification of MC dose algorithms. As the MC method is an emerging technology, this report is not meant to be prescriptive. Rather, it is intended as a preliminary report to review the tenets of the MC method and to provide the framework upon which to build a comprehensive program for commissioning and routine quality assurance of MC-based treatment planning systems.

Mendeley readers

The data shown below were compiled from readership statistics for 457 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 9 2%
Japan 7 2%
United States 6 1%
Canada 6 1%
United Kingdom 5 1%
Netherlands 2 <1%
France 2 <1%
Turkey 2 <1%
Portugal 1 <1%
Other 8 2%
Unknown 409 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 97 21%
Researcher 92 20%
Student > Master 73 16%
Other 65 14%
Professor > Associate Professor 30 7%
Other 100 22%
Readers by discipline Count As %
Physics and Astronomy 296 65%
Medicine and Dentistry 66 14%
Unspecified 44 10%
Engineering 21 5%
Computer Science 7 2%
Other 23 5%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 31 October 2017.
All research outputs
#3,552,049
of 12,362,639 outputs
Outputs from Medical Physics
#1,066
of 5,412 outputs
Outputs of similar age
#120,618
of 352,192 outputs
Outputs of similar age from Medical Physics
#11
of 41 outputs
Altmetric has tracked 12,362,639 research outputs across all sources so far. This one is in the 49th percentile – i.e., 49% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,412 research outputs from this source. They receive a mean Attention Score of 3.0. This one is in the 48th percentile – i.e., 48% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 352,192 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 64% of its contemporaries.
We're also able to compare this research output to 41 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.