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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

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (74th percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

Mentioned by

4 patents


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629 Mendeley
1 CiteULike
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

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


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 629 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 8 1%
Japan 7 1%
Canada 6 <1%
United States 5 <1%
United Kingdom 4 <1%
France 2 <1%
Brazil 1 <1%
Australia 1 <1%
Netherlands 1 <1%
Other 8 1%
Unknown 586 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 121 19%
Researcher 112 18%
Student > Master 101 16%
Other 72 11%
Student > Doctoral Student 33 5%
Other 102 16%
Unknown 88 14%
Readers by discipline Count As %
Physics and Astronomy 355 56%
Medicine and Dentistry 79 13%
Engineering 27 4%
Nursing and Health Professions 11 2%
Agricultural and Biological Sciences 8 1%
Other 28 4%
Unknown 121 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 09 March 2021.
All research outputs
of 20,439,515 outputs
Outputs from Medical Physics
of 7,254 outputs
Outputs of similar age
of 438,592 outputs
Outputs of similar age from Medical Physics
of 62 outputs
Altmetric has tracked 20,439,515 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,254 research outputs from this source. They receive a mean Attention Score of 3.3. This one has done well, scoring higher than 82% of its peers.
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 438,592 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 74% of its contemporaries.
We're also able to compare this research output to 62 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.