Literature DB >> 10473202

Monte Carlo-based inverse treatment planning.

R Jeraj1, P Keall.   

Abstract

A Monte Carlo based inverse treatment planning system (MCI) has been developed which combines arguably the most accurate dose calculation method (Monte Carlo particle transport) with a 'guaranteed' optimization method (simulated annealing). A distribution of photons is specified in the tumour volume; they are transported using an adjoint calculation method to outside the patient surface to build up an intensity distribution. This intensity distribution is used as the initial input into an optimization algorithm. The dose distribution from each beam element from a number of fields is pre-calculated using Monte Carlo transport. Simulated annealing optimization is then used to find the weighting of each beam element, to yield the optimal dose distribution for the given criteria and constraints. MCI plans have been generated in various theoretical phantoms and patient geometries. These plans show conformation of the dose to the target volume and avoidance of critical structures. To verify the code, an experiment was performed on an anthropomorphic phantom.

Entities:  

Mesh:

Year:  1999        PMID: 10473202     DOI: 10.1088/0031-9155/44/8/303

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


  7 in total

1.  Generation of a novel phase-space-based cylindrical dose kernel for IMRT optimization.

Authors:  Hualiang Zhong; Indrin J Chetty
Journal:  Med Phys       Date:  2012-05       Impact factor: 4.071

2.  Motion management strategies and technical issues associated with stereotactic body radiotherapy of thoracic and upper abdominal tumors: A review from NRG oncology.

Authors:  Edward D Brandner; Indrin J Chetty; Tawfik G Giaddui; Ying Xiao; M Saiful Huq
Journal:  Med Phys       Date:  2017-04-20       Impact factor: 4.071

3.  EGSnrc application for IMRT planning.

Authors:  Sitti Yani; Ilmi Rizkia; Mohamad Fahdillah Rhani; Mohammad Haekal; Freddy Haryanto
Journal:  Rep Pract Oncol Radiother       Date:  2020-01-22

4.  The effect of statistical noise on IMRT plan quality and convergence for MC-based and MC-correction-based optimized treatment plans.

Authors:  Jeffrey V Siebers
Journal:  J Phys Conf Ser       Date:  2008-04-04

5.  Motion management with phase-adapted 4D-optimization.

Authors:  Omid Nohadani; Joao Seco; Thomas Bortfeld
Journal:  Phys Med Biol       Date:  2010-08-16       Impact factor: 3.609

6.  First steps towards a fast-neutron therapy planning program.

Authors:  Sylvia Garny; Werner Rühm; Maria Zankl; Franz M Wagner; Herwig G Paretzke
Journal:  Radiat Oncol       Date:  2011-11-25       Impact factor: 3.481

7.  Review of fast monte carlo codes for dose calculation in radiation therapy treatment planning.

Authors:  Keyvan Jabbari
Journal:  J Med Signals Sens       Date:  2011-01
  7 in total

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