Literature DB >> 12462725

On the degeneracy of the IMRT optimization problem.

M Alber1, G Meedt, F Nüsslin, R Reemtsen.   

Abstract

One approach to the computation of photon IMRT treatment plans is the formulation of an optimization problem with an objective function that derives from an objective density. An investigation of the second-order properties of such an objective function in a neighborhood of the minimizer opens an intuitive access to many traits of this approach. A general finding is that only a small subset of the parameter space has nonzero curvature, while the objective function is entirely flat in a neighborhood of the minimizer in most directions. The dimension of the subspace of vanishing curvature serves as a measure for the degeneracy of the solution. This finding is important both for algorithm design and evaluation of the mathematical model of clinical intuition, expressed by the objective function. The structure of the subspace of great curvature is found to be imposed on the problem by conflicts between objectives of target and critical structures. These conflicts and their corresponding modes of resolution form a common trait between all reasonable treatment plans of a given case. The high degree of degeneracy makes the use of a conjugate gradient optimization algorithm particularly favorable since the number of iterations to convergence is equivalent to the number of different eigenvalues of the curvature tensor and is hence independent from the number of optimization parameters. A high level of degeneracy of the fluence profiles implies that it should be possible to stipulate further delivery-related conditions without causing severe deterioration of the dose distribution.

Mesh:

Year:  2002        PMID: 12462725     DOI: 10.1118/1.1500402

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  8 in total

1.  Visualization of a variety of possible dosimetric outcomes in radiation therapy using dose-volume histogram bands.

Authors:  Alexei Trofimov; Jan Unkelbach; Thomas F DeLaney; Thomas Bortfeld
Journal:  Pract Radiat Oncol       Date:  2011-09-09

2.  Reduced order constrained optimization (ROCO): clinical application to lung IMRT.

Authors:  Hans Stabenau; Linda Rivera; Ellen Yorke; Jie Yang; Renzhi Lu; Richard J Radke; Andrew Jackson
Journal:  Med Phys       Date:  2011-05       Impact factor: 4.071

3.  Inverse 4D conformal planning for lung SBRT using particle swarm optimization.

Authors:  A Modiri; X Gu; A Hagan; R Bland; P Iyengar; R Timmerman; A Sawant
Journal:  Phys Med Biol       Date:  2016-08-01       Impact factor: 3.609

4.  Proton energy optimization and reduction for intensity-modulated proton therapy.

Authors:  Wenhua Cao; Gino Lim; Li Liao; Yupeng Li; Shengpeng Jiang; Xiaoqiang Li; Heng Li; Kazumichi Suzuki; X Ronald Zhu; Daniel Gomez; Xiaodong Zhang
Journal:  Phys Med Biol       Date:  2014-10-08       Impact factor: 3.609

5.  Reduced-order constrained optimization in IMRT planning.

Authors:  Renzhi Lu; Richard J Radke; Jie Yang; Laura Happersett; Ellen Yorke; Andrew Jackson
Journal:  Phys Med Biol       Date:  2008-11-07       Impact factor: 3.609

6.  Radiotherapy Planning Using an Improved Search Strategy in Particle Swarm Optimization.

Authors:  Arezoo Modiri; Xuejun Gu; Aaron M Hagan; Amit Sawant
Journal:  IEEE Trans Biomed Eng       Date:  2016-06-27       Impact factor: 4.538

7.  On the visualization of universal degeneracy in the IMRT problem.

Authors:  Markus L Alber; Gustav Meedt
Journal:  Radiat Oncol       Date:  2006-12-18       Impact factor: 3.481

8.  Multiobjective, Multidelivery Optimization for Radiation Therapy Treatment Planning.

Authors:  William Tyler Watkins; Hamidreza Nourzadeh; Jeffrey V Siebers
Journal:  Adv Radiat Oncol       Date:  2019-09-27
  8 in total

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