Literature DB >> 15651619

Adaptive radiation therapy for compensation of errors in patient setup and treatment delivery.

Henrik Rehbinder1, Camilla Forsgren, Johan Löf.   

Abstract

In this paper, an adaptive radiation therapy algorithm is derived and evaluated using numerical simulations. Patient setup errors are considered and an off-line adaptive method to compensate for the effect of these is provided. The method consists of two parts, one for correction of patient position to account for the systematic error, and one for modulation of the fluence profiles to account for the random errors. The method is based on standard control theory for linear systems. It is investigated if this adaptive method can replace the use of a planning target volume (PTV) and therefore increase the possibilities to escalate the dose. Numerical simulations of treatments of a prostate patient indicate that this is the case. The simulations show that better organ-at-risk protection can be achieved when using the adaptation algorithm to correct for the geometrical uncertainties than when using a PTV.

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Year:  2004        PMID: 15651619     DOI: 10.1118/1.1809768

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


  10 in total

1.  Coverage-based treatment planning: optimizing the IMRT PTV to meet a CTV coverage criterion.

Authors:  J J Gordon; J V Siebers
Journal:  Med Phys       Date:  2009-03       Impact factor: 4.071

Review 2.  Adaptive radiation therapy for prostate cancer.

Authors:  Michel Ghilezan; Di Yan; Alvaro Martinez
Journal:  Semin Radiat Oncol       Date:  2010-04       Impact factor: 5.934

3.  Coverage optimized planning: probabilistic treatment planning based on dose coverage histogram criteria.

Authors:  J J Gordon; N Sayah; E Weiss; J V Siebers
Journal:  Med Phys       Date:  2010-02       Impact factor: 4.071

4.  Effect of anatomic motion on proton therapy dose distributions in prostate cancer treatment.

Authors:  Xiaodong Zhang; Lei Dong; Andrew K Lee; James D Cox; Deborah A Kuban; Ron X Zhu; Xiaochun Wang; Yupeng Li; Wayne D Newhauser; Michael Gillin; Radhe Mohan
Journal:  Int J Radiat Oncol Biol Phys       Date:  2007-02-01       Impact factor: 7.038

5.  On-line adaptive radiation therapy: feasibility and clinical study.

Authors:  Taoran Li; Xiaofeng Zhu; Danthai Thongphiew; W Robert Lee; Zeljko Vujaskovic; Qiuwen Wu; Fang-Fang Yin; Q Jackie Wu
Journal:  J Oncol       Date:  2010-11-22       Impact factor: 4.375

6.  Comparisons of treatment optimization directly incorporating random patient setup uncertainty with a margin-based approach.

Authors:  Joseph A Moore; John J Gordon; Mitchell S Anscher; Jeffrey V Siebers
Journal:  Med Phys       Date:  2009-09       Impact factor: 4.071

7.  The perils of adapting to dose errors in radiation therapy.

Authors:  Velibor V Mišić; Timothy C Y Chan
Journal:  PLoS One       Date:  2015-05-05       Impact factor: 3.240

8.  A method for generating large datasets of organ geometries for radiotherapy treatment planning studies.

Authors:  Nan Hu; Laura Cerviño; Paul Segars; John Lewis; Jinlu Shan; Steve Jiang; Xiaolin Zheng; Ge Wang
Journal:  Radiol Oncol       Date:  2014-11-05       Impact factor: 2.991

9.  The effect and stability of MVCT images on adaptive TomoTherapy.

Authors:  Poonam Yadav; Ranjini Tolakanahalli; Yi Rong; Bhudatt R Paliwal
Journal:  J Appl Clin Med Phys       Date:  2010-07-02       Impact factor: 2.102

Review 10.  The Role of Machine Learning in Knowledge-Based Response-Adapted Radiotherapy.

Authors:  Huan-Hsin Tseng; Yi Luo; Randall K Ten Haken; Issam El Naqa
Journal:  Front Oncol       Date:  2018-07-27       Impact factor: 6.244

  10 in total

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