Literature DB >> 17148821

Ideal spatial radiotherapy dose distributions subject to positional uncertainties.

Mustafa Y Sir1, Stephen M Pollock, Marina A Epelman, Kwok L Lam, Randall K Ten Haken.   

Abstract

In radiotherapy a common method used to compensate for patient setup error and organ motion is to enlarge the clinical target volume (CTV) by a 'margin' to produce a 'planning target volume' (PTV). Using weighted power loss functions as a measure of performance for a treatment plan, a simple method can be developed to calculate the ideal spatial dose distribution (one that minimizes expected loss) when there is uncertainty. The spatial dose distribution is assumed to be invariant to the displacement of the internal structures and the whole patient. The results provide qualitative insights into the suitability of using a margin at all, and (if one is to be used) how to select a 'good' margin size. The common practice of raising the power parameters in the treatment loss function, in order to enforce target dose requirements, is shown to be potentially counter-productive. These results offer insights into desirable dose distributions and could be used, in conjunction with well-established inverse radiotherapy planning techniques, to produce dose distributions that are robust against uncertainties.

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Year:  2006        PMID: 17148821     DOI: 10.1088/0031-9155/51/24/004

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


  3 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

2.  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

3.  Robust Optimization of SBRT Planning for Patients With Early Stage Non-Small Cell Lung Cancer.

Authors:  Haijiao Shang; Yuehu Pu; Yuenan Wang
Journal:  Technol Cancer Res Treat       Date:  2020 Jan-Dec
  3 in total

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