Intensity-modulated radiotherapy optimization in a quasi-periodically deforming patient model.

Purpose: To present the implementation of a probability-based, four-dimensional (4D) intensity-modulated radiotherapy (IMRT) planning approach that explicitly optimizes the accumulated dose to moving tissue, estimated using the patient's probability density function (pdf) of respiratory motion. This...

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Publicado en:International Journal of Radiation Oncology, Biology, Physics Vol. 75; no. 3; pp. 906 - 915
Autores principales: Söhn M, Weinmann M, Alber M, Söhn, Matthias, Weinmann, Martin, Alber, Markus
Formato: research Journal Article
Publicado: Pergamon Press - An Imprint of Elsevier Science Nov2009
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Nov2009
      vid: 75
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      pub: Pergamon Press - An Imprint of Elsevier Science
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        10.1016/j.ijrobp.2009.04.016
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        atl: Intensity-modulated radiotherapy optimization in a quasi-periodically deforming patient model.
      aug:
        au:
          Söhn M
          Weinmann M
          Alber M
          Söhn, Matthias
          Weinmann, Martin
          Alber, Markus
        affil: Section for Biomedical Physics, University Hospital for Radiation Oncology, Hoppe-Seyler-Strasse 3, Tübingen, Germany
      sug:
        subj:
          Algorithms
          Lung Neoplasms Radiotherapy
          Movement
          Radiotherapy, Computer-Assisted Methods
          Radiotherapy, Conformal Methods
          Respiration
          Body Weights and Measures
          Image Processing, Computer Assisted Methods
          Lung Neoplasms Radiography
          Probability
          Radiation Dosage
          Systems Analysis
          Tomography, X-Ray Computed
          Human
      ab: Purpose: To present the implementation of a probability-based, four-dimensional (4D) intensity-modulated radiotherapy (IMRT) planning approach that explicitly optimizes the accumulated dose to moving tissue, estimated using the patient's probability density function (pdf) of respiratory motion. This is termed "optimization in tissue's-eye-view". Methods and Materials: The method incorporates 4D Monte Carlo dose calculation in multiple geometries of a respiratory-correlated CT dataset. The instance doses are weighted according to the breathing pdf and accumulated in a common reference geometry, which involves dose warping based on deformable registration. The algorithm produces deliverable multileaf collimator segments and was tested on a sample lung cancer patient dataset with large target excursion. Accumulated doses of the moving target and organs at risk of this plan were compared with those of corresponding margin-based static IMRT plans for free-breathing and gated treatment, as well as target tracking. Results: Target tracking provided best target coverage. Both the presented 4D IMRT approach for free-breathing treatment and gated treatment gave similar results for target coverage and lung dose, with significantly better target coverage than the margin-based static IMRT plan for free-breathing treatment. Conclusions: The presented 4D planning concept offers an alternative to gating by providing the optimal dose for free-breathing IMRT treatment. Although the focus of this study was 4D lung planning, the approach can be generally applied for IMRT optimization in randomly deforming patient models.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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