DVH-Based Inverse Planning Using Monte Carlo Dosimetry for LDR Prostate Brachytherapy.

Purpose: Inverse planning is an integral part of modern low-dose-rate brachytherapy. Current clinical planning systems do not exploit the total dose information and largely use the American Association of Physicists in Medicine TG-43 dosimetry formalism to ensure clinically acceptable planning times...

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Publicado en:International Journal of Radiation Oncology, Biology, Physics Vol. 103; no. 2; pp. 503 - 511
Autores principales: Mountris, Konstantinos A., Visvikis, Dimitris, Bert, Julien
Formato: research Journal Article
Publicado: Pergamon Press - An Imprint of Elsevier Science Feb2019
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Feb2019
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      pub: Pergamon Press - An Imprint of Elsevier Science
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        10.1016/j.ijrobp.2018.09.041
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        atl: DVH-Based Inverse Planning Using Monte Carlo Dosimetry for LDR Prostate Brachytherapy.
      aug:
        au:
          Mountris, Konstantinos A.
          Visvikis, Dimitris
          Bert, Julien
        affil: LaTIM, INSERM, UMR 1101, Brest, France
      sug:
        subj:
          Prostatic Neoplasms Radiotherapy
          Radiotherapy, Computer-Assisted Methods
          Image Processing, Computer Assisted Methods
          Brachytherapy Methods
          Male
          Algorithms
          Reproducibility of Results
          Radiometry
          Phantoms, Imaging
          Radiation Dosage
          Quality Control (Technology)
          Systems Analysis
          Computer Simulation
          Software
          Human
          Prostate Radiation Effects
          Validation Studies
          Comparative Studies
          Evaluation Research
          Multicenter Studies
          Male
      ab: Purpose: Inverse planning is an integral part of modern low-dose-rate brachytherapy. Current clinical planning systems do not exploit the total dose information and largely use the American Association of Physicists in Medicine TG-43 dosimetry formalism to ensure clinically acceptable planning times. Thus, suboptimal plans may be derived as a result of TG-43-related dose overestimation and nonconformity with dose distribution requirements. The purpose of this study was to propose an inverse planning approach that can improve planning quality by combining dose-volume information and precision without compromising the overall execution times.Methods and Materials: The dose map was generated by accumulating precomputed Monte Carlo (MC) dose kernels for each candidate source implantation site. The MC computational burden was reduced by using graphics processing unit acceleration, allowing accurate dosimetry calculations to be performed in the intraoperative environment. The proposed dose-volume histogram (DVH) fast simulated annealing optimization algorithm was evaluated using clinical plans that were delivered to 18 patients who underwent low-dose-rate prostate brachytherapy.Results: Our method generated plans in 37.5 ± 3.2 seconds with similar prostate dose coverage, improved prostate dose homogeneity of up to 6.1%, and lower dose to the urethra of up to 4.0%.Conclusions: A DVH-based optimization algorithm using MC dosimetry was developed. The inclusion of the DVH requirements allowed for increased control over the optimization outcome. The optimal plan's quality was further improved by considering tissue heterogeneity.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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