Sensitivity study of prompt gamma imaging of scanned beam proton therapy in heterogeneous anatomies

Janssens, Guillaume;Smeets, Julien;Vander Stappen, François;Prieels, Damien;Sterpin, Edmond;et.al.
(2016) Radiotherapy & Oncology — Vol. 118, n° 3, p. 562-567 (2016)

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Authors
  • Author
  • Smeets, Julien
    Author
  • Vander Stappen, François
    Author
  • Prieels, Damien
    Author
  • Clementel, EnricoUCLouvain
    Author
  • Hotoiu, Eugen-LucianUCLouvain
    Author
  • Author
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Abstract
Background and purpose: To investigate the use of a fast analytical prediction algorithm in the evaluation of the accuracy in Bragg peak position estimation using prompt gamma imaging in realistic anatomies. Material and methods: Brain, nasal cavity and lung spot scanning treatments were planned on an anthro- pomorphic phantom. Plan delivery in a clinical proton therapy facility was monitored using a prompt gamma camera. A pencil-beam algorithm was developed to simulate prompt gamma acquisition. For each spot, the sensitivity to setup and CT conversion errors was evaluated based on error scenarios. Results: Good agreement was found between simulations and measurements (average shift of 0.4 mm on whole-layer profiles). The spots with greatest sensitivity to setup or CT conversion errors could be iden- tified. The comparison between expected and estimated shifts showed that the errors in shift estimation due to heterogeneities were in average lower than 1 mm in all cases except the lung. In the lung case, only 40% of the spots showed accuracy better than 2 mm. Conclusions: The analytical prediction algorithm was successfully used to simulate prompt gamma acqui- sitions of scanned treatment plans. The accuracy in Bragg peak position estimation was generally sub- millimeter in heterogeneous anatomies, except in lung tissues.
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Citations

Janssens, G., Smeets, J., Vander Stappen, F., Prieels, D., Clementel, E., Hotoiu, E.-L., & Sterpin, E. (2016). Sensitivity study of prompt gamma imaging of scanned beam proton therapy in heterogeneous anatomies. Radiotherapy & Oncology, 118(3), 562-567. https://doi.org/10.1016/j.radonc.2015.11.002 (Original work published 2016)