Literature DB >> 36092269

The effects of Compton camera data acquisition and readout timing on PG imaging for proton range verification.

Jerimy C Polf1, Paul Maggi2, Rajesh Panthi3, Stephen Peterson4, Dennis Mackin5, Sam Beddar6.   

Abstract

The purpose of this study was to determine how the characteristics of the data acquisition (DAQ) electronics of a Compton camera (CC) affect the quality of the recorded prompt gamma (PG) interaction data and the reconstructed images, during clinical proton beam delivery. We used the Monte-Carlo-plus-Detector-Effect (MCDE) model to simulate the delivery of a 150 MeV clinical proton pencil beam to a tissue-equivalent plastic phantom. With the MCDE model we analyzed how the recorded PG interaction data changed as two characteristics of the DAQ electronics of a CC were changed: (1) the number of data readout channels; and (2) the active charge collection, readout, and reset time. As the proton beam dose rate increased, the number of recorded PG single-, double-, and triple-scatter events decreased by a factor of 60× for the current DAQ configuration of the CC. However, as the DAQ readout channels were increased and the readout/reset timing decreased, the number of recorded events decreased by <5× at the highest clinical dose rate. The increased number of readout channels and reduced readout/reset timing also resulted in higher quality recorded data. That is, a higher percentage of the recorded double- and triple-scatters were "true" events (caused by a single incident gamma) and not "false" events (caused by multiple incident gammas). The increase in the number and the quality of recorded data allowed higher quality PG images to be reconstructed even at the highest clinical dose rates.

Entities:  

Keywords:  Compton camera; prompt gamma imaging; proton range verification; proton therapy

Year:  2021        PMID: 36092269      PMCID: PMC9457195          DOI: 10.1109/trpms.2021.3057341

Source DB:  PubMed          Journal:  IEEE Trans Radiat Plasma Med Sci        ISSN: 2469-7303


  30 in total

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2.  Evaluation of proton inelastic reaction models in Geant4 for prompt gamma production during proton radiotherapy.

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Journal:  Med Phys       Date:  2015-12       Impact factor: 4.071

4.  First clinical application of a prompt gamma based in vivo proton range verification system.

Authors:  Christian Richter; Guntram Pausch; Steffen Barczyk; Marlen Priegnitz; Isabell Keitz; Julia Thiele; Julien Smeets; Francois Vander Stappen; Luca Bombelli; Carlo Fiorini; Lucian Hotoiu; Irene Perali; Damien Prieels; Wolfgang Enghardt; Michael Baumann
Journal:  Radiother Oncol       Date:  2016-01-13       Impact factor: 6.280

5.  Imaging of prompt gamma rays emitted during delivery of clinical proton beams with a Compton camera: feasibility studies for range verification.

Authors:  Jerimy C Polf; Stephen Avery; Dennis S Mackin; Sam Beddar
Journal:  Phys Med Biol       Date:  2015-08-28       Impact factor: 3.609

6.  Towards offline PET monitoring of proton therapy at MedAustron.

Authors:  Heide Meißner; Hermann Fuchs; Albert Hirtl; Christian Reschl; Markus Stock
Journal:  Z Med Phys       Date:  2018-05-30       Impact factor: 4.820

7.  Design optimisation of a TOF-based collimated camera prototype for online hadrontherapy monitoring.

Authors:  M Pinto; D Dauvergne; N Freud; J Krimmer; J M Letang; C Ray; F Roellinghoff; E Testa
Journal:  Phys Med Biol       Date:  2014-12-21       Impact factor: 3.609

8.  Simulation of prompt gamma-ray emission during proton radiotherapy.

Authors:  Joost M Verburg; Helen A Shih; Joao Seco
Journal:  Phys Med Biol       Date:  2012-08-03       Impact factor: 3.609

9.  Secondary Particle Interactions in a Compton Camera Designed for in vivo Range Verification of Proton Therapy.

Authors:  Rajesh Panthi; Paul Maggi; Stephen Peterson; Dennis Mackin; Jerimy Polf; Sam Beddar
Journal:  IEEE Trans Radiat Plasma Med Sci       Date:  2020-10-12

Review 10.  Proton therapy verification with PET imaging.

Authors:  Xuping Zhu; Georges El Fakhri
Journal:  Theranostics       Date:  2013-09-19       Impact factor: 11.556

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  1 in total

1.  Applications of Machine Learning to Improve the Clinical Viability of Compton Camera Based in vivo Range Verification in Proton Radiotherapy.

Authors:  Jerimy C Polf; Carlos A Barajas; Stephen W Peterson; Dennis S Mackin; Sam Beddar; Lei Ren; Matthias K Gobbert
Journal:  Front Phys       Date:  2022-04-11
  1 in total

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