Performance evaluation of a multiple-scattering Compton imager for distribution of prompt gamma-rays in proton therapy

Taewoong Lee, Hyounggun Lee, Younghak Kim, Won Ho Lee

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

The purpose of this study is to compare and evaluate the performance of a multiple-scattering Compton imager (MSCI) to measure prompt gamma-rays emitted during proton therapy. Because prompt gamma-rays are generated simultaneously during the proton beam delivery, the falloff position of the Bragg peak of the proton beam can be determined from the distribution of prompt gamma-rays. The detection system was designed using three CdZnTe detector layers that can track radiation of unknown energy on the basis of effective Compton scattering events. The simple back-projection, filtered back-projection, and maximum likelihood expectation maximization (MLEM) algorithms were applied for the reconstructed Compton images. The falloff positions of the Bragg peaks determined from individual MSCIs were compared with the theoretical values calculated using the Monte Carlo N-Particle eXtended code. Moreover, the performance of the MSCI was compared with that of a previously developed system based on a slit collimator gamma camera. In summary, the MSCI with the MLEM reconstruction algorithm was better than the other reconstruction methods in terms of the falloff position of the Bragg peak, the angular resolution, and the signal-to-noise ratio.

Original languageEnglish
Pages (from-to)184-191
Number of pages8
JournalJournal of the Korean Physical Society
Volume70
Issue number2
DOIs
Publication statusPublished - 2017 Jan 1

Keywords

  • Falloff position of the Bragg peak
  • MCNPX
  • Multiple-scattering Compton imager (MSCI)

ASJC Scopus subject areas

  • Physics and Astronomy(all)

Fingerprint

Dive into the research topics of 'Performance evaluation of a multiple-scattering Compton imager for distribution of prompt gamma-rays in proton therapy'. Together they form a unique fingerprint.

Cite this