140
Views
13
CrossRef citations to date
0
Altmetric
Research Article

Recent improvements in the SHIELD-HIT code

, , , &
Pages 195-199 | Received 10 Jan 2011, Accepted 28 Jul 2011, Published online: 07 Sep 2011
 

Abstract

Purpose: The SHIELD-HIT Monte Carlo particle transport code has previously been used to study a wide range of problems for heavy-ion treatment and has been benchmarked extensively against other Monte Carlo codes and experimental data. Here, an improved version of SHIELD-HIT is developed concentrating on three objectives, namely: Enhanced functionality, improved efficiency, and a modification of employed physical models.

Methodological developments: SHIELD-HIT (currently at version ‘10A’) is now equipped with an independent detector geometry, ripple filter implementations, and it is capable of using accelerator control files as a basis for the primaries. Furthermore, the code has been parallelized and efficiency is improved. The physical description of inelastic ion collisions has been modified.

Results: The simulation of an experimental depth-dose distribution including a ripple filter reproduces experimental measurements with high accuracy.

Conclusions: SHIELD-HIT is now faster, more user-friendly and accurate, and has an enhanced functionality with some features being currently unique to SHIELD-HIT. The possibility of data file exchange with existing treatment planning software for heavy-ion therapy allows for benchmarking under treatment conditions as well as extending the capabilities of treatment planning software.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 65.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 1,004.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.