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RaySearch introduces micro-RayStation for research on small animals

RaySearch introduces micro-RayStation for research on small animals

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RaySearch has launched µ-RayStation, a version of its innovative treatment planning system specially adapted for research on small animals. Now those engaged in pre-clinical research can have access to the advanced functionality of RayStation, in a system tailored to the specific needs of this field.

The µ-RayStation system is based on the RayStation 5 platform and includes all the tools relevant to pre-clinical research. The tools have been adjusted to handle the higher-resolution images used in small animal research. The system features a Monte Carlo dose engine and a beam model adapted for small animal X-ray irradiators, and supports static beams and arcs collimated by cones apertures, as well as RayStation’s powerful Python scripting capabilities.

Other innovative system features include:

  • Deformable image registration
  • Manual, semi-automatic and automatic image segmentation tools
  • Plan evaluation/comparison, including summation of deformed doses
  • Script export of plan text files

The dose engine has been extensively validated against an independent Monte Carlo code (EGSnrc). Dose computation for the X-RAD 225Cx has been validated at Institut Cancérologie de l’Ouest (Nantes, France), and the system will be modified to support other small animal X-ray irradiators. µ-RayStation will continue to evolve to meet the needs of this pre-clinical research segment. Currently, it is being extended to support proton irradiators using the proton Monte Carlo dose engine provided in RayStation which will also provide distributions of LET and other related quantities.

Johan Löf, CEO of RaySearch, says:

Pre-clinical research plays an important role in the ongoing fight against cancer. We are pleased to support this vital field with a specially adapted version of RayStation, and we will continue to develop it in response to emerging needs in cutting-edge research.

Source:

https://www.raysearchlabs.com/press/?year=2017&cisionid=2773432

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