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Effects of Tissue Material Properties on X-Ray Image, Scatter and Patient Dose A Monte Carlo Simulation

  • Philipp RoserEmail author
  • Annette Birkhold
  • Xia Zhong
  • Elizaveta Stepina
  • Markus Kowarschik
  • Rebecca Fahrig
  • Andreas Maier
Conference paper
Part of the Informatik aktuell book series (INFORMAT)

Zusammenfassung

With increasing patient and staff X-ray radiation awareness, many efforts have been made to develop accurate patient dose estimation methods. To date, Monte Carlo (MC) simulations are considered golden standard to simulate the interaction of X-ray radiation with matter. However, sensitivity of MC simulation results to variations in the experimental or clinical setup of image guided interventional procedures are only limited studied. In particular, the impact of patient material compositions is poorly investigated. This is mainly due to the fact, that these methods are commonly validated in phantom studies utilizing a single anthropomorphic phantom. In this study, we therefore investigate the impact of patient material parameters mapping on the outcome of MC X-ray dose simulations. A computation phantom geometry is constructed and three different commonly used material composition mappings are applied. We used the MC toolkit Geant4 to simulate X-ray radiation in an interventional setup and compared the differences in dose deposition, scatter distributions and resulting X-ray images. The evaluation shows a discrepancy between different material composition mapping up to 20% concerning directly irradiated organs. These results highlight the need for standardization of material composition mapping for MC simulations in a clinical setup.

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Copyright information

© Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature 2019

Authors and Affiliations

  • Philipp Roser
    • 1
    Email author
  • Annette Birkhold
    • 2
  • Xia Zhong
    • 1
  • Elizaveta Stepina
    • 2
  • Markus Kowarschik
    • 2
  • Rebecca Fahrig
    • 2
  • Andreas Maier
    • 1
    • 3
  1. 1.Pattern Recognition LabFAU Erlangen-NürnbergErlangenDeutschland
  2. 2.Siemens Healthcare GmbHForchheimDeutschland
  3. 3.Erlangen Graduate School in Advanced Optical Technologies (SAOT)ErlangenDeutschland

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