Quantitative electron density CT imaging for radiotherapy planning

Jonathan H. Mason*, Alessandro Perelli, William H. Nailon, Mike E. Davies

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Computed tomography (CT) is the imaging modality used to calculate the deposit of dose in radiotherapy planning, where the physical interactions are modelled based upon the electron density, which can be calculated from CT images. Traditionally this is a three step process: linearising the raw x-ray measurements and correcting for beam-hardening and scatter; inverting the system with analytic or iterative reconstruction algorithms into linear attenuation coefficient; then applying a nonlinear calibration into electron density. In this work, we propose a new method for statistically inferring a quantitative image of electron density directly from the raw CT measurements, with no pre- or post-processing necessary, and able to cope with both beam-hardening from a single polyenergetic source and additive scatter. We evaluate this concept with cone-beam CT (CBCT) imaging for bladder cancer, where we demonstrate significantly higher electron density accuracy than other quantitative approaches. We also show through simulated photon and proton beam calculation, that our method may facilitate superior dose estimation, especially with regions containing bony structures.

Original languageEnglish
Title of host publicationMedical Image Understanding and Analysis - 21st Annual Conference, MIUA 2017, Proceedings
PublisherSpringer-Verlag
Pages297-308
Number of pages12
Volume723
ISBN (Print)9783319609638
DOIs
Publication statusPublished - 2017
Event21st Annual Conference on Medical Image Understanding and Analysis, MIUA 2017 - Edinburgh, United Kingdom
Duration: 11 Jul 201713 Jul 2017

Publication series

NameCommunications in Computer and Information Science
Volume723
ISSN (Print)18650929

Conference

Conference21st Annual Conference on Medical Image Understanding and Analysis, MIUA 2017
CountryUnited Kingdom
CityEdinburgh
Period11/07/1713/07/17

Keywords

  • Computed tomography
  • Imaging
  • Proton therapy
  • Quantitative
  • Radiotherapy
  • Reconstruction
  • Statistical

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