ESTRO 36 Abstract Book

S899 ESTRO 36 2017 _______________________________________________________________________________________________

C. Möhler 1,2 , P. Wohlfahrt 3,4 , C. Richter 3,4,5,6 , S. Greilich 1,2 1 German Cancer Research Center DKFZ, Division of Medical Physics in Radiation Oncology, Heidelberg, Germany 2 National Center for Radiation Research in Oncology NCRO, Heidelberg Institute for Radiation Oncology HIRO, Heidelberg, Germany 3 OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus- Technische Universität Dresden- Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany 4 Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiooncology, Dresden, Germany 5 Department of Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus- Technische Universität Dresden, Dresden, Germany 6 German Cancer Consortium DKTK, Dresden, Germany Purpose or Objective Current treatment planning for essentially every external radiation therapy (photons, electrons, protons, heavier ions) is not able to account for patient-specific tissue variability or non-tissue materials (e.g. implants, contrast agent) which can lead to considerable differences in dose distributions (figure 1). This is due to the conversion of CT numbers to electron density or stopping power using a heuristic Hounsfield look-up table. In contrast, dual- energy CT (DECT) allows for a patient-specific determination of electron density – the only (most important) parameter influencing photon (ion) dose distributions. Among the many algorithms proposed for this purpose, a trend towards increased complexity is observed, which is not necessarily accompanied by increased accuracy and might at the same time militate against clinical implementation. Here, we therefore investigated the performance of a seemingly simple linear-superposition method (Saito, 2012, Hünemohr et al., 2014).

Material and Methods Key feature of the studied approach is a parameterization of the electron density, given by 'alpha blending” of the two DECT images. The blending parameter can be obtained by empirical calibration using a set of bone tissue surrogates and a linear relationship between relative photon absorption cross sections of the higher and lower voltage spectrum. First, this linear relation was analyzed to quantify the purely methodological uncertainty (i.e. with ideal CT numbers as input), based on calculated spectral-weighted cross sections from the NIST XCOM database for tabulated reference tissues (Woodard and White, 1986). A clear separation from CT-related sources of uncertainty (e.g. noise, beam hardening) is hereby crucial for a conclusive assessment of accuracy. Secondly, we tested the proposed calibration method on published

Conclusion Large differences in proton SPR estimation were found between DECT and SECT, although these were within the uncertainties which are currently used for dose calculation in particle therapy. These differences indicate that DECT will allow for reduction of treatment margins, resulting in better dose conformity. We are currently performing proton treatment planning for the patients comparing DECT- and SECT-based proton SPRs to investigate the dose difference in the tumour and in the surrounding healthy tissues, as well as potential impact on the range uncertainty margins used in proton treatment planning. EP-1673 Electron-density assessment using dual-energy CT: accuracy and robustness