Abstract Book

S44

ESTRO 37

USA 4 Siemens, Siemens Healthineers, Forchheim, Germany Purpose or Objective Dual energy CT (DECT) has been shown, in theoretical and phantom studies, to improve the stopping power ratio (SPR) estimation used for proton treatment planning compared to the use of single energy CT (SECT). The purpose of this study was to investigate if the superiority extends to organic tissues. The accuracy of SPR estimation was therefore assessed for fresh pork and beef tissue samples used as surrogates of human tissues. Material and Methods The reference SPRs for fourteen tissue samples, which included fat, muscle and femur bone, were calculated from proton range measurements, using a multi-layer ionization chamber (MLIC) and pencil beams. The tissue samples were tightly packed in plastic boxes to avoid air pockets. Repeated measurements were performed to evaluate the homogeneity of the tissue samples and the containing boxes. The tissue samples were subsequently CT scanned at a clinical dose level. Each tissue sample was scanned separately immersed in a water tank of 35 cm lateral dimension to provide beam hardening similar to a torso scan. Four different scanners with various dual- energy acquisition modes were used, Edge (with TwinBeam), AS64 (using two consecutive scans), Flash and Force (with dual source) (all from Siemens Healthcare, Forchheim, Germany). In total, six DECT- based SPR estimations were performed for each sample. The SPR was estimated using a proprietary algorithm ( syngo .via DE Rho/Z Maps, Siemens Healthcare) for extracting the electron density and the effective atomic number. SECT images were also acquired and SECT-based SPR estimations were performed using a clinical Hounsfield look-up table (HLUT). The mean of the pixel- wise SPR estimates over large volume-of-interests (VOIs) were calculated. Results For the six different DECT acquisition methods, the root- mean-square errors (RMSEs) of the SPR estimates over all tissue samples were between 0.9% and 1.5% (Table 1, Fig. 1). For the SECT-based SPR estimation the RMSE was 2.8%. For one DECT acquisition method (TwinBeam), a positive bias was seen in the SPR estimates, having a mean error of 1.3%. The best results were found for dual source DECT. The RMSE for the more clinically relevant DECT acquisition, with two consecutive scans, was 1.4%, whereas the SECT-based SPR estimation had a RMSE of 2.8%. The largest errors were generally found in the very dense cortical bone from a beef femur.

Conclusion DECT provides patient-specific information on tissue diversity and its respective proportion, which is applicable to HLUT refinement reducing systematic deviations of a standard clinical CT calibration. In principal, this can also be transferred to particle-therapy centers not using DECT. The HLUT adaptation was clinically implemented in our institution and represents a further step toward full integration of DECT for proton treatment planning. A future clinical implementation of patient-specific DECT-based SPR prediction would also individually consider intra- and inter-patient tissue variability. OC-0086 Validation of proton stopping power ratio estimation based on dual energy CT using organic tissues V.T. Taasti 1 , G.J. Michalak 2 , D.C. Hansen 1 , A.J. Deisher 3 , J.J. Kruse 3 , B. Krauss 4 , L.P. Muren 1 , J.B.B. Petersen 1 , C.H. McCollough 2 1 Aarhus University Hospital, Dept. of Medical Physics, Aarhus, Denmark 2 Mayo Clinic, Dept. of Radiology, Rochester, USA 3 Mayo Clinic, Dept. of Radiation Oncology, Rochester,