ESTRO 37 Abstract book

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ESTRO 37

2 Mayo Clinic, Dept. of Radiology, Rochester, USA 3 Mayo Clinic, Dept. of Radiation Oncology, Rochester, 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 This study confirmed the advantages of DECT-based SPR estimation for organic tissue samples. We validated the SPR estimation methods on several homogenous tissue samples, including both soft tissues and bone, with reference SPR values obtained from proton pencil beam measurements. This study therefore showed that using clinical CT doses, DECT improved the SPR estimation accuracy for organic tissue samples compared SECT. These results show that DECT can be used to improve proton treatment planning and reduce range uncertainty margins.