ESTRO 36 Abstract Book

S910 ESTRO 36 2017 _______________________________________________________________________________________________

We based our retrospective study on a total of N =122 high- risk prostate patients treated with radiotherapy, with inclusion criteria to have a pre-treatment PSA<60 µg/L and biopsies analyzed a Uppsala University Hospital. The 5- year local tumor control probability was estimated with Kaplan Meier analysis to TCP obs =94.7% (CI 86.4-98.0%). The PSA inclusion condition was used to exclude patients with possible pre-treatment spread. The homogeneous treatment dose D h was estimated to 91.6 Gy EQD 2 based on α/β=1.93 for the given proton boost (20Gy in 4 fractions, RBE=1.1) and photon dose (50 Gy in 25 fractions). All patients underwent androgen deprivation therapy. We parameterized the populations dose-response TCP pop ( D ) with a logistic function with the parameter γ 50 =2.01 and D 50 chosen so that TCP pop ( D h )= TCP obs . The patients’ biopsy statements were used to construct simulated prostates with voxelized distributions of Gleason scores G varying per voxel. Voxel specific dose-response functions TCP vox ( D , G ) were derived with the logistic parameters γ 50,eff and D 50 ( G ) set so that the average TCP pat for all patients equals TCP obs at D h , and the average slope for the patients TCP pat equals the slope for TCP pop ( D ) at D h . Hence, the voxel specific dose-response functions are be described by TCP vox ( D , G )=1/(1+( D 50 ( G )/ D ) 4γ50,eff ), where D 50 ( G ) and γ 50,eff , for D = D h , reconstructs TCP vox ( D h , G <6)= C and TCP vox ( D h , G ≥6)= C - k ×( G -6). For G <6 TCP vox was set to not vary with Gleason scores since ADC-MRI likely not distinguish G <6 from normal tissue. We used 3 different values of C , a high value C high =1 resulting in zero desired dose for G <6 voxels, a low value C min resulting in a homogeneous dose distribution ( k =0), and an intermediate C im for a certain minimum dose. ADC images for a high-risk patient were translated into a 3D-map of Gleason scores based on results published by Turkbey et al. We used the above functions for dose painting to minimize the average dose while keeping the TCP pat equal to that for a homogeneous dose of D h . Results For the C high scenario the average dose decreased by 9 Gy (max dose 98 Gy). For the intermediate C im scenario the average dose decreased by 2 Gy with doses in the range of 74 to 98 Gy. Fig. 1 shows resulting Gleason score to TCP mappings normalized for a 50cc prostate while Fig. 2 shows a dose painted prostate for the C im scenario.

reduction in dose is strongly dependent on the minimum dose assigned to voxels with G <6. EP-1690 Validating the robustness of PET features in a phantom in a multicenter setting T. Konert 1 , M. La Fontaine 2 , S. Van Kranen 2 , W. Vogel 1 , J. Van de Kamer 2 , J.J. Sonke 2 1 Netherlands Cancer Institute Antoni van Leeuwenhoek Hospital, Nuclear Medicine, Amsterdam, The Netherlands 2 Netherlands Cancer Institute Antoni van Leeuwenhoek Hospital, Radiation Oncology, Amsterdam, The Netherlands Purpose or Objective PET features may have prognostic or predictive value and could therefore assist treatment decisions. However, PET features are sensitive to differences in data collection, reconstruction settings, and image analysis. It is insufficiently known which features are least affected by these differences, especially in a multicenter setting. Therefore, this study investigates the robustness of PET features in a phantom after repeated measurements (repeatability), due to varying scanner type (reproducibility) and their dependence on binning method and SUV activity. Material and Methods PET scans from a NEMA image quality phantom were used for assessment of PET feature robustness. Scans were acquired on a Philips, a Siemens and a GE scanner from three medical centers (see figure 1 and table 1 for more details). Per sphere, a VOI was created by applying a threshold of 40% of the SUV max . Per VOI, 10 first order statistics and 10 textural features, often reported in literature, were extracted. Two common implementations of image pre-processing, before feature extraction, were compared: using a fixed bin size (SUV = 1) versus a number of fixed bins (64 bins). To examine the feature repeatability, measurements were repeated two or three times on the same scanner. The reproducibility was assessed in images by comparing all scanners. The degree of variation was calculated per VOI with the coefficient of repeatability (1.96 x SD/mean), normalized to a percentage (CR % ). Features were seen as robust with a CR < 30%, matching the level of uncertainty found in response of PERCIST criteria. Wilcoxon signed rank tests were used to estimate the significance of differences due to binning method and p-values ≤ 0.05 were considered significant. Results For an overview of the results, see Table 1. The CR % of SUV max in all scans depended on sphere volume, and ranged from 1.1% (largest sphere) to 15.2% (smallest sphere). In the repeatability study, 9 out of 10 PET features were robust with 64 bins in more than one scanner, and significantly higher (p < 0.05) when compared to using a fixed bin size, where 7 out of 10 PET features were robust. Reproducibility was achieved in 3 out of 10 PET features when 64 bins were used. PET features were not reproducible when using a fixed bin size. Dissimilarity (CR % : 6.3-24.9), homogeneity 1 (CR % : 16.9-22.5), and inertia (CR % : 10.2-22.5) were robust to binning method, scanner type, and SUV activity. Coarseness, contrast, busyness, energy, correlation were not robust (CR % > 30%).

Fig 1. TCP vs Gleason scores comprising a 50cc prostate volume and corresponding dose-response functions for the intermediate C im scenario.

Fig 2. ADC in prostate and dose painted prostate for C im scenario. Conclusion Gleason driven dose painting for prostate cancer using ADC-MRI is feasible to reduce the average dose. The