ESTRO 36 Abstract Book

S135 ESTRO 36 _______________________________________________________________________________________________

plan for delivery. Gamma pass-rate and mean Gamma ( γ mean ) were evaluated for 380 daily adaptive fractions for over 5 months. The independent MC dose engine was verified for site specific class solutions (Pancreas, Liver, Lung and Prostate) using film dosimetry before clinical implementation. Results Online patient specific QA for daily plan adaptation, including 3D MC dose calculation, gamma evaluation and automatic check of plan parameters was performed on average in 1 min 45 sec. A typical result is shown in Figure 1. Average gamma pass-rate and γ mean over 380 fractions was 99.5 (95% CI [97.1, 100]) and 0.38 (95% CI [0.33,0.44]), respectively. All daily adapted plans passed criteria for approval. Verification of MC dose engine for site specific class- solutions exhibited an excellent agreement with film dosimetry, with average gamma pass-rate and γ mean of 100% of 0.14, respectively.

Forty random prostate patient cases were selected for this study. Each dataset consisted of a CT, a structure set (including prostate, rectum, bladder, anal canal and penile bulb) and the original dose matrix. Two systems were used, the single-atlas based Raystation ('RS”,version 5.0.2, Stockholm, Sweden) and the multi-atlas based RTx ('MIR”, version 1.6.3, Mirada Medical, Oxford, UK). The 1- 5 th case was used as base atlas. The learning phase was completed in an incremental way, where each new auto- contours generated using an atlas consisting of all former cases (6 th case used the atlas of 1-5 th , 7 th the 1-6 th etc.) until the 20 th case. Performance was evaluated using the complete (1-20 th ) atlas on another 20 cases (21-40 th ). Analysis included the Dice Similarity Coefficient (DSC), Jaccard index (JI), commonly contoured volumes (CCV), volumetric ratios (VR) and 95% of the Hausdorff distance (HD95%). Furthermore using the dose matrix, DVHs were generated for all volumes and the differences of relevant organs at risk specific parameters were compared. Mean values and standard deviations (SD) were used for the descriptive statistics and paired t-test to compare the MIR vs. RS performance, while the Root mean squares (RMS) were compared for the dosimetrical differences. Results For volumetric comparison (DSC, JI, and CCV, VR, HD95%) 21 vs. 14 out of 24 parameters improved from the learning to the performance stages for MIR vs. RS respectively (table 1). For rectum, MIR underestimated the volume (VR for MIR 0.75 vs. RS 0.79, p<0.001), while for all other parameters outperformed RS (p<0.001). Results for bladder and prostate showed superior performance of MIR with the exception of bladder CCV, which was not significantly better compared to RS. Anal canal and penile bulb showed poor agreement (for both systems). RS was more accurate to estimate the anal canal volume; similar results were obtained for penile bulb’s CCV, while all other parameters were significantly better with MIR. RMS values of MIR vs. RS resulting in 10.1 vs. 11.9 cc of V50Gy and 4.7 vs. 8.0 Gy of mean dose for rectum, for bladder V55Gy 22.4 vs. 27.3 cc and mean dose 8.6 vs. 8.6 Gy, while for anal canal V20Gy of 6.9 vs. 6.3 cc and mean dose of 9.1 vs. 12.5 Gy respectively.

Conclusion A patient specific QA procedure for online adaptive MR- guided radiotherapy was successfully implemented at our institution. This procedure, which takes less than 2 minutes, include online independent 3D MC dose calculation after daily plan adaption and automatic check of plan parameters while the patient is in treatment position. A very good agreement with dose distribution from the TPS was found for all adaptive fractions.

Proffered Papers: Variabilities in volume definition

OC-0263 Single vs. multi-atlas auto-segmentation for prostate RT: Comparison of two commercial systems A. Gulyban 1 , P. Berkovic 1 , F. Lakosi 2 , J. Hermesse 1 , P.A. Coucke 1 , V. Baart 1 , D. Dechambre 1 1 Liege University hospital, Department of Radiation Oncology, Liege, Belgium 2 Health Science Center- University of Kaposvar, Radiation Oncology, Kaposvar, Hungary Purpose or Objective Using atlas-based auto-segmentation during treatment planning has the potential to reduce the workload of the staff while improving delineation consistency. Our aim was to evaluate two commercial systems for prostate treatment planning: evaluating volumetric accuracy 1) while completing the atlas (learning curve), 2) using the full atlas (performance) and 3) determining dose volume histogram parameter (DVH) variations between of the auto-generated and reference contours. Material and Methods

Conclusion