Abstract Book

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Conclusion With APM it is possible to quantify and automatically minimize the joint dosimetric impact of biological and physical sources of uncertainty within a probabilistic optimization process. The resulting robust treatment plans feature an automated homogenization of RBE. OC-0089 How reliable are deformable image registration methods for scanned proton 4D dose calculations? C. O. Ribeiro 1 , A. Knopf 1 , J.A. Langendijk 1 , D.C. Weber 2 , A.J. Lomax 2 , Y. Zhang 1 University Medical Center Groningen UMCG, Department of Radiation Oncology, Groningen, The Netherlands 2 Paul Scherrer Institut PSI, Center for Proton Therapy, Villigen-PSI, Switzerland Purpose or Objective Due to the dosimetric sensitivity of pencil beam scanned proton therapy (PBS-PT), respiratory-induced dosimetric impacts need to be evaluated by extensive 4D dose calculations (4DDCs). To achieve a 4DDC, deformable image registration (DIR) is mandatory for estimating deformation vector fields (DVFs) from 4D images, which represent the deformation of the structures/organs. Although geometric uncertainties induced by different DIR algorithms were investigated in the literature, errors in the resulting 4D dose distributions are often not evaluated due to the lack of a dense ground truth (GT) for validation. Therefore, we aim here to quantify the systematic and random errors induced by different DIR methods in their resulting 4DDCs by using GT-DVFs extracted from 4DMRI. Material and Methods Six different DIR methods : ANACONDA (DIR1), Morfeus (DIR2), B-splines (DIR3), Demons (DIR4), C T Deformable (DIR5), and Total Variation (DIR6), were respectively applied to nine 4DCT-MRI data sets. These 4DCT-MRI data sets consist of end-of-exhalation 3DCTs of three liver cancer patients (CTV volumes of 122, 264, and 403 cm 3 ), each modulated by consecutive GT-DVFs from 4DMRI with three different amplitudes (mean of 7.82, 20.61, and 16.88 mm). The GT-DVFs and the derived DVFs from the six DIRs were then used as input for the 4DDC. Different plan configurations (single- or three-field plans) and rescanning scenarios (single scan/rescanning) were investigated. Mean and standard deviation (SD) dose distributions of the six DIR estimated 4D plans (mean(DIR) and SD(DIR)) for each patient geometry, motion amplitude, plan configuration, and rescanning strategy were calculated. DIR induced systematic error was assessed by individually comparing the resultant mean(DIR) 4D dose distributions to those obtained with GT-DVFs. The random error gives the extent of potential variation induced by multiple DIR algorithms and was quantified with the SD(DIR) dose distribution. Results Substantial differences in 4D dose distributions among different DIR algorithms, and compared to the results using GT-DVFs, were observed (Fig. 1). The systematic error of DIR estimated 4D plans, given by the absolute difference of V95(CTV) and D5-D95(CTV) between GT and mean(DIR) dose distribution, were up to 5.01 ± 3.56 % and 5.40 ± 2.62 % respectively (Table 1). Additionally, the random error of DIR 4DDCs, quantified by the mean of the SD(DIR) dose distribution, went up to 2.55 ± 0.77 % in the CTV + 1 cm volume. Multiple-field plans or rescanning helped to decrease the systematic and random errors resulting from DIR for 4D dose distributions.

Conclusion Geometric uncertainties induced by motions estimated from 4D imaging using DIRs can introduce pronounced systematic and random errors in 4DDCs, which are significant for the clinical evaluation of liver 4D PBS-PT plans. Therefore, for an accurate and safe treatment, we recommend to interpret individual 4D dose distributions with caution. OC-0090 A Planning Strategy for Near Real-Time Adaptive Proton Therapy T. Jagt 1 , S. Breedveld 1 , B. Heijmen 1 , M. Hoogeman 1 1 Erasmus Medical Center Rotterdam Daniel den Hoed Cancer Center, Radiation Oncology, Rotterdam, The Netherlands Purpose or Objective Intensity-modulated proton therapy allows for highly localized dose deposition, but is also very sensitive to daily variations in tissue density along the pencil beam paths and variations in target, OAR and patient shape. This study develops and evaluates a method to automatically adapt the treatment plan in near real-time to the anatomy of the day. This allows for tight dose distributions around the target. Our method simultaneously aims for target dose reconstruction, as well as minimizing the dose to the OARs as far as possible, while maintaining the multi-criteria trade-offs of the treatment plan, generated for the planning CT (original plan). Material and Methods The re-optimization method consists of two steps. 1) Restoration of the spot positions (Bragg peaks) from the original plan by adapting the energy of each pencil beam to the water equivalent path length (WEPL) in the repeat CT. To compensate for deformed target shape, new energy layers and spots are added. 2) Using the reference point method (RPM) for optimizing the spot weights, while respecting the trade-offs made in the original plan. The RPM uses the achieved clinical objective values of the original plan as reference point to guide the re-