ESTRO 2022 - Abstract Book

S340

Abstract book

ESTRO 2022

Conclusion Heterogeneous dose escalation in lung cancer patients, may lead to overdose of OAR due to anatomical changes during the seven weeks of radiotherapy. The overdosage may be mitigated by daily dose calculation based on CBCT used for setup followed by plan adaption. The described method can be used for real time dose calculation improving the online treatment process.

PD-0400 Quantitative deformable image registration uncertainty framework for proton head and neck treatment

F. Amstutz 1,2 , P.G. D'Almeida 1,3 , X. Wu 1,4 , F. Albertini 1 , B. Bachtiary 1 , D.C. Weber 1,5,6 , J. Unkelbach 5 , A.J. Lomax 1,7 , Y. Zhang 1

1 Paul Scherrer Institut, Center for Proton Therapy, Villigen, Switzerland; 2 ETH Zurich, Department of Physics, Zurich, Switzerland; 3 ETH Zurich, Department of Information Technology & Electrical Engineering, Zurich, Switzerland; 4 ETH Zurich, Department of Information Technology & Electrical Engineering , Zurich, Switzerland; 5 University Hospital Zurich, Department of Radiation Oncology, Zurich, Switzerland; 6 University Hospital Bern, Department of Radiation Oncology, Bern, Switzerland; 7 ETH Zurich, Department of Physics, Villigen, Switzerland Purpose or Objective Deformable image registration (DIR) is one key component for adaptive radiotherapy treatments (e.g. dose accumulation), but discrepancies among different DIRs are inescapable [Nenoff et al. 2020]. To overcome one barrier for its broader clinical implementation, we developed a quantitative uncertainty evaluation and estimation framework at both geometric and dosimetric levels and validated its effectiveness and accuracy for pencil beam scanning proton therapy (PT) for head and neck (HN) cancer. Materials and Methods For five HN cancer patients with pronounced anatomy variations during PT, five different DIR algorithms (namely Elastix, Plastimatch Bspline & Demon, Velocity, NiftyReg) were used to establish geometric correspondences (represented by deformable vector fields (DVF)) between the planning CT (pCT) and each of 4-8 CTs acquired during the treatment course (repCT). A geometric quality assurance (gQA) of DVFs for each DIR was achieved by calculating the Dice coefficient between the binary image of the patient surface from repCT, with respect to propagated surfaces of the pCT using the derived DVFs (Fig. 1a). Accumulated dose distributions were computed by averaging over the warped dose distributions recalculated on each repCT based on their individual DVFs. Dosimetric uncertainties were quantified as voxel-wise dose differences resulting from the accumulated dose distributions between the different DIRs (Fig. 1b). Moreover, we also compared actual dosimetric uncertainties to model-based estimates using a previously developed approach [Amstutz et al. 2021]. This validation was performed for both, first series of sequential boost and simultaneous integrated boost (SIB) plans (Fig. 1c).