ESTRO 38 Abstract book

S1101 ESTRO 38

to unconventional Hounsfield Unit (HU) numbers of CBCT, by reshaping the pCT into CBCT. VMAT treatment plans were recomputed on each adaptive-CT and back- projected to the pCT via both the gt-DVF (gs-dose) and test-DVF (test-dose), respectively. The differences between gs-dose and test-dose on pCT were evaluated. The following organs at risk (OARs) were considered in the analysis:  · spinal canal and mandible (inserted in the original phantom manufacture);  · oral cavity, left and right parotids (digitally created by post-processing CT and CBCT image sets with real patient HU contrast). Results DIR error statistics were quantified using the target registration error (TRE) between gt-DVF and test-DVF, on a voxel basis. In both fractions of all patients, we found a TRE (mean±std(max)) of 2.5±1.0(5.5) mm, 2.9±0.7(3.9) mm, 1.4±0.4(2.6) mm, 1.8±0.6(3.1) mm, 2.0±0.9(4.0) mm and 1.5±0.5(2.7) mm for body, spinal cord, mandible, left and right parotid and oral cavity respectively. The difference between the two dose propagation methods (mean±std(max)) were 1.1±0.5(2.0) Gy, 0.9±0.3(1.6) Gy, 1.0±0.4(2.0) Gy, 1.6±0.7(3.7) Gy, 1.7±1.0(4.1) Gy and 1.1±0.5(2.6) Gy for body, spinal cord, mandible, left and right parotid and oral cavity respectively. Table 1 reports TRE and dose errors for all OARs, for each patient and in each fraction, in terms of mean±std calculated on a voxel basis. Conclusion The proposed method based on the use of an anthropomorphic phantom was able to evaluate spatial and dosimetric errors of CT -CBCT DIR. This method could be applied as a patient specific based DIR QA tool which is a necessary step toward image-guided adaptive radiotherapy process. EP-2011 Dose calculation accuracy of using tailored synthetic CT for MR-guided online adaptive radiotherapy D. Cusumano 1 , L. Placidi 1 , S. Teodoli 1 , L. Boldrini 2 , F. Greco 1 , S. Longo 2 , F. Cellini 3 , N. Dinapoli 3 , V. Valentini 2 , M. De Spirito 1 , L. Azario 3 1 Fondazione Policlinico Universitario A.Gemelli IRCCS, U.O.C. Fisica Sanitaria- Dipartimento di Diagnostica per immagini- Radioterapia Oncologica ed Ematologia, Roma, Italy ; 2 Università Cattolica del Sacro Cuore, Istituto di Radiologia, Roma, Italy ; 3 Fondazione Policlinico Universitario A.Gemelli IRCCS, U.O.C. Radioterapia- Dipartimento di Diagnostica per immagini- Radioterapia Oncologica ed Ematologia, Roma, Italy Purpose or Objective The online MR-guided adaptive Radiotherapy (MRgART) workflow relies on the assignation of the water relative electron density (RED) map to the daily MR image (dMRI), to allow the dose calculation. The actual approach consists in co-registering the CT image acquired during the simulation procedure with the dMRI and then transfering the RED values obtained from the CT to the dMRI.

EP-2010 A QA method for evaluation of deformable image registration in head and neck adaptive radiotherapy E. Cagni 1 , A. Botti 1 , M. Orlandi 1 , M. Galaverni 2 , R. Sghedoni 1 , C. Iotti 2 , E. Spezi 3 , M. Iori 1 1 Azienda USL-IRCCS di Reggio Emilia, Medical Physics Unit, Reggio Emilia, Italy ; 2 Azienda USL-IRCCS di Reggio Emilia, Radiotherapy Department, Reggio Emilia, Italy ; 3 Cardiff University, School of Engineering, Cardiff, United Kingdom Purpose or Objective This study aimed to assess a method for evaluation of delivered VMAT dose based on multimodal deformable image registration (DIR) using for head and neck (HN) adaptive radiotherapy. The main goal was to develop the proof-of-concept to be used as QA registration tool for adaptive radiotherapy. Material and Methods The HN phantom, “ATOM Max TM Dental and Diagnostic Head Model-711”(CIRS, Virginia) was scanned with CT and and cone-beam computed tomography (CBCT). Firstly, CT images of the phantom were artificially deformed in a warped CT (wCT) by using 20 clinical representative deformable vector fields (DVFs), considered the ground truth (gt-DVF). These DVFs were created by deformable registration between the planning CT (pCT) and two CBCTs of the 16 th and 26 th fraction of 10 HN patient treated in our Institute with VMAT plans. The CT–CBCT deformable registration was performed using Velocity AI (Varian Medical System. Palo Alto, CA) software, version 3.2. Secondly, the phantom CBCT was registered with the wCT resulting in a test-DVF and generated a warped CBCT (wCBCT) ( Figure1 ). Quality of the registration was assessed as the ability of the test-DVF to recover the artificially induced gs-DVF..

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To assess dosimetric errors, adaptive-CT was created for each patient gs-DVFs to overcome the limitation related