## 1 Introduction
Moreover, in a recent publication, the NRG Oncology medical physics subcommittee working group, composed of nine institutions, reported the limitations of commercial systems in implementing the TG132-recommended metrics [11], due to the inconsistency of the DVF format exported from each individual commercial system with the format of the refDVF provided by the AAPM. The lack of proper Digital Imaging and Communications in Medicine (DICOM) [15] standard definitions for this registration-type limits the direct comparison between the user-provided DVF and the gold-standard refDVF and further limits the interpretability and usability outside the original system. [PERSON] et al. [16] investigated the correlation between contour-based metrics and DVF errors. They reported a moderate correlation between the contour propagation and accurate dose deformation, and the summation/accumulation within each contour. Therefore, for adaptive radiation therapy, the accurate dose deformation and summation/accumulation within each contour is determined by the DVF accuracy. Several studies have been conducted to validate the reliability of DVF accuracy. [PERSON] et al. [17; 18] tested the transformations that mapped the anatomy between the planning CT and CBCT, which were obtained using four different DIR approaches. The data from five HN patients were used to evaluate the performance of each implementation, based on geometrical matching, the physical properties of the DVFs and the similarity between the warped dose distributions. They found a variability between the different DIR algorithms used, in terms of impact on the uncertainties in the dose warping. As reported in [PERSON] et al. [19], the main limitation of these approaches relies on the fact that a deformation field may fulfil the requirements of physical fidelity, but still differ from the underlying ground truth of the deformation, without conveying any information on the DIR uncertainties and related dose errors. Indeed, a global validation of user-obtained DVF against ground-truth DVF is considered the most accurate DIR evaluation method, yet the ground-truth DVF is not always available in a clinical setting. This paper is focused on DIR verification for HN adaptive radiotherapy. Practical guidelines and dedicated phantoms for clinical implementation are still needed to test the accuracy of deformable image registration (DIR) in various clinical situations. The registration between the CT and CBCT image sets can be considered a multimodal registration problem. The consistency of the pixel intensity values between the two modalities is restricted because the image quality of CBCT is poorer than that of CT [20], and CBCT images are commonly affected by artefacts due to scatter contamination and truncated CBCT patient volumes [21]. The use of digital phantoms for CT-CBCT DIR QA is limited by the fact that the applied transformations are not patient-specific but are based on pre-defined DVFs. Furthermore, the deformed images of digital phantoms do not have any representative noise variation, inherent in the CBCT images of an actual patient [6]. It is possible to overcome such limitations using images of a physical phantom acquired with the systems and acquisition protocols used in clinical practice. Physical phantoms do not reflect the complexity of real human anatomy, which is affected by many factors, such as the setup variation, organ motion and organ deformation. These factors contribute to the inherent differences between CT and CBCT images, even if both image sets are obtained on the same day. However, the use of a rigid anthropomorphic phantom allows the acquisition of image datasets with identical anatomy for both the CT and CBCT scans. This is the main reason for the use of physical anthropomorphic phantom images in the presented method instead of real patient images: the patient's CT and CBCT scans are always different, due to patient organ motion and setup uncertainties.