## 4 Discussion  
In this study, a novel method to evaluate the quality of patient-based multimodal CT-CBCT DIR using a post-processed, digitally enhanced anthropomorphic HN phantom has been presented. All post-processed ATOM Max Dental and Diagnostic Head Phantom image datasets (CT and CBCT) are in the DICOM format, derived using the procedure described in Section 2.1, and have been made publicly available as additional downloadable material for this paper as Supplementary Material. This allows the use of the proposed method for CT-CBCT HN DIR accuracy evaluation in other centres, by processing the image sets with two different image registration software systems (reference and clinical), as described in Section 2.1. The refDVF represents the known transformation map derived with third-party reference software based on the clinically observed anatomical changes, which is then applied to create the warped phantom image. Thus, the transformation of each voxel in the warped image was known because it was deliberately applied to each voxel. As a verification method, the refDVF data did not necessarily represent the real, individual deformations of the patients, but they served as a reference to check how much the clinical algorithm under investigation (in this study, the Velocity AI) was able to reproduce the known deformation for that patient case. However, care must be taken to avoid applying a deformation derived using the same third-party algorithm that the user employs for the clinical deformation, as this would create a testDVF that was biased to the results expected from the same third-party and clinical DIR algorithms [6]. The registration algorithms used in this work to generate the refDVFs and testDVFs were both of the same class (B-spline) but implemented independently (i.e., different optimiser, similarity measure and general parameters). Because of these differences, the registrations can be considered independent between the two software programmes, in line with the previous studies [24; 25]. The dose error variations were found to be related to both the registrations and the OAR of interest. This is in line with the findings of [PERSON] et al. [29], who revealed that the impact of the DIR method on treatment dose warping is a function of the registration and is organ-specific. The OTL was derived from the material provided by the AAPM TG132 for quality assurance purposes. However, the TG132 utilised only pelvic anatomical data sets, processed using the ImSimQA, for the DIR accuracy assessment with a ground-truth transformation. Our findings confirmed that the registration accuracy is also a function of the selected organ at risk, underlying the importance of using an anatomical phantom for the DIR accuracy assessment, consistent with the clinical data considered. Thus, the OTLderived for this study, using the generic pelvic phantom proposed by the TG132, could have some limitations on the practical level. However, it was used here primarily as an exemplar to describe a suggested workflow for the DIR accuracy, as described in Figure 1a. In the published report on DIR validation by the AAPM's Task Group 132, the proposed ideal goal for the TRE is 95% of voxels within 2 mm, using the Report's provided image sets. Our results showed a considerably lower value, OTL = 45%, using the Velocity AI. The Velocity AI was previously benchmarked with different commercial DIR algorithms by [PERSON] et al. [13] and found to be very similar in accuracy with respect to the other commercial software systems included in the study. Based on this, it can be assumed that the OTL value found in this study could be considered a typical practical accuracy value using the commercial software, based on the B-spline method, for the CT-CBCT DIR registration using the TG-132 basic anatomical phantom.