Abstract
BackgroundIn IGRT of deformable head-and-neck anatomy, patient setup corrections are derived by rigid registration methods. In practice, experienced radiation therapists often correct the resulting vectors, thus indicating a different prioritization of alignment of local structures. Purpose of this study is to transfer the knowledge experts apply when correcting the automatically generated result (pre-match) to automated registration.MethodsDatasets of 25 head-and-neck-cancer patients with daily CBCTs and corresponding approved setup correction vectors were analyzed. Local similarity measures were evaluated to identify the criteria for human corrections with regard to alignment quality, analogous to the radiomics approach. Clustering of similarity improvement patterns is applied to reveal priorities in the alignment quality.ResultsThe radiation therapists prioritized to align the spinal cord closest to the high-dose area. Both target volumes followed with second and third highest priority. The bony pre-match influenced the human correction along the crania-caudal axis. Based on the extracted priorities, a new rigid registration procedure is constructed which is capable of reproducing the corrections of experts.ConclusionsThe proposed approach extracts knowledge of experts performing IGRT corrections to enable new rigid registration methods that are capable of mimicking human decisions. In the future, the deduction of knowledge-based corrections for different cohorts can be established automating such supervised learning approaches.
Highlights
In Image-guided radiotherapy (IGRT) of deformable head-and-neck anatomy, patient setup corrections are derived by rigid registration methods
This study proposes a knowledge-based registration approach that automatically generates a pre-match, with the goal of not needing further time-consuming expert correction
Correction vectors resulting from a registration with a small clipping box around the tPTV result in higher Pearson’s correlation coefficients in right-left and anterior-posterior direction compared to the bony match
Summary
In IGRT of deformable head-and-neck anatomy, patient setup corrections are derived by rigid registration methods. Experienced radiation therapists often correct the resulting vectors, indicating a different prioritization of alignment of local structures. IGRT is a process with two main components: An automatic component, which involves the acquisition and registration of images, and a manual one, that involves experts to review the images and approve the correction vector [3]. The resulting vector and rotations can be used to correct for patient positioning variations by adjusting the treatment couch prior to treatment. In the presence of anatomical deformations, an optimal alignment of all deformed structures is not possible [4] and the deduction of the best rigid couch correction is ambiguous [5].
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