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  • Title: Anatomic structure-based deformable image registration of brachytherapy implants in the treatment of locally advanced cervix cancer.
    Author: Ryckman JM, Shelton JW, Waller AF, Schreibmann E, Latifi K, Diaz R.
    Journal: Brachytherapy; 2016; 15(5):584-92. PubMed ID: 27263057.
    Abstract:
    PURPOSE: To examine the impact of anatomic structure-based image sets in deformable image registration (DIR) for cervical cancer patients. METHODS AND MATERIALS: CT examinations of 7 patients previously treated for locally advanced cervical cancer with external beam radiation therapy and from three to five fractions of high-dose-rate brachytherapy (HDR-BT) were used. Structure-based image sets were created from "free" structures already made for planning purposes, with each structure of interest assigned a unique, homogeneous Hounsfield number. Subsequent HDR fractions were registered to the pretreatment external beam radiation therapy and/or the first HDR fraction using commercially available software by rigid alignment (RIG) followed by DIR. Comparison methods included quantification of external contour displacement between source and target images and calculation of mean voxel displacement values. Registration results for structure-based image sets were then compared and contrasted to intensity-based registrations of the original grayscale images. RESULTS: Utilization of anatomic structure-based image sets resulted in better initial rigid matching (A-RIG) with more importance on applicator positioning and soft tissue structures. Subsequent DIR of anatomic structure-based images allowed for intermodality registrations, whereas all intermodality registrations using original CT images failed to produce anatomically feasible results. CONCLUSIONS: We have investigated the use of structure-based CT image sets for image registrations and have produced anatomically favorable registrations with excellent matching of external contours as compared to registrations of original grayscale images. Commercial software registrations using treatment-planning structures required no manual tweaking on a per-patient basis, suggesting results are reproducible and broadly applicable.
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