Validation of Varian’s SmartAdapt® deformable image registration algorithm for clinical application

Abstract

BackgroundRe-contouring of structures on consecutive planning computed tomography (CT) images for patients that exhibit anatomical changes is elaborate and may negatively impact the turn-around time if this is required for many patients. This study was therefore initiated to validate the accuracy and usefulness of automatic contour propagation for head and neck cancer patients using SmartAdapt® which is the deformable image registration (DIR) application in Varian’s Eclipse™ treatment planning system.MethodsCT images of eight head and neck cancer patients with multiple planning CTs were registered using SmartAdapt®. The contoured structures of target volumes and OARs of the primary planning CT were deformed accordingly and subsequently compared with a reference structure set being either: 1) a structure set independently contoured by the treating Radiation Oncologist (RO), or 2) the DIR-generated structure set after being reviewed and modified by the RO.ResultsApplication of DIR offered a considerable time saving for ROs in delineation of structures on CTs that were acquired mid-treatment. Quantitative analysis showed that 84% of the volume of the DIR-generated structures overlapped with the independently re-contoured structures, while 94% of the volume overlapped with the DIR-generated structures after review by the RO. This apparent intra-observer variation was further investigated resulting in the identification of several causes. Qualitative analysis showed that 92% of the DIR-generated structures either need no or only minor modification during RO reviews.ConclusionsSmartAdapt is a powerful tool with sufficient accuracy that saves considerable time in re-contouring structures on re-CTs. However, careful review of the DIR-generated structures is mandatory, in particular in areas where tumour regression plays a role.

An adaptive motion regularization technique to support sliding motion in deformable image registration

“…Deformable image registration (DIR) is a key technology for many important advanced radiotherapy techniques, e.g., adaptive radiotherapy (ART), [1][2][3][4] and critical clinical tasks, e.g., target definition, [5][6][7] automatic segmentation, [8][9][10][11] motion estimation, [12][13][14] dose accumulation, 15,16 and treatment response evaluation. [17][18][19] DIR is commonly used to establish plausible spatial correspondences between moving and target images.…”

Online dosimetric evaluation of larynx SBRT: A pilot study to assess the necessity of adaptive replanning

“…Reference simulation CT images and target volumes were deformably registered to daily images via commercially available software (SmartAdapt; Varian Medical Systems, Palo Alto, CA, USA). SmartAdapt uses “accelerated demons” algorithm 16. Figs.…”

A multiparametric method to assess the MIM deformable image registration algorithm

“…This approach is interesting even if realistic deformations are quite difficult to be implemented in large regions. Finally, when patient data are used, DIR performances are usually assessed comparing anatomical marker positions in deformed and original images. Even if these tests offer useful clinical information, they are inadequate to fully describe algorithm behavior and to point out its limits.…”