Accuracy estimation for projection‐to‐volume targeting during rotational therapy: A feasibility study

Abstract

Purpose: Estimating motion and deformation parameters from a series of projection radiographs acquired during arc therapy using a reference CT volume has become a promising technique for targeting treatment. The purpose of this work is to investigate the influence of rotational arc length on maximum achievable accuracy of motion estimation. Methods: The projection-to-volume alignment procedure used a nonrigid model to describe motion in thorax area, a cost function consisting of a least-squared error metric and a simple regularizer that encourages local invertibility, and a four-level multiresolution scheme with a conjugate gradient method to optimize the cost function. The authors tested both small and large scale deformations typically found in the thorax of a radiotherapy patient at different breathing states and limitedangle scans of six angular widths ͑12°, 18°, 24°, 36°, 60°, and 90°͒ centered at three angles ͑0°, 45°, and 90°͒. Results:The experiments illustrate the potential accuracy of limited-angle projection-to-volume alignment. Registration accuracy can be sensitive to angular center, tends to be lower along direction of the projection set, and tends to decrease away from the rotation center. The studies of small as well as large but realistically scaled deformations show similar dependencies. These trends appear to have fairly low sensitivity to quantum noise effects. Conclusions: There is potentially sufficient information present in a small spread of projections to monitor the configuration of reasonably high contrast tumors without implanted markers.

Reconstruction of a cone‐beam CT image via forward iterative projection matching

“…We will refer to it as CBCT image reconstruction via forward iterative projection matching. It is similar in concept to the projection-to-volume method recently proposed by Long et al 14 An initial proof of concept for this method, using 2D source images and 1D projections, was reported by Docef and Murphy in 2005. 11 To continue developing the method under progressively more realistic conditions, we have carried out two simulation studies using 3D CBCT imaging scenarios.…”

3D-2D Deformable Image Registration Using Feature-Based Nonuniform Meshes

“…We evaluate and compare our proposed nonuniform tetrahedral meshing for 3D-2D DIR with other 3D-2D DIR methods, that is, voxel-based method [ 1 – 3 ], uniform orthogonal grid mesh [ 16 ], and uniform tetrahedral mesh on image visualization and quantitative evaluations on two XCAT phantoms and five H&N cancer patients.…”

“…This is a drawback of voxel-based deformation and is due to its localized deformation (i.e., there are too many sampling points and it is easy to be trapped into some local minima). The feature-based nonuniform meshing method overcomes this drawback and yields more anatomically accurate DVF (both the NCC and NRMSE measurements on DVF of the nonuniform meshing method are better than those of the voxel-based method, which were applied in [ 1 – 3 ]). Furthermore, from Figure 12 , it is clearly seen that the energy curve of the feature-based meshing method (the red line with triangle marker) decreases dramatically faster than any other methods; that is, it has faster convergence speed during the image registration optimization.…”

“…Traditionally, Conventional Cone-Beam Computed Tomography (CBCT) image reconstruction in radiation therapy needs hundreds of projections, which deliver high imaging dose to patients. In order to reduce the number of CBCT projections, recently, some researchers have proposed methods to reconstruct images by using the information of prior images, such as a planning CT [ 1 – 3 ] or a previous CBCT [ 4 ], and a deformation model, which is essentially a 3D-2D deformable image registration (DIR) procedure. A lot of researches have been done related to 3D-2D image registration.…”

“…Previously, only rigid registrations between 3D images and 2D fluoroscopic images have been addressed [ 5 – 7 ]. For 3D-2D nonrigid registration [ 1 , 2 , 4 , 8 , 9 ], the multiscale technique was applied, instead of using the finite element method- (FEM-) based methods to speed up the reconstruction process and increase the accuracy. For nonrigid modeling of respiratory motion, Zeng et al [ 10 ] introduced a method to estimate the 3D motion parameters of a nonrigid, free breathing motion model from a set of projection views.…”