Erik Pearson

Region‐of‐interest image reconstruction with intensity weighting in circular cone‐beam CT for image‐guided radiation therapy

Imaging plays a vital role in radiation therapy and with recent advances in technology considerable emphasis has been placed on cone-beam CT (CBCT). Attaching a kV x-ray source and a flat panel detector directly to the linear accelerator gantry has enabled progress in target localization techniques, which can include daily CBCT setup scans for some treatments. However, with an increasing number of CT scans there is also an increasing concern for patient exposure. An intensity-weighted region-of-interest (IWROI) technique, which has the potential to greatly reduce CBCT dose, in conjunction with the chord-based backprojection-filtration (BPF) reconstruction algorithm, has been developed and its feasibility in clinical use is demonstrated in this article. A nonuniform filter is placed in the x-ray beam to create regions of two different beam intensities. In this manner, regions outside the target area can be given a reduced dose but still visualized with a lower contrast to noise ratio. Image artifacts due to transverse data truncation, which would have occurred in conventional reconstruction algorithms, are avoided and image noise levels of the low- and high-intensity regions are well controlled by use of the chord-based BPF reconstruction algorithm. The proposed IWROI technique can play an important role in image-guided radiation therapy.

Algorithm-enabled exploration of image-quality potential of cone-beam CT in image-guided radiation therapy.

Kilo-voltage (KV) cone-beam computed tomography (CBCT) unit mounted onto a linear accelerator treatment system, often referred to as on-board imager (OBI), plays an increasingly important role in image-guided radiation therapy. While the FDK algorithm is currently used for reconstructing images from clinical OBI data, optimization-based reconstruction has also been investigated for OBI CBCT. An optimization-based reconstruction involves numerous parameters, which can significantly impact reconstruction properties (or utility). The success of an optimization-based reconstruction for a particular class of practical applications thus relies strongly on appropriate selection of parameter values. In the work, we focus on tailoring the constrained-TV-minimization-based reconstruction, an optimization-based reconstruction previously shown of some potential for CBCT imaging conditions of practical interest, to OBI imaging through appropriate selection of parameter values. In particular, for given real data of phantoms and patient collected with OBI CBCT, we first devise utility metrics specific to OBI-quality-assurance tasks and then apply them to guiding the selection of parameter values in constrained-TV-minimization-based reconstruction. The study results show that the reconstructions are with improvement, relative to clinical FDK reconstruction, in both visualization and quantitative assessments in terms of the devised utility metrics.

Artifact reduction in short-scan CBCT by use of optimization-based reconstruction.

Increasing interest in optimization-based reconstruction in research on, and applications of, cone-beam computed tomography (CBCT) exists because it has been shown to have to potential to reduce artifacts observed in reconstructions obtained with the Feldkamp-Davis-Kress (FDK) algorithm (or its variants), which is used extensively for image reconstruction in current CBCT applications. In this work, we carried out a study on optimization-based reconstruction for possible reduction of artifacts in FDK reconstruction specifically from short-scan CBCT data. The investigation includes a set of optimization programs such as the image-total-variation (TV)-constrained data-divergency minimization, data-weighting matrices such as the Parker weighting matrix, and objects of practical interest for demonstrating and assessing the degree of artifact reduction. Results of investigative work reveal that appropriately designed optimization-based reconstruction, including the image-TV-constrained reconstruction, can reduce significant artifacts observed in FDK reconstruction in CBCT with a short-scan configuration.

Prior-image-based few-view cone beam CT for applications to daily scan in image-guided radiation therapy: preliminary study

Interfraction motion of a treatment target such as the prostate in radiation therapy (RT) is, in part, responsible for large planning target volume (PTV) margins and related side effects. Online adjustment of the treatment based on timely cone-beam CT (CBCT) images can be particularly useful for patients with large interfraction motion. However, radiation dose to the patient due to frequent CBCT poses a radiation safety concern. One unique feature of CBCT for interfraction motion detection is the availability of a prior anatomical image most of which has not changed. We propose an iterative algorithm, for image reconstruction from a very limited number of projections in CBCT, that is based on total variation (TV) minimization subject to the constraints of data fidelity and positivity and that utilizes anatomical image prior information. Numerical studies for a 2D fan-beam geometry suggests the proposed algorithm can potentially contribute to lowering the radiation dose to the patient by allowing satisfactory image reconstruction from a very limited number of projections.

Development of a 6DOF robotic motion phantom for radiation therapy.

PURPOSE The use of medical technology capable of tracking patient motion or positioning patients along 6 degree-of-freedom (6DOF) has steadily increased in the field of radiation therapy. However, due to the complex nature of tracking and performing 6DOF motion, it is critical that such technology is properly verified to be operating within specifications in order to ensure patient safety. In this study, a robotic motion phantom is presented that can be programmed to perform highly accurate motion along any X (left-right), Y (superior-inferior), Z (anterior-posterior), pitch (around X), roll (around Y), and yaw (around Z) axes. In addition, highly synchronized motion along all axes can be performed in order to simulate the dynamic motion of a tumor in 6D. The accuracy and reproducibility of this 6D motion were characterized. METHODS An in-house designed and built 6D robotic motion phantom was constructed following the Stewart-Gough parallel kinematics platform archetype. The device was controlled using an inverse kinematics formulation, and precise movements in all 6 degrees-of-freedom (X, Y, Z, pitch, roll, and yaw) were performed, both simultaneously and separately for each degree-of-freedom. Additionally, previously recorded 6D cranial and prostate motions were effectively executed. The robotic phantom movements were verified using a 15 fps 6D infrared marker tracking system and the measured trajectories were compared quantitatively to the intended input trajectories. The workspace, maximum 6D velocity, backlash, and weight load capabilities of the system were also established. RESULTS Evaluation of the 6D platform demonstrated translational root mean square error (RMSE) values of 0.14, 0.22, and 0.08 mm over 20 mm in X and Y and 10 mm in Z, respectively, and rotational RMSE values of 0.16°, 0.06°, and 0.08° over 10° of pitch, roll, and yaw, respectively. The robotic stage also effectively performed controlled 6D motions, as well as reproduced cranial trajectories over 15 min, with a maximal RMSE of 0.04 mm translationally and 0.04° rotationally, and a prostate trajectory over 2 min, with a maximal RMSE of 0.06 mm translationally and 0.04° rotationally. CONCLUSIONS This 6D robotic phantom has proven to be accurate under clinical standards and capable of reproducing tumor motion in 6D. Such functionality makes the robotic phantom usable for either quality assurance or research purposes.

Non-circular cone beam CT trajectories: A preliminary investigation on a clinical scanner

The use of cone beam CT (CBCT) image guidance in interventional and therapeutic procedures is becoming increasingly common. Clinical systems consist of a kV x-ray source mounted opposite a flat panel digital detector often on a C-arm system. The source and detector typically rotate in a circle about the patient. However data acquired in such a circular cone beam manner provides insufficient coverage of the object and thus the reconstructed image volume is degraded by artifacts. Several combinations of trajectories and exact analytical reconstruction algorithms have been proposed to overcome these artifacts, however to the knowledge of the authors few if any of these have been studied with data acquired from a real system, with the exception of the widely used standard helical trajectory. An apparatus for performing non-circular scans without altering a clinical scanner has been constructed and the accuracy of achieving a specified trajectory verified. A Defrise style disk phantom was fabricated to test the reduction of cone angle artifacts. Reconstruction results are shown.

Preliminary investigation of dose allocation in low-dose cone-beam CT

Current cone-beam CT imaging requires dense angular sampling that is imposed by the FDK-type image-reconstruction algorithm. In an attempt to investigate the possibility of low-dose CBCT by reducing the number of projection views, we applied the adaptive-steepest-descent-projection-onto-convex-sets (ASD-POCS) algorithm for CBCT image reconstruction. Given a reduced amount of total radiation-dose, we applied both ASD-POCS and FDK algorithms for reconstruction of CBCT images from real measurement data acquired at different mAs settings, and investigated how the quality of images reconstructed by these algorithms changes when the amount of total dose is allocated to angular views in different ways. Preliminary results of the study suggest that the ASD-POCS algorithm can yield images of quality better than that achieved by the FDK algorithm with each low-dose data set, and comparable to images obtained with the standard dose level. While FDK image quality degrades with decreased number of views, the ASD-POCS image quality appears to be less affected by different dose-allocation parameters under investigation.

WE-G-BRF-07: Non-Circular Scanning Trajectories with Varian Developer Mode

PURPOSE Cone-beam CT (CBCT) in image-guide radiation therapy (IGRT) typicallyacquires scan data via the circular trajectory of the linearaccelerators (linac) gantry rotation. Though this lends itself toanalytic reconstruction algorithms like FDK, iterative reconstructionalgorithms allow for a broader range of scanning trajectories. Weimplemented a non-circular scanning trajectory with Varians TrueBeamDeveloper Mode and performed some preliminary reconstructions toverify the geometry. METHODS We used TrueBeam Developer Mode to program a new scanning trajectorythat increases the field of view (FOV) along the gantry rotation axiswithout moving the patient. This trajectory consisted of moving thegantry in a circle, then translating the source and detector along theaxial direction before acquiring another circular scan 19 cm away fromthe first. The linear portion of the trajectory includes an additional4.5 cm above and below the axial planes of the sources circularrotation. We scanned a calibration phantom consisting of a lucite tubewith a spiral pattern of CT spots and used the maximum-likelihoodalgorithm to iteratively reconstruct the CBCT volume. RESULTS With the TrueBeam trajectory definition, we acquired projection dataof the calibration phantom using the previously described trajectory.We obtained a scan of the treatment couch for log normalization byscanning with the same trajectory but without the phantom present.Using the nominal geometric parameters reported in the projectionheaders with our iterative reconstruction algorithm, we obtained acorrect reconstruction of the calibration phantom. CONCLUSION The ability to implement new scanning trajectories with the TrueBeamDeveloper Mode enables us access to a new parameter space for imagingwith CBCT for IGRT. Previous simulations and simple dual circle scanshave shown iterative reconstruction with non-circular trajectories canincrease the axial FOV with CBCT. Use of Developer Mode allowsexperimentally testing these and other new scanning trajectories. Support was provided in part by the University of Chicago Research Computing Center, Varian Medical Systems, and NIH Grants 1RO1CA120540, T32EB002103, S10 RR021039 and P30 CA14599. The contents of this work are solely the responsibility of the authors and do not necessarily represent the official views of the supporting organizations.

An investigation of regularization for basis image reconstruction in spectral CT

Spectral CT adds an additional dimension of energy to the conventional CT imaging. As a result, more than one images are usually to be reconstructed. Conventionally, these images are reconstructed separately as isolated inverse problems, requiring minimum effort in adapting existing reconstruction algorithm. Joint reconstruction, on the other hand, takes advantages of the correlation among the images and seems to be more robust and less demanding on the scanning configuration. In this study, we develop an one-step optimization-based reconstruction method with regularization for the basis images. In a simulation study with a dual kVp scan consisting of two sequential limited-angle acquisition, the results have suggested that the method with the regularization improves the basis images by reducing the crosstalk in the bone regions and rendering more uniform textures in soft tissue regions.

Iterative image reconstruction with variable resolution in CT

For some applications in computed tomography (CT), precise knowledge of the subject within a particular region of interest (ROI) is often desired, while rough (or little) knowledge outside the ROI is sufficient. Therefore, it is of practical merit to develop iterative algorithms for reconstructing a high-resolution ROI image while yielding a coarse image outside the ROI. Conventional iterative algorithms can only yield image values on the entire array of discrete grids. In this work, we investigate and develop an iterative algorithm for image reconstruction with variable spatial resolution. Our results show that the proposed approach can yield ROI images of high resolution.