Timo Berkus

Autoadaptive phase-correlated (AAPC) reconstruction for 4D CBCT

PURPOSE Kilovoltage cone-beam computed tomography (CBCT) is widely used in image-guided radiation therapy for exact patient positioning prior to the treatment. However, producing time series of volumetric images (4D CBCT) of moving anatomical structures remains challenging. The presented work introduces a novel method, combining high temporal resolution inside anatomical regions with strong motion and image quality improvement in regions with little motion. METHODS In the proposed method, the projections are divided into regions that are subject to motion and regions at rest. The latter ones will be shared among phase bins, leading thus to an overall reduction in artifacts and noise. An algorithm based on the concept of optical flow was developed to analyze motion-induced changes between projections. The technique was optimized to distinguish patient motion and motion deriving from gantry rotation. The effectiveness of the method is shown in numerical simulations and patient data. RESULTS The images reconstructed from the presented method yield an almost the same temporal resolution in the moving volume segments as a conventional phase-correlated reconstruction, while reducing the noise in the motionless regions down to the level of a standard reconstruction without phase correlation. The proposed simple motion segmentation scheme is yet limited to rotation speeds of less than3°∕s. CONCLUSIONS The method reduces the noise in the reconstruction and increases the image quality. More data are introduced for each phase-correlated reconstruction, and therefore the applied dose is used more efficiently.

Efficient scatter correction using asymmetric kernels

X-ray cone-beam (CB) projection data often contain high amounts of scattered radiation, which must be properly modeled in order to produce accurate computed tomography (CT) reconstructions. A well known correction technique is the scatter kernel superposition (SKS) method that involves deconvolving projection data with kernels derived from pencil beam-generated scatter point-spread functions. The method has the advantages of being practical and computationally efficient but can suffer from inaccuracies. We show that the accuracy of the SKS algorithm can be significantly improved by replacing the symmetric kernels that traditionally have been used with nonstationary asymmetric kernels. We also show these kernels can be well approximated by combinations of stationary kernels thus allowing for efficient implementation of convolution via FFT. To test the new algorithm, Monte Carlo simulations and phantom experiments were performed using a table-top system with geometry and components matching those of the Varian On-Board Imager (OBI). The results show that asymmetric kernels produced substantially improved scatter estimates. For large objects with scatter-to-primary ratios up to 2.0, scatter profiles were estimated to within 10% of measured values. With all corrections applied, including beam hardening and lag, the resulting accuracies of the CBCT reconstructions were within ±25 Hounsfield Units (±2.5%).

Motion-compensated 4D cone-beam computed tomography

In image-guided radiation therapy (IGRT) beside the linear particle accelerator an additional kV system provides information for an accurate patient positioning. The precise execution of the treatment plan is assured that way. An extra goal is the refinement of further planned treatment fractions based on the on-board imaging system information. Additional inter-fractional planning CTs become thus obsolete. However, the acquisition time of the system is much longer than the patients breathing cycle due to technical limitations on the gantry rotation speed. Severe artifacts like blurring or streaks are the consequence. They affect image quality and thus also the refinement of the treatment plan.

Cone-beam CT sequence scan reconstruction with improved dose usage and scan coverage

For circular cone-beam CT often one scan covers not the complete z-range of interest. If this is the case two or more circle scans are made. These sequence scans are typically reconstructed by separately reconstructing each circle scan followed by combining the resulting partial volumes. This image-based concatenation method uses only those data that are needed for each partial volume, the contribution of rays to neighboring volumes are ignored, redundancies are not used, and dose is wasted. Therefore an algorithm that uses all rays that run through a voxel by appropriately weighting the rays followed by filtered backprojection was developed and evaluated. This leads to improved dose usage and increases the overlap region of neighboring volumes, potentially leading to reduced artifacts in this region. Alternatively, our approach allows to increase the table increment between adjacent circle acquisitions, and thereby the scan coverage, without impairing image quality or increasing dose. To evaluate our method we use the geometry of the Varian OBI flat panel detector CT scanner. Simulated and measured data are processed at varying table increment values and an evaluation of image noise, spatial resolution and artifacts has been performed. The method shows good image quality on simulated phantom data as well as on clinical patient data. In this paper the algorithm demonstrates its ability to extend the z-range of sequence scans and to improve the image quality in the overlap region and turns out to be usable on devices in the clinical practice.

A comparison of 4D cone-beam CT algorithms for slowly rotating scanners

The study compares several algorithms for the 4D reconstruction of cone-beam computed tomography (CBCT) data that were recently proposed and which can be used from slowly rotating devices. In our case the imaging units are mounted to linear particle accelerators (LINAC). The algorithms are the conventional phase-correlated reconstruction (PC), the McKinnon/Bates-Algorithm, the prior image constrained compressed sensing (PICCS) algorithm, the total-variation minimization (TV) algorithm, and our auto-adaptive phase-correlation (AAPC) algorithm. For each algorithm the same motion-affected rawdata are used and the reconstruction results compared to each other regarding their noise and artifact levels, as well as temporal resolution, and computational complexity and convergence. These criteria result in a discussion of the advantages and disadvantages of each algorithm. The temporal resolution is best in the algorithms which exclusively use data from a single motion phase only. The iterative algorithms show lower noise and artifact levels but are computationally complex and therefore may have a limited usage in the clinical application. Algorithms which include image enhancements beside a faster reconstruction represent a suitable trade-off for the clinical workflow.

TU‐A‐204B‐01: The CBCT Performance of a New Treatment Platform

Purpose: To characterize the CBCT performance of a new radiation therapy platform (Trilogy MX). Methods: An entirely new CBCT system has been developed for Trilogy MX. The new CBCT system differs from that of the On‐Board Imager® (OBI) in the use of a beam hardening filter, which reduces patient dose, and an improved reconstructor, which uses scatter correction algorithms to account for the x‐ray scatter caused by the cone‐beam geometry. Scans of Catphan® and electron density (Model 062A, CIRS) phantoms have been compared with OBI scans. Hounsfield unit (HU) accuracy was checked by changing the z scan length and the phantom diameters for pelvis (125kVp, 680mAs, 45cm dia.) acquisitions. The Catphan was imaged using doses ranging between 5–20mGy (CTDIw). Projections acquired using clinical OBI units were also reconstructed for comparison using the new reconstructor.Results: The new CBCT system has higher dose efficiency and higher HU accuracy. When the volume length is reduced from 160mm to 90mm or when the phantom diameter is reduced from 330mm to 180mm, the HU values measured for the same inserts differ by −190 to +80HU for OBI scans and by –60 to +50HU for Trilogy MX scans (for electron densities between 0.2 and 1.2). The contrast detectability of the 1% contrast objects in the Catphan phantom improves from 9mm to 4mm diameter when using the same CTDIwdose as OBI. Clinical images exhibit much better uniformity, elimination of streaks and better definition of the skin surface. Conclusions: The new reconstruction algorithm makes substantial improvements in CBCTimage quality, reduces patient dose and increases HU accuracy. The new system produces CBCTimages, which are much better suited to image guidance and which may be suitable for other tasks such as adaptive RT planning.

Voxel-based reconstruction combined with motion detection for slow rotating 4D CBCT

Flat panel detector (FPD) cone-beam computed tomography (CBCT) systems, such as C-arm CT scanners or onboard imaging systems, rotate far slower than a typical motion cycle of the heart or lung. Therefore 4D CBCT is more complicated with flat panel detectors than with clinical CT. Recent approaches for 4D imaging from FPD CBCT either use multiple scans over the same angular range or a single slow rotation, and they perform a motion phase-dependent weighting of complete projections (e.g. using a respiratory monitor). This leads to a relatively high temporal resolution but also to high image noise and in the second approach to artifacts due to sparse angular sampling. Our proposed method also uses the data from several scans without causing streak artifacts. But instead of weighting the whole projections the weighting is applied to the motion affected areas in the projection only. These regions are automatically estimated using motion detection techniques between consecutive projections. Thus, projection data are used in our algorithm that are completely ignored in conventional approaches. To evaluate our method simulated data of a breathing thorax phantom and measurements acquired with the OBI scanner (Varian Medical Systems, Palo Alto, CA) were reconstructed. Image quality was compared with the projection-weighting approach for whole projections and standard reconstructions without phase-correlation.

SU‐E‐I‐15: Comparison of State‐Of‐The‐Art Interpolation‐Based Metal Artifact Reduction (MAR) Algorithms for Cone‐Beam Computed Tomography (CBCT)

PURPOSE To compare four metal-artifact-reduction (MAR) algorithms in their ability to correct the typical streaking artifacts that appear in cone- beam computed tomography (CBCT) images. METHODS The goal was to compare the strengths and weaknesses of four MAR algorithms, Basic; Wei; Mazin and Meyer, using typical clinical situations where metal is present. Three clinical situations were evaluated: fiducial markers in the abdomen; hip implants and multiple dental fillings. The algorithms take original CBCT projections as input and produce a corrected image. The location of the metal is identified in the CBCT images and a forward projection identifies which pixels in the projections need to be replaced by interpolation of neighboring pixels. The three advanced algorithms extend the Basic technique with more sophisticated interpolation schemes. Wei and Meyer identify the high contrast structures using image segmentation in order to reduce their appearance in the projections before interpolation. Mazin corrects the original projections using a forward projection of the Basic correction. RESULTS All the algorithms reduced the streak artifacts typical of metal structures. Nevertheless, depending upon the clinical task, the algorithms also added shading and streaks which reduced the overall visual impression. Images containing fiducial markers in the abdomen showed obvious improvements; images containing hip implants were improved but also showed distracting shading artifacts; and, images with multiple dental fillings all appeared visually worse than the uncorrected images. In almost all cases, Mazin outperformed the other approaches and introduced the fewest additional streaks and shading artifacts. CONCLUSIONS This work indicates that the Mazin algorithm is best suited for clinical usage of MAR. Furthermore the algorithm is fairly simple and can be computational very efficient making it well suited for clinical use. Nevertheless, the overall improvement is highly dependent on the individual characteristics of the original image. For dental implants no correction is recommended.