Dose reduction for kilovotage cone-beam computed tomography in radiation therapy

Kilovotage cone-beam computed tomography (kV-CBCT) has shown potentials to improve the accuracy of a patient setup in radiotherapy. However, daily and repeated use of CBCT will deliver high extra radiation doses to patients. One way to reduce the patient dose is to lower mAs when acquiring projection data. This, however, degrades the quality of low mAs CBCT images dramatically due to excessive noises. In this work, we aim to improve the CBCT image quality from low mAs scans. Based on the measured noise properties of the sinogram, a penalized weighted least-squares (PWLS) objective function was constructed, and the ideal sinogram was then estimated by minimizing the PWLS objection function. To preserve edge information in the projection data, an anisotropic penalty term was designed using the intensity difference between neighboring pixels. The effectiveness of the presented algorithm was demonstrated by two experimental phantom studies. Noise in the reconstructed CBCT image acquired with a low mAs protocol was greatly suppressed after the proposed sinogram domain image processing, without noticeable sacrifice of the spatial resolution.     

Compensators for dose and scatter management in cone-beam computed tomography

The ability of compensators (e.g., bow-tie filters) designed for kV cone-beam computed tomography (CT) to reduce both scatter reaching the detector and dose to the patient is investigated. Scattered x rays reaching the detector are widely recognized as one of the most significant challenges to cone-beam CT imaging performance. With cone-beam CT gaining popularity as a method of guiding treatments in radiation therapy, any methods that have the potential to reduce the dose to patients and/or improve image quality should be investigated. Simple compensators with a design that could realistically be implemented on a cone-beam CT imaging system have been constructed to determine the magnitude of reduction of scatter and/or dose for various cone-beam CT imaging conditions. Depending on the situation, the compensators were shown to reduce x-ray scatter at the detector and dose to the patient by more than a factor of 2. Further optimization of the compensators is a possibility to achieve greater reductions in both scatter and dose.     

Characteristics of kilovoltage x-ray beams used for cone-beam computed tomography in radiation therapy

The purpose of this investigation is to characterize the beams produced by a kilovoltage (kV) imager integrated into a linear accelerator (Varian on-board imager integrated into the Trilogy accelerator) for acquiring high resolution volumetric cone-beam computed tomography (CBCT) images of the patient on the treatment table. The x-ray tube is capable of generating photon spectra with kVp values between 40 and 125 kV. The Monte Carlo simulations were used to study the characteristics of kV beams and the properties of imaged target scatters. The Monte Carlo results were benchmarked against measurements, and excellent agreements were obtained. We also studied the effect of including the electron impact ionization (EII), and the simulation showed that the characteristic radiation is increased significantly in the energy spectra when EII is included. Although only slight beam hardening is observed in the spectra of all photons after passing through the phantom target, there is a significant difference in the spectra and angular distributions between scattered and primary photons. The results also show that the photon fluence distributions are significantly altered by adding bow tie filters. The results indicate that a combination of large cone-beam field size and large imaged target significantly increases scatter-to-primary ratios for photons that reach the detector panel. For phantoms 10 cm, 20 cm and 30 cm thick of water placed at the isocentre, the scatter-to-primary ratios are 0.94, 3.0 and 7.6 respectively for an open 125 kVp CBCT beam. The Monte Carlo simulations show that the increase of the scatter is proportional to the increase of the imaged volume, and this also applies to scatter-to-primary ratios. This study shows both the magnitude and the characteristics of scattered x-rays. The knowledge obtained from this investigation may be useful in the future design of the image detector to improve the image quality.     

Simultaneous misalignment correction for approximate circular cone-beam computed tomography

Currently, CT scanning is often performed using flat detectors which are mounted on C-arm units or dedicated gantries as in radiation therapy or micro CT. For perspective cone-beam backprojection of the Feldkamp type (FDK) the geometry of an approximately circular scan trajectory has to be available for reconstruction. If the system or the scan geometry is afflicted with geometrical instabilities, referred to as misalignment, a non-perfect approximate circular scan is the case. Reconstructing a misaligned scan without knowledge of the true trajectory results in severe artefacts in the CT images. Unlike current methods which use a pre-scan calibration of the geometry for defined scan protocols and calibration phantoms, we propose a real-time iterative restoration of reconstruction geometry by means of entropy minimization. Entropy minimization is performed combining a simplex algorithm for multi-parameter optimization and iterative graphics card (GPU)-based FDK-reconstructions. Images reconstructed with the misaligned geometry were used as an input for the entropy minimization algorithm. A simplex algorithm changes the geometrical parameters of the source and detector with respect to the reduction of entropy. In order to reduce the size of the high-dimensional space required for minimization, the trajectory was described by only eight fix points. A virtual trajectory is generated for each iteration using a least-mean-squares algorithm to calculate an approximately circular path including these points. Entropy was minimal for the ideal dataset, whereas strong misalignment resulted in a higher entropy value. For the datasets used in this study, the simplex algorithm required 64-200 iterations to achieve an entropy value equivalent to the ideal dataset, depending on the grade of misalignment using random initialization conditions. The use of the GPU reduced the time per iteration as compared to a quad core CPU-based backprojection by a factor of 10 resulting in a total of 15-20 ms per iteration, and thus providing an online geometry restoration after a total computation time of approximately 1-3 s, depending on the number of iterations. The proposed method provides accurate geometry restoration for approximately circular scans and eliminates the need for an elaborate off-line calibration for each scan. If a priori information about the trajectory is used to initialize the simplex algorithm, it is expected that the entropy minimization will converge significantly faster.     

Image reconstruction in circular cone-beam computed tomography by constrained, total-variation minimization

An iterative algorithm, based on recent work in compressive sensing, is developed for volume image reconstruction from a circular cone-beam scan. The algorithm minimizes the total variation (TV) of the image subject to the constraint that the estimated projection data is within a specified tolerance of the available data and that the values of the volume image are non-negative. The constraints are enforced by the use of projection onto convex sets (POCS) and the TV objective is minimized by steepest descent with an adaptive step-size. The algorithm is referred to as adaptive-steepest-descent-POCS (ASD-POCS). It appears to be robust against cone-beam artifacts, and may be particularly useful when the angular range is limited or when the angular sampling rate is low. The ASD-POCS algorithm is tested with the Defrise disk and jaw computerized phantoms. Some comparisons are performed with the POCS and expectation-maximization (EM) algorithms. Although the algorithm is presented in the context of circular cone-beam image reconstruction, it can also be applied to scanning geometries involving other x-ray source trajectories.     

Motion correction for improved target localization with on-board cone-beam computed tomography

On-board imager (OBI) based cone-beam computed tomography (CBCT) has become available in radiotherapy clinics to accurately identify the target in the treatment position. However, due to the relatively slow gantry rotation (typically about 60 s for a full 360 degrees scan) in acquiring the CBCT projection data, the patient's respiratory motion causes serious problems such as blurring, doubling, streaking and distortion in the reconstructed images, which heavily degrade the image quality and the target localization. In this work, we present a motion compensation method for slow-rotating CBCT scans by incorporating into image reconstruction a patient-specific motion model, which is derived from previously obtained four-dimensional (4D) treatment planning CT images of the same patient via deformable registration. The registration of the 4D CT phases results in transformations representing a temporal sequence of three-dimensional (3D) deformation fields, or in other words, a 4D model of organ motion. The algorithm was developed heuristically in two-dimensional (2D) parallel-beam geometry and extended to 3D cone-beam geometry. By simulations with digital phantoms capable of translational motion and other complex motion, we demonstrated that the algorithm can reduce the motion artefacts locally, and restore the tumour size and shape, which may thereby improve the accuracy of target localization and patient positioning when CBCT is used as the treatment guidance.     

Large deformation three-dimensional image registration in image-guided radiation therapy

In this paper, we present and validate a framework, based on deformable image registration, for automatic processing of serial three-dimensional CT images used in image-guided radiation therapy. A major assumption in deformable image registration has been that, if two images are being registered, every point of one image corresponds appropriately to some point in the other. For intra-treatment images of the prostate, however, this assumption is violated by the variable presence of bowel gas. The framework presented here explicitly extends previous deformable image registration algorithms to accommodate such regions in the image for which no correspondence exists. We show how to use our registration technique as a tool for organ segmentation, and present a statistical analysis of this segmentation method, validating it by comparison with multiple human raters. We also show how the deformable registration technique can be used to determine the dosimetric effect of a given plan in the presence of non-rigid tissue motion. In addition to dose accumulation, we describe a method for estimating the biological effects of tissue motion using a linear-quadratic model. This work is described in the context of a prostate treatment protocol, but it is of general applicability.     

PI-line-based image reconstruction in helical cone-beam computed tomography with a variable pitch

Current applications of helical cone-beam computed tomography (CT) involve primarily a constant pitch where the translating speed of the table and the rotation speed of the source-detector remain constant. However, situations do exist where it may be more desirable to use a helical scan with a variable translating speed of the table, leading a variable pitch. One of such applications could arise in helical cone-beam CT fluoroscopy for the determination of vascular structures through real-time imaging of contrast bolus arrival. Most of the existing reconstruction algorithms have been developed only for helical cone-beam CT with constant pitch, including the backprojection-filtration (BPF) and filtered-backprojection (FBP) algorithms that we proposed previously. It is possible to generalize some of these algorithms to reconstruct images exactly for helical cone-beam CT with a variable pitch. In this work, we generalize our BPF and FBP algorithms to reconstruct images directly from data acquired in helical cone-beam CT with a variable pitch. We have also performed a preliminary numerical study to demonstrate and verify the generalization of the two algorithms. The results of the study confirm that our generalized BPF and FBP algorithms can yield exact reconstruction in helical cone-beam CT with a variable pitch. It should be pointed out that our generalized BPF algorithm is the only algorithm that is capable of reconstructing exactly region-of-interest image from data containing transverse truncations.     

基于旋转准直器的锥形束CT散射矫正方法

针对锥形束CT（CBCT）图像质量受散射影响比较严重的情况,提出一种基于旋转准直器的CBCT散射矫正方法。该方法在射线源和模体之间放置一个圆形的旋转准直器,并通过准直器的旋转使透过准直器的射线不断沿轴向来回扫描,以获取整个容积图像的投影图像信息,然后利用投影图像的遮挡区域估计整幅图像的散射信息并将其从投影图像中去除,最后利用改进FDK算法重建图像。结果表明,与CBCT图像相比,散射矫正后的重建图像CBCT值的均方根误差从16.00%下降为1.18%,杯状伪影从14.005%下降为0.660%,峰值信噪比从16.959 4提高到31.450 0。CBCT图像质量得到明显提高。     

Empirical cupping correction: a first-order raw data precorrection for cone-beam computed tomography

We propose an empirical cupping correction (ECC) algorithm to correct for CT cupping artifacts that are induced by nonlinearities in the projection data. The method is raw data based, empirical, and requires neither knowledge of the x-ray spectrum nor of the attenuation coefficients. It aims at linearizing the attenuation data using a precorrection function of polynomial form. The coefficients of the polynomial are determined once using a calibration scan of a homogeneous phantom. Computing the coefficients is done in image domain by fitting a series of basis images to a template image. The template image is obtained directly from the uncorrected phantom image and no assumptions on the phantom size or of its positioning are made. Raw data are precorrected by passing them through the once-determined polynomial. As an example we demonstrate how ECC can be used to perform water precorrection for an in vivo micro-CT scanner (TomoScope 30 s, VAMP GmbH, Erlangen, Germany). For this particular case, practical considerations regarding the definition of the template image are given. ECC strives to remove the cupping artifacts and to obtain well-calibrated CT values. Although ECC is a first-order correction and cannot compete with iterative higher-order beam hardening or scatter correction algorithms, our in vivo mouse images show a significant reduction of bone-induced artifacts as well. A combination of ECC with analytical techniques yielding a hybrid cupping correction method is possible and allows for channel-dependent correction functions.     

Low-dose megavoltage cone-beam computed tomography for lung tumors using a high-efficiency image receptor

We report on the capabilities of a low-dose megavoltage cone-beam computed tomography (MV CBCT) system. The high-efficiency image receptor consists of a photodiode array coupled to a scintillator composed of individual CsI crystals. The CBCT system uses the 6 MV beam from a linear accelerator. A synchronization circuit allows us to limit the exposure to one beam pulse [0.028 monitor units (MU)] per projection image. 150-500 images (4.2-13.9 MU total) are collected during a one-minute scan and reconstructed using a filtered backprojection algorithm. Anthropomorphic and contrast phantoms are imaged and the contrast-to-noise ratio of the reconstruction is studied as a function of the number of projections and the error in the projection angles. The detector dose response is linear (R2 value 0.9989). A 2% electron density difference is discernible using 460 projection images and a total exposure of 13 MU (corresponding to a maximum absorbed dose of about 12 cGy in a patient). We present first patient images acquired with this system. Tumors in lung are clearly visible and skeletal anatomy is observed in sufficient detail to allow reproducible registration with the planning kV CT images. The MV CBCT system is shown to be capable of obtaining good quality three-dimensional reconstructions at relatively low dose and to be clinically usable for improving the accuracy of radiotherapy patient positioning.     

Streaking artifacts reduction in four-dimensional cone-beam computed tomography

Cone-beam computed tomography (CBCT) using an "on-board" x-ray imaging device integrated into a radiation therapy system has recently been made available for patient positioning, target localization, and adaptive treatment planning. One of the challenges for gantry mounted image-guided radiation therapy (IGRT) systems is the slow acquisition of projections for cone-beam CT (CBCT), which makes them sensitive to any patient motion during the scans. Aiming at motion artifact reduction, four-dimensional CBCT (4D CBCT) techniques have been introduced, where a surrogate for the target's motion profile is utilized to sort the cone-beam data by respiratory phase. However, due to the limited gantry rotation speed and limited readout speed of the on-board imager, fewer than 100 projections are available for the image reconstruction at each respiratory phase. Thus, severe undersampling streaking artifacts plague 4D CBCT images. In this paper, the authors propose a simple scheme to significantly reduce the streaking artifacts. In this method, a prior image is first reconstructed using all available projections without gating, in which static structures are well reconstructed while moving objects are blurred. The undersampling streaking artifacts from static structures are estimated from this prior image volume and then can be removed from the phase images using gated reconstruction. The proposed method was validated using numerical simulations, experimental phantom data, and patient data. The fidelity of stationary and moving objects is maintained, while large gains in streak artifact reduction are observed. Using this technique one can reconstruct 4D CBCT datasets using no more projections than are acquired in a 60 s scan. At the same time, a temporal gating window as narrow as 100 ms was utilized. Compared to the conventional 4D CBCT reconstruction, streaking artifacts were reduced by 60% to 70%.     

An error-reduction-based algorithm for cone-beam computed tomography

Image reconstruction from cone-beam projections collected along a single circular source trajectory is commonly done using the Feldkamp algorithm, which performs well only with a small cone angle. In this report, we propose an error-reduction-based algorithm to increase the cone angle by several folds to achieve satisfactory image quality at the same radiation dose. In our scheme, we first reconstruct the object using the Feldkamp algorithm. Then, we synthesize cone-beam projection data from the reconstructed volume in the same geometry, and reconstruct the volume again from the synthesized projections. Finally, these two reconstruction results are combined to reduce the reconstruction error and produce a superior image volume. The merit of this algorithm is demonstrated in numerical simulation.