CBCT Projections Research Articles

Shading correction assisted iterative cone-beam CT reconstruction

Recent advances in total variation (TV) technology enable accurate CT image reconstruction from highly under-sampled and noisy projection data. The standard iterative reconstruction algorithms, which work well in conventional CT imaging, fail to perform as expected in cone beam CT (CBCT) applications, wherein the non-ideal physics issues, including scatter and beam hardening, are more severe. These physics issues result in large areas of shading artifacts and cause deterioration to the piecewise constant property assumed in reconstructed images. To overcome this obstacle, we incorporate a shading correction scheme into low-dose CBCT reconstruction and propose a clinically acceptable and stable three-dimensional iterative reconstruction method that is referred to as the shading correction assisted iterative reconstruction. In the proposed method, we modify the TV regularization term by adding a shading compensation image to the reconstructed image to compensate for the shading artifacts while leaving the data fidelity term intact. This compensation image is generated empirically, using image segmentation and low-pass filtering, and updated in the iterative process whenever necessary. When the compensation image is determined, the objective function is minimized using the fast iterative shrinkage-thresholding algorithm accelerated on a graphic processing unit. The proposed method is evaluated using CBCT projection data of the Catphan© 600 phantom and two pelvis patients. Compared with the iterative reconstruction without shading correction, the proposed method reduces the overall CT number error from around 200 HU to be around 25 HU and increases the spatial uniformity by a factor of 20 percent, given the same number of sparsely sampled projections. A clinically acceptable and stable iterative reconstruction algorithm for CBCT is proposed in this paper. Differing from the existing algorithms, this algorithm incorporates a shading correction scheme into the low-dose CBCT reconstruction and achieves more stable optimization path and more clinically acceptable reconstructed image. The method proposed by us does not rely on prior information and thus is practically attractive to the applications of low-dose CBCT imaging in the clinic.

Abstract ID: 85 Investigating the physics of a CBCT projection shading correction based on a prior CT

The adoption of cone beam computed tomography (CBCT) image guidance in proton therapy has spurred research on CBCT image correction for dose calculation. Initially, methods based on deformable image registration gained attention [1] , however projection correction approaches based on prior CT information [2] have been shown to perform well for several body sites [3] . The shading correction algorithm used in [2] , [3] relies on image processing of the subtraction of digitally reconstructed radiographs (DRR) of a DIR-registered prior CT, and CBCT projections. In this study we have performed Monte Carlo (MC) simulation of CBCT imaging to disentangle the different sources of projection degradation, and to evaluate the physicality of the shading correction. The GATE MC toolkit’s fixed-forced-detection actor was employed, along with source and detector models optimized for an Elekta XVI CBCT system, to simulate CBCT imaging of an electron density phantom. The shading correction algorithm was applied to the measured projections and the so-called scatter component (SCA) was compared to the MC simulated scatter. Measured and simulated CBCT projections (scatter + primary) agreed well, with the largest discrepancy found for a bone insert (3% of log transformed projections). Important disagreement was observed with the MC scatter signal when the contribution from beam hardening was kept in the SCA. Undoing the beam hardening correction from the SCA using functions derived from MC primary projections and DRRs greatly improved agreement of scatter signals from MC and SCA (3% on average), with the largest discrepancy found for the bone insert (12%). Residual discrepancies were shown to stem from the intrinsic limitations of the SCA. Proton therapy dose calculations on corrected CBCT will be presented in addition to the results above.

Liver CBCT Reconstruction by Prior-Knowledge Guided Motion Modeling and Biomechanical Modeling

We developed a new liver CBCT reconstruction technique, which solves a deformation vector field (DVF) to deform a prior high-quality liver CT/CBCT to the new CBCT. The DVF also enables fast on-board liver tumor tracking, dose warping, and adaptive radiation therapy. The new liver CBCT reconstruction technique is based on the foundation of “2D-3D deformation,” which solves the DVF by matching 2D projections simulated from the deformed prior image to 2D on-board CBCT projections. The accuracy of 2D-3D deformation is limited by the low-contrast liver tumors, which lack sufficient intensity variations from liver parenchyma in 2D projections. The new technique applies two strategies to enhance the accuracy of 2D-3D deformation: 1) prior-knowledge guided motion modeling; and 2) finite-element-analysis based biomechanical modeling. To improve the DVF accuracy at the liver boundary, especially for the inferior liver boundary, the liver is contoured on a prior liver 4D-CT and the contoured liver volume at each phase is then density-overridden to enhance the boundary contrasts. Deformable registration is then performed between the 4D-CT phase images to study the liver boundary motion pattern to extract a motion model. Based on the patient-specific liver motion model, an initial DVF is generated and input into 2D-3D deformation for refinement. Based on the refined DVF, biomechanical modeling is further applied to improve the intra-liver DVF accuracy. Biomechanical modeling uses the DVF at the liver boundary to drive finite element analysis, which fine-tunes the DVFs within the liver volume, including those of the tumor. The fine-tuned DVF is fed back into 2D-3D deformation to form an iterative loop until convergence. The efficacy of the reconstruction algorithm was tested on 3 liver cancer patients. Each patient had a prior CT and a new CT. On-board cone-beam projections were simulated from the new CT for reconstruction. The low-contrast liver tumors were contoured on the prior and new CT images. The new tumor contour (“ground-truth”) was compared against those propagated from the prior tumor contour by the solved DVFs. Their DICE coefficients were calculated to evaluate the reconstruction accuracy. Compared with the other techniques, the new technique generated CBCTs with the highest accuracy (Table 1) for the liver tumor.Abstract 206; Table 1The DICE coefficient between the deformed tumor volume and the “ground-truth” tumor volumePatient No.No. of projections for reconstruction2D-3D deformation2D-3D deformation w/ biomechanical modelingThe new technique150.6020.8510.924100.6220.8750.926200.6490.8920.927250.6580.8350.885100.6710.8690.889200.6710.8820.897350.4110.5630.772100.4110.5980.780200.4110.6610.802 Open table in a new tab The new technique substantially improved the accuracy of the reconstructed liver tumor volume. It can also reduce 3D/4D-CBCT imaging dose by acquiring fewer projections for reconstruction.

John\u2019s Equation-based Consistency Condition and Corrupted Projection Restoration in Circular Trajectory Cone Beam CT

In transmitted X-ray tomography imaging, the acquired projections may be corrupted for various reasons, such as defective detector cells and beam-stop array scatter correction problems. In this study, we derive a consistency condition for cone-beam projections and propose a method to restore lost data in corrupted projections. In particular, the relationship of the geometry parameters in circular trajectory cone-beam computed tomography (CBCT) is utilized to convert an ultra-hyperbolic partial differential equation (PDE) into a second-order PDE. The second-order PDE is then transformed into a first-order ordinary differential equation in the frequency domain. The left side of the equation for the newly derived consistency condition is the projection derivative of the current and adjacent views, whereas the right side is the projection derivative of the geometry parameters. A projection restoration method is established based on the newly derived equation to restore corrupted data in projections in circular trajectory CBCT. The proposed method is tested in beam-stop array scatter correction, metal artifact reduction, and abnormal pixel correction cases to evaluate the performance of the consistency condition and corrupted projection restoration method. Qualitative and quantitative results demonstrate that the present method has considerable potential in restoring lost data in corrupted projections.

Decomposing a prior-CT-based cone-beam CT projection correction algorithm into scatter and beam hardening components

Abstract A scatter correction algorithm (SCA) for cone beam CT (CBCT) projections, making use of prior information obtained by deformable image registration of CT to CBCT, has recently been proposed and tested for particle therapy dose calculation. The SCA relies on subtraction of digitally reconstructed radiographs (DRR) from scaled measured projections and smoothing operations, followed by a subtraction correction and reconstruction. In this note, we compared the SCA’s correction to one based on a Monte Carlo simulation of the scatter, and a separate beam hardening correction. Agreement better than 3% between the two approaches was obtained when comparing corrected log-transformed projections.

Transmission characteristics of a two dimensional antiscatter grid prototype for CBCT.

High fraction of scattered radiation in cone-beam CT (CBCT) imaging degrades CT number accuracy and visualization of low contrast objects. To suppress scatter in CBCT projections, we developed a focused, two-dimensional antiscatter grid (2DASG) prototype. In this work, we report on the primary and scatter transmission characteristics of the 2DASG prototype aimed for linac mounted, offset detector geometry CBCT systems in radiation therapy, and compared its performance to a conventional one-dimensional ASG (1DASG). The 2DASG is an array of through-holes separated by 0.1mm septa that was fabricated from tungsten using additive manufacturing techniques. Through-holes' focusing geometry was designed for offset detector CBCT in Varian TrueBeam system. Two types of ASGs were evaluated: (a) a conventional 1DASG with a grid ratio of 10, (b) the 2DASG prototype with a grid ratio of 8.2. To assess the scatter suppression performance of both ASGs, Scatter-to-primary ratio (SPR) and scatter transmission fraction (Ts) were measured using the beam stop method. Scatter and primary intensities were modulated by varying the phantom thickness between 10 and 40cm. Additionally, the effect of air gap and bow tie (BT) filter on SPR and Ts were evaluated. Average primary transmission fraction (TP ) and pixel specific primary transmission were also measured for both ASGs. To assess the effect of transmission characteristics on projection image signal-to-noise ratio (SNR), SNR improvement factor was calculated. Improvement in contrast to noise ratio (CNR) was demonstrated using a low contrast object. In comparison to 1DASG, 2DASG reduced SPRs by a factor of 3 to 6 across the range of phantom setups investigated. Ts values for 1D and 2DASGs were in the range of 21 to 29%, and 5 to 14% respectively. 2DASG continued to provide lower SPR and Ts at increased air gap and with BT filter. Tp of 1D and 2DASGs were 70.6% and 84.7% respectively. Due to the septal shadow of the 2DASG, its pixel specific primary transmission values varied between 32.5% and 99.1%. With respect to 1DASG, 2DASG provided up to factor of 1.7 more improvement in SNR across the SPR range investigated. Moreover, 2DASG provided improved visualization of low contrast objects with respect to 1DASG and NOASG setups. When compared to a conventional 1DASG, 2DASG prototype provided noticeably lower SPR and Ts values, indicating its superior scatter suppression performance. 2DASG also provided 19% higher average primary transmission that was attributed to the absence of interseptal spacers and optimized grid geometry. Our results indicate that the combined effect of lower scatter and higher primary transmission provided by 2DASG may potentially translate into more accurate CT numbers and improved contrast resolution in CBCT images.

An evaluation of motion mitigation techniques for pancreatic SBRT

Background and purposeAblative radiation therapy can be beneficial for pancreatic cancer, and motion mitigation helps to reduce dose to nearby organs-at-risk. Here, we compared two competing methods of motion mitigation—abdominal compression and respiratory gating. Materials and methodsCBCT scans of 19 pancreatic cancer patients receiving stereotactic body radiation therapy were acquired with and without abdominal compression, and 3D target motion was reconstructed from CBCT projection images. Daily target motion without mitigation was compared against motion with compression and with simulated respiratory gating. Gating was free-breathing and based on an external surrogate. Target coverage was also evaluated for each scenario by simulating reduced target margins. ResultsWithout mitigation, average daily target motion in LR/AP/SI directions was 5.3, 7.3, and 13.9mm, respectively. With abdominal compression, these values were 5.2, 5.3, and 8.5mm, and with respiratory gating they were 3.2, 3.9, and 5.5mm, respectively. Reductions with compression were significant in AP/SI directions, while reductions with gating were significant in all directions. Respiratory gating also demonstrated better coverage in the reduced margins scenario. ConclusionRespiratory gating is the most effective strategy for reducing motion in pancreatic SBRT, and may allow for dose escalation through a reduction in target margin.

OC-0158: a priori scatter correction of cone-beam CT projections in photon vs. proton therapy gantries

OC-0158: a priori scatter correction of cone-beam CT projections in photon vs. proton therapy gantries

Convolution-based scatter correction usingkernels combining measurements andMonte Carlo simulations.

One of the well-recognized challenge of Cone-Beam Computed Tomography (CBCT) is scatter contamination within the projection images. Scatter degrades the image quality by decreasing the contrast, introducing cupping and shading artifacts and thus leading to inaccuracies in the reconstructed values. The higher scatter to primary ratio experienced in industrial applications leads to even more important artifacts. Various strategies have been investigated to manage the scatter signal in CBCT projection data. One of these strategies is to calculate the scatter intensity by deconvolution of primary intensity using Scatter Kernel Superposition (SKS). In this paper, we present an approach combining experimental measurements and Monte Carlo simulations to estimate the scatter kernels for industrial applications based on the continuously thickness-adapted kernels strategy with a four-Gaussian modeling of kernels. We compare this approach with an experimental technique based on a two-Gaussian modeling of the kernels. The results obtained prove the superiority of a four-Gaussian model to effectively take into account both the contribution of object and detector scattering as compared to a two-Gaussian approach. We also present the parameterisation of the scatter kernels with respect to object to detector distance. This approach facilitates the use of a single geometry for calculation of scatter kernels over the whole magnification range of the acquisition setup.

Dual-energy imaging method to improve the image quality and the accuracy of dose calculation for cone-beam computed tomography

PurposeTo improve the image quality and accuracy of dose calculation for cone-beam computed tomography (CT) images through implementation of a dual-energy cone-beam computed tomography method (DE-CBCT), and evaluate the improvement quantitatively. MethodsTwo sets of CBCT projections were acquired using the X-ray volumetric imaging (XVI) system on a Synergy (Elekta, Stockholm, Sweden) system with 120kV (high) and 70kV (low) X-rays, respectively. Then, the electron density relative to water (relative electron density (RED)) of each voxel was calculated using a projection-based dual-energy decomposition method. As a comparison, single-energy cone-beam computed tomography (SE-CBCT) was used to calculate RED with the Hounsfield unit–RED calibration curve generated by a CIRS phantom scan with identical imaging parameters. The imaging dose was measured with a dosimetry phantom. The image quality was evaluated quantitatively using a Catphan 503 phantom with the evaluation indices of the reproducibility of the RED values, high-contrast resolution (MTF50%), uniformity, and signal-to-noise ratio (SNR). Dose calculation of two simulated volumetric-modulated arc therapy plans using an Eclipse treatment-planning system (Varian Medical Systems, Palo Alto, CA, USA) was performed on an Alderson Rando Head and Neck (H&N) phantom and a Pelvis phantom. Fan-beam planning CT images for the H&N and Pelvis phantom were set as the reference. A global three-dimensional gamma analysis was used to compare dose distributions with the reference. The average gamma values for targets and OAR were analyzed with paired t-tests between DE-CBCT and SE-CBCT. ResultsIn two scans (H&N scan and body scan), the imaging dose of DE-CBCT increased by 1.0% and decreased by 1.3%. It had a better reproducibility of the RED values (mean bias: 0.03 and 0.07) compared with SE-CBCT (mean bias: 0.13 and 0.16). It also improved the image uniformity (57.5% and 30.1%) and SNR (9.7% and 2.3%), but did not affect the MTF50%. Gamma analyses of the 3D dose distribution with criteria of 1%/1mm showed a pass rate of 99.0–100% and 85.3–97.6% for DE-CBCT and 73.5–99.1% and 80.4–92.7% for SE-CBCT. The average gamma values were reduced significantly by DE-CBCT (p< 0.05). Gamma index maps showed that matching of the dose distribution between CBCT-based and reference was improved by DE-CBCT. ConclusionsDE-CBCT can achieve both better image quality and higher accuracy of dose calculation, and could be applied to adaptive radiotherapy.

A Novel Method of Cone Beam CT Projection Binning Based on Image Registration.

Accurate sorting of beam projections is important in 4D cone beam computed tomography (4D CBCT) to improve the quality of the reconstructed 4D CBCT image by removing motion-induced artifacts. We propose image registration-based projection binning (IRPB), a novel marker-less binning method for 4D CBCT projections, which combines intensity-based feature point detection and trajectory tracking using random sample consensus. IRPB extracts breathing motion and phases by analyzing tissue feature point trajectories. We conducted experiments with two phantom and six patient datasets, including both regular and irregular respirations. In experiments, we compared the performance of the proposed IRPB, Amsterdam Shroud method (AS), Fourier transform-based method (FT), and local intensity feature tracking method (LIFT). The results showed that the average absolute phase shift of IRPB was 3.74 projections and 0.48 projections less than that of FT and LIFT, respectively. AS lost the most breathing cycles in the respiration extraction for the five patient datasets, so we could not compare the average absolute phase shift between IRPB and AS. Based on the peak signal-to-noise ratio (PSNR) of the reconstructed 4D CBCT images, IRPB had 5.08, 1.05, and 2.90 dB larger PSNR than AS, FT, and LIFT, respectively. The average Structure SIMilarity Index (SSIM) of the 4D CBCT image reconstructed by IRPB, AS, and LIFT were 0.87, 0.74, 0.84, and 0.70, respectively. These results demonstrated that IRPB has superior performance to the other standard methods.

Directional sinogram interpolation for motion weighted 4D cone-beam CT reconstruction

The image quality of respiratory sorted four-dimensional (4D) cone-beam (CB) computed tomography (CT) is often limited by streak artifacts due to insufficient projections. A motion weighted reconstruction (MWR) method is proposed to decrease streak artifacts and improve image quality. Firstly, respiratory correlated CBCT projections were interpolated by directional sinogram interpolation (DSI) to generate additional CB projections for each phase and subsequently reconstructed. Secondly, local motion was estimated by deformable image registration of the interpolated 4D CBCT. Thirdly, a regular 3D FDK CBCT was reconstructed from the non-interpolated projections. Finally, weights were assigned to each voxel, based on the local motion, and then were used to combine the 3D FDK CBCT and interpolated 4D CBCT to generate the final 4D image. MWR method was compared with regular 4D CBCT scans as well as McKinnon and Bates (MKB) based reconstructions. Comparisons were made in terms of (1) comparing the steepness of an extracted profile from the boundary of the region-of-interest (ROI), (2) contrast-to-noise ratio (CNR) inside certain ROIs, and (3) the root-mean-square-error (RMSE) between the planning CT and CBCT inside a homogeneous moving region. Comparisons were made for both a phantom and four patient scans. In a 4D phantom, RMSE were reduced by 24.7% and 38.7% for MKB and MWR respectively, compared to conventional 4D CBCT. Meanwhile, interpolation induced blur was minimal in static regions for MWR based reconstructions. In regions with considerable respiratory motion, image blur using MWR is less than the MKB and 3D Feldkamp (FDK) methods. In the lung cancer patients, average CNRs of MKB, DSI and MWR improved by a factor 1.7, 2.8 and 3.5 respectively relative to 4D FDK. MWR effectively reduces RMSE in 4D cone-beam CT and improves the image quality in both the static and respiratory moving regions compared to 4D FDK and MKB methods.

A longitudinal four-dimensional computed tomography and cone beam computed tomography dataset for image-guided radiation therapy research in lung cancer.

To describe in detail a dataset consisting of serial four-dimensional computed tomography (4DCT) and 4D cone beam CT (4DCBCT) images acquired during chemoradiotherapy of 20 locally advanced, nonsmall cell lung cancer patients we have collected at our institution and shared publicly with the research community. As part of an NCI-sponsored research study 82 4DCT and 507 4DCBCT images were acquired in a population of 20 locally advanced nonsmall cell lung cancer patients undergoing radiation therapy. All subjects underwent concurrent radiochemotherapy to a total dose of 59.4-70.2 Gy using daily 1.8 or 2 Gy fractions. Audio-visual biofeedback was used to minimize breathing irregularity during all fractions, including acquisition of all 4DCT and 4DCBCT acquisitions in all subjects. Target, organs at risk, and implanted fiducial markers were delineated by a physician in the 4DCT images. Image coordinate system origins between 4DCT and 4DCBCT were manipulated in such a way that the images can be used to simulate initial patient setup in the treatment position. 4DCT images were acquired on a 16-slice helical CT simulator with 10 breathing phases and 3 mm slice thickness during simulation. In 13 of the 20 subjects, 4DCTs were also acquired on the same scanner weekly during therapy. Every day, 4DCBCT images were acquired on a commercial onboard CBCT scanner. An optically tracked external surrogate was synchronized with CBCT acquisition so that each CBCT projection was time stamped with the surrogate respiratory signal through in-house software and hardware tools. Approximately 2500 projections were acquired over a period of 8-10 minutes in half-fan mode with the half bow-tie filter. Using the external surrogate, the CBCT projections were sorted into 10 breathing phases and reconstructed with an in-house FDK reconstruction algorithm. Errors in respiration sorting, reconstruction, and acquisition were carefully identified and corrected. 4DCT and 4DCBCT images are available in DICOM format and structures through DICOM-RT RTSTRUCT format. All data are stored in the Cancer Imaging Archive (TCIA, http://www.cancerimagingarchive.net/) as collection 4D-Lung and are publicly available. Due to high temporal frequency sampling, redundant (4DCT and 4DCBCT) data at similar timepoints, oversampled 4DCBCT, and fiducial markers, this dataset can support studies in image-guided and image-guided adaptive radiotherapy, assessment of 4D voxel trajectory variability, and development and validation of new tools for image registration and motion management.

Fully automatic segmentation of arbitrarily shaped fiducial markers in cone-beam CT projections

Radio-opaque fiducial markers of different shapes are often implanted in or near abdominal or thoracic tumors to act as surrogates for the tumor position during radiotherapy. They can be used for real-time treatment adaptation, but this requires a robust, automatic segmentation method able to handle arbitrarily shaped markers in a rotational imaging geometry such as cone-beam computed tomography (CBCT) projection images and intra-treatment images. In this study, we propose a fully automatic dynamic programming (DP) assisted template-based (TB) segmentation method. Based on an initial DP segmentation, the DPTB algorithm generates and uses a 3D marker model to create 2D templates at any projection angle. The 2D templates are used to segment the marker position as the position with highest normalized cross-correlation in a search area centered at the DP segmented position. The accuracy of the DP algorithm and the new DPTB algorithm was quantified as the 2D segmentation error (pixels) compared to a manual ground truth segmentation for 97 markers in the projection images of CBCT scans of 40 patients. Also the fraction of wrong segmentations, defined as 2D errors larger than 5 pixels, was calculated. The mean 2D segmentation error of DP was reduced from 4.1 pixels to 3.0 pixels by DPTB, while the fraction of wrong segmentations was reduced from 17.4% to 6.8%. DPTB allowed rejection of uncertain segmentations as deemed by a low normalized cross-correlation coefficient and contrast-to-noise ratio. For a rejection rate of 9.97%, the sensitivity in detecting wrong segmentations was 67% and the specificity was 94%. The accepted segmentations had a mean segmentation error of 1.8 pixels and 2.5% wrong segmentations.

Analysis of Dose Calculation Accuracy in Cone Beam Computed Tomography with Various Amount of Scattered Photon Contamination

Cone-beam computed tomography (CBCT) images have inaccurate CT numbers because of scattered photons. Thus, quantitative analysis of scattered photons that affect an electron density (ED) curve and calculated doses may be effective information to achieve CBCT-based radiation treatment planning. We quantitatively evaluated the effect of scattered photons on the accuracy of dose calculations from a lung image. The Monte Carlo method was used to calculate CBCT projection data, and we made two calibration curves for conditions with or without scattered photons. Moreover, we applied cupping artifact correction and evaluated the effects on image uniformity and dose calculation accuracy. Dose deviations were compared with those of conventional CT in conventional and volumetric intensity modulated arc therapy (VMAT) planning by using γ analysis and dose volume histogram (DVH) analysis. We found that cupping artifacts contaminated the scattered photons, and the γ analysis showed that the dose distribution was most decreased for a scattered photon ratio of 40%. Cupping artifact correction significantly improved image uniformity; therefore, ED curves were near ideal, and the pass rate results were significantly higher than those associated with the scattered photon effect in 65.1% and 78.4% without correction, 99.5% and 97.7% with correction, in conventional and VMAT planning, respectively. In the DVH analysis, all organ dose indexes were reduced in the scattered photon images, but dose index error rates with cupping artifact correction were improved within approximately 10%. CBCT image quality was strongly affected by scattered photons, and the dose calculation accuracy based on the CBCT image was improved by removing cupping artifacts caused by the scattered photons.

Observer Evaluation of a Metal Artifact Reduction Algorithm Applied to Head and Neck Cone Beam Computed Tomography Images

To quantify, through an observer study, the reduction in metal artifacts on cone beam computed tomography (CBCT) images using a projection-interpolation algorithm, on images containing metal artifacts from dental fillings. A projection-interpolation algorithm was applied to CBCT images containing metal artifacts from dental fillings. This technique involved identifying metal regions in individual CBCT projections and interpolating the surrounding values to remove the metal from the projection data. Axial CBCT images were then reconstructed, resulting in a reduction in the streak artifacts produced by the metal. Five radiation oncologists were subsequently asked to rank images (before and after metal artifact reduction) using a modified 5-point Likert scale. The scale consisted of the following: 1, very poor image quality, severe artifacts; 2, poor image quality, major artifacts; 3, moderate image quality, some artifacts; 4, good image quality, limited artifacts; and 5, excellent image quality, no artifacts. The interpolation substitution technique successfully reduced metal artifacts in all cases. From a total of 28 images, the mean Likert score on the original images was 2.0 +/- 0.8, while the mean score on the postartifact reduction images was 3.3 +/- 0.7 (P<0.0001). The mean difference in ranking score between uncorrected and corrected images was 1.4 with a 95% confidence interval (1.2, 1.6). Corrected images had fewer or no streak artifacts compared to their uncorrected counterparts. Artifact correction tended to perform better on patient images with less complex metal objects versus those with multiple large dental fillings. The interpolation substitution is an efficient and effective technique for reducing metal artifacts caused by dental fillings on CBCT images as demonstrated by the statistically significant increase in observer image quality ranking score between corrected and uncorrected images. This technique may be effective in reducing such artifacts in patients with head and neck cancer receiving daily image guided radiation therapy. The long-term goals of this study are to develop a user interface for application of this technique in head and neck image guided radiation therapy, thereby reducing metal artifacts and improving interpretation of CBCT image data.

Effect of anatomical noise on the detectability of cone beam CT images with different slice direction, slice thickness, and volume glandular fraction.

We investigate the effect of anatomical noise on the detectability of cone beam CT (CBCT) images with different slice directions, slice thicknesses, and volume glandular fractions (VGFs). Anatomical noise is generated using a power law spectrum of breast anatomy, and spherical objects with diameters from 1mm to 11mm are used as breast masses. CBCT projection images are simulated and reconstructed using the FDK algorithm. A channelized Hotelling observer (CHO) with Laguerre-Gauss (LG) channels is used to evaluate detectability for the signal-known-exactly (SKE) binary detection task. Detectability is calculated for various slice thicknesses in the transverse and longitudinal planes for 15%, 30% and 60% VGFs. The optimal slice thicknesses that maximize the detectability of the objects are determined. The results show that the β value increases as the slice thickness increases, but that thicker slices yield higher detectability in the transverse and longitudinal planes, except for the case of a 1mm diameter spherical object. It is also shown that the longitudinal plane with a 0.1mm slice thickness provides higher detectability than the transverse plane, despite its higher β value. With optimal slice thicknesses, the longitudinal plane exhibits better detectability for all VGFs and spherical objects.

Cardiac and respiration induced motion of mediastinal lymph node targets in lung cancer patients throughout the radiotherapy treatment course

Background and purposeInvolved mediastinal lymph nodes (LNs) are often included in the radiotherapy target for lung cancer patients. Their motion may differ from the primary tumor motion, possibly undermining the loco-regional control. This study determines the detailed differential target motion throughout the treatment course. Material and methodsTen lung cancer patients with 2–4 fiducial markers implanted in LN targets received IMRT with a daily pre-treatment cone-beam CT (CBCT) scan. Offline, the 3D trajectory of the markers was determined from their projected trajectory in the CBCT projections. Frequency analysis was performed to separate the intrafraction motion into a respiratory and cardiac component. The mean setup error of the markers and the motion range were used to calculate margins required for LN targets when setup is based on soft-tissue match. ResultsRespiration motion was largest in the CC direction and more prominent for more caudal LNs. Cardiac motion was often (73%) largest in the AP direction and tended to be largest for more cranial LNs. Margins for intrafraction motion and daily baseline shifts of LNs were 4.8mm (LR), 6.0mm (CC) and 6.7mm (AP). ConclusionsDetailed mapping showed that LN motion was in general governed by breathing, but some LNs had substantial cardiac induced motion.

Reconstruction of implanted marker trajectories from cone-beam CT projection images using interdimensional correlation modeling.

Cone-beam CT (CBCT) is a widely used imaging modality for image-guided radiotherapy. Most vendors provide CBCT systems that are mounted on a linac gantry. Thus, CBCT can be used to estimate the actual 3-dimensional (3D) position of moving respiratory targets in the thoracic/abdominal region using 2D projection images. The authors have developed a method for estimating the 3D trajectory of respiratory-induced target motion from CBCT projection images using interdimensional correlation modeling. Because the superior-inferior (SI) motion of a target can be easily analyzed on projection images of a gantry-mounted CBCT system, the authors investigated the interdimensional correlation of the SI motion with left-right and anterior-posterior (AP) movements while the gantry is rotating. A simple linear model and a state-augmented model were implemented and applied to the interdimensional correlation analysis, and their performance was compared. The parameters of the interdimensional correlation models were determined by least-square estimation of the 2D error between the actual and estimated projected target position. The method was validated using 160 3D tumor trajectories from 46 thoracic/abdominal cancer patients obtained during CyberKnife treatment. The authors' simulations assumed two application scenarios: (1) retrospective estimation for the purpose of moving tumor setup used just after volumetric matching with CBCT; and (2) on-the-fly estimation for the purpose of real-time target position estimation during gating or tracking delivery, either for full-rotation volumetric-modulated arc therapy (VMAT) in 60 s or a stationary six-field intensity-modulated radiation therapy (IMRT) with a beam delivery time of 20 s. For the retrospective CBCT simulations, the mean 3D root-mean-square error (RMSE) for all 4893 trajectory segments was 0.41 mm (simple linear model) and 0.35 mm (state-augmented model). In the on-the-fly simulations, prior projections over more than 60° appear to be necessary for reliable estimations. The mean 3D RMSE during beam delivery after the simple linear model had established with a prior 90° projection data was 0.42 mm for VMAT and 0.45 mm for IMRT. The proposed method does not require any internal/external correlation or statistical modeling to estimate the target trajectory and can be used for both retrospective image-guided radiotherapy with CBCT projection images and real-time target position monitoring for respiratory gating or tracking.

Metal Artifact Reduction in Cone-Beam Computed Tomography for Head and Neck Radiotherapy.

To evaluate a method for reducing metal artifacts, arising from dental fillings, on cone-beam computed tomography images. A projection interpolation algorithm is applied to cone-beam computed tomography images containing metal artifacts from dental fillings. This technique involves identifying metal regions in individual cone-beam computed tomography projections and interpolating the surrounding values to remove the metal from the projection data. Axial cone-beam computed tomography images are then reconstructed, resulting in a reduction in the streak artifacts produced by the metal. Both phantom and patient imaging data are used to evaluate this technique. The interpolation substitution technique successfully reduced metal artifacts in all cases. Corrected images had fewer or no streak artifacts compared to their noncorrected counterparts. Quantitatively, regions of interest containing the artifacts showed reduced variance in the corrected images versus the uncorrected images. Average pixel values in regions of interest around the metal object were also closer in value to nonmetal regions after artifact reduction. Artifact correction tended to perform better on patient images with less complex metal objects versus those with multiple large dental fillings. The interpolation substitution is potentially an efficient and effective technique for reducing metal artifacts caused by dental fillings on cone-beam computed tomography image. This technique may be effective in reducing such artifacts in patients with head and neck cancer receiving daily image-guided radiotherapy.