Low-dose Cone-beam CT Research Articles

Evaluation of a system for high-accuracy 3D image-based registration of endoscopic video to C-arm cone-beam CT for image-guided skull base surgery.

The safety of endoscopic skull base surgery can be enhanced by accurate navigation in preoperative computed tomography (CT) or, more recently, intraoperative cone-beam CT (CBCT). The ability to register real-time endoscopic video with CBCT offers an additional advantage by rendering information directly within the visual scene to account for intraoperative anatomical change. However, tracker localization error ( ∼1-2 mm ) limits the accuracy with which video and tomographic images can be registered. This paper reports the first implementation of image-based video-CBCT registration, conducts a detailed quantitation of the dependence of registration accuracy on system parameters, and demonstrates improvement in registration accuracy achieved by the image-based approach. Performance was evaluated as a function of parameters intrinsic to the image-based approach, including system geometry, CBCT image quality, and computational runtime. Overall system performance was evaluated in a cadaver study simulating transsphenoidal skull base tumor excision. Results demonstrated significant improvement in registration accuracy with a mean reprojection distance error of 1.28 mm for the image-based approach versus 1.82 mm for the conventional tracker-based method. Image-based registration was highly robust against CBCT image quality factors of noise and resolution, permitting integration with low-dose intraoperative CBCT.

Lung Imaging Data Analysis

Early detection and diagnosis of lung cancer, causing most of cancer-related deaths worldwide, can improve effectiveness of the treatment and increase chances of patients to survive. Comparing to conventional chest radiography, advanced lung imaging modalities, for example, low-dose helical CT, cone-beam CT, and PET (positron emission tomography), together with the progress of image analysis techniques provide the means for detecting smaller pulmonary nodules and at earlier stages. These developments help in diagnosing other diseases and conditions, such as chronic obstructive lung disease, interstitial lung disease, and pulmonary embolism, too.

Low-Dose and Scatter-Free Cone-Beam CT Imaging Using a Stationary Beam Blocker in a Single Scan: Phantom Studies

Excessive imaging dose from repeated scans and poor image quality mainly due to scatter contamination are the two bottlenecks of cone-beam CT (CBCT) imaging. Compressed sensing (CS) reconstruction algorithms show promises in recovering faithful signals from low-dose projection data but do not serve well the needs of accurate CBCT imaging if effective scatter correction is not in place. Scatter can be accurately measured and removed using measurement-based methods. However, these approaches are considered unpractical in the conventional FDK reconstruction, due to the inevitable primary loss for scatter measurement. We combine measurement-based scatter correction and CS-based iterative reconstruction to generate scatter-free images from low-dose projections. We distribute blocked areas on the detector where primary signals are considered redundant in a full scan. Scatter distribution is estimated by interpolating/extrapolating measured scatter samples inside blocked areas. CS-based iterative reconstruction is finally carried out on the undersampled data to obtain scatter-free and low-dose CBCT images. With only 25% of conventional full-scan dose, our method reduces the average CT number error from 250 HU to 24 HU and increases the contrast by a factor of 2.1 on Catphan 600 phantom. On an anthropomorphic head phantom, the average CT number error is reduced from 224 HU to 10 HU in the central uniform area.

SU-E-J-05: Validation of an Iterative Tomosynthesis Algorithm for Low Dose on Board Cone Beam CT Patient Localization.

Cone beam CT (CBCT) is a well established technique to localize patients using bone and soft tissue anatomy. Current protocols are limited to one weekly CBCT due to the considerable imaging dose delivered to the patient. The purpose of this project is to develop and validate a low dose CBCT algorithm to reduce dose and imaging time of current 3D imaging localization procedures using a novel iterative tomosynthesis algorithm to allow daily CBCT for patient positioning and target localization. The algorithm is based on the combination of a tomosynthesis filtered back propagation (TFBP) acquisition geometry algorithm and a maximum likelihood expectation maximization (MLEM) iterative reconstruction. Circular or arc acquisition trajectory, projection number, and angular projection position are optimized according to the anatomical treatment site and region of interest. The TFBP method provides the first 3D image estimate, and the MLEM improves its quality. In this study, we focused on head and neck treatment localization imaging. We studied the performance of our tomosynthesis algorithm imaging resolution on an anthropomorphic head and neck phantom to determine image quality as a function of dose reduction techniques. Reconstructed anatomy shows that a 1/8 dose reduction provides similar image quality and resolution as current CBCT protocols. Seven iterations show an optimal compromise between image quality and reconstruction time. Tomosynthesis images provide digitally reconstructed radiographs with similar resolution and contrast as full CBCT. We verified that the iterative process eliminates phantom images originated by the acquired sparse angular data projections. We developed and validated an iterative algorithm for low dose cone beam CT based on circular or arc tomosynthesis geometries and iterative reconstruction techniques. The algorithm combines the strengths of both techniques to provide a novel low dose method to image patient anatomy for patient positioning and target localization.

TU-E-BRA-08: A Comprehensive Study on the Relationship between Image Quality and Imaging Dose in Low-Dose Cone Beam CT.

To investigate image quality as a function of number of projections and tube load per projection in compressive sensing (CS) based low-dose cone beam CT (CBCT), and achieve optimal low-dose scan protocols in image guided radiation therapy (IGRT). We have performed CS-based CBCT reconstruction with different combinations of number of projections (from 46 to 364) and mAs (from 0.2 to 2.4 mAs/view), which covers the whole clinically relevant range. Image quality is assessed in each case. On this basis, optimal scan protocols are analyzed according to various IGRT applications. Image quality degrades ∼10% when the imaging dose decreases from 400 to 100 total mAs, further ∼10% from 100 to 40 total mAs, and another ∼80% below 40 total mAs. Image quality on iso-low-dose lines at 36.8, 72.6, 109.2 and 145.6 total mAs varies 17.16%, 13.69%, 11.99% and 5.74% in terms RMSE with various scanning protocols. 1) In CS-based CBCT, image quality has little degradation with imaging dose> 100 total mAs. Optimal low-dose scan protocols likely fall in the range of 40-100 total mAs. 2) At a constant low-dose level, the scan protocol that with super sparse views (projection number < 50) is the most challenging case. 3) The optimal scan protocol is the combination of a medium number of projections and a medium level of mAs/view. This is more evident when the dose is ∼72.8 total mAs or below, and when the ROI is a low-contrast or high-resolution object. 4) The clinically acceptable lowest imaging dose level is task dependent. In our study, 72.8mAs is a safe dose level for visualizing low-contrast objects, while 12.2 total mAs is sufficient for detecting high-contrast objects of diameter greater than 3 mm. This work is supported in part by NIH (1R01CA154747-01), Varian Medical Systems through a Master Research Agreement, and the Thrasher Research Fund.

A comprehensive study on the relationship between the image quality and imaging dose in low-dose cone beam CT

While compressed sensing (CS)-based algorithms have been developed for the low-dose cone beam CT (CBCT) reconstruction, a clear understanding of the relationship between the image quality and imaging dose at low-dose levels is needed. In this paper, we qualitatively investigate this subject in a comprehensive manner with extensive experimental and simulation studies. The basic idea is to plot both the image quality and imaging dose together as functions of the number of projections and mAs per projection over the whole clinically relevant range. On this basis, a clear understanding of the tradeoff between the image quality and imaging dose can be achieved and optimal low-dose CBCT scan protocols can be developed to maximize the dose reduction while minimizing the image quality loss for various imaging tasks in image-guided radiation therapy (IGRT). Main findings of this work include (1) under the CS-based reconstruction framework, image quality has little degradation over a large range of dose variation. Image quality degradation becomes evident when the imaging dose (approximated with the x-ray tube load) is decreased below 100 total mAs. An imaging dose lower than 40 total mAs leads to a dramatic image degradation, and thus should be used cautiously. Optimal low-dose CBCT scan protocols likely fall in the dose range of 40–100 total mAs, depending on the specific IGRT applications. (2) Among different scan protocols at a constant low-dose level, the super sparse-view reconstruction with the projection number less than 50 is the most challenging case, even with strong regularization. Better image quality can be acquired with low mAs protocols. (3) The optimal scan protocol is the combination of a medium number of projections and a medium level of mAs/view. This is more evident when the dose is around 72.8 total mAs or below and when the ROI is a low-contrast or high-resolution object. Based on our results, the optimal number of projections is around 90 to 120. (4) The clinically acceptable lowest imaging dose level is task dependent. In our study, 72.8 mAs is a safe dose level for visualizing low-contrast objects, while 12.2 total mAs is sufficient for detecting high-contrast objects of diameter greater than 3 mm.

Model-based Reconstruction of Objects with Inexactly Known Components.

Because tomographic reconstructions are ill-conditioned, algorithms that incorporate additional knowledge about the imaging volume generally have improved image quality. This is particularly true when measurements are noisy or have missing data. This paper presents a general reconstruction framework for including attenuation contributions from objects known to be in the field-of-view. Components such as surgical devices and tools may be modeled explicitly as part of the attenuating volume but are inexactly known with respect to their locations poses, and possible deformations. The proposed reconstruction framework, referred to as Known-Component Reconstruction (KCR), is based on this novel parameterization of the object, a likelihood-based objective function, and alternating optimizations between registration and image parameters to jointly estimate the both the underlying attenuation and unknown registrations. A deformable KCR (dKCR) approach is introduced that adopts a control point-based warping operator to accommodate shape mismatches between the component model and the physical component, thereby allowing for a more general class of inexactly known components. The KCR and dKCR approaches are applied to low-dose cone-beam CT data with spine fixation hardware present in the imaging volume. Such data is particularly challenging due to photon starvation effects in projection data behind the metallic components. The proposed algorithms are compared with traditional filtered-backprojection and penalized-likelihood reconstructions and found to provide substantially improved image quality. Whereas traditional approaches exhibit significant artifacts that complicate detection of breaches or fractures near metal, the KCR framework tends to provide good visualization of anatomy right up to the boundary of surgical devices.

Fast compressed sensing-based CBCT reconstruction using Barzilai-Borwein formulation for application to on-line IGRT

Compressed sensing theory has enabled an accurate, low-dose cone-beam computed tomography (CBCT) reconstruction using a minimal number of noisy projections. However, the reconstruction time remains a significant challenge for practical implementation in the clinic. In this work, we propose a novel gradient projection algorithm, based on the Gradient-Projection-Barzilai-Borwein formulation (GP-BB), that handles the total variation (TV)-norm regularization-based least squares problem for the CBCT reconstruction in a highly efficient manner, with speed acceptable for routine use in the clinic. CBCT is reconstructed by minimizing an energy function consisting of a data fidelity term and a TV-norm regularization term. Both terms are simultaneously minimized by calculating the gradient projection of the energy function with the step size determined using an approximate Hessian calculation at each iteration, based on the Barzilai-Borwein formulation. To speed up the process, a multiresolution optimization is used. In addition, the entire algorithm was designed to run with a single graphics processing unit (GPU) card. To evaluate the performance, the Shepp-Logan numerical phantom, the CatPhan 600 physical phantom, and a clinically-treated head-and-neck patient were acquired from the TrueBeam™ system (Varian Medical Systems, Palo Alto, CA). For each scan, in total, 364 projections were acquired in a 200° rotation. The imager has 1024 × 768 pixels with 0.388 × 0.388-mm resolution. This was down-sampled to 512 × 384 pixels with 0.776 × 0.776-mm resolution for reconstruction. Evenly spaced angles were subsampled and used for varying the number of projections for the image reconstruction. To assess the performance of our GP-BB algorithm, we have implemented and compared with three compressed sensing-type algorithms, the two of which are popular and published (forward-backward splitting techniques), and the other one with a basic line-search technique. In addition, the conventional Feldkamp-Davis-Kress (FDK) reconstruction of the clinical patient data is compared as well. In comparison with the other compressed sensing-type algorithms, our algorithm showed convergence in ≤30 iterations whereas other published algorithms need at least 50 iterations in order to reconstruct the Shepp-Logan phantom image. With the CatPhan phantom, the GP-BB algorithm achieved a clinically-reasonable image with 40 projections in 12 iterations, in less than 12.6 s. This is at least an order of magnitude faster in reconstruction time compared with the most recent reports utilizing GPU technology given the same input projections. For the head-and-neck clinical scan, clinically-reasonable images were obtained from 120 projections in 34-78 s converging in 12-30 iterations. In this reconstruction range (i.e., 120 projections) the image quality is visually similar to or better than the conventional FDK reconstructed images using 364 projections. This represents a dose reduction of nearly 67% (120∕364 projections) while maintaining a reasonable speed in clinical implementation. In this paper, we proposed a novel, fast, low-dose CBCT reconstruction algorithm using the Barzilai-Borwein step-size calculation. A clinically viable head-and-neck image can be obtained within ∼34-78 s while simultaneously cutting the dose by approximately 67%. This makes our GP-BB algorithm potentially useful in an on-line image-guided radiation therapy (IGRT).

High-resolution cone-beam computed tomography: a potential tool to improve atraumatic electrode design and position

Conclusions: Flat-panel cone-beam computed tomography (CBCT) is able to assess the trajectory of the implanted cochlear implant (CI) array. This is essential to determine specific effects of electrode design and surgical innovations on outcomes in cochlear implantation. CBCT is a non-invasive approach yielding similar data to histopathological analyses, with encouraging potential for use in surgical, clinical and research settings. Objectives: To examine the fidelity of CBCT imaging and custom 3D visualization in characterizing CI insertion in comparison to gold standard, histopathological examination. Methods: Eleven human temporal bones were implanted with the ‘Straight Research Array’ (SRA). Post-insertion, they were imaged with a prototype mobile C-arm for intraoperative CBCT. Post-acquisition processing of low-dose CBCT images produced high-resolution 3D volumes with sub-millimetre spatial resolution (isotropic 0.2 mm3 voxels). The bones were resin impregnated and sectioned for light microscopic examination. Dimensional electrode characteristics visible in section images were compared with corresponding CBCT images by independent observers. Results: Overall, CBCT demonstrated adequate resolution to detect: 1) scala implanted; 2) kinking; 3) number of intracochlear contacts; 4) appropriate ascension of the array; and overall confirms ideal insertion. CBCT did not demonstrate adequate resolution to detect reversal of electrode contacts or basilar membrane rupture.

Antiscatter grids in mobile C-arm cone-beam CT: Effect on image quality and dose

X-ray scatter is a major detriment to image quality in cone-beam CT (CBCT). Existing geometries exhibit strong differences in scatter susceptibility with more compact geometries, e.g., dental or musculoskeletal, benefiting from antiscatter grids, whereas in more extended geometries, e.g., IGRT, grid use carries tradeoffs in image quality per unit dose. This work assesses the tradeoffs in dose and image quality for grids applied in the context of low-dose CBCT on a mobile C-arm for image-guided surgery. Studies were performed on a mobile C-arm equipped with a flat-panel detector for high-quality CBCT. Antiscatter grids of grid ratio (GR) 6:1-12:1, 40 lp∕cm, were tested in "body" surgery, i.e., spine, using protocols for bone and soft-tissue visibility in the thoracic and abdominal spine. Studies focused on grid orientation, CT number accuracy, image noise, and contrast-to-noise ratio (CNR) in quantitative phantoms at constant dose. There was no effect of grid orientation on possible gridline artifacts, given accurate angle-dependent gain calibration. Incorrect calibration was found to result in gridline shadows in the projection data that imparted high-frequency artifacts in 3D reconstructions. Increasing GR reduced errors in CT number from 31%, thorax, and 37%, abdomen, for gridless operation to 2% and 10%, respectively, with a 12:1 grid, while image noise increased by up to 70%. The CNR of high-contrast objects was largely unaffected by grids, but low-contrast soft-tissues suffered reduction in CNR, 2%-65%, across the investigated GR at constant dose. While grids improved CT number accuracy, soft-tissue CNR was reduced due to attenuation of primary radiation. CNR could be restored by increasing dose by factors of ~1.6-2.5 depending on GR, e.g., increase from 4.6 mGy for the thorax and 12.5 mGy for the abdomen without antiscatter grids to approximately 12 mGy and 30 mGy, respectively, with a high-GR grid. However, increasing the dose poses a significant impediment to repeat intraoperative CBCT and can cause the cumulative intraoperative dose to exceed that of a single diagnostic CT scan. This places the mobile C-arm in the category of extended CBCT geometries with sufficient air gap for which the tradeoffs between CNR and dose typically do not favor incorporation of an antiscatter grid.

Effects of the penalty on the penalized weighted least-squares image reconstruction for low-dose CBCT

Statistical iterative reconstruction (SIR) algorithms have shown potential to substantially improve low-dose cone-beam CT (CBCT) image quality. The penalty term plays an important role in determining the performance of SIR algorithms. In this work, we quantitatively evaluate the impact of the penalties on the performance of a statistics-based penalized weighted least-squares (PWLS) iterative reconstruction algorithm for improving the image quality of low-dose CBCT. Three different edge-preserving penalty terms, exponential form anisotropic quadratic (AQ) penalty (PWLS-Exp), inverse square form AQ penalty (PWLS-InverseSqr) and total variation penalty (PWLS-TV), were compared against the conventional isotropic quadratic form penalty (PWLS-Iso) using both computer simulation and experimental studies. Noise in low-dose CBCT can be substantially suppressed by the PWLS reconstruction algorithm and edges are well preserved by both AQ- and TV-based penalty terms. The noise-resolution tradeoff measurement shows that the PWLS-Exp exhibits the best spatial resolution of all the three anisotropic penalty terms at matched noise level for reconstructing high-contrast objects. For the reconstruction of low-contrast objects, the TV-based penalty outperforms the AQ-based one with better resolution preservation at matched noise levels. Different penalty terms may be used for better edge preservation at different targeted contrast levels.

SU-E-J-04: Half-Fan-Based Intensity-Weighted Region-of-Interest Imaging for Low-Dose Cone-Beam CT

Purpose: To reduce imaging radiation dose to the patient in cone-beam CT (CBCT) for image-guided radiation therapy via intensity-weighted region-of-interest (IWROI) imaging with a half-fan geometry. Methods: An intensity-weighting (IW) filter made of copper was mounted on the X-ray tube unit of the on-board imager (OBI) for CBCT data acquisition. Since a half-fan full-scan mode is the choice of scanning for most treatment sites including the chest and the abdomen due to its enlarged field-of-view (FOV), the half-fan scan mode has been used in this study. Accordingly, the IW filter was placed asymmetrically to cover outer part of the FOV. As a result, the region corresponding to the outer FOV was illuminated by the filtered beam during the scan. By sacrificing the image quality of the outer ROI-region, one can reduce the overall imaging radiation dose to the patient dramatically. A humanoid abdomen phantom was used for the IWROI imaging experiment. Both the Feldkamp-Davis-Kress (FDK) and the chord- based backprojection-filtration (BPF) algorithms were used for image reconstruction, and the results were compared. Correction of image artifacts caused by the edge of filter and the heterogeneity in beam-quality was also made. Results: FDK algorithm produced images with artifacts when truncated data were used, whereas the BPF algorithm was capable of reconstructing exact ROI images without truncation artifacts from the truncated cone-beam data. Dosimetric measurements are in progress to assess quantitative evaluation of imaging dose reduction. In addition, a feasibility study of image registration using the ROI images obtained by the proposed method is also going to be presented. Conclusions: The proposed half-fan-based IWROI imaging technique can be a valuable option for CBCT in IGRT applications, considering the substantial radiation dose imposed by the repeated use of conventional CBCT.

SU-E-J-07: A Preliminary Study on Optimal Dose-Allocation Parameters for Low-Dose Cone-Beam CT

Purpose: Cone-beam CT (CBCT) is widely used for providing image guidance in radiotherapy and interventional procedures. Due to the patient safety concern involved in repetitive CBCT scans, significant effort has been devoted to possibly lowering imaging dose in CBCT. For a given total dose, it is also important to investigate how image quality can be affected by dose allocations over projection views and by image-reconstruction algorithms. In this work, we investigate quantitatively how image quality changes resulted from different combinations of dose-allocation parameters and some existing reconstruction algorithms. Methods: We performed simulation studies by using a numerical phantom containing structures ofdifferent contrast levels. We also acquired real data of a Catphan phantom (The Phantom Laboratory, Salem, NY) by using the on-board imaging system (Varian Medical Systems, Palo Alto, CA). At three different total dose levels, we allocated each of them to different numbers of views ranging from 120 to 650. For each allocation scheme we applied the FDK and ASD-POCS algorithms to obtain reconstructed images. A set of quantitative metrics were used to evaluate image quality based on relevant tasks. Results: Preliminary results showed that for total dose levels under study, both FDK and ASD-POCS algorithms yield images with comparable quality when a large number of views are considered and that images reconstructed by the ASD-POCS from smaller number of views generally exhibit higher quality. Overall, for each given total dose level the ASD-POCS algorithm yields images of comparable or higher quality than does the FDK algorithm. Conclusions: We demonstrated that CBCT image quality can be optimized for a fixed total dose by choosing an appropriate combination of dose- allocation parameters and reconstruction algorithm. This finding may potentially be used for improving current CBCT image quality and for designing innovative, low-dose CBCT imaging protocols.

GPU-based fast low-dose cone beam CT reconstruction via total variation

X-ray imaging dose from serial Cone-beam CT (CBCT) scans raises a clinical concern in most image guided radiation therapy procedures. The goal of this paper is to develop a fast GPU-based algorithm to reconstruct high quality CBCT images from undersampled and noisy projection data so as to lower the imaging dose. The CBCT is reconstructed by minimizing an energy functional consisting of a data fidelity term and a total variation regularization term. We develop a GPU-friendly version of a forward-backward splitting algorithm to solve this problem. A multi-grid technique is also employed. We test our CBCT reconstruction algorithm on a digital phantom and a head-and-neck patient case. The performance under low mAs is also validated using physical phantoms. It is found that 40 x-ray projections are sufficient to reconstruct CBCT images with satisfactory quality for clinical purposes. Phantom experiments indicate that CBCT images can be successfully reconstructed under 0.1 mAs/projection. Comparing with the widely used head-and-neck scanning protocol of about 360 projections with 0.4 mAs/projection, an overall 36 times dose reduction has been achieved. The reconstruction time is about 130 sec on an NVIDIA Tesla C1060 GPU card, which is estimated ∼ 100 times faster than similar regularized iterative reconstruction approaches.

GPU-based Fast Low Dose Cone Beam CT Reconstruction via Total Variation

Cone-beam CT (CBCT) has been widely used in image guided radiation therapy (IGRT) to acquire updated volumetric anatomical information before treatment fractions for accurate patient alignment purpose. However, the excessive x-ray imaging doses (a few c Gy per scan) delivered to patients from serial CBCT scans raises a clinical concern in most IGRT procedures. This fact has greatly limited exploitation of IGRT's maximal potential. The excessive imaging dose can be effectively reduced by reducing the number of x-ray projections and/or lowering mAs levels in a CBCT scan.

High Quality and Low Dose Cone-beam CT Imaging with Anisotropic Regularized FDK Reconstruction Algorithm

High Quality and Low Dose Cone-beam CT Imaging with Anisotropic Regularized FDK Reconstruction Algorithm

Sci-Fri PM: Delivery - 12: Performance of Two Automated Image Guidance Techniques Employing Low Dose CBCT

Image‐guidedradiotherapy(IGRT) is becoming the standard treatment for prostate cancer. One approach employs a linear accelerator‐mounted, cone‐beam computed tomography(CBCT) system to acquire 3D images at treatment. Typically, radiation therapists manually register such images to the planning CT to determine couch shifts, thereby ignoring anatomical rotations and deformations. Furthermore, CBCT systems deliver significant imagingdoses over long fractionation schedules. Therefore, we continue developing image guidance (IG) techniques relying on automatic registration and low doseCBCTimages. Our “global” method computes couch corrections while the “local” variant provides a deformable transformation that can be used to adapt the original plan. Previous validation with Varian's On‐board Imager (OBI v1.3) showed that IG error is maintained despite reducing the mAs to 15% of the standard 1300. Recent improvements in OBI v1.4 result in similar image quality at 680 mAs (“pelvis” mode). Additionally, “pelvis spotlight” mode was introduced with additional lateral collimation and 720 mAs employed over 200 degrees. Retesting showed that global IG error is 3.5 ±1.0 mm irrespective of the OBI version down to 10% of the standard dose. Local IG required 20% of the standard dose to achieve 1.8 ± 0.6 mm accuracy with OBI v1.4 pelvis, while the 2.0 ± 0.5 mm error was maintained down to 15% with OBI v1.3 and v1.4 spotlight. In absolute terms, the dose savings achieved by our IG methods are cumulative with those offered by the upgrade. Our local IG technique has great potential to significantly improve the precision of radiation therapy.

Automatic image guidance for prostate IMRT using low dose CBCT

Varian's On-Board Imager is a linac-integrated cone-beam CT (CBCT) system used at the authors' institution to acquire images prior to delivering each fraction of prostate intensity modulated radiotherapy. The images are used to determine a couch shift that realigns the tumor with the position obtained in the planning CT. However, this manual image-guided radiotherapy (IGRT) technique is operator dependent, time consuming, offers limited degrees of freedom, and requires significant imaging dose over the course of treatment. To overcome these problems, the authors propose two fully automatic IGRT techniques that require significantly less imaging dose. Dose is reduced by lowering the x-ray tube mA s during CBCT acquisition at the cost of increasing image noise. In "forward" IGRT, the CBCT image is automatically registered to the planning CT to obtain the necessary couch shift. The "reverse" technique offers additional degrees of freedom as it involves nonrigid registration of the planning CT to the CBCT. Both techniques were evaluated using images of an anthropomorphic phantom with simulated motion and by retrospectively analyzing data from ten prostate cancer patients. IGRT error for the phantom data at 100% relative imaging dose was 8.2 +/- 3.7, 3.5 +/- 1.2,, and 2.1 +/- 0.6 mm for setup only, forward, and reverse techniques, respectively. For patient images acquired at 100% relative imaging dose, the errors were 5.4 +/- 1.7, 5.0 +/- 1.6, 5.0 +/- 2.0, and 4.0 +/- 1.6 mm for setup only, manual forward (performed clinically), automatic forward, and reverse IGRT, respectively. Furthermore, imaging dose could be reduced to 20% without a significant loss in image guidance accuracy. The presented image guidance methods are accurate while requiring only 20% of the standard imaging dose. The combination of low dose, automation, and accuracy enables frequent corrections during treatment, possibly leading to reduced margins and improved treatment outcomes.

SU-GG-I-77: Quality Control Management of Low-Dose Cone Beam CT (CBCT) Dental and Eye &amp; Ear Scanners

Purpose: The use of low‐dose CBCTscanners in dental and eye&ear clinics is becoming very popular. Due to limited literature and guidance on the quality control (QC) management for these units, we investigate the need for a systematic approach to QC for these special scanners.Methods and Materials: QC that included image quality tests, radiation safety checks and dosimetry measurements has been performed for three different CBCT dental scanners (XORAN‐miniCAT, i‐CAT, ILUMA). The tests were based on manufacturer provided phantoms and they included: uniformity and noise (water in a plastic bowl was used as phantom for this test), high contrast and linearity, spatial resolution and image artifacts. For all three scanners, predefined scanning protocols are selected by the manufacturer in order to run the specific tests. For dosimetry measurements, the standard head CTDI PMMA phantom was used, along with calibrated CTDI ion chamber and electrometer. Results: The i‐CAT and MiniCAT passed all the image quality tests, during the first QC testing. Spatial resolution: 14 lp/mm was visible for the i‐CAT and 16 lp/mm for the MiniCAT. High contrast and linearity: both scanners measured within the expected range and showed linearity with a correlation coefficient of 0.999. Uniformity and noise: both scanners satisfied the required ranges by the manufacturer. For the ILUMA scanner the manufacturer was contacted to remotely adjust the appropriate parameters in the reconstruction software in order to satisfy the required tolerances for the tests performed. The dose measurements were: CTDIw=3.5–5.5 mGy for all scanners.Conclusions: We have seen that these low‐dose systems have the appropriate image quality for dental applications. The dose levels are much lower than in conventional adult CT scanning protocols (i.e., 58mGy for typical sinus scans). Perhaps a more systematic QC approach for these systems will be necessary to be developed in the near future.

TH‐C‐BRA‐03: GPU‐Based Cone Beam CT Reconstruction

Cone‐beam CT (CBCT) has been widely used in image guided radiation therapy (IGRT) to acquire updated volumetric anatomical information before treatment fractions for accurate patient alignment purpose. However the excessive x‐ray imaging doses (a few cGy per scan) delivered to patients from serial CBCT scans raise a clinical concern in most IGRT procedures. This fact has greatly limited exploitation of IGRT's maximal potential. The imaging dose can be effectively reduced by reducing the number of x‐ray projections and/or lowering mAs levels in a CBCT scan. The image quality reconstructed from conventional FDK‐type algorithms however will be highly degraded. Recently total variation (TV) method has demonstrated its ability to reconstruct CBCT images from a few number of noisy x‐ray projections. Nonetheless such a method can hardly be applied in real clinical environments due to its long computational time (a few hours). It is highly desirable to develop a fast reconstruction scheme to obtain high quality CBCT images from undersampled and noisy projection data so as to lower the imaging dose.Utilizing GPU to speed up the computationally intensive tasks in CBCT reconstruction problems has drawn a lot of attention recently. In this talk GPU‐based CBCT reconstruction algorithms will be reviewed with an emphasis on an iterative CBCT reconstruction algorithm via TV regularization. We have recently developed a GPU‐friendly version of the forward‐backward splitting algorithm to solve the TV‐based reconstruction problem. Multi‐grid technique is also employed. It is found that 40 x‐ray projections are sufficient to reconstruct CBCT images with satisfactory quality for IGRT patient alignment purpose. Phantom studies indicate that CBCT images can be successfully reconstructed with our algorithm under as low as 0.1 mAs/projection level. Comparing with currently widely used full‐fan head‐and‐neck scanning protocol of about 360 projections with 0.4 mAs/projection it is estimated that an overall 36 times dose reduction has been achieved. Moreover the reconstruction time is about 130 sec on an NVIDIA Tesla C1060 GPU card which is estimated ∼100 times faster than similar iterative reconstruction approaches. The high computational efficiency and satisfactory image quality make the iterative low dose CBCT reconstruction approach feasible in real clinical environments.Learning Objectives:1. Understand basic concepts of GPU‐based CBCT reconstruction.2. Understand main challenges in GPU‐based iterative CBCT reconstruction approach and how an iterative CBCT reconstruction problem is solved on GPU.Conflict of Interest: The research presented here is partially supported by NVIDIA.