Reduce Imaging Dose Research Articles

SU‐E‐J‐57: Clinical Protocol for DTS‐Based APBI Setup: Optimal Data Acquisition, Reconstruction and Registration Parameters Using Varian DTS Software

Purpose: Digital tomosynthesis (DTS) was evaluated as an alternative to CBCT for minimizing possibility of collisions and reducing imaging dose. While feasibility of DTS was demonstrated for APBI patient setup, clinical implementation has not been optimized for this technique. This work characterizes data acquisition/registration parameters and establishes clinical protocol for accurate setup using: Varian OBI system for data acquisition; and non‐clinical Varian DTS software for DTS reconstruction/registration for APBI patient setup. Methods: Backprojection‐and‐deblurring algorithms were used for DTS volume reconstructions. DTS volume registrations were done manually and automatically (cross‐correlation). Subsequent triangulation on two short DTS arcs was done to improve registration accuracy. Software performance was evaluated on a breast phantom and nine breast cancer patients, under an IRB‐approved protocol. Parameters investigated include arc lengths, arc orientations, number of arcs, reconstruction slice spacing and other limiting factors relevant to clinical practice. Shifts determined from the registration of DTS volumes were compared to the shifts based on registration between planning CT and CBCT. The difference between these shifts was used to evaluate the software performance and accuracy. The findings were quantified and optimal parameters for clinical use of DTS technique were determined. Results: At least two arcs were necessary for accurate setup evaluation. Registration accuracy of 2 mm was achieved when reconstruction arc length was > 5 deg for clips with HU>1000; larger arc length (> 8 deg) was required for low HU clips. Optimal arc separation was found to be > 20 deg. Optimal arc length was determined to be 8–10 deg. No dependence on DTS slice spacing was found. Time required for DTS reconstruction was 10s– 45 s and it was less than 20s for registration. Conclusions: Optimal data acquisition/registration parameters were determined for DTS imaging utilized for APBI patient setup, and performance of the software was objectively quantified.This study is supported by grant from Varian Medical Systems Inc. and Kayes grant

SU‐C‐301‐04: Development of Iterative Image Reconstruction Algorithm for TBCT System

Purpose: Tetrahedron Beam Computed Tomography (TBCT) circumvents some problems of cone beam CT (CBCT) but still shares the same approximate reconstruction artifact with FDK algorithm. Recently, iterative image reconstruction has been widely employed in diagnostic CT scanners in order to suppress noise and reduce imaging dose. In this study we developed an iterative TBCT image reconstruction algorithm which is able to mitigate the cone beam reconstruction artifact as well as reduce image noise. Methods: Simultaneous algebraic reconstruction technique (SART) image reconstruction algorithms were developed based on our TBCT benchtop geometry. The algorithms were tested using both numerical and physical phantoms. The projection matrix was calculated using a distance driven method. Noise levels in reconstructed images were quantified. The approximate image reconstruction artifact at larger cone angle was evaluated. Results: With the same numerical and real scanned projection data, SART algorithm produces similar spatial resolution as the FDK algorithm. The cone artifact was significantly reduced as compared with FDK algorithm. The noise levels were reduced 16–20% by the iterative algorithm at different regions of the images. Conclusions: Iterative reconstruction algorithm further improves the image quality of the TBCT system. TBCT system with SART image reconstruction algorithm potentially may be used as a mobile CT scanner for diagnostics.This work is partially supported by NIH grant 1R21CA130330‐01A1 and DOD Prostate Cancer Research Program W81XWH‐07‐0083.

TH-E-110-03: Simultaneous Acquisition of Scatter and Image Data in CBCT Using a Novel Half Beam Blocker Method and a FDK Based Reconstruction Algorithm

Purpose: We propose a half blocker‐based approach, in conjunction with a Feldkamp‐Davis‐Kress (FDK) algorithm, to correct scatter‐induced shading artifacts by simultaneously acquiring image and scatter information from a single‐rotation CBCT scan. Methods: A custom beam blocker, comprising of finely spaced lead strips, was mounted to the kV x‐ray source of the Varian TrueBeam OBI system in a novel manner that enables imagedata acquisition on one side of the projection data and scatter data measurement on the other half side. Using the scatter distributions on strips, interpolation and extrapolation are applied to arrive at patient specific scatter information for the CBCT scan. The estimated scatter is subtracted from the image data of projection image acquired at the opposite view. To suppress the noise level produced by geometric errors between two opposed projections and interpolated scatter information, total variation regularization is applied by the minimization procedure based on the steepest gradient decent optimization. With half regions of all projections where subtraction and regularization steps are completed, a FDK algorithm based on cosine weighting function is performed to reconstructCBCT volume. The experimental studies using Catphan504 phantom were carried out to evaluate the performance of the proposed scheme. Results: The scatter‐ induced shading artifacts were markedly suppressed in CBCT using the proposed scheme. Compared with CBCT without a blocker, the mean relative error and CT number errors in the regions of interest were significantly reduced to 2% and less than 20. Also, the proposed approach showed the contrast‐to‐noise ratio with spatial resolution comparable to imagesreconstructed with scatter‐free projections acquired from narrow x‐ ray collimation. Conclusions: A half blocker‐based FDK reconstruction algorithm has been established. The proposed scheme simultaneously reduces imaging dose at shaded regions and leads to complete volumetric information from current CBCT acquisition protocol without additional requirements such as prior images, dual scans, or moving strips. This work was supported in part by Mid‐career Researcher Program (2009‐ 0085999) through NRF grant funded by the MEST and in part by the Industrial Strategic Technology Development Program (10035495) funded by the Ministry of Knowledge Economy (MKE, Korea).

SU‐E‐I‐29: A Prior Information Based Total‐Variation Digital Tomosynthesis Reconstruction Algorithm

Purpose: To develop a total‐variation (TV) based compressive sensing image reconstruction algorithm using a set of limited‐angle projections by applying a prior image information to enhance the image quality and anatomic information of current Four‐dimensiona Digital Tomosynthesis (4D‐DTS). In the iterative algorithm, both TV regularization and Bspline deformation field are included to accurately reconstruct 4D‐DTS images in order to reduce imaging dose. Methods: For 4D Cone Beam Computed Tomography (4D‐CBCT), images of different phases share similar anatomical struture, and their difference can be used as sparseness prior in the 4D‐DTS reconstruction. The Bspline tensor transforms the reference image to fit the target image, and is regulated by TV penalty terms in the cost function of the unconstrained optimization problem. Nonlinear conjugate gradient method is applied to solve the unconstrained problem. Results: Several phase pairs of 4D‐CBCT are used examples. With voxel per region sets 50, the algorithm can have the most similarity with the target image with the fastest convergence. By decreasing Bspline resolution, the deformation will be become more flexible while losing some accuracy of registration. The similarity between target image and resulted image can be tuned by regularization factor, which will enable us to determine how much additional information is needed to build the new image volume. The integrated built CPU and GPU platform provides the acceleration tools of forward/backward projection and Bspline coefficients calculation for large‐scale 4D‐CBCT data in the iteration process, which is 100 times faster than using only software method. Conclusions: The performance of the algorithm is determined by two built‐in parameters in the algorithm: Bspline Resolution and Regulization Factor, whose tuning can favor different edge and resolution performances or fidelity and similarity to the target measurements, and also determine the flexibility and accuracy during the registration.Research sponsored by Varian Medical System.

TH-E-220-09: Dose Reduction in X-Ray Fluoroscopic Tracking via Online Exposure Modulation

Purpose: A growing class of complex X-ray fluoroscopy guided procedures, particularly in interventional cardiology, neuroradiology, and in real-time tumor-tracking radiotherapy and radiosurgery involve long treatment durations. There is increasing concern regarding the amount of imaging dose delivered to the patient in these procedures. Recently, a method has been proposed for modulating imaging parameters using feedback of tracking precision. We evaluate such a method on respiratory motion data in the context of tracking a fiducial under X-ray fluoroscopy and present an online framework for modulating exposure to reduce imaging dose. Methods: A Teflon sphere (1.5mm in diameter, 1000HU) was imaged at tube currents ranging from 0.5 mA to 0.9mA at a fixed energy of 100 kVp. The images were acquired on a Varian Paxscan 4030A (2048×1536) under the kV imaging geometry typically found on kV enabled medical linear accelerator systems (1000 mm source to axis distance, 1550 mm source to detector distance). This set of images was then used to generate motion sequences using published respiratory motion data, which were then composited to include a regions of high and low noise. The sphere was then tracked in these images using a particle filter. Tracking uncertainty from the particle filter was used to modulate the tube current such that the desired operating tracking precision was maintained while minimizing the imaging dose used. Performance was assessed using entrance surface exposure and mean squared error as metrics. An online framework for tracking objects of interested is developed that modulates the tube current in near real time. Results: Comparison of the exposure modulation framework with a similar system employing fixed exposure reveals a dose savings of up to 27.4% when using an operating uncertainty of 0.2 mm. Conclusions: This work presents a near real-time framework with a potential for dose reduction in X- ray fluoroscopic tracking procedures.

SU‐E‐I‐38: Constrained ‐ Total ‐ Variation ‐ Minimization ‐ Based Image Reconstruction in Breast CT

Purpose: Current breast‐CT prototypes acquire data at a large number of views because analytical algorithms such as FDK are used. Constrained‐ total‐variation‐minimization‐based algorithms, however, have the potential to reconstruct images from data collected at a substantially lower number of views, thus further reducing imaging dose to patients. In this study, we investigate and compare reconstructions from data collected in breast‐CT patient studies with both FDK and constrained‐TV‐minimization‐based algorithms. Methods: In breast CT, a small imaging dose has to been distributed among a large number of views required by analytic algorithms, which results in a low signal‐to‐noise ratio (SNR) level of the data. Reconstruction from low‐SNR data is challenging for analytic and, in particular, iterative algorithms such as constrained‐TV‐minimization‐based algorithms, which often leads to artifacts such as blocky appearance or salt‐ and‐pepper artifact. We have developed a constrained‐TV‐minimization algorithm (ASD‐POCS) and carefully implemented for reconstruction from low‐SNR breast‐CT data. In this work, we investigate image reconstruction using ASD‐POCS algorithm from breast‐CT patient data acquired in a clinical trial carried out at UC‐Davis. For each study, data were acquired at 500 views over 360 degrees with a circular‐cone‐beam configuration. We also created data sets that are subsets of the 500‐view data. Images were reconstructed from the 500‐view and created data sets, using both FDK and ASD‐POCS algorithms. Results: The results of our study suggest that the ASD‐POCS algorithm may yield improved images, depending on data quantitative and evaluation metrics, over the FDK algorithm. For example, the contrast‐to‐noise ratios in ASD‐POCS images are generally higher than that in FDK images. For images with calcifications, this means possibly higher calcifications contrast. Conclusions: Our preliminary results suggest that the proposed technique can potentially improve image quality of breast CT. The proposed algorithm can further reduce total imaging dose in breast CT by reducing the number of views.

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.

WE‐A‐301‐06: Adaptive Prior Image Constrained Compressed Sensing‐Based CBCT Reconstruction Algorithm

Purpose: Cone‐beam CT (CBCT) images are acquired repeatedly during a course of radiation therapy and a natural question to ask is whether CBCT images obtained earlier in the process can be utilized as prior knowledge to reduce patient imaging dose in subsequent scans. The purpose of this work is to develop an adaptive prior image constrained compressed sensing (APICCS) method to solve this problem. Methods: The smoothed prior images are utilized as an initial guess and are incorporated into the objective function under the PICCS framework. The clustered prior images are additionally employed to detect any possible mismatched areas compared with the current images that are classified by the k‐means algorithm at each iteration step. A distance transformation is then introduced to convert the mismatched information into a weighted relaxation map for an adaptive update. In constructing the relaxation map, the matched regions between the prior and current images are assigned with smaller values and thus are much less influenced by the sparse projections, thereby leading to fewer streaking artifacts. On the other hand, mismatched regions are associated with larger values and the regions are updated more by the new projections, thus avoiding any possible adverse effects of prior images. The APICCS approach was assessed by using patient data acquired under standard‐ and low‐dose protocols. Results: The APICCS method provides an effective way to enhance the image quality at the matched regions between the prior and current images compared to the existing PICCS algorithm. In addition, the APICCS algorithm allows an imaging dose reduction of 10 to 40 times due to the greatly reduced number of projections and X‐ray tube current. Conclusions:The APICCS technique allows us to effectively take advantage of previously obtained CBCT images and provides high quality CBCT images with sparse projections.This work was supported in part by Mid‐career Researcher Program (2009‐0085999) through NRF grant funded by the MEST and in part by the Industrial Strategic Technology Development Program (10035495) funded by the Ministry of Knowledge Economy (MKE, Korea).

Reconstruction of a cone‐beam CT image via forward iterative projection matching

To demonstrate the feasibility of reconstructing a cone-beam CT (CBCT) image by deformably altering a prior fan-beam CT (FBCT) image such that it matches the anatomy portrayed in the CBCT projection data set. A prior FBCT image of the patient is assumed to be available as a source image. A CBCT projection data set is obtained and used as a target image set. A parametrized deformation model is applied to the source FBCT image, digitally reconstructed radiographs (DRRs) that emulate the CBCT projection image geometry are calculated and compared to the target CBCT projection data, and the deformation model parameters are adjusted iteratively until the DRRs optimally match the CBCT projection data set. The resulting deformed FBCT image is hypothesized to be an accurate representation of the patient's anatomy imaged by the CBCT system. The process is demonstrated via numerical simulation. A known deformation is applied to a prior FBCT image and used to create a synthetic set of CBCT target projections. The iterative projection matching process is then applied to reconstruct the deformation represented in the synthetic target projections; the reconstructed deformation is then compared to the known deformation. The sensitivity of the process to the number of projections and the DRR/CBCT projection mismatch is explored by systematically adding noise to and perturbing the contrast of the target projections relative to the iterated source DRRs and by reducing the number of projections. When there is no noise or contrast mismatch in the CBCT projection images, a set of 64 projections allows the known deformed CT image to be reconstructed to within a nRMS error of 1% and the known deformation to within a nRMS error of 7%. A CT image nRMS error of less than 4% is maintained at noise levels up to 3% of the mean projection intensity, at which the deformation error is 13%. At 1% noise level, the number of projections can be reduced to 8 while maintaining CT image and deformation errors of less than 4% and 13%, respectively. The method is sensitive to contrast mismatch between the simulated projections and the target projections when the soft-tissue contrast in the projections is low. By using prior knowledge available in a FBCT image, the authors show that a CBCT image can be iteratively reconstructed from a comparatively small number of projection images, thus saving acquisition time and reducing imaging dose. This will enable more frequent daily imaging during radiation therapy. Because the process preserves the CT numbers of the FBCT image, the resulting 3D image intensities will be more accurate than a CBCT image reconstructed via conventional backprojection methods. Reconstruction errors are insensitive to noise at levels beyond what would typically be found in CBCT projection data, but are sensitive to contrast mismatch errors between the CBCT projection data and the DRRs.

Phase Window and Frame Rate Optimization for On-board 4D Imaging Dose Reduction

Phase Window and Frame Rate Optimization for On-board 4D Imaging Dose Reduction

TU‐C‐204B‐03: Reducing Imaging Dose without Sacrificing Target Localization Accuracy: A Feasibility Study

Purpose: We develop and investigate the feasibility of reducing concomitant imaging dose without sacrificing tumor localization accuracy in IGRT, by making “smart” imaging decisions in real‐time. This study focuses on demonstrating the utility of adaptive imaging triggers instead of uniform triggering. Method and Materials: We demonstrate the sub‐optimality of the current uniform imaging scheme, in terms of accuracy v.s. imaging dose tradeoff. We developed an oracle imaging triggering strategy, which retrospectively distributes the kV imaging events to maximize localization accuracy over the treatment duration. The tradeoff between localization accuracy and total imaging dose from the oracle solution provides a performance upper bound and its deviation from the corresponding uniform image triggering scheme alludes to the potential of imaging less with the same localization accuracy. The proposed concept is tested on 159 patient derived 3D abdominal and thoracic tumor traces. Results: The oracle tradeoff curve dominates the current practiced uniform image triggering scheme, in the sense that for the same localization accuracy, it consistently reduces the required total number of images. Quantitatively, it manage to decrease the average imaging frequency by 40% to 50% in most cases. Furthermore, significant potential dose reduction is observed throughout a large range of motion patterns and under various total imaging dose conditions. Conclusion: We have proposed a feasibility study to investigate the As Low As Reasonably Achievable (ALARA) principle in IGRT, by reducing imaging dose while maintaining tumor localization accuracy. Future work will focus on developing real‐time heuristics to approach the oracle performance and experimental verification of geometric and dosimetric accuracy. Research supported by NIH/NCI R01 93626 and AAPM Seed Funding Initiative.

TU‐E‐204B‐04: DMLC Implementation of a Prostate Intrafraction Motion Correction Strategy Based on Failure Detection Concept

Purpose: To develop a dynamic MLC‐based real‐time motion tracking system through stereoscopic MV‐kV target localization and to utilize a failure detection concept to reduce kV imaging dose while maintaining high targeting accuracy. Methods and Materials: Continuous MV‐kV target localization, although informative, imposes excessive kV imaging dose. In order to reduce kV usage, we attempted for a first step to only detect potential motion beyond a pre‐defined threshold using MV images and in a second step, through applying as‐needed MV‐kV imaging, to confirm the over‐threshold event and obtain accurate marker position information which could be used to instruct instantaneous MLC adjustment. This technique is particularly useful for slow non‐periodic motion. A Varian Trilogy linac with onboard imaging and a Millennium 120‐leaf MLC was used to examine selected typical prostate trajectories using a 4D motion platform. Geometric and dosimetric tracking performances were evaluated by tracking a moving gold marker during dose delivery from 7 gantry angles. In‐house designed software was used for marker extraction, decision making, and MLC adjustment. Results: Total system latency from occurrence of an over‐threshold motion to the end of MLC repositioning was found to be 0.5 – 0.6 sec. The target was kept within a preset 2.5mm range 99% and 96% of the beam‐on time requiring only 1 and 13 kV‐on for a slow drifting and a high‐frequency motion case, respectively. The MLC repositioning accuracy is ∼0.5mm with system calibration. Dosimetric benefits are seen in reduced failure rate of the gamma‐test applied to dose measurements. Conclusions: Cine MV imaging during therapy delivery provides a valuable tool for detecting non‐negligible intrafraction prostate motion and facilitates intelligent kV use to significantly reduce imaging dose. Successful integration of this monitoring strategy and DMLC motion compensation is demonstrated. The developed system is intriguing for prostate intrafraction motion management with low kV imaging overhead.

TU‐D‐204B‐04: 4DCT Reconstruction from Undersampled Projections Using Edge‐Preserving Total Variation and Non Local Means

Purpose: Four‐dimensional computed tomography (4DCT) is widely used in radiotherapy planning for thorax and upper abdomen to take respiratory motion into consideration. However, its high radiation dose becomes a major concern and impedes its wide application. In this work, we proposed an iterative 4DCT reconstruction algorithm with both an Edge‐Preserving Total Variation (EPTV) regularization and a Non‐Local Means (NLM) regularization to accurately reconstruct 4DCT images from highly undersampled projections to reduce imaging dose. Methods and Materials: In 4DCT, images of neighboring phases usually share similar structures, though these structures are apart from each other spatially in neighboring phases due to breathing motion. To take this temporal correlation into the reconstruction process, we propose to use NLM as a temporal regularization in 4DCT reconstruction. For this purpose, each phase of the 4DCT is iteratively reconstructed by a modified total variation method, namely EPTV method. NLM regularization is imposed in each iteration step to enhance image quality. Specifically, we consider every possible small patch in all phases. Patches spatially close to each other in successive phases are weighted averaged, with high weights assigned to similar patches. We tested our reconstruction algorithm on a NCAT phantom at thorax region and a real patient 4DCT thorax data. 4DCT images obtained from our EPTV+NLM approach are compared with those obtained from the EPTV method. Relative errors are computed and are used to evaluate the reconstruction quality. Results: About 40 x‐ray projections for each breathing phase are enough to accurately reconstruct the 4DCT image in both test cases. The images reconstructed with NLM regularization are found to have lower relative error and hence better image quality than those reconstructed otherwise. Conclusions: Our proposed EPTV+NLM method is a robust approach for the 4DCT reconstruction, where NLM as a temporal regularization can considerably enhance the reconstructed image quality.

TU‐C‐204B‐01: Reduce Patient Dose and Improve Image Quality in CBCT for Image Guided Radiotherapy

Introduction: We have demonstrated that cone beam CT (CBCT) image quality was substantially improved in terms of eliminating scatter related artifacts and enhancing contrast‐to‐noise ratio, using a 1D grid placed between the x‐ray source and the imaging object. The grid serves to physically reduce scatter while also enabling measurements of scatter simultaneously for post‐scan scatter correction. A full set of CBCT images can be generated from the partially‐blocked imaging data using either one‐ or dual‐rotation modes. Using one‐rotation has particularly the advantage of reducing imaging dose by a factor of two in comparison to conventional CBCT. The tradeoff is that longitudinal resolution is degraded. This study evaluates the feasibility of using CBCT images from the single‐rotation mode for image‐guided radiotherapy (IGRT). Methods and material: A lead grid of approximately 1‐mm septa width and interspace was placed at a source‐to‐grid distance of approximately 30‐cm in a Varian Trilogy CBCT system for the single‐rotation mode. An anthropomorphic pelvis phantom was used for the test. Various steps in imaging processing were performed for each projection, including measuring the scatter distribution, performing scatter correction, deriving imaging information in the grid penumbral regions by dividing the projection with a blank scan, and interpolating the remaining blocked information. Rigid body image fusion was performed for the reconstructed CBCT images with the simulation CT, and compared with CBCT images from the two‐rotation and conventional CBCT. Results: The single‐rotation CBCT images showed substantially reduced scatter‐related artifacts. Despite the degradation in longitudinal resolution, the visibility of anatomic structures (an important requirement of IGRT) was not significantly affected. The auto‐registration error was 0.8±0.3 mm in longitudinal direction, and was negligible in AP and lateral directions and three rotational directions. Conclusion: CBCT images from the single‐rotation mode can achieve reasonable longitudinal resolution for anatomic structure visualization and accurate auto‐registration in IGRT.

Investigation of Sparse Data Mouse Imaging Using Micro-CT with a Carbon-Nanotube-Based X-ray Source

There has been a renewed interest in algorithm development for image reconstruction from highly incomplete data in computed tomography (CT). Such algorithms may lead to reduced imaging dose and time, and to the design of innovative configurations tailored to specific imaging tasks. In recent years, a carbon-nanotube (CNT)-based field-emission x-ray source has been developed, which offers easy electronic control of radiation and thus can be an ideal candidate for gated imaging. We have recently proposed algorithms for image reconstruction from fan-and cone-beam data collected at highly sparse angular views through minimization of the total-variation (TV) of the image subject to the condition that the estimated data are consistent with the measured data. In this work, we investigate and demonstrate the application of the TV-minimization algorithm to reconstructing images from mouse data acquired with a CNT-based CT scanner at a number of views much lower than what is used in conventional CT imaging. The results demonstrate that the TV-minimization algorithm can yield images with quality comparable to those obtained from a large number of views by use of the conventional algorithms. The significance of the work may lie in that the substantial reduction of projection views promised by the TV-minimization algorithm can be exploited for reducing imaging dose and time or for improving temporal resolution in tasks such as dynamic imaging.

State of the art: technologies for computed tomography dose reduction

The utilization of computed tomography (CT) in the emergency department has grown rapidly in the last decade, driven by strong evidence supporting its effectiveness in the rapid diagnosis of an increasing range of diseases. Concerns have been raised about potential cancer induction caused by the increased use of CT and the high radiation dose associated with some multidetector row CT examinations. Recent research into protocol design and new CT scanner technologies enable high-quality examinations to be performed with a significant reduction in radiation dose. These advances are discussed, with emphasis on their application to emergency radiology.

Incorporation of Prior Volumetric Image Information into Cone-beam CT (CBCT) Reconstruction: A Novel Strategy of Imaging Dose Reduction for Daily Patient Setup and Adaptive Radiation Therapy

Incorporation of Prior Volumetric Image Information into Cone-beam CT (CBCT) Reconstruction: A Novel Strategy of Imaging Dose Reduction for Daily Patient Setup and Adaptive Radiation Therapy

Progress in the Reduction of Imaging Dose without Compromise of Image Quality with the use of New kV-CBCT Acquisition Techniques

Progress in the Reduction of Imaging Dose without Compromise of Image Quality with the use of New kV-CBCT Acquisition Techniques

SU‐FF‐J‐17: Image‐Guided Radiotherapy Using Nanotube Stantionary Tomosynthesis Technology

Purpose: To develop image guidance approaches for clinical application of Nanotube Stationary Tomosynthesis (NST), a nanotechnology‐based online image‐guided radiotherapy (IGRT) technology that is capable of unprecedented temporal‐resolution and imaging speed. Method and Materials: NST is an accelerator gantry‐mounted multi‐source array kV imaging technology under development by Siemens. Using a single image panel, the patient can be imaged by 50 x‐ray sources on the array in the treatment volume within ∼ 2 sec before and even during treatment. However, translating the NST's imaging acquisition strengths into real clinical benefits requires significant software development including new image registration tools that take full advantage of the real‐time aspects of tomosynthesis imaging while minimizing its intrinsic resolution limitation. We propose a fast, versatile image registration approach that: integrates information from the large field‐of‐view projection images, the high‐temporal resolution tomosynthesis images, and the high spatial‐resolution planning 3D CT image; has tradeoffs to balance the user's needs of quality vs. speed; and potentially extracts a daily image deformation from NST tomosynthesis image for soft tissue based IGRT and treatment course dose accumulation. Results: We have developed the initial image registration approaches for clinical testing of the first protocol type NST IGRT system. In this presentation we will describe the proposed NST IGRT image registration approaches in lung and prostate treatments and discuss imaging dose and imaging dose reduction approaches. Other aspects of the NST technology including system design, NST reconstruction, image registration, and imaging geometry may be presented separately in the meeting. Conclusion: We have demonstrated that Nanotube Stationary Tomosynthesis technology has the potential to offer temporal resolution and imaging speed ‐ important features that have not been adequately addressed by the existing IGRT technology today.Conflict of Interest: This work is partially funded by a grant from Siemens Oncology Care System.

Sci-Thurs PM: Delivery-11: Image guidance for prostate IMRT using low dose cone beam CT.

Linac-mounted cone beam computed tomography (CBCT) using Varian's On Board Imager (OBI) currently delivers significant imaging dose and lacks automatic methods for clinical target volume (CTV) registration. In this work, we address these two issues to enable frequent treatment corrections during a course of prostate intensity modulated radiation therapy (IMRT). The process starts by acquiring a low dose (low mAs) CBCT image after patient setup. The image is then used in one of two automatic image guidance strategies. The "global" technique provides the couch corrections necessary to improve patient setup by registering the CBCT to the planning CT. The "local" method involves non-rigid registration of the planning CT to the CBCT followed by automatic treatment re-optimization using the deformed planning CT and contours. Thus, the global method attempts to correct patient setup to match the planned treatment, while the local method corrects the treatment to match the patient setup. Both techniques were evaluated using images of an anthropomorphic male pelvis phantom. Global image guidance resulted in a registration error of 3.6 ± 1.3 mm (imaging dose independent) and high treatment doses to the bladder and rectum for large magnitude motion. The local technique always resulted in clinically acceptable treatment doses due to a reduced registration error of 2.3 ± 0.8 mm, obtained at 15% of the OBI's default dose (125 kVp, 2 mAs per projection). These preliminary results show that our automatic local image guidance technique reduces imaging dose and is sufficiently accurate and robust for application in prostate IMRT.