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DOE OSTI2022

Exploiting voxel-sparsity for bone imaging with sparse-view cone-beam computed tomography

An optimization-based image reconstruction frame work is developed specifically for bone imaging. This framework exploits voxel-sparsity by use of ℓ 1 -norm image regularization and it enables image reconstruction from sparse-view cone-beam computed tomography (CBCT) acquisition. The effectiveness of the voxel-sparsity regularization is enhanced by using a blurred image representation. Ramp-filtering is included in the data discrepancy term and it has the effect of acting as a preconditioner, reducing the necessary number of iterations. The bone image reconstruction framework is demonstrated on CBCT data taken from an equine metacarpal condyle specimen.

Bone imaging↗
DOE OSTI2011

Robustness of phase retrieval methods in x-ray phase contrast imaging: A comparison

Purpose: The robustness of the phase retrieval methods is of critical importance for limiting and reducing radiation doses involved in x-ray phase contrast imaging. This work is to compare the robustness of two phase retrieval methods by analyzing the phase maps retrieved from the experimental images of a phantom. Methods: Two phase retrieval methods were compared. One method is based on the transport of intensity equation (TIE) for phase contrast projections, and the TIE-based method is the most commonly used method for phase retrieval in the literature. The other is the recently developed attenuation-partition based (AP-based) phase retrieval method. The authors applied these two methods to experimental projection images of an air-bubble wrap phantom for retrieving the phase map of the bubble wrap. The retrieved phase maps obtained by using the two methods are compared. Results: In the wrap's phase map retrieved by using the TIE-based method, no bubble is recognizable, hence, this method failed completely for phase retrieval from these bubble wrap images. Even with the help of the Tikhonov regularization, the bubbles are still hardly visible and buried in the cluttered background in the retrieved phase map. The retrieved phase values with this method are grossly erroneous. In contrast, in the wrap's phase map retrieved by using the AP-based method, the bubbles are clearly recovered. The retrieved phase values with the AP-based method are reasonably close to the estimate based on the thickness-based measurement. The authors traced these stark performance differences of the two methods to their different techniques employed to deal with the singularity problem involved in the phase retrievals. Conclusions: This comparison shows that the conventional TIE-based phase retrieval method, regardless if Tikhonov regularization is used or not, is unstable against the noise in the wrap's projection images, while the AP-based phase retrieval method is shown in these experiments to be superior to the TIE-based method for the robustness in performing the phase retrieval.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2012

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

Purpose: 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. Methods: 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 deg. rotation. The imager has 1024 x 768 pixels with 0.388 x 0.388-mm resolution. This was down-sampled to 512 x 384 pixels with 0.776 x 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. Results: 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. Conclusions: 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 {approx}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).

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2012

Dynamic volume vs respiratory correlated 4DCT for motion assessment in radiation therapy simulation

Purpose: Conventional (i.e., respiratory-correlated) 4DCT exploits the repetitive nature of breathing to provide an estimate of motion; however, it has limitations due to binning artifacts and irregular breathing in actual patient breathing patterns. The aim of this work was to evaluate the accuracy and image quality of a dynamic volume, CT approach (4D{sub vol}) using a 320-slice CT scanner to minimize these limitations, wherein entire image volumes are acquired dynamically without couch movement. This will be compared to the conventional respiratory-correlated 4DCT approach (RCCT). Methods: 4D{sub vol} CT was performed and characterized on an in-house, programmable respiratory motion phantom containing multiple geometric and morphological ''tumor'' objects over a range of regular and irregular patient breathing traces obtained from 3D fluoroscopy and compared to RCCT. The accuracy of volumetric capture and breathing displacement were evaluated and compared with the ground truth values and with the results reported using RCCT. A motion model was investigated to validate the number of motion samples needed to obtain accurate motion probability density functions (PDF). The impact of 4D image quality on this accuracy was then investigated. Dose measurements using volumetric and conventional scan techniques were also performed and compared. Results: Both conventional and dynamic volume 4DCT methods were capable of estimating the programmed displacement of sinusoidal motion, but patient breathing is known to not be regular, and obvious differences were seen for realistic, irregular motion. The mean RCCT amplitude error averaged at 4 mm (max. 7.8 mm) whereas the 4D{sub vol} CT error stayed below 0.5 mm. Similarly, the average absolute volume error was lower with 4D{sub vol} CT. Under irregular breathing, the 4D{sub vol} CT method provides a close description of the motion PDF (cross-correlation 0.99) and is able to track each object, whereas the RCCT method results in a significantly different PDF from the ground truth, especially for smaller tumors (cross-correlation ranging between 0.04 and 0.69). For the protocols studied, the dose measurements were higher in the 4D{sub vol} CT method (40%), but it was shown that significant mAs reductions can be achieved by a factor of 4-5 while maintaining image quality and accuracy. Conclusions: 4D{sub vol} CT using a scanner with a large cone-angle is a promising alternative for improving the accuracy with which respiration-induced motion can be characterized, particularly for patients with irregular breathing motion. This approach also generates 4DCT image data with a reduced total scan time compared to a RCCT scan, without the need for image binning or external respiration signals within the 16 cm scan length. Scan dose can be made comparable to RCCT by optimization of the scan parameters. In addition, it provides the possibility of measuring breathing motion for more than one breathing cycle to assess stability and obtain a more accurate motion PDF, which is currently not feasible with the conventional RCCT approach.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2013

Cone beam x-ray luminescence computed tomography: A feasibility study

Purpose: The appearance of x-ray luminescence computed tomography (XLCT) opens new possibilities to perform molecular imaging by x ray. In the previous XLCT system, the sample was irradiated by a sequence of narrow x-ray beams and the x-ray luminescence was measured by a highly sensitive charge coupled device (CCD) camera. This resulted in a relatively long sampling time and relatively low utilization of the x-ray beam. In this paper, a novel cone beam x-ray luminescence computed tomography strategy is proposed, which can fully utilize the x-ray dose and shorten the scanning time. The imaging model and reconstruction method are described. The validity of the imaging strategy has been studied in this paper. Methods: In the cone beam XLCT system, the cone beam x ray was adopted to illuminate the sample and a highly sensitive CCD camera was utilized to acquire luminescent photons emitted from the sample. Photons scattering in biological tissues makes it an ill-posed problem to reconstruct the 3D distribution of the x-ray luminescent sample in the cone beam XLCT. In order to overcome this issue, the authors used the diffusion approximation model to describe the photon propagation in tissues, and employed the sparse regularization method for reconstruction. An incomplete variables truncated conjugate gradient method and permissible region strategy were used for reconstruction. Meanwhile, traditional x-ray CT imaging could also be performed in this system. The x-ray attenuation effect has been considered in their imaging model, which is helpful in improving the reconstruction accuracy. Results: First, simulation experiments with cylinder phantoms were carried out to illustrate the validity of the proposed compensated method. The experimental results showed that the location error of the compensated algorithm was smaller than that of the uncompensated method. The permissible region strategy was applied and reduced the reconstruction error to less than 2 mm. The robustness and stability were then evaluated from different view numbers, different regularization parameters, different measurement noise levels, and optical parameters mismatch. The reconstruction results showed that the settings had a small effect on the reconstruction. The nonhomogeneous phantom simulation was also carried out to simulate a more complex experimental situation and evaluated their proposed method. Second, the physical cylinder phantom experiments further showed similar results in their prototype XLCT system. With the discussion of the above experiments, it was shown that the proposed method is feasible to the general case and actual experiments. Conclusions: Utilizing numerical simulation and physical experiments, the authors demonstrated the validity of the new cone beam XLCT method. Furthermore, compared with the previous narrow beam XLCT, the cone beam XLCT could more fully utilize the x-ray dose and the scanning time would be shortened greatly. The study of both simulation experiments and physical phantom experiments indicated that the proposed method was feasible to the general case and actual experiments.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Mapping motion from 4D-MRI to 3D-CT for use in 4D dose calculations: A technical feasibility study

Purpose: Target sites affected by organ motion require a time resolved (4D) dose calculation. Typical 4D dose calculations use 4D-CT as a basis. Unfortunately, 4D-CT images have the disadvantage of being a 'snap-shot' of the motion during acquisition and of assuming regularity of breathing. In addition, 4D-CT acquisitions involve a substantial additional dose burden to the patient making many, repeated 4D-CT acquisitions undesirable. Here the authors test the feasibility of an alternative approach to generate patient specific 4D-CT data sets. Methods: In this approach motion information is extracted from 4D-MRI. Simulated 4D-CT data sets [which the authors call 4D-CT(MRI)] are created by warping extracted deformation fields to a static 3D-CT data set. The employment of 4D-MRI sequences for this has the advantage that no assumptions on breathing regularity are made, irregularities in breathing can be studied and, if necessary, many repeat imaging studies (and consequently simulated 4D-CT data sets) can be performed on patients and/or volunteers. The accuracy of 4D-CT(MRI)s has been validated by 4D proton dose calculations. Our 4D dose algorithm takes into account displacements as well as deformations on the originating 4D-CT/4D-CT(MRI) by calculating the dose of each pencil beam based on an individual time stamp of when that pencil beam is applied. According to corresponding displacement and density-variation-maps the position and the water equivalent range of the dose grid points is adjusted at each time instance. Results: 4D dose distributions, using 4D-CT(MRI) data sets as input were compared to results based on a reference conventional 4D-CT data set capturing similar motion characteristics. Almost identical 4D dose distributions could be achieved, even though scanned proton beams are very sensitive to small differences in the patient geometry. In addition, 4D dose calculations have been performed on the same patient, but using 4D-CT(MRI) data sets based on variable breathing patterns to show the effect of possible irregular breathing on active scanned proton therapy. Using a 4D-CT(MRI), including motion irregularities, resulted in significantly different proton dose distributions. Conclusions: The authors have demonstrated that motion information from 4D-MRI can be used to generate realistic 4D-CT data sets on the basis of a single static 3D-CT data set. 4D-CT(MRI) presents a novel approach to test the robustness of treatment plans in the circumstance of patient motion.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

Evaluation of normalized metal artifact reduction (NMAR) in kVCT using MVCT prior images for radiotherapy treatment planning

Purpose: To evaluate the metal artifacts in kilovoltage computed tomography (kVCT) images that are corrected using a normalized metal artifact reduction (NMAR) method with megavoltage CT (MVCT) prior images.Methods: Tissue characterization phantoms containing bilateral steel inserts are used in all experiments. Two MVCT images, one without any metal artifact corrections and the other corrected using a modified iterative maximum likelihood polychromatic algorithm for CT (IMPACT) are translated to pseudo-kVCT images. These are then used as prior images without tissue classification in an NMAR technique for correcting the experimental kVCT image. The IMPACT method in MVCT included an additional model for the pair/triplet production process and the energy dependent response of the MVCT detectors. An experimental kVCT image, without the metal inserts and reconstructed using the filtered back projection (FBP) method, is artificially patched with the known steel inserts to get a reference image. The regular NMAR image containing the steel inserts that uses tissue classified kVCT prior and the NMAR images reconstructed using MVCT priors are compared with the reference image for metal artifact reduction. The Eclipse treatment planning system is used to calculate radiotherapy dose distributions on the corrected images and on the reference image using the Anisotropic Analytical Algorithm with 6 MV parallel opposed 5 × 10 cm{sup 2} fields passing through the bilateral steel inserts, and the results are compared. Gafchromic film is used to measure the actual dose delivered in a plane perpendicular to the beams at the isocenter.Results: The streaking and shading in the NMAR image using tissue classifications are significantly reduced. However, the structures, including metal, are deformed. Some uniform regions appear to have eroded from one side. There is a large variation of attenuation values inside the metal inserts. Similar results are seen in commercially corrected image. Use of MVCT prior images without tissue classification in NMAR significantly reduces these problems. The radiation dose calculated on the reference image is close to the dose measured using the film. Compared to the reference image, the calculated dose difference in the conventional NMAR image, the corrected images using uncorrected MVCT image, and IMPACT corrected MVCT image as priors is ∼15.5%, ∼5%, and ∼2.7%, respectively, at the isocenter.Conclusions: The deformation and erosion of the structures present in regular NMAR corrected images can be largely reduced by using MVCT priors without tissue segmentation. The attenuation value of metal being incorrect, large dose differences relative to the true value can result when using the conventional NMAR image. This difference can be significantly reduced if MVCT images are used as priors. Reduced tissue deformation, better tissue visualization, and correct information about the electron density of the tissues and metals in the artifact corrected images could help delineate the structures better, as well as calculate radiation dose more correctly, thus enhancing the quality of the radiotherapy treatment planning.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

Quantification of organ motion based on an adaptive image-based scale invariant feature method

Purpose: The availability of corresponding landmarks in IGRT image series allows quantifying the inter and intrafractional motion of internal organs. In this study, an approach for the automatic localization of anatomical landmarks is presented, with the aim of describing the nonrigid motion of anatomo-pathological structures in radiotherapy treatments according to local image contrast.Methods: An adaptive scale invariant feature transform (SIFT) was developed from the integration of a standard 3D SIFT approach with a local image-based contrast definition. The robustness and invariance of the proposed method to shape-preserving and deformable transforms were analyzed in a CT phantom study. The application of contrast transforms to the phantom images was also tested, in order to verify the variation of the local adaptive measure in relation to the modification of image contrast. The method was also applied to a lung 4D CT dataset, relying on manual feature identification by an expert user as ground truth. The 3D residual distance between matches obtained in adaptive-SIFT was then computed to verify the internal motion quantification with respect to the expert user. Extracted corresponding features in the lungs were used as regularization landmarks in a multistage deformable image registration (DIR) mapping the inhale vs exhale phase. The residual distances between the warped manual landmarks and their reference position in the inhale phase were evaluated, in order to provide a quantitative indication of the registration performed with the three different point sets.Results: The phantom study confirmed the method invariance and robustness properties to shape-preserving and deformable transforms, showing residual matching errors below the voxel dimension. The adapted SIFT algorithm on the 4D CT dataset provided automated and accurate motion detection of peak to peak breathing motion. The proposed method resulted in reduced residual errors with respect to standard SIFT, providing a motion description comparable to expert manual identification, as confirmed by DIR.Conclusions: The application of the method to a 4D lung CT patient dataset demonstrated adaptive-SIFT potential as an automatic tool to detect landmarks for DIR regularization and internal motion quantification. Future works should include the optimization of the computational cost and the application of the method to other anatomical sites and image modalities.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Dosimetric evaluation of the interplay effect in respiratory-gated RapidArc radiation therapy

Purpose: Volumetric modulated arc therapy (VMAT) with gating capability has had increasing adoption in many clinics in the United States. In this new technique, dose rate, gantry rotation speed, and the leaf motion speed of multileaf collimators (MLCs) are modulated dynamically during gated beam delivery to achieve highly conformal dose coverage of the target and normal tissue sparing. Compared with the traditional gated intensity-modulated radiation therapy technique, this complicated beam delivery technique may result in larger dose errors due to the intrafraction tumor motion. The purpose of this work is to evaluate the dosimetric influence of the interplay effect for the respiration-gated VMAT technique (RapidArc, Varian Medical Systems, Palo Alto, CA). Our work consisted of two parts: (1) Investigate the interplay effect for different target residual errors during gated RapidArc delivery using a one-dimensional moving phantom capable of producing stable sinusoidal movement; (2) Evaluate the dosimetric influence in ten clinical patients’ treatment plans using a moving phantom driven with a patient-specific respiratory curve. Methods: For the first part of this study, four plans were created with a spherical target for varying residual motion of 0.25, 0.5, 0.75, and 1.0 cm. Appropriate gating windows were applied for each. The dosimetric effect was evaluated using EDR2 film by comparing the gated delivery with static delivery. For the second part of the project, ten gated lung stereotactic body radiotherapy cases were selected and reoptimized to be delivered by the gated RapidArc technique. These plans were delivered to a phantom, and again the gated treatments were compared to static deliveries by the same methods. Results: For regular sinusoidal motion, the dose delivered to the target was not substantially affected by the gating windows when evaluated with the gamma statistics, suggesting the interplay effect has a small role in respiratory-gated RapidArc therapy. Varied results were seen when gated therapy was performed on the patient plans that could only be attributed to differences in patient respiratory patterns. Patients whose plans had the largest percentage of pixels failing the gamma statistics exhibited irregular breathing patterns including substantial interpatient variation in depth of respiration. Conclusions: The interplay effect has a limited impact on gated RapidArc therapy when evaluated with a linear phantom. Variations in patient breathing patterns, however, are of much greater clinical significance. Caution must be taken when evaluating patients’ respiratory efforts for gated arc therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

A modern Monte Carlo investigation of the TG-43 dosimetry parameters for an {sup 125}I seed already having AAPM consensus data

Purpose: To investigate potential causes for differences in TG-43 brachytherapy dosimetry parameters in the existent literature for the model IAI-125A{sup 125}I seed and to propose new standard dosimetry parameters. Methods: The MCNP5 code was used for Monte Carlo (MC) simulations. Sensitivity of dose distributions, and subsequently TG-43 dosimetry parameters, was explored to reproduce historical methods upon which American Association of Physicists in Medicine (AAPM) consensus data are based. Twelve simulation conditions varying{sup 125}I coating thickness, coating mass density, photon interaction cross-section library, and photon emission spectrum were examined. Results: Varying{sup 125}I coating thickness, coating mass density, photon cross-section library, and photon emission spectrum for the model IAI-125A seed changed the dose-rate constant by up to 0.9%, about 1%, about 3%, and 3%, respectively, in comparison to the proposed standard value of 0.922 cGy h{sup −1} U{sup −1}. The dose-rate constant values by Solberg et al. [“Dosimetric parameters of three new solid core {sup 125}I brachytherapy sources,” J. Appl. Clin. Med. Phys. 3, 119–134 (2002)], Meigooni et al. [“Experimental and theoretical determination of dosimetric characteristics of IsoAid ADVANTAGE™ {sup 125}I brachytherapy source,” Med. Phys. 29, 2152–2158 (2002)], and Taylor and Rogers [“An EGSnrc Monte Carlo-calculated database of TG-43 parameters,” Med. Phys. 35, 4228–4241 (2008)] for the model IAI-125A seed and Kennedy et al. [“Experimental and Monte Carlo determination of the TG-43 dosimetric parameters for the model 9011 THINSeed™ brachytherapy source,” Med. Phys. 37, 1681–1688 (2010)] for the model 6711 seed were +4.3% (0.962 cGy h{sup −1} U{sup −1}), +6.2% (0.98 cGy h{sup −1} U{sup −1}), +0.3% (0.925 cGy h{sup −1} U{sup −1}), and −0.2% (0.921 cGy h{sup −1} U{sup −1}), respectively, in comparison to the proposed standard value. Differences in the radial dose functions between the current study and both Solberg et al. and Meigooni et al. were <10% for r ≤ 5 cm, and increased for r > 5 cm with a maximum difference of 29% at r = 9 cm. In comparison to Taylor and Rogers, these differences were lower (maximum of 2% at r = 9 cm). For the similarly designed model 6711 {sup 125}I seed, differences did not exceed 0.5% for 0.5 ≤ r ≤ 10 cm. Radial dose function values varied by 1% as coating thickness and coating density were changed. Varying the cross-section library and source spectrum altered the radial dose function by 25% and 12%, respectively, but these differences occurred at r = 10 cm where the dose rates were very low. The 2D anisotropy function results were most similar to those of Solberg et al. and most different to those of Meigooni et al. The observed order of simulation condition variables from most to least important for influencing the 2D anisotropy function was spectrum, coating thickness, coating density, and cross-section library. Conclusions: Several MC radiation transport codes are available for calculation of the TG-43 dosimetry parameters for brachytherapy seeds. The physics models in these codes and their related cross-section libraries have been updated and improved since publication of the 2007 AAPM TG-43U1S1 report. Results using modern data indicated statistically significant differences in these dosimetry parameters in comparison to data recommended in the TG-43U1S1 report. Therefore, it seems that professional societies such as the AAPM should consider reevaluating the consensus data for this and others seeds and establishing a process of regular evaluations in which consensus data are based upon methods that remain state-of-the-art.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2014

Dual-energy cone-beam CT with a flat-panel detector: Effect of reconstruction algorithm on material classification

Purpose: Cone-beam CT (CBCT) with a flat-panel detector (FPD) is finding application in areas such as breast and musculoskeletal imaging, where dual-energy (DE) capabilities offer potential benefit. The authors investigate the accuracy of material classification in DE CBCT using filtered backprojection (FBP) and penalized likelihood (PL) reconstruction and optimize contrast-enhanced DE CBCT of the joints as a function of dose, material concentration, and detail size. Methods: Phantoms consisting of a 15 cm diameter water cylinder with solid calcium inserts (50–200 mg/ml, 3–28.4 mm diameter) and solid iodine inserts (2–10 mg/ml, 3–28.4 mm diameter), as well as a cadaveric knee with intra-articular injection of iodine were imaged on a CBCT bench with a Varian 4343 FPD. The low energy (LE) beam was 70 kVp (+0.2 mm Cu), and the high energy (HE) beam was 120 kVp (+0.2 mm Cu, +0.5 mm Ag). Total dose (LE+HE) was varied from 3.1 to 15.6 mGy with equal dose allocation. Image-based DE classification involved a nearest distance classifier in the space of LE versus HE attenuation values. Recognizing the differences in noise between LE and HE beams, the LE and HE data were differentially filtered (in FBP) or regularized (in PL). Both a quadratic (PLQ) and a total-variation penalty (PLTV) were investigated for PL. The performance of DE CBCT material discrimination was quantified in terms of voxelwise specificity, sensitivity, and accuracy. Results: Noise in the HE image was primarily responsible for classification errors within the contrast inserts, whereas noise in the LE image mainly influenced classification in the surrounding water. For inserts of diameter 28.4 mm, DE CBCT reconstructions were optimized to maximize the total combined accuracy across the range of calcium and iodine concentrations, yielding values of ∼88% for FBP and PLQ, and ∼95% for PLTV at 3.1 mGy total dose, increasing to ∼95% for FBP and PLQ, and ∼98% for PLTV at 15.6 mGy total dose. For a fixed iodine concentration of 5 mg/ml and reconstructions maximizing overall accuracy across the range of insert diameters, the minimum diameter classified with accuracy >80% was ∼15 mm for FBP and PLQ and ∼10 mm for PLTV, improving to ∼7 mm for FBP and PLQ and ∼3 mm for PLTV at 15.6 mGy. The results indicate similar performance for FBP and PLQ and showed improved classification accuracy with edge-preserving PLTV. A slight preference for increased smoothing of the HE data was found. DE CBCT discrimination of iodine and bone in the knee was demonstrated with FBP and PLTV at 6.2 mGy total dose. Conclusions: For iodine concentrations >5 mg/ml and detail size ∼20 mm, material classification accuracy of >90% was achieved in DE CBCT with both FBP and PL at total doses <10 mGy. Optimal performance was attained by selection of reconstruction parameters based on the differences in noise between HE and LE data, typically favoring stronger smoothing of the HE data, and by using penalties matched to the imaging task (e.g., edge-preserving PLTV in areas of uniform enhancement)

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Automatic tracking of arbitrarily shaped implanted markers in kilovoltage projection images: A feasibility study

Purpose: Certain types of commonly used fiducial markers take on irregular shapes upon implantation in soft tissue. This poses a challenge for methods that assume a predefined shape of markers when automatically tracking such markers in kilovoltage (kV) radiographs. The authors have developed a method of automatically tracking regularly and irregularly shaped markers using kV projection images and assessed its potential for detecting intrafractional target motion during rotational treatment. Methods: Template-based matching used a normalized cross-correlation with simplex minimization. Templates were created from computed tomography (CT) images for phantom studies and from end-expiration breath-hold planning CT for patient studies. The kV images were processed using a Sobel filter to enhance marker visibility. To correct for changes in intermarker relative positions between simulation and treatment that can introduce errors in automatic matching, marker offsets in three dimensions were manually determined from an approximately orthogonal pair of kV images. Two studies in anthropomorphic phantom were carried out, one using a gold cylindrical marker representing regular shape, another using a Visicoil marker representing irregular shape. Automatic matching of templates to cone beam CT (CBCT) projection images was performed to known marker positions in phantom. In patient data, automatic matching was compared to manual matching as an approximate ground truth. Positional discrepancy between automatic and manual matching of less than 2 mm was assumed as the criterion for successful tracking. Tracking success rates were examined in kV projection images from 22 CBCT scans of four pancreas, six gastroesophageal junction, and one lung cancer patients. Each patient had at least one irregularly shaped radiopaque marker implanted in or near the tumor. In addition, automatic tracking was tested in intrafraction kV images of three lung cancer patients with irregularly shaped markers during 11 volumetric modulated arc treatments. Purpose-built software developed at our institution was used to create marker templates and track the markers embedded in kV images. Results: Phantom studies showed mean ± standard deviation measurement uncertainty of automatic registration to be 0.14 ± 0.07 mm and 0.17 ± 0.08 mm for Visicoil and gold cylindrical markers, respectively. The mean success rate of automatic tracking with CBCT projections (11 frames per second, fps) of pancreas, gastroesophageal junction, and lung cancer patients was 100%, 99.1% (range 98%–100%), and 100%, respectively. With intrafraction images (approx. 0.2 fps) of lung cancer patients, the success rate was 98.2% (range 97%–100%), and 94.3% (range 93%–97%) using templates from 1.25 mm and 2.5 mm slice spacing CT scans, respectively. Correction of intermarker relative position was found to improve the success rate in two out of eight patients analyzed. Conclusions: The proposed method can track arbitrary marker shapes in kV images using templates generated from a breath-hold CT acquired at simulation. The studies indicate its feasibility for tracking tumor motion during rotational treatment. Investigation of the causes of misregistration suggests that its rate of incidence can be reduced with higher frequency of image acquisition, templates made from smaller CT slice spacing, and correction of changes in intermarker relative positions when they occur.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-J-265: Practical Issues and Solutions in Reconstructing and Using 4DCT for Radiotherapy Planning of Lung Cancer

Purpose: To report practical issues and solutions in reconstructing and using 4DCT to account for respiratory motion in radiotherapy planning. Methods: Quiet breathing 4DCT was used to account for respiratory motion for patients with lung or upper abdomen tumor. A planning CT and a 4DCT were acquired consecutively with a Philips Brilliance CT scanner and Varian RPM System. The projections were reconstructed into 10 phases. In Pinnacle RTP system, we contour a GTV in each phase and unite all 10 GTVs as ITV. The ITV is then mapped to the planning CT. We describe practical issues, their causes, our solutions and reasoning during this process. Results: In 6 months, 9 issues were reported for 8 patients with lung cancer. For two patients, part of the GTV (∼50% and 10%) in planning CT fell outside the ITV in 4DCT. There was a 7 mm variation in first patient back position because less restricted immobilization had to be used. The second discrepancy was due to moderate variation in breathing amplitude. We extended the ITV to include the GTV since both variations may likely happen during treatment. A LUL tumor showed no motion due to a 10-s long no-breathing period. An RLL tumor appeared double due to an abnormally deeper breath at the tumor region. We repeated 4DCT reiterating the importance of quiet, regular breathing. One patient breathed too light to generate RPM signal. Two issues (no motion in lung, incomplete images in 90% phase) were due to incorrect tag positions. Two unexplainable errors disappeared when repeating reconstruction. In summary, 5 issues were patient-related and 4 were technique issues. Conclusion: Improving breathing regularity avoided large artifacts in 4DCT. One needs to closely monitor patient breathing. For uncontrollable variations, larger PTVs are necessary which requires appropriate communication between physics and the treating physician.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

TU-F-18A-02: Iterative Image-Domain Decomposition for Dual-Energy CT

Purpose: Dual energy CT (DECT) imaging plays an important role in advanced imaging applications due to its material decomposition capability. Direct decomposition via matrix inversion suffers from significant degradation of image signal-to-noise ratios, which reduces clinical value. Existing de-noising algorithms achieve suboptimal performance since they suppress image noise either before or after the decomposition and do not fully explore the noise statistical properties of the decomposition process. We propose an iterative image-domain decomposition method for noise suppression in DECT, using the full variance-covariance matrix of the decomposed images. Methods: The proposed algorithm is formulated in the form of least-square estimation with smoothness regularization. It includes the inverse of the estimated variance-covariance matrix of the decomposed images as the penalty weight in the least-square term. Performance is evaluated using an evaluation phantom (Catphan 600) and an anthropomorphic head phantom. Results are compared to those generated using direct matrix inversion with no noise suppression, a de-noising method applied on the decomposed images, and an existing algorithm with similar formulation but with an edge-preserving regularization term. Results: On the Catphan phantom, our method retains the same spatial resolution as the CT images before decomposition while reducing the noise standard deviation of decomposed images by over 98%. The other methods either degrade spatial resolution or achieve less low-contrast detectability. Also, our method yields lower electron density measurement error than direct matrix inversion and reduces error variation by over 97%. On the head phantom, it reduces the noise standard deviation of decomposed images by over 97% without blurring the sinus structures. Conclusion: We propose an iterative image-domain decomposition method for DECT. The method combines noise suppression and material decomposition into an iterative process and achieves both goals simultaneously. The proposed algorithm shows superior performance on noise suppression with high image spatial resolution and low-contrast detectability. This work is supported by a Varian MRA grant.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

WE-G-18A-03: Cone Artifacts Correction in Iterative Cone Beam CT Reconstruction

Purpose: For iterative reconstruction (IR) in cone-beam CT (CBCT) imaging, data truncation along the superior-inferior (SI) direction causes severe cone artifacts in the reconstructed CBCT volume images. Not only does it reduce the effective SI coverage of the reconstructed volume, it also hinders the IR algorithm convergence. This is particular a problem for regularization based IR, where smoothing type regularization operations tend to propagate the artifacts to a large area. It is our purpose to develop a practical cone artifacts correction solution. Methods: We found it is the missing data residing in the truncated cone area that leads to inconsistency between the calculated forward projections and measured projections. We overcome this problem by using FDK type reconstruction to estimate the missing data and design weighting factors to compensate the inconsistency caused by the missing data. We validate the proposed methods in our multi-GPU low-dose CBCT reconstruction system on multiple patients' datasets. Results: Compared to the FDK reconstruction with full datasets, while IR is able to reconstruct CBCT images using a subset of projection data, the severe cone artifacts degrade overall image quality. For head-neck case under a full-fan mode, 13 out of 80 slices are contaminated. It is even more severe in pelvis case under half-fan mode, where 36 out of 80 slices are affected, leading to inferior soft-tissue delineation. By applying the proposed method, the cone artifacts are effectively corrected, with a mean intensity difference decreased from ∼497 HU to ∼39HU for those contaminated slices. Conclusion: A practical and effective solution for cone artifacts correction is proposed and validated in CBCT IR algorithm. This study is supported in part by NIH (1R01CA154747-01)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

TH-A-BRF-12: Assessment of 4D-MRI for Robust Motion and Volume Characterization

Purpose: Precise radiation therapy for abdominal lesions is complicated by respiratory motion and poor soft tissue contrast from 4DCT whereas 4DMRI provides superior tissue discrimination. We evaluated a novel 4D-MRI algorithm for MR-SIM motion management. Methods: Respiratory-triggered, T2-weighted single-shot Turbo Spin Echo 4D-MRI was evaluated for open high-field 1.0T MR-SIM. A programmable platform pulled objects on a trolley ∼2 cm superior-inferior (S-I) for “regular” (sinusoidal, (1-cos{sup 2}), 3-5 second periods) and “irregular” breathing patterns (exaggerated (1-cos{sup 2}) and patient curves), while a respiratory waveform was generated via a pressure sensor device. Coronal 4D-MRIs (2–12;10 phases, TE/TR/α = 35−61/6100 ms/90°, voxel=1×1×4 mm{sup 3}) were acquired for 54 unique phantom cases. Abdominal 4D−MRIs were evaluated for 5 healthy volunteers and 1 liver cancer patient (6–10 phases, TE/TR/α = 30−96/4500−6100 ms/90°, voxel=1×1×5–10 mm{sup 3}) on an IRB-approved protocol. Duty cycle, scan time, and excursion were evaluated between phase acquisitions and compared to coronal cine-MRI (∼1 frame/sec). Maximum intensity projections (MIPs) were analyzed. Results: In phantom, average duty cycle was 42.6 ± 11.4% (range: 23.6–69.1%). Regular, periodic breathing (sinusoidal, (1-cos{sup 2})) yielded higher duty cycles than irregular (48.5% and 35.9%, respectively, p<0.001) and fast periods had higher duty cycles than slow (50.4% for 3s and 39.4% for 5s, p<0.001). ∼4-fold acquisition time increase was measured for 10-phase versus 2-phase. MIP renderings revealed that SI object extent was underestimated a maximum of 4% (3mm) and 8% (6mm) for cine and 2-phase 4D-MRI, respectively, with respect to 10-phases. However, this was waveform dependent. A highly irregular breathing volunteer yielded lowest duty cycle (23%) and longest 10-phase scan time (∼14 minutes), although 6-phase acquisition for a liver cancer patient was reasonable (50% and 7.4 minutes, respectively). Conclusion: 4D-MRI offers potential for excursion characterization, although results suggest the use of adequate phases is important. Further application and clinical validation are warranted. Research supported in part by a grant from Philips HealthCare (Best, Netherlands) and an Internal Mentored Grant from Henry Ford Health System.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

The ANACONDA algorithm for deformable image registration in radiotherapy

Purpose: The purpose of this work was to describe a versatile algorithm for deformable image registration with applications in radiotherapy and to validate it on thoracic 4DCT data as well as CT/cone beam CT (CBCT) data. Methods: ANAtomically CONstrained Deformation Algorithm (ANACONDA) combines image information (i.e., intensities) with anatomical information as provided by contoured image sets. The registration problem is formulated as a nonlinear optimization problem and solved with an in-house developed solver, tailored to this problem. The objective function, which is minimized during optimization, is a linear combination of four nonlinear terms: 1. image similarity term; 2. grid regularization term, which aims at keeping the deformed image grid smooth and invertible; 3. a shape based regularization term which works to keep the deformation anatomically reasonable when regions of interest are present in the reference image; and 4. a penalty term which is added to the optimization problem when controlling structures are used, aimed at deforming the selected structure in the reference image to the corresponding structure in the target image. Results: To validate ANACONDA, the authors have used 16 publically available thoracic 4DCT data sets for which target registration errors from several algorithms have been reported in the literature. On average for the 16 data sets, the target registration error is 1.17 ± 0.87 mm, Dice similarity coefficient is 0.98 for the two lungs, and image similarity, measured by the correlation coefficient, is 0.95. The authors have also validated ANACONDA using two pelvic cases and one head and neck case with planning CT and daily acquired CBCT. Each image has been contoured by a physician (radiation oncologist) or experienced radiation therapist. The results are an improvement with respect to rigid registration. However, for the head and neck case, the sample set is too small to show statistical significance. Conclusions: ANACONDA performs well in comparison with other algorithms. By including CT/CBCT data in the validation, the various aspects of the algorithm such as its ability to handle different modalities, large deformations, and air pockets are shown.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Interactive prostate segmentation using atlas-guided semi-supervised learning and adaptive feature selection

Purpose: Accurate prostate segmentation is necessary for maximizing the effectiveness of radiation therapy of prostate cancer. However, manual segmentation from 3D CT images is very time-consuming and often causes large intra- and interobserver variations across clinicians. Many segmentation methods have been proposed to automate this labor-intensive process, but tedious manual editing is still required due to the limited performance. In this paper, the authors propose a new interactive segmentation method that can (1) flexibly generate the editing result with a few scribbles or dots provided by a clinician, (2) fast deliver intermediate results to the clinician, and (3) sequentially correct the segmentations from any type of automatic or interactive segmentation methods. Methods: The authors formulate the editing problem as a semisupervised learning problem which can utilize a priori knowledge of training data and also the valuable information from user interactions. Specifically, from a region of interest near the given user interactions, the appropriate training labels, which are well matched with the user interactions, can be locally searched from a training set. With voting from the selected training labels, both confident prostate and background voxels, as well as unconfident voxels can be estimated. To reflect informative relationship between voxels, location-adaptive features are selected from the confident voxels by using regression forest and Fisher separation criterion. Then, the manifold configuration computed in the derived feature space is enforced into the semisupervised learning algorithm. The labels of unconfident voxels are then predicted by regularizing semisupervised learning algorithm. Results: The proposed interactive segmentation method was applied to correct automatic segmentation results of 30 challenging CT images. The correction was conducted three times with different user interactions performed at different time periods, in order to evaluate both the efficiency and the robustness. The automatic segmentation results with the original average Dice similarity coefficient of 0.78 were improved to 0.865–0.872 after conducting 55–59 interactions by using the proposed method, where each editing procedure took less than 3 s. In addition, the proposed method obtained the most consistent editing results with respect to different user interactions, compared to other methods. Conclusions: The proposed method obtains robust editing results with few interactions for various wrong segmentation cases, by selecting the location-adaptive features and further imposing the manifold regularization. The authors expect the proposed method to largely reduce the laborious burdens of manual editing, as well as both the intra- and interobserver variability across clinicians.

07 ISOTOPE AND RADIATION SOURCES↗