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At least 991 records · Page 55
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DOE OSTI2014

Experimental evaluation and basis function optimization of the spatially variant image-space PSF on the Ingenuity PET/MR scanner

Purpose: The Ingenuity time-of-flight (TF) PET/MR is a recently developed hybrid scanner combining the molecular imaging capabilities of PET with the excellent soft tissue contrast of MRI. It is becoming common practice to characterize the system's point spread function (PSF) and understand its variation under spatial transformations to guide clinical studies and potentially use it within resolution recovery image reconstruction algorithms. Furthermore, due to the system's utilization of overlapping and spherical symmetric Kaiser-Bessel basis functions during image reconstruction, its image space PSF and reconstructed spatial resolution could be affected by the selection of the basis function parameters. Hence, a detailed investigation into the multidimensional basis function parameter space is needed to evaluate the impact of these parameters on spatial resolution. Methods: Using an array of 12 × 7 printed point sources, along with a custom made phantom, and with the MR magnet on, the system's spatially variant image-based PSF was characterized in detail. Moreover, basis function parameters were systematically varied during reconstruction (list-mode TF OSEM) to evaluate their impact on the reconstructed resolution and the image space PSF. Following the spatial resolution optimization, phantom, and clinical studies were subsequently reconstructed using representative basis function parameters. Results: Based on the analysis and under standard basis function parameters, the axial and tangential components of the PSF were found to be almost invariant under spatial transformations (∼4 mm) while the radial component varied modestly from 4 to 6.7 mm. Using a systematic investigation into the basis function parameter space, the spatial resolution was found to degrade for basis functions with a large radius and small shape parameter. However, it was found that optimizing the spatial resolution in the reconstructed PET images, while having a good basis function superposition and keeping the image representation error to a minimum, is feasible, with the parameter combination range depending upon the scanner's intrinsic resolution characteristics. Conclusions: Using the printed point source array as a MR compatible methodology for experimentally measuring the scanner's PSF, the system's spatially variant resolution properties were successfully evaluated in image space. Overall the PET subsystem exhibits excellent resolution characteristics mainly due to the fact that the raw data are not under-sampled/rebinned, enabling the spatial resolution to be dictated by the scanner's intrinsic resolution and the image reconstruction parameters. Due to the impact of these parameters on the resolution properties of the reconstructed images, the image space PSF varies both under spatial transformations and due to basis function parameter selection. Nonetheless, for a range of basis function parameters, the image space PSF remains unaffected, with the range depending on the scanner's intrinsic resolution properties.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

SU-C-18A-02: Image-Based Camera Tracking: Towards Registration of Endoscopic Video to CT

Purpose: Endoscopic examinations are routinely performed on head and neck and esophageal cancer patients. However, these images are underutilized for radiation therapy because there is currently no way to register them to a CT of the patient. The purpose of this work is to develop a method to track the motion of an endoscope within a structure using images from standard clinical equipment. This method will be incorporated into a broader endoscopy/CT registration framework. Methods: We developed a software algorithm to track the motion of an endoscope within an arbitrary structure. We computed frame-to-frame rotation and translation of the camera by tracking surface points across the video sequence and utilizing two-camera epipolar geometry. The resulting 3D camera path was used to recover the surrounding structure via triangulation methods. We tested this algorithm on a rigid cylindrical phantom with a pattern spray-painted on the inside. We did not constrain the motion of the endoscope while recording, and we did not constrain our measurements using the known structure of the phantom. Results: Our software algorithm can successfully track the general motion of the endoscope as it moves through the phantom. However, our preliminary data do not show a high degree of accuracy in the triangulation of 3D point locations. More rigorous data will be presented at the annual meeting. Conclusion: Image-based camera tracking is a promising method for endoscopy/CT image registration, and it requires only standard clinical equipment. It is one of two major components needed to achieve endoscopy/CT registration, the second of which is tying the camera path to absolute patient geometry. In addition to this second component, future work will focus on validating our camera tracking algorithm in the presence of clinical imaging features such as patient motion, erratic camera motion, and dynamic scene illumination.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-C-18A-04: 3D Markerless Registration of Lung Based On Coherent Point Drift: Application in Image Guided Radiotherapy

Purpose: This study evaluated a new probabilistic non-rigid registration method called coherent point drift for real time 3D markerless registration of the lung motion during radiotherapy. Method: 4DCT image datasets Dir-lab (www.dir-lab.com) have been used for creating 3D boundary element model of the lungs. For the first step, the 3D surface of the lungs in respiration phases T0 and T50 were segmented and divided into a finite number of linear triangular elements. Each triangle is a two dimensional object which has three vertices (each vertex has three degree of freedom). One of the main features of the lungs motion is velocity coherence so the vertices that creating the mesh of the lungs should also have features and degree of freedom of lung structure. This means that the vertices close to each other tend to move coherently. In the next step, we implemented a probabilistic non-rigid registration method called coherent point drift to calculate nonlinear displacement of vertices between different expiratory phases. Results: The method has been applied to images of 10-patients in Dir-lab dataset. The normal distribution of vertices to the origin for each expiratory stage were calculated. The results shows that the maximum error of registration between different expiratory phases is less than 0.4 mm (0.38 SI, 0.33 mm AP, 0.29 mm RL direction). This method is a reliable method for calculating the vector of displacement, and the degrees of freedom (DOFs) of lung structure in radiotherapy. Conclusions: We evaluated a new 3D registration method for distribution set of vertices inside lungs mesh. In this technique, lungs motion considering velocity coherence are inserted as a penalty in regularization function. The results indicate that high registration accuracy is achievable with CPD. This method is helpful for calculating of displacement vector and analyzing possible physiological and anatomical changes during treatment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-C-18A-05: Registration Accuracy of MR-Based Images to On-Board Megavoltage Cone-Beam CT for Brain Patient Setup

Purpose: To quantify the difference in isocenter shifts when co-registering MR and MR-based pseudo CTs (pCT) with on-board megavoltage conebeam CT (CBCT) images. Methods: Fast Spoiled Gradient Echo MRs were used to generate pCTs (research version of Advantage Sim MD™, GE Healthcare) for ten patients who had prior brain radiotherapy. The planning CT (rCT) for each was co-registered with the MR, and the plan isocenter and two other reference points were transferred to the MR and pCT. CBCT images (with the machine isocenter) from a single treatment day were coregistered with the 3 test images (MR, pCT and rCT), by two observers and by an automated registration algorithm. The reference points were used to calculate patient shifts and rotations from the registrations. The shifts calculated from the test image registrations were compared to each other and to the shifts performed by the therapists who treated the patients on that day. Results: The average difference in absolute value between the isocenter shifts from the MR-, pCT- and rCT-CBCT registrations, and the therapist shifts, were 2.02, 3.01 and 0.89 mm (craniocaudal), 1.14, 1.34 and 0.46 mm (lateral), and 1.37, 3.43 and 1.43 mm (vertical), respectively. The MR- and pCT-CBCT registrations differed by 1.99, and 2.53 mm (craniocaudal), 1.36, and 1.37 mm (lateral), and 0.74 and 2.34 mm (vertical), respectively, from the average rCT-CBCT shifts. On average, differences of 2.39 (craniocaudal), 1.28 (lateral) and 2.84 mm (vertical) were seen between the MR and pCT shifts. Rotations relative to the CBCT coordinate system were on average <2° for the MR and rCT, and <6° for the pCT. Conclusion: In this study, FSPGR MR-CBCT registrations were more precise compared to the pCT-CBCT registrations. For improved accuracy, MR sequences that are optimal for bony anatomy visualization are necessary. GE healthcare has provided a research version of Advantage Sim MD to UCSF. No financial support was provided.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-C-18C-02: Specifcation of X-Ray Projection Angles Which Are Aligned with the Aortic Valve Plane From a Planar Image of a Valvuloplasty Balloon Inflated Across the Aortic Valve

Purpose: Transcatheter aortic valve replacement (TAVR) procedures provide a method to implant a prosthetic aortic valve via a minimallyinvasive, catheter-based procedure. TAVR procedures require use of interventional fluoroscopy c-arm projection angles which are aligned with the aortic valve plane to minimize prosthetic valve positioning error due to x-ray imaging parallax. The purpose of this work is to calculate the continuous range of interventional fluoroscopy c-arm projection angles which are aligned with the aortic valve plane from a single planar image of a valvuloplasty balloon inflated across the aortic valve. Methods: Computational methods to measure the 3D angular orientation of the aortic valve were developed. Required inputs include a planar x-ray image of a known valvuloplasty balloon inflated across the aortic valve and specifications of x-ray imaging geometry from the DICOM header of the image. A-priori knowledge of the species-specific typical range of aortic orientation is required to specify the sign of the angle of the long axis of the balloon with respect to the x-ray beam. The methods were validated ex-vivo and in a live pig. Results: Ex-vivo experiments demonstrated that the angular orientation of a stationary inflated valvuloplasty balloon can be measured with precision less than 1 degree. In-vivo pig experiments demonstrated that cardiac motion contributed to measurement variability, with precision less than 3 degrees. Error in specification of x-ray geometry directly influences measurement accuracy. Conclusion: This work demonstrates that the 3D angular orientation of the aortic valve can be calculated precisely from a planar image of a valvuloplasty balloon inflated across the aortic valve and known x-ray geometry. This method could be used to determine appropriate c-arm angular projections during TAVR procedures to minimize x-ray imaging parallax and thereby minimize prosthetic valve positioning errors.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-D-17A-04: The Impact of Audiovisual Biofeedback On Image Quality During 4D Functional and Anatomic Imaging: Results of a Prospective Clinical Trial

Purpose: The ability of audiovisual (AV) biofeedback to improve breathing regularity has not previously been investigated for functional imaging studies. The purpose of this study was to investigate the impact of AV biofeedback on 4D-PET and 4D-CT image quality in a prospective clinical trial. We hypothesized that motion blurring in 4D-PET images and the number of artifacts in 4D-CT images are reduced using AV biofeedback. Methods: AV biofeedback is a real-time, interactive and personalized system designed to help a patient self-regulate his/her breathing using a patient-specific representative waveform and musical guides. In an IRB-approved prospective clinical trial, 4D-PET and 4D-CT images of 10 lung cancer patients were acquired with AV biofeedback (AV) and free breathing (FB). The 4D-PET images in 6 respiratory bins were analyzed for motion blurring by: (1) decrease of GTVPET and (2) increase of SUVmax in 4-DPET compared to 3D-PET. The 4D-CT images were analyzed for artifacts by: (1) comparing normalized cross correlation-based scores (NCCS); and (2) quantifying a visual assessment score (VAS). A two-tailed paired t-test was used to test the hypotheses. Results: The impact of AV biofeedback on 4D-PET and 4D-CT images varied widely between patients, suggesting inconsistent patient comprehension and capability. Overall, the 4D-PET decrease of GTVPET was 2.0±3.0cm3 with AV and 2.3±3.9cm{sup 3} for FB (p=0.61). The 4D-PET increase of SUVmax was 1.6±1.0 with AV and 1.1±0.8 with FB (p=0.002). The 4D-CT NCCS were 0.65±0.27 with AV and 0.60±0.32 for FB (p=0.32). The 4D-CT VAS was 0.0±2.7 (p=ns). Conclusion: A 10-patient study demonstrated a statistically significant reduction of motion blurring of AV over FB for 1/2 functional 4D-PET imaging metrics. No difference between AV and FB was found for 2 anatomic 4D-CT imaging metrics. Future studies will focus on optimizing the human-computer interface and including patient training sessions for improved comprehension and capability. Supported by NIH/NCI R01 CA 093626, Stanford BioX Interdisciplinary Initiatives Program, NHMRC Australia Fellowship, and Kwanjeong Educational Foundation. GE Healthcare provided the Respiratory Gating Toolbox for 4D-PET image reconstruction. Stanford University owns US patent #E7955270 which is unlicensed to any commercial entity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-D-9A-01: Listmode-Driven Optimal Gating (OG) Respiratory Motion Management: Potential Impact On Quantitative PET Imaging

Purpose: To evaluate the potential impact of listmode-driven amplitude based optimal gating (OG) respiratory motion management technique on quantitative PET imaging. Methods: During the PET acquisitions, an optical camera tracked and recorded the motion of a tool placed on top of patients' torso. PET event data were utilized to detect and derive a motion signal that is directly coupled with a specific internal organ. A radioactivity-trace was generated from listmode data by accumulating all prompt counts in temporal bins matching the sampling rate of the external tracking device. Decay correction for 18F was performed. The image reconstructions using OG respiratory motion management technique that uses 35% of total radioactivity counts within limited motion amplitudes were performed with external motion and radioactivity traces separately with ordered subset expectation maximization (OSEM) with 2 iterations and 21 subsets. Standard uptake values (SUVs) in a tumor region were calculated to measure the effect of using radioactivity trace for motion compensation. Motion-blurred 3D static PET image was also reconstructed with all counts and the SUVs derived from OG images were compared with SUVs from 3D images. Results: A 5.7 % increase of the maximum SUV in the lesion was found for optimal gating image reconstruction with radioactivity trace when compared to a static 3D image. The mean and maximum SUVs on the image that was reconstructed with radioactivity trace were found comparable (0.4 % and 4.5 % increase, respectively) to the values derived from the image that was reconstructed with external trace. Conclusion: The image reconstructed using radioactivity trace showed that the blurring due to the motion was reduced with impact on derived SUVs. The resolution and contrast of the images reconstructed with radioactivity trace were comparable to the resolution and contrast of the images reconstructed with external respiratory traces. Research supported by Siemens.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

SU-D-9A-03: STAMP: Simulator for Texture Analysis in MRI/PET

Purpose: To develop a convenient simulation platform to facilitate PET/MR image analysis with the prospect of gaining a better understanding of the influence of acquisition parameters on PET/MRI textural features. The simulation platform is demonstrated by showing textural variations of a representative case study using different image acquisition parameters. Methods: The simulation platform is composed of MRI simulators JEMRIS and SIMRI to achieve simulations of customized MRI sequences on sample tumor models. The PET simulator GATE is used to get 2D and 3D Monte Carlo acquisitions of voxelized PET sources using a phantom geometry and a customized scanner architecture. The platform incorporates a series of graphical user interfaces written in Matlab. Two GUIs are used to facilitate communication with the simulation executables installed on a computer cluster. A third GUI is used to collect and display the clinical and simulated images, as well as fused PET/MRI images, and perform computation of textural features.To illustrate the capabilities of this platform, one FDG-PET and T1-weighted (T1w) digitized tumor models were generated from clinical images of a soft-tissue sarcoma patient. Numerically simulated MR images were produced using 3 different echo times (TE) and 5 different repetition times (TR). PET 2D images were simulated using an OSEM algorithm with 1 to 32 iterations and a post-reconstruction Gaussian filter of 0, 2, 4 or 6 mm width. Results: STAMP was successfully used to produce numerically simulated FDG-PET and MRI images, and to calculate their corresponding textures. Three typical textures (GLCM-Contrast, GLSZM-ZSV and NGTDM-Coarseness) were found to vary by a range of 45% on average compared to reference scanning conditions in the case of FDG-PET, and by a range of 40% in the case of T1w MRI. Conclusion: We have successfully developed a Matlab-based simulation platform to facilitate PET/MRI texture image analysis for outcome prediction.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-I-07: An Improved Technique for Scatter Correction in PET

Purpose: In positron emission tomography (PET), the single scatter simulation (SSS) algorithm is widely used for scatter estimation in clinical scans. However, bias usually occurs at the essential steps of scaling the computed SSS distribution to real scatter amounts by employing the scatter-only projection tail. The bias can be amplified when the scatter-only projection tail is too small, resulting in incorrect scatter correction. To this end, we propose a novel scatter calibration technique to accurately estimate the amount of scatter using pre-determined scatter fraction (SF) function instead of the employment of scatter-only tail information. Methods: As the SF depends on the radioactivity distribution and the attenuating material of the patient, an accurate theoretical relation cannot be devised. Instead, we constructed an empirical transformation function between SFs and average attenuation coefficients based on a serious of phantom studies with different sizes and materials. From the average attenuation coefficient, the predicted SFs were calculated using empirical transformation function. Hence, real scatter amount can be obtained by scaling the SSS distribution with the predicted SFs. The simulation was conducted using the SimSET. The Siemens Biograph™ 6 PET scanner was modeled in this study. The Software for Tomographic Image Reconstruction (STIR) was employed to estimate the scatter and reconstruct images. The EEC phantom was adopted to evaluate the performance of our proposed technique. Results: The scatter-corrected image of our method demonstrated improved image contrast over that of SSS. For our technique and SSS of the reconstructed images, the normalized standard deviation were 0.053 and 0.182, respectively; the root mean squared errors were 11.852 and 13.767, respectively. Conclusion: We have proposed an alternative method to calibrate SSS (C-SSS) to the absolute scatter amounts using SF. This method can avoid the bias caused by the insufficient tail information and therefore improve the accuracy of scatter estimation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

SU-E-I-30: Image Analysis in Ultrasonography for Diagnosis of Sjoegren's Syndrome Using Dual-Tree Complex Wavelet Transform

Purpose: Sjoegren's syndrome (SS) is an autoimmune disease invading mainly salivary and lacrimal glands. Ultrasonography is used for an initial and non-invasive examination of this disease. However, the ultrasonography diagnosis tends to lack in objectivity and depends on the operator's skills. The purpose of this study is to propose a computer-aided diagnosis (CAD) system for SS based on a dual-tree complex wavelet transform (DT-CWT) and machine learning. Methods: The subjects of this study were 174 patients suspected of having SS at Nagasaki University Hospital and examined with ultrasonography of the parotid glands. Out of these patients, 77 patients were diagnosed with SS by sialography. A region of interest (ROI) of 128 × 128 pixels was set within the parotid gland that was indicated by a dental radiologist. The DT-CWT was applied to the images in the ROI and every image was decomposed into 72 sub-images of the real and imaginary components in six different resolution levels and six orientations. The statistical features of the sub-image were calculated and used as data input for the support vector machine (SVM) classifier for the detection of SS. A ten-fold cross-validation was employed to verify the Resultof SVM. The accuracy of diagnosis was compared by a CAD system with a human observer performance. Results: The sensitivity, specificity, and accuracy in the detection of SS were 95%, 86%, and 91% through our CAD system respectively, while those by a human observer were 84%, 81%, and 83% respectively. Conclusion: The proposed computer-aided diagnosis system for Sjoegren's syndrome in ultrasonography based on dual-tree complex wavelet transform had a better performance than a human observer.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-I-72: First Experimental Study of On-Board CBCT Imaging Using 2.5MV Beam On a Radiotherapy Linac

Purpose: Varian TrueBeam version 2.0 comes with a new inline 2.5MV beam modality for image guided patient setup. In this work we develop an iterative volumetric image reconstruction technique specific to the beam and investigate the possibility of obtaining metal artifact free CBCT images using the new imaging modality. Methods: An iterative reconstruction algorithm with a sparse representation constraint based on dictionary learning is developed, in which both sparse projection and low dose rate (10 MU/min) are considered. Two CBCT experiments were conducted using the newly available 2.5MV beam on a Varian TrueBeam linac. First, a Rando anthropomorphic head phantom with and without a copper bar inserted in the center was scanned using both 2.5MV and kV (100kVp) beams. In a second experiment, an MRI phantom with many coils was scanned using 2.5MV, 6MV, and kV (100kVp) beams. Imaging dose and the resultant image quality is studied. Results: Qualitative assessment suggests that there were no visually detectable metal artifacts in MV CBCT images, compared with significant metal artifacts in kV CBCT images, especially in the MRI phantom. For a region near the metal object in the head phantom, the 2.5MV CBCT gave a more accurate quantification of the electron density compared with kV CBCT, with a ∼50% reduction in mean HU error. As expected, the contrast between bone and soft-tissue in 2.5MV CBCT decreased compared with kV CBCT. Conclusion: On-board CBCT imaging with the new 2.5MV beam can effectively reduce metal artifacts, although with a reduced softtissue contrast. Combination of kV and MV scanning may lead to metal artifact free CBCT images with uncompromised soft-tissue contrast.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-I-93: Improved Imaging Quality for Multislice Helical CT Via Sparsity Regularized Iterative Image Reconstruction Method Based On Tensor Framelet

Purpose: Inspired by compressive sensing, sparsity regularized iterative reconstruction method has been extensively studied. However, its utility pertinent to multislice helical 4D CT for radiotherapy with respect to imaging quality, dose, and time has not been thoroughly addressed. As the beginning of such an investigation, this work carries out the initial comparison of reconstructed imaging quality between sparsity regularized iterative method and analytic method through static phantom studies using a state-of-art 128-channel multi-slice Siemens helical CT scanner. Methods: In our iterative method, tensor framelet (TF) is chosen as the regularization method for its superior performance from total variation regularization in terms of reduced piecewise-constant artifacts and improved imaging quality that has been demonstrated in our prior work. On the other hand, X-ray transforms and its adjoints are computed on-the-fly through GPU implementation using our previous developed fast parallel algorithms with O(1) complexity per computing thread. For comparison, both FDK (approximate analytic method) and Katsevich algorithm (exact analytic method) are used for multislice helical CT image reconstruction. Results: The phantom experimental data with different imaging doses were acquired using a state-of-art 128-channel multi-slice Siemens helical CT scanner. The reconstructed image quality was compared between TF-based iterative method, FDK and Katsevich algorithm with the quantitative analysis for characterizing signal-to-noise ratio, image contrast, and spatial resolution of high-contrast and low-contrast objects. Conclusion: The experimental results suggest that our tensor framelet regularized iterative reconstruction algorithm improves the helical CT imaging quality from FDK and Katsevich algorithm for static experimental phantom studies that have been performed.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-I-96: A Study About the Influence of ROI Variation On Tumor Segmentation in PET

Purpose: To study the influence of different regions of interest (ROI) on tumor segmentation in PET. Methods: The experiments were conducted on a cylindrical phantom. Six spheres with different volumes (0.5ml, 1ml, 6ml, 12ml, 16ml and 20 ml) were placed inside a cylindrical container to mimic tumors of different sizes. The spheres were filled with 11C solution as sources and the cylindrical container was filled with 18F-FDG solution as the background. The phantom was continuously scanned in a Biograph-40 True Point/True View PET/CT scanner, and 42 images were reconstructed with source-to-background ratio (SBR) ranging from 16:1 to 1.8:1. We took a large and a small ROI for each sphere, both of which contain the whole sphere and does not contain any other spheres. Six other ROIs of different sizes were then taken between the large and the small ROI. For each ROI, all images were segmented by eitht thresholding methods and eight advanced methods, respectively. The segmentation results were evaluated by dice similarity index (DSI), classification error (CE) and volume error (VE). The robustness of different methods to ROI variation was quantified using the interrun variation and a generalized Cohen's kappa. Results: With the change of ROI, the segmentation results of all tested methods changed more or less. Compared with all advanced methods, thresholding methods were less affected by the ROI change. In addition, most of the thresholding methods got more accurate segmentation results for all sphere sizes. Conclusion: The results showed that the segmentation performance of all tested methods was affected by the change of ROI. Thresholding methods were more robust to this change and they can segment the PET image more accurately. This work was supported in part by National Natural Science Foundation of China (NNSFC), under Grant Nos. 60971112 and 61375018, and Fundamental Research Funds for the Central Universities, under Grant No. 2012QN086. Wei Lu was supported in part by the National Institutes of Health (NIH) Grant No. R01 CA172638.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-I-99: Estimation of Effective Charge Distribution by Dual-Energy CT Reconstruction

Purpose: Computed Tomography (CT) is a method to produce slice image of specific volume from the scanned x-ray projection images. The contrast of CT image is correlated with the attenuation coefficients of the x-ray in the object. The attenuation coefficient is strongly dependent on the x-ray energy and the effective charge of the material. The purpose of this presentation is to show the effective charge distribution predicted by CT images reconstructed with kilovoltage(kV) and megavoltage(MV) x-ray energy. Methods: The attenuation coefficients of x-ray can be characterized by cross section of photoionization and Compton scattering for the specific xray energy. In particular, the photoionization cross section is strongly correlated with the effective charge of the object. Hence we can calculate effective charge by solving the coupled equation between the attenuation coefficient and the theoretical cross section. For this study, we use the megavoltage (MV) and kilovoltage (kV) x-rays of Elekta Synergy as the dual source x-ray, and CT image of the Phantom Laboratory CatPhan is reconstructed by the filtered back projection (FBP) and iterative algorithm for cone-beam CT (CBCT). Results: We report attenuation coefficients of each component of the CatPhan specified by each x-ray source. Also the effective charge distribution is evaluated by the MV and kV dual x-ray sources. The predicted effective charges are comparable with the nominal ones. Conclusion: We developed the MV and kV dual-source CBCT reconstruction to yield the effective charge distribution. For more accuracy, it is critical to remove an effect of the scattering photon in the CBCT reconstruction algorithm. The finding will be fine reference of the effective charge of tissue and lead to the more realistic absorbed-dose calculation. This work was partly supported by the JSPS Core-to-Core Program(No. 23003), and this work was partly supported by JSPS KAKENHI 24234567.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

SU-E-I-100: Heterogeneity Studying for Primary and Lymphoma Tumors by Using Multi-Scale Image Texture Analysis with PET-CT Images

Purpose: The purpose of this research is studying tumor heterogeneity of the primary and lymphoma by using multi-scale texture analysis with PET-CT images, where the tumor heterogeneity is expressed by texture features. Methods: Datasets were collected from 12 lung cancer patients, and both of primary and lymphoma tumors were detected with all these patients. All patients underwent whole-body 18F-FDG PET/CT scan before treatment.The regions of interest (ROI) of primary and lymphoma tumor were contoured by experienced clinical doctors. Then the ROI of primary and lymphoma tumor is extracted automatically by using Matlab software. According to the geometry size of contour structure, the images of tumor are decomposed by multi-scale method.Wavelet transform was performed on ROI structures within images by L layers sampling, and then wavelet sub-bands which have the same size of the original image are obtained. The number of sub-bands is 3L+1.The gray level co-occurrence matrix (GLCM) is calculated within different sub-bands, thenenergy, inertia, correlation and gray in-homogeneity were extracted from GLCM.Finally, heterogeneity statistical analysis was studied for primary and lymphoma tumor using the texture features. Results: Energy, inertia, correlation and gray in-homogeneity are calculated with our experiments for heterogeneity statistical analysis.Energy for primary and lymphomatumor is equal with the same patient, while gray in-homogeneity and inertia of primaryare 2.59595±0.00855, 0.6439±0.0007 respectively. Gray in-homogeneity and inertia of lymphoma are 2.60115±0.00635, 0.64435±0.00055 respectively. The experiments showed that the volume of lymphoma is smaller than primary tumor, but thegray in-homogeneity and inertia were higher than primary tumor with the same patient, and the correlation with lymphoma tumors is zero, while the correlation with primary tumor isslightly strong. Conclusion: This studying showed that there were effective heterogeneity differences between primary and lymphoma tumor by multi-scale image texture analysis. This work is supported by National Natural Science Foundation of China (No. 61201441), Research Fund for Excellent Young and Middle-aged Scientists of Shandong Province (No. BS2012DX038), Project of Shandong Province Higher Educational Science and Technology Program (No. J12LN23), Jinan youth science and technology star (No.20120109)

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

SU-E-J-01: 3D Fluoroscopic Image Estimation From Patient-Specific 4DCBCT-Based Motion Models

Purpose: 3D motion modeling derived from 4DCT images, taken days or weeks before treatment, cannot reliably represent patient anatomy on the day of treatment. We develop a method to generate motion models based on 4DCBCT acquired at the time of treatment, and apply the model to estimate 3D time-varying images (referred to as 3D fluoroscopic images). Methods: Motion models are derived through deformable registration between each 4DCBCT phase, and principal component analysis (PCA) on the resulting displacement vector fields. 3D fluoroscopic images are estimated based on cone-beam projections simulating kV treatment imaging. PCA coefficients are optimized iteratively through comparison of these cone-beam projections and projections estimated based on the motion model. Digital phantoms reproducing ten patient motion trajectories, and a physical phantom with regular and irregular motion derived from measured patient trajectories, are used to evaluate the method in terms of tumor localization, and the global voxel intensity difference compared to ground truth. Results: Experiments included: 1) assuming no anatomic or positioning changes between 4DCT and treatment time; and 2) simulating positioning and tumor baseline shifts at the time of treatment compared to 4DCT acquisition. 4DCBCT were reconstructed from the anatomy as seen at treatment time. In case 1) the tumor localization error and the intensity differences in ten patient were smaller using 4DCT-based motion model, possible due to superior image quality. In case 2) the tumor localization error and intensity differences were 2.85 and 0.15 respectively, using 4DCT-based motion models, and 1.17 and 0.10 using 4DCBCT-based models. 4DCBCT performed better due to its ability to reproduce daily anatomical changes. Conclusion: The study showed an advantage of 4DCBCT-based motion models in the context of 3D fluoroscopic images estimation. Positioning and tumor baseline shift uncertainties were mitigated by the 4DCBCT-based motion models, while they caused errors when using 4DCT-based motion models. Partially funded by Varian research grant.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-J-02: 4D Digital Tomosynthesis Based On Algebraic Image Reconstruction and Total-Variation Minimization for the Improvement of Image Quality

Purpose: In this paper, we implemented the four-dimensional (4D) digital tomosynthesis (DTS) imaging based on algebraic image reconstruction technique and total-variation minimization method in order to compensate the undersampled projection data and improve the image quality. Methods: The projection data were acquired as supposed the cone-beam computed tomography system in linear accelerator by the Monte Carlo simulation and the in-house 4D digital phantom generation program. We performed 4D DTS based upon simultaneous algebraic reconstruction technique (SART) among the iterative image reconstruction technique and total-variation minimization method (TVMM). To verify the effectiveness of this reconstruction algorithm, we performed systematic simulation studies to investigate the imaging performance. Results: The 4D DTS algorithm based upon the SART and TVMM seems to give better results than that based upon the existing method, or filtered-backprojection. Conclusion: The advanced image reconstruction algorithm for the 4D DTS would be useful to validate each intra-fraction motion during radiation therapy. In addition, it will be possible to give advantage to real-time imaging for the adaptive radiation therapy. This research was supported by Leading Foreign Research Institute Recruitment Program (Grant No.2009-00420) and Basic Atomic Energy Research Institute (BAERI); (Grant No. 2009-0078390) through the National Research Foundation of Korea(NRF) funded by the Ministry of Science, ICT and Future Planning (MSIP)

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

SU-E-J-10: A Moving-Blocker-Based Strategy for Simultaneous Megavoltage and Kilovoltage Scatter Correction in Cone-Beam Computed Tomography Image Acquired During Volumetric Modulated Arc Therapy

Purpose: To evaluate a moving-blocker-based approach in estimating and correcting megavoltage (MV) and kilovoltage (kV) scatter contamination in kV cone-beam computed tomography (CBCT) acquired during volumetric modulated arc therapy (VMAT). Methods: XML code was generated to enable concurrent CBCT acquisition and VMAT delivery in Varian TrueBeam developer mode. A physical attenuator (i.e., “blocker”) consisting of equal spaced lead strips (3.2mm strip width and 3.2mm gap in between) was mounted between the x-ray source and patient at a source to blocker distance of 232mm. The blocker was simulated to be moving back and forth along the gantry rotation axis during the CBCT acquisition. Both MV and kV scatter signal were estimated simultaneously from the blocked regions of the imaging panel, and interpolated into the un-blocked regions. Scatter corrected CBCT was then reconstructed from un-blocked projections after scatter subtraction using an iterative image reconstruction algorithm based on constraint optimization. Experimental studies were performed on a Catphan 600 phantom and an anthropomorphic pelvis phantom to demonstrate the feasibility of using moving blocker for MV-kV scatter correction. Results: MV scatter greatly degrades the CBCT image quality by increasing the CT number inaccuracy and decreasing the image contrast, in addition to the shading artifacts caused by kV scatter. The artifacts were substantially reduced in the moving blocker corrected CBCT images in both Catphan and pelvis phantoms. Quantitatively, CT number error in selected regions of interest reduced from 377 in the kV-MV contaminated CBCT image to 38 for the Catphan phantom. Conclusions: The moving-blockerbased strategy can successfully correct MV and kV scatter simultaneously in CBCT projection data acquired with concurrent VMAT delivery. This work was supported in part by a grant from the Cancer Prevention and Research Institute of Texas (RP130109) and a grant from the American Cancer Society (RSG-13-326-01-CCE)

60 APPLIED LIFE SCIENCES↗