Engineering topics

Xing, L

Publications and source records attributed to Xing, L.

At least 19 records

DOE OSTI2016

SU-C-BRC-03: Development of a Novel Strategy for On-Demand Monte Carlo and Deterministic Dose Calculation Treatment Planning and Optimization for External Beam Photon and Particle Therapy

Purpose: Accurate and fast dose calculation is a prerequisite of precision radiation therapy in modern photon and particle therapy. While Monte Carlo (MC) dose calculation provides high dosimetric accuracy, the drastically increased computational time hinders its routine use. Deterministic dose calculation methods are fast, but problematic in the presence of tissue density inhomogeneity. We leverage the useful features of deterministic methods and MC to develop a hybrid dose calculation platform with autonomous utilization of MC and deterministic calculation depending on the local geometry, for optimal accuracy and speed. Methods: Our platform utilizes a Geant4 based “localized Monte Carlo” (LMC) method that isolates MC dose calculations only to volumes that have potential for dosimetric inaccuracy. In our approach, additional structures are created encompassing heterogeneous volumes. Deterministic methods calculate dose and energy fluence up to the volume surfaces, where the energy fluence distribution is sampled into discrete histories and transported using MC. Histories exiting the volume are converted back into energy fluence, and transported deterministically. By matching boundary conditions at both interfaces, deterministic dose calculation account for dose perturbations “downstream” of localized heterogeneities. Hybrid dose calculation was performed for water and anthropomorphic phantoms. Results: We achieved <1% agreement between deterministic and MC calculations in the water benchmark for photon and proton beams, and dose differences of 2%–15% could be observed in heterogeneous phantoms. The saving in computational time (a factor ∼4–7 compared to a full Monte Carlo dose calculation) was found to be approximately proportional to the volume of the heterogeneous region. Conclusion: Our hybrid dose calculation approach takes advantage of the computational efficiency of deterministic method and accuracy of MC, providing a practical tool for high performance dose calculation in modern RT. The approach is generalizable to all modalities where heterogeneities play a large role, notably particle therapy.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-C-206-01: Impact of Charge Sharing Effect On Sub-Pitch Resolution for CZT-Based Photon Counting CT Systems

Purposes: Photon counting CT is a new imaging technology that can provide tissue composition information such as calcium/iodine content quantification. Cadmium zinc telluride CZT is considered a good candidate the photon counting CT due to its relatively high atomic number and band gap. One potential challenge is the degradation of both spatial and energy resolution as the fine electrode pitch is deployed (<50 µm). We investigated the extent of charge sharing effect as functions of gap width, bias voltage and depth-of-interaction (DOI). Methods: The initial electron cloud size and diffusion process were modeled analytically. The valid range of charge sharing effect refers to the range over which both signals of adjacent electrodes are above the triggering threshold (10% of the amplitude of 60keV X-ray photons). The intensity ratios of output in three regions (I1/I2/I3: left pixel, gap area and right pixel) were calculated. With Gaussian white noises modeled (a SNR of 5 based upon the preliminary experiments), the sub-pitch resolution as a function of the spatial position in-between two pixels was studied. Results: The valid range of charge sharing increases linearly with depth-of-interaction (DOI) but decreases with gap width and bias voltage. For a 1.5mm thickness CZT detector (pitch: 50µm, bias: 400 V), the range increase from ∼90µm up to ∼110µm. Such an increase can be attributed to a longer travel distance and the associated electron cloud broadening. The achievable sub-pitch resolution is in the range of ∼10–30µm. Conclusion: The preliminary results demonstrate that sub-pixel spatial resolution can be achieved using the ratio of amplitudes of two neighboring pixels. Such ratio may also be used to correct charge loss and help improve energy resolution of a CZT detector. The impact of characteristic X-rays hitting adjacent pixels (i.e., multiple interaction) on charge sharing is currently being investigated.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2016

SU-D-BRA-07: Applications of Combined KV/MV CBCT Imaging with a High-DQE MV Detector

Purpose: To investigate whether a high detection quantum efficiency (DQE) MV detector makes combined kV/MV CBCT clinically practical. Methods: Combined kV/MV CBCT was studied for scan time reduction (STR) and metal artifact reduction (MAR). 6MV CBCT data (dose rate = 0.017 MU/degree) were collected using 1) a novel focused pixelated cadmium tungstate (CWO) scintillator (15mm thickness, DQE(0) = 22%, 0.784mm pixel pitch) coupled to a flat panel imager, and 2) a commercial portal imager with a 133mg/cm{sup 2} gadolinium oxysulfide (GOS) screen (DQE(0) = 1.2%). The 100kVp data were acquired using a commercial imager employing a columnar cesium iodide scintillator (DQE(0) = 70%) with a dose rate of 0.0016 cGy/degree. For STR, MV and kV projections spanning 105° were combined to constitute a complete CBCT scan. Total dose was ∼2cGy and acquisition time was 18s. For MAR, only the metalcorrupted pixels in the kV projections were replaced with MV data resulting in a total dose of less than 1cGy for a 360° scan. Image quality was assessed using an 18-cm diameter electron density phantom with nine tissue inserts, some of which were replaced with steel rods for MAR studies. Results: The CWO contrast-to-noise ratio (CNR) was ∼4.0x higher than the GOS CNR and was ∼4.8x lower than the kV CNR when normalized for dose. When CWO MV data were combined with kV data for STR, all contrast inserts were visible, but only two were detectable in the composite kV/GOS image. Metal artifacts were greatly reduced using the kV/MV MAR technique with all contrast inserts clearly visible in the composite kV/CWO image but only two inserts visible in the composite kV/GOS image. Conclusion: We have demonstrated that a high DQE MV detector significantly improves kV/MV CBCT image quality thus enabling scan time reduction and metal artifact reduction without a severe dose penalty. AW and JS-L are employees of Varian, RF is an employee of Siemens.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-I-12: Region-Specific Dictionary Learning for Low-Dose X-Ray CT Reconstruction

Purpose: Dictionary learning based method has attracted more and more attentions in low-dose CT due to the superior performance on suppressing noise and preserving structural details. Considering the structures and noise vary from region to region in one imaging object, we propose a region-specific dictionary learning method to improve the low-dose CT reconstruction. Methods: A set of normal-dose images was used for dictionary learning. Segmentations were performed on these images, so that the training patch sets corresponding to different regions can be extracted out. After that, region-specific dictionaries were learned from these training sets. For the low-dose CT reconstruction, a conventional reconstruction, such as filtered back-projection (FBP), was performed firstly, and then segmentation was followed to segment the image into different regions. Sparsity constraints of each region based on its dictionary were used as regularization terms. The regularization parameters were selected adaptively according to different regions. A low-dose human thorax dataset was used to evaluate the proposed method. The single dictionary based method was performed for comparison. Results: Since the lung region is very different from the other part of thorax, two dictionaries corresponding to lung region and the rest part of thorax respectively were learned to better express the structural details and avoid artifacts. With only one dictionary some artifact appeared in the body region caused by the spot atoms corresponding to the structures in the lung region. And also some structure in the lung regions cannot be recovered well by only one dictionary. The quantitative indices of the result by the proposed method were also improved a little compared to the single dictionary based method. Conclusion: Region-specific dictionary can make the dictionary more adaptive to different region characteristics, which is much desirable for enhancing the performance of dictionary learning based method.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-I-41: Calibration-Free Material Decomposition for Dual-Energy CT

Purpose: To eliminate tedious phantom calibration or manually region of interest (ROI) selection as required in dual-energy CT material decomposition, we establish a new projection-domain material decomposition framework with incorporation of energy spectrum. Methods: Similar to the case of dual-energy CT, the integral of the basis material image in our model is expressed as a linear combination of basis functions, which are the polynomials of high- and low-energy raw projection data. To yield the unknown coefficients of the linear combination, the proposed algorithm minimizes the quadratic error between the high- and low-energy raw projection data and the projection calculated using material images. We evaluate the algorithm with an iodine concentration numerical phantom at different dose and iodine concentration levels. The x-ray energy spectra of the high and low energy are estimated using an indirect transmission method. The derived monochromatic images are compared with the high- and low-energy CT images to demonstrate beam hardening artifacts reduction. Quantitative results were measured and compared to the true values. Results: The differences between the true density value used for simulation and that were obtained from the monochromatic images, are 1.8%, 1.3%, 2.3%, and 2.9% for the dose levels from standard dose to 1/8 dose, and are 0.4%, 0.7%, 1.5%, and 1.8% for the four iodine concentration levels from 6 mg/mL to 24 mg/mL. For all of the cases, beam hardening artifacts, especially streaks shown between dense inserts, are almost completely removed in the monochromatic images. Conclusion: The proposed algorithm provides an effective way to yield material images and artifacts-free monochromatic images at different dose levels without the need for phantom calibration or ROI selection. Furthermore, the approach also yields accurate results when the concentration of the iodine concentrate insert is very low, suggesting the algorithm is robust with respect to the low-contrast scenario.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-J-140: Using Handheld Stereo Depth Cameras to Extend Medical Imaging for Radiation Therapy Planning

Purpose: A correct body contour is essential for the accuracy of dose calculation in radiation therapy. While modern medical imaging technologies provide highly accurate representations of body contours, there are times when a patient’s anatomy cannot be fully captured or there is a lack of easy access to CT/MRI scanning. Recently, handheld cameras have emerged that are capable of performing three dimensional (3D) scans of patient surface anatomy. By combining 3D camera and medical imaging data, the patient’s surface contour can be fully captured. Methods: A proof-of-concept system matches a patient surface model, created using a handheld stereo depth camera (DC), to the available areas of a body contour segmented from a CT scan. The matched surface contour is then converted to a DICOM structure and added to the CT dataset to provide additional contour information. In order to evaluate the system, a 3D model of a patient was created by segmenting the body contour with a treatment planning system (TPS) and fabricated with a 3D printer. A DC and associated software were used to create a 3D scan of the printed phantom. The surface created by the camera was then registered to a CT model that had been cropped to simulate missing scan data. The aligned surface was then imported into the TPS and compared with the originally segmented contour. Results: The RMS error for the alignment between the camera and cropped CT models was 2.26 mm. Mean distance between the aligned camera surface and ground truth model was −1.23 +/−2.47 mm. Maximum deviations were < 1 cm and occurred in areas of high concavity or where anatomy was close to the couch. Conclusion: The proof-of-concept study shows an accurate, easy and affordable method to extend medical imaging for radiation therapy planning using 3D cameras without additional radiation. Intel provided the camera hardware used in this study.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-J-212: Enabling Conventional Cone Beam CT with the Capability of Dual Energy Imaging Using a Simple Add-On Beam Modifier

Purpose: In searching for a robust, efficient and cost-effective dual energy cone beam CT (DECBCT) solution for various radiation oncology applications, in particularly for improved proton dose planning/replanning accuracy and DE-CBCT guided radiation therapy, we investigate a novel energy modulation scheme using a beam modifier placed between the source and patient and optimize its geometric configuration for routine clinical use. Methods: The study was performed using a Hitachi CBCT scanner and the tube voltage was set at 125 kVp. The higher energy beam was obtained by filtering the incident utilizing a beam modulation layer (material: copper, thickness: 1.8 mm). To avoid the need for double scans (one with and one without the energy modulator), the modulation layer was configured to cover only the half of the X-ray beam so that two sets of sinograms corresponding low and high energies were collected after a single gantry rotation of 360 deg. The average high energy and low energy HU numbers (HUhigh and HUlow) were derived for pixels in a defined region-of-interest, respectively. Results: The beam modifier increased the threshold of the energy spectrum from ∼20 keV up to ∼50 keV. Two complete sets of images were obtained with good alignment between the high energy and low-energy cases without any artifact observed (Fig. 2). The HUlow/HUhigh is ∼0/0 (water), ∼394/238 (brain), ∼1283/1085 (cortical bone) and ∼3000/1800 (titanium). Conclusion: The feasibility of the proposed DECT implementation using a beam modifier has been demonstrated. Compared to the existing DECT solutions, the proposed scheme is much more cost-effective and requires minimum hardware modification. The work lays foundation for us to study the quantification of HU values to derive material density images and atomic number (and electron density) of substances.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-J-213: Feasibility Study of Using a Dual-Energy Cone Beam CT (DECBCT) in Proton Therapy Treatment Planning

Purpose: The aim of this study is to evaluate the feasibility of using a dual-energy CBCT (DECBCT) in proton therapy treatment planning to allow for accurate electron density estimation. Methods: For direct comparison, two scenarios were selected: a dual-energy fan-beam CT (high: 140 kVp, low: 80 kVp) and a DECBCT (high: 125 kVp, low: 80 kVp). A Gammex 467 tissue characterization phantom was used, including the rods of air, water, bone (B2–30% mineral), cortical bone (SB3), lung (LN-300), brain, liver and adipose. For the CBCT, Hounsfield Unit (HU) numbers were first obtained from the reconstructed images after a calibration was made based on water (=0) and air materials (=−1000). For each tissue surrogate, region-of-interest (ROI) analyses were made to derive high-energy and low-energy HU values (HUhigh and HUlow), which were subsequently used to estimate electron density based on the algorithm as previously described by Hunemohr N., et al. Parameters k1 and k2 are energy dependent and can be derived from calibration materials. Results: While for the dual-energy FBCT, the electron density is found be within +/−3% error relative to the values provided by the phantom vendor: −1.8% (water), 0.03% (lung), 1.1% (brain), −2.82% (adipose), −0.49% (liver) and −1.89% (cortical bones). While for the DECBCT, the estimation of electron density exhibits a relatively larger variation: −1.76% (water), −36.7% (lung), −1.92% (brain), −3.43% (adipose), 8.1% (liver) and 9.5% (cortical bones). Conclusion: For DECBCT, the accuracy of electron density estimation is inferior to that of a FBCT, especially for materials of either low-density (lung) or high density (cortical bone) compared to water. Such limitation arises from inaccurate HU number derivation in a CBCT. Advanced scatter-correction and HU calibration routines, as well as the deployment of photon counting CT detectors need be investigated to minimize the difference between FBCT and CBCT.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-T-340: Direct Editing of Dose Volume Histograms: Algorithms and a Unified Convex Formulation for Treatment Planning with Dose Constraints

Purpose: To develop a procedure for including dose constraints in convex programming-based approaches to treatment planning, and to support dynamic modification of such constraints during planning. Methods: We present a mathematical approach that allows mean dose, maximum dose, minimum dose and dose volume (i.e., percentile) constraints to be appended to any convex formulation of an inverse planning problem. The first three constraint types are convex and readily incorporated. Dose volume constraints are not convex, however, so we introduce a convex restriction that is related to CVaR-based approaches previously proposed in the literature. To compensate for the conservatism of this restriction, we propose a new two-pass algorithm that solves the restricted problem on a first pass and uses this solution to form exact constraints on a second pass. In another variant, we introduce slack variables for each dose constraint to prevent the problem from becoming infeasible when the user specifies an incompatible set of constraints. We implement the proposed methods in Python using the convex programming package cvxpy in conjunction with the open source convex solvers SCS and ECOS. Results: We show, for several cases taken from the clinic, that our proposed method meets specified constraints (often with margin) when they are feasible. Constraints are met exactly when we use the two-pass method, and infeasible constraints are replaced with the nearest feasible constraint when slacks are used. Finally, we introduce ConRad, a Python-embedded free software package for convex radiation therapy planning. ConRad implements the methods described above and offers a simple interface for specifying prescriptions and dose constraints. Conclusion: This work demonstrates the feasibility of using modifiable dose constraints in a convex formulation, making it practical to guide the treatment planning process with interactively specified dose constraints. This work was supported by the Stanford BioX Graduate Fellowship and NIH Grant 5R01CA176553.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-T-503: Trajectory Modulated Arc Therapy of Intracranial Lesions: Development of a Standardized Path-Based Technique for Fully Dynamic Couch-Gantry Modulated Treatments

Purpose: The integration of couch motion during arc delivery is necessitated to enable irradiation trajectories such as coronal arcs, and to enhance the geometrical sampling for dynamic deliveries to the highest extent. To enable such capability, a platform of Trajectory Modulated Arc Therapy (TMAT) is developed in conjunction with standardized noncollisional dynamic path-set for irradiation of intracranial lesions. Methods: A generalized path-set was constructed through the combination of sagittal arcs (45 degrees from the CAX), axial arcs, and coronal arcs produced through modulation of the dynamic rotation of couch. The standardized path was implemented in a contiguous manner enabling the formation of fully automated sub-trajectories to provide maximal geometrical convergence with minimal number of arcs. Progressive sampling technique is used for direct aperture optimization of the MLCs and the selection of couch positions across the control points. Dosimetry of the resulting plans was assessed relative to clinically delivered plans. Using the TrueBeam Developer Mode, plan deliverability was tested. Results: Treatment planning of TMAT sub-trajectories for central, anterior and posterior tumor sites with volumes ranging from 4.75cc to 107cc demonstrated radically reduced doses to the critical OARs when compared to the clinically treated VMAT. Specifically, percentage reduction in mean dose for critical organs such as brainstem, cochlea, and optic nerve are found to be as low as 74±15%, 50±26% and 74±30% respectively as compared to VMAT. Conformity Index, defined as the ratio of tumor volume (VPTV) and 100% dose volume (V(D100%)), was reduced up to 12% while the Gradient Index, defined as V(D100%)/V(D50%), was concurrently improved by up to 14%. Conclusion: An automated standardized trajectory with dynamically modulated couch-gantry arcs has been developed for intracranial radiotherapy. Through the incorporation of coronal arcs, it is demonstrated that significantly reduced OAR doses can be achieved relative to clinically treated patient plans via VMAT. Research Grant Funding Support by Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-G-201-03: Automation of High Dose Rate Brachytherapy Quality Assurance: Development of a Radioluminescent Detection System for Simultaneous Detection of Activity, Timing, and Positioning

Purpose: Accuracy of positioning, timing and activity is of critical importance for High Dose Rate (HDR) brachytherapy delivery. Respective measurements via film autoradiography, stop-watches and well chambers can be cumbersome, crude or lack dynamic source evaluation capabilities. To address such limitations, a single device radioluminescent detection system enabling automated real-time quantification of activity, position and timing accuracy is presented and experimentally evaluated. Methods: A radioluminescent sheet was fabricated by mixing Gd?O?S:Tb with PDMS and incorporated into a 3D printed device where it was fixated below a CMOS digital camera. An Ir-192 HDR source (VS2000, VariSource iX) with an effective active length of 5 mm was introduced using a 17-gauge stainless steel needle below the sheet. Pixel intensity values for determining activity were taken from an ROI centered on the source location. A calibration curve relating intensity values to activity was generated and used to evaluate automated activity determination with data gathered over 6 weeks. Positioning measurements were performed by integrating images for an entire delivery and fitting peaks to the resulting profile. Timing measurements were performed by evaluating source location and timestamps from individual images. Results: Average predicted activity error over 6 weeks was .35 ± .5%. The distance between four dwell positions was determined by the automated system to be 1.99 ± .02 cm. The result from autoradiography was 2.00 ± .03 cm. The system achieved a time resolution of 10 msec and determined the dwell time to be 1.01 sec ± .02 sec. Conclusion: The system was able to successfully perform automated detection of activity, positioning and timing concurrently under a single setup. Relative to radiochromic and radiographic film-based autoradiography, which can only provide a static evaluation positioning, optical detection of temporary radiation induced luminescence enables dynamic detection of position enabling automated quantification of timing with millisecond accuracy.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-G-BRB-10: New Generation of High Frame-Rate and High Spatial-Resolution EPID QA System for Full-Body MLC-Based Robotic Radiosurgery

Purpose: To systematically investigate an ultra-high spatial-resolution amorphous silicon flat-panel electronic portal imaging device (EPID) for MLC-based full-body robotic radiosurgery geometric and dosimetric quality assurance (QA). Methods: The high frame-rate and ultra-high spatial resolution EPID is an outstanding detector for measuring profiles, MLC-shaped radiosurgery field aperture verification, and small field dosimetry. A Monte Carlo based technique with a robotic linac specific response and calibration is developed to convert a raw EPID-measured image of a radiosurgery field into water-based dose distribution. The technique is applied to measure output factors and profiles for 6MV MLC-defined radiosurgery fields with various sizes ranging from 7.6mm×7.7mm to 100mm×100.1mm and the results are compared with the radiosurgery diode scan measurements in water tank. The EPID measured field sizes and the penumbra regions are analyzed to evaluate the MLC positioning accuracy. Results: For all MLC fields, the EPID measured output factors of MLC-shaped fields are in good agreement with the diode measurements. The mean output difference between the EPID and diode measurement is 0.05±0.87%. The max difference is −1.33% for 7.6mm×7.7mm field. The MLC field size derived from the EPID measurements are in good agreement comparing to the diode scan result. For crossline field sizes, the mean difference is −0.17mm±0.14mm with a maximum of −0.35mm for the 30.8mm×30.8mm field. For inline field sizes, the mean difference is +0.08mm±0.18mm with a maximum of +0.45mm for the 100mm×100.1mm field. The high resolution EPID is able to measure the whole radiation field, without the need to align the detector center perfectly at field center as diode or ion chamber measurement. The setup time is greatly reduced so that the whole process is possible for machine and patient-specific QA. Conclusion: The high spatial-resolution EPID is proved to be an accurate and efficient tool for QA of MLC-equipped robotic radiosurgery system.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-G-JeP2-02: A Unifying Multi-Atlas Approach to Electron Density Mapping Using Multi-Parametric MRI for Radiation Treatment Planning

Purpose: MRI has a number of advantages over CT as a primary modality for radiation treatment planning (RTP). However, one key bottleneck problem still remains, which is the lack of electron density information in MRI. In the work, a reliable method to map electron density is developed by leveraging the differential contrast of multi-parametric MRI. Methods: We propose a probabilistic Bayesian approach for electron density mapping based on T1 and T2-weighted MRI, using multiple patients as atlases. For each voxel, we compute two conditional probabilities: (1) electron density given its image intensity on T1 and T2-weighted MR images, and (2) electron density given its geometric location in a reference anatomy. The two sources of information (image intensity and spatial location) are combined into a unifying posterior probability density function using the Bayesian formalism. The mean value of the posterior probability density function provides the estimated electron density. Results: We evaluated the method on 10 head and neck patients and performed leave-one-out cross validation (9 patients as atlases and remaining 1 as test). The proposed method significantly reduced the errors in electron density estimation, with a mean absolute HU error of 138, compared with 193 for the T1-weighted intensity approach and 261 without density correction. For bone detection (HU>200), the proposed method had an accuracy of 84% and a sensitivity of 73% at specificity of 90% (AUC = 87%). In comparison, the AUC for bone detection is 73% and 50% using the intensity approach and without density correction, respectively. Conclusion: The proposed unifying method provides accurate electron density estimation and bone detection based on multi-parametric MRI of the head with highly heterogeneous anatomy. This could allow for accurate dose calculation and reference image generation for patient setup in MRI-based radiation treatment planning.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-G-IeP3-10: Molecular Imaging with Clinical X-Ray Sources and Compton Cameras

Purpose: The application of Compton cameras (CC) is a novel approach translating XFCT to a practical modality realized with clinical CT systems without the restriction of pencil beams. The dual modality design offers additional information without extra patient dose. The purpose of this work is to investigate the feasibility and efficacy of using CCs for volumetric x-ray fluorescence (XF) imaging by Monte Carlo (MC) simulations and statistical image reconstruction. Methods: The feasibility of a CC for imaging x-ray fluorescence emitted from targeted lesions is examined by MC simulations. 3 mm diameter water spheres with various gold concentrations and detector distances are placed inside the lung of an adult human phantom (MIRD) and are irradiated with both fan and cone-beam geometries. A sandwich design CC composed of Silicon and CdTe is used to image the gold nanoparticle distribution. The detection system comprises four 16×26 cm{sup 2} detector panels placed on the chest of a MIRD phantom. Constraints of energy-, spatial-resolution, clinical geometries and Doppler broadening are taken into account. Image reconstruction is performed with a list-mode MLEM algorithm with cone-projector on a GPU. Results: The comparison of reconstruction of cone- and fan-beam excitation shows that the spatial resolution is improved by 23% for fan-beams with significantly decreased processing time. Cone-beam excitation increases scatter content disturbing quantification of lesions near the body surface. Spatial resolution and detectability limit in the center of the lung is 8.7 mm and 20 fM for 50 nm diameter gold nanoparticles at 20 mGy. Conclusion: The implementation of XFCT with a CC is a feasible method for molecular imaging with high atomic number probes. Given constrains of detector resolutions, Doppler broadening, and limited exposure dose, spatial resolutions comparable with PET and molecular sensitivities in the fM range are realizable with current detector technology.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2016

SU-G-IeP4-03: Cone Beam X-Ray Luminescence Computed Tomography Based On Generalized Gaussian Markov Random Field

Purpose: Cone beam X-ray luminescence computed tomography (CB-XLCT), which aims to achieve molecular and functional imaging by X-rays, has recently been proposed as a new imaging modality. However, the inverse problem of CB-XLCT is seriously ill-conditioned, hindering us to achieve good image quality. In this work, a novel reconstruction method based on Bayesian theory is proposed to tackle this problem Methods: Bayesian theory provides a natural framework for utilizing various kinds of available prior information to improve the reconstruction image quality. A generalized Gaussian Markov random field (GGMRF) model is proposed here to construct the prior model of the Bayesian theory. The most important feature of GGMRF model is the adjustable shape parameter p, which can be continuously adjusted from 1 to 2. The reconstruction image tends to have more edge-preserving property when p is slide to 1, while having more noise tolerance property when p is slide to 2, just like the behavior of L1 and L2 regularization methods, respectively. The proposed method provides a flexible regularization framework to adapt to a wide range of applications. Results: Numerical simulations were implemented to test the performance of the proposed method. The Digimouse atlas were employed to construct a three-dimensional mouse model, and two small cylinders were placed inside to serve as the targets. Reconstruction results show that the proposed method tends to obtain better spatial resolution with a smaller shape parameter, while better signal-to-noise image with a larger shape parameter. Quantitative indexes, contrast-to-noise ratio (CNR) and full-width at half-maximum (FWHM), were used to assess the performance of the proposed method, and confirmed its effectiveness in CB-XLCT reconstruction. Conclusion: A novel reconstruction method for CB-XLCT is proposed based on GGMRF model, which enables an adjustable performance tradeoff between L1 and L2 regularization methods. Numerical simulations were conducted to demonstrate its performance.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

MO-DE-207A-05: Dictionary Learning Based Reconstruction with Low-Rank Constraint for Low-Dose Spectral CT

Purpose: Spectral CT enabled by an energy-resolved photon-counting detector outperforms conventional CT in terms of material discrimination, contrast resolution, etc. One reconstruction method for spectral CT is to generate a color image from a reconstructed component in each energy channel. However, given the radiation dose, the number of photons in each channel is limited, which will result in strong noise in each channel and affect the final color reconstruction. Here we propose a novel dictionary learning method for spectral CT that combines dictionary-based sparse representation method and the patch based low-rank constraint to simultaneously improve the reconstruction in each channel and to address the inter-channel correlations to further improve the reconstruction. Methods: The proposed method has two important features: (1) guarantee of the patch based sparsity in each energy channel, which is the result of the dictionary based sparse representation constraint; (2) the explicit consideration of the correlations among different energy channels, which is realized by patch-by-patch nuclear norm-based low-rank constraint. For each channel, the dictionary consists of two sub-dictionaries. One is learned from the average of the images in all energy channels, and the other is learned from the average of the images in all energy channels except the current channel. With average operation to reduce noise, these two dictionaries can effectively preserve the structural details and get rid of artifacts caused by noise. Combining them together can express all structural information in current channel. Results: Dictionary learning based methods can obtain better results than FBP and the TV-based method. With low-rank constraint, the image quality can be further improved in the channel with more noise. The final color result by the proposed method has the best visual quality. Conclusion: The proposed method can effectively improve the image quality of low-dose spectral CT. This work is partially supported by the National Natural Science Foundation of China (No. 61302136), and the Natural Science Basic Research Plan in Shaanxi Province of China (No. 2014JQ8317).

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

MO-DE-207A-09: Low-Dose CT Image Reconstruction Via Learning From Different Patient Normal-Dose Images

Purpose: To investigate a novel low-dose CT (LdCT) image reconstruction strategy for lung CT imaging in radiation therapy. Methods: The proposed approach consists of four steps: (1) use the traditional filtered back-projection (FBP) method to reconstruct the LdCT image; (2) calculate structure similarity (SSIM) index between the FBP-reconstructed LdCT image and a set of normal-dose CT (NdCT) images, and select the NdCT image with the highest SSIM as the learning source; (3) segment the NdCT source image into lung and outside tissue regions via simple thresholding, and adopt multiple linear regression to learn high-order Markov random field (MRF) pattern for each tissue region in the NdCT source image; (4) segment the FBP-reconstructed LdCT image into lung and outside regions as well, and apply the learnt MRF prior in each tissue region for statistical iterative reconstruction of the LdCT image following the penalized weighted least squares (PWLS) framework. Quantitative evaluation of the reconstructed images was based on the signal-to-noise ratio (SNR), local binary pattern (LBP) and histogram of oriented gradients (HOG) metrics. Results: It was observed that lung and outside tissue regions have different MRF patterns predicted from the NdCT. Visual inspection showed that our method obviously outperformed the traditional FBP method. Comparing with the region-smoothing PWLS method, our method has, in average, 13% increase in SNR, 15% decrease in LBP difference, and 12% decrease in HOG difference from reference standard for all regions of interest, which indicated the superior performance of the proposed method in terms of image resolution and texture preservation. Conclusion: We proposed a novel LdCT image reconstruction method by learning similar image characteristics from a set of NdCT images, and the to-be-learnt NdCT image does not need to be scans from the same subject. This approach is particularly important for enhancing image quality in radiation therapy.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

MO-FG-CAMPUS-TeP1-05: Rapid and Efficient 3D Dosimetry for End-To-End Patient-Specific QA of Rotational SBRT Deliveries Using a High-Resolution EPID

Purpose: EPID-based patient-specific quality assurance provides verification of the planning setup and delivery process that phantomless QA and log-file based virtual dosimetry methods cannot achieve. We present a method for EPID-based QA utilizing spatially-variant EPID response kernels that allows for direct calculation of the entrance fluence and 3D phantom dose. Methods: An EPID dosimetry system was utilized for 3D dose reconstruction in a cylindrical phantom for the purposes of end-to-end QA. Monte Carlo (MC) methods were used to generate pixel-specific point-spread functions (PSFs) characterizing the spatially non-uniform EPID portal response in the presence of phantom scatter. The spatially-variant PSFs were decomposed into spatially-invariant basis PSFs with the symmetric central-axis kernel as the primary basis kernel and off-axis representing orthogonal perturbations in pixel-space. This compact and accurate characterization enables the use of a modified Richardson-Lucy deconvolution algorithm to directly reconstruct entrance fluence from EPID images without iterative scatter subtraction. High-resolution phantom dose kernels were cogenerated in MC with the PSFs enabling direct recalculation of the resulting phantom dose by rapid forward convolution once the entrance fluence was calculated. A Delta4 QA phantom was used to validate the dose reconstructed in this approach. Results: The spatially-invariant representation of the EPID response accurately reproduced the entrance fluence with >99.5% fidelity with a simultaneous reduction of >60% in computational overhead. 3D dose for 10{sub 6} voxels was reconstructed for the entire phantom geometry. A 3D global gamma analysis demonstrated a >95% pass rate at 3%/3mm. Conclusion: Our approach demonstrates the capabilities of an EPID-based end-to-end QA methodology that is more efficient than traditional EPID dosimetry methods. Displacing the point of measurement external to the QA phantom reduces the necessary complexity of the phantom itself while offering a method that is highly scalable and inherently generalizable to rotational and trajectory based deliveries. This research was partially supported by Varian.

60 APPLIED LIFE SCIENCES↗