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DOE OSTI2023

A Multi-Fidelity Gaussian Process Regression Method for Probabilistic Wind Farm Power Curve Estimation

Accurate estimation of the power curve for wind turbines or wind farms is crucial to ensure their efficient operation and management. However, conventional methods for power curve estimation rely either on expensive and infrequent measurements or on low-quality numerical simulations. Moreover, the majority of previous studies on power curve estimation for wind turbines or wind farms focused on deterministic estimation, which provides a point estimate of the relationship between wind speed and power generation. Nevertheless, the deterministic approach fails to consider the inherent uncertainty associated with wind energy production resulting from varying turbine characteristics. This can lead to inaccurate power generation estimation and suboptimal decisions regarding energy management. In this paper, a kernel density estimation (KDE) based Multi-Fidelity Gaussian Process Regression (MFGPR) model is proposed to fuse theoretical power curve data and the ground true measurements to create a mapping of wind speed and wind power. By conducting a case study on an actual wind farm in China, the efficacy of the proposed MFGPR model was demonstrated in characterizing the variability of wind power. The probabilistic MFGPR model was also able to generate confidence intervals that encompassed the measured power, thereby improving the accuracy and confidence in wind power estimation or wind resource assessment. Overall, the proposed MFGPR model offers a reliable approach to integrate high-fidelity ground measurements and theoretical power curve data, resulting in precise wind resource assessment and power estimation.

Gaussian process regression↗

DOE OSTI2013

A method for removing arm backscatter from EPID images

Purpose: To develop a method for removing the support arm backscatter from images acquired using current Varian electronic portal imaging devices (EPIDs).Methods: The effect of arm backscatter on EPID images was modeled using a kernel convolution method. The parameters of the model were optimized by comparing on-arm images to off-arm images. The model was used to develop a method to remove the effect of backscatter from measured EPID images. The performance of the backscatter removal method was tested by comparing backscatter corrected on-arm images to measured off-arm images for 17 rectangular fields of different sizes and locations on the imager. The method was also tested using on- and off-arm images from 42 intensity modulated radiotherapy (IMRT) fields.Results: Images generated by the backscatter removal method gave consistently better agreement with off-arm images than images without backscatter correction. For the 17 rectangular fields studied, the root mean square difference of in-plane profiles compared to off-arm profiles was reduced from 1.19% (standard deviation 0.59%) on average without backscatter removal to 0.38% (standard deviation 0.18%) when using the backscatter removal method. When comparing to the off-arm images from the 42 IMRT fields, the mean {gamma} and percentage of pixels with {gamma} < 1 were improved by the backscatter removal method in all but one of the images studied. The mean {gamma} value (1%, 1 mm) for the IMRT fields studied was reduced from 0.80 to 0.57 by using the backscatter removal method, while the mean {gamma} pass rate was increased from 72.2% to 84.6%.Conclusions: A backscatter removal method has been developed to estimate the image acquired by the EPID without any arm backscatter from an image acquired in the presence of arm backscatter. The method has been shown to produce consistently reliable results for a wide range of field sizes and jaw configurations.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2014

Motion as perturbation. II. Development of the method for dosimetric analysis of motion effects with fixed-gantry IMRT

Purpose: In this work, the feasibility of implementing a motion-perturbation approach to accurately estimate volumetric dose in the presence of organ motion—previously demonstrated for VMAT-–is studied for static gantry IMRT. The method's accuracy is improved for the voxels that have very low planned dose but acquire appreciable dose due to motion. The study describes the modified algorithm and its experimental validation and provides an example of a clinical application. Methods: A contoured region-of-interest is propagated according to the predefined motion kernel throughout time-resolved 4D phantom dose grids. This timed series of 3D dose grids is produced by the measurement-guided dose reconstruction algorithm, based on an irradiation of a staticARCCHECK (AC) helical dosimeter array (Sun Nuclear Corp., Melbourne, FL). Each moving voxel collects dose over the dynamic simulation. The difference in dose-to-moving voxel vs dose-to-static voxel in-phantom forms the basis of a motion perturbation correction that is applied to the corresponding voxel in the patient dataset. A new method to synchronize the accelerator and dosimeter clocks, applicable to fixed-gantry IMRT, was developed. Refinements to the algorithm account for the excursion of low dose voxels into high dose regions, causing appreciable dose increase due to motion (LDVE correction). For experimental validation, four plans using TG-119 structure sets and objectives were produced using segmented IMRT direct machine parameters optimization in Pinnacle treatment planning system (v. 9.6, Philips Radiation Oncology Systems, Fitchburg, WI). All beams were delivered with the gantry angle of 0°. Each beam was delivered three times: (1) to the static AC centered on the room lasers; (2) to a static phantom containing a MAPCHECK2 (MC2) planar diode array dosimeter (Sun Nuclear); and (3) to the moving MC2 phantom. The motion trajectory was an ellipse in the IEC XY plane, with 3 and 1.5 cm axes. The period was 5 s, with the resulting average motion speed of 1.45 cm/s. The motion-perturbed high resolution (2 mm voxel) volumetric dose grids on the MC2 phantom were generated for each beam. From each grid, a coronal dose plane at the detector level was extracted and compared to the corresponding moving MC2 measurement, using gamma analysis with both global (G) and local (L) dose-error normalization. Results: Using the TG-119 criteria of (3%G/3 mm), per beam average gamma analysis passing rates exceeded 95% in all cases. No individual beam had a passing rate below 91%. LDVE correction eliminated systematic disagreement patterns at the beams’ aperture edges. In a representative example, application of LDVE correction improved (2%L/2 mm) gamma analysis passing rate for an IMRT beam from 74% to 98%. Conclusions: The effect of motion on the moving region-of-interest IMRT dose can be estimated with a standard, static phantom QA measurement, provided the motion characteristics are independently known from 4D CT or otherwise. The motion-perturbed absolute dose estimates were validated by the direct planar diode array measurements, and were found to reliably agree with them in a homogeneous phantom.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2014

SU-E-T-456: Development of An EPID-Based Output Measurement and Dosimetric Verification Tool for Electron Beam Therapy

Purpose: To develop an efficient and robust method for output and absolute dosimetric measurements of electron beam therapy by using a high spatialresolution and high frame-rate amorphous silicon flat-panel electronic portal imaging device (EPID). Methods: A previously-established EPID dosimetry system was extended to measure the output factors of electron beams of various sizes and their planar dose distributions at reference depths. Specific EPID responses to different electron energies were derived from Monte Carlo (MC) simulations to de-convolve the EPID raw images to the incident electron fluence map. To reconstruct the 2D water-based dose distribution map at reference depths for different energies, the fluence map was further convolved with a MC simulated pencil beam kernel. Different energies of 6, 9, 12, 16, and 20 MeV from a Varian C-series linac were tested. Standard square fields ranging from 2×2 to 15×15 cm{sup 2} were measured and validated against film/ion chamber measurements. Small fields of different patient cases with irregular cutout shapes were also tested. Results: The EPIDmeasured output factors for 2×2, 3×3, 6×6, and 10×10 cm{sup 2} fields with all electron energies agree with the film/ion chamber data within 2.7%. The average discrepancy between EPID and film/ion chamber measurements was 1.4%. The differences for the three patient cases were 0.1%, 2.1%, and 1.6%. Deliveries with different monitor units were tested and the results exhibited good linearity. Measurements with different dose rate showed that the dose rate dependence was less than 1%. Using the proposed method, 2D absolute dose maps were created from the EPID raw images and the results were consistent with film measurements. Conclusion: The efficient data readout and portability of the newly developed EPID system provides an efficient and accurate solution for electron beam therapy. It addresses an important unmet clinical need for a fast and reliable small field output factor measurement.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2014

SU-E-CAMPUS-I-06: Y90 PET/CT for the Instantaneous Determination of Both Target and Non-Target Absorbed Doses Following Hepatic Radioembolization

Purpose The process of converting Yttrium-90 (Y90) PET/CT images into 3D absorbed dose maps will be explained. The simple methods presented will allow the medical physicst to analyze Y90 PET images following radioembolization and determine the absorbed dose to tumor, normal liver parenchyma and other areas of interest, without application of Monte-Carlo radiation transport or dose-point-kernel (DPK) convolution. Methods Absorbed dose can be computed from Y90 PET/CT images based on the premise that radioembolization is a permanent implant with a constant relative activity distribution after infusion. Many Y90 PET/CT publications have used DPK convolution to obtain 3D absorbed dose maps. However, this method requires specialized software limiting clinical utility. The Local Deposition method, an alternative to DPK convolution, can be used to obtain absorbed dose and requires no additional computer processing. Pixel values from regions of interest drawn on Y90 PET/CT images can be converted to absorbed dose (Gy) by multiplication with a scalar constant. Results There is evidence that suggests the Local Deposition method may actually be more accurate than DPK convolution and it has been successfully used in a recent Y90 PET/CT publication. We have analytically compared dose-volume-histograms (DVH) for phantom hot-spheres to determine the difference between the DPK and Local Deposition methods, as a function of PET scanner point-spread-function for Y90. We have found that for PET/CT systems with a FWHM greater than 3.0 mm when imaging Y90, the Local Deposition Method provides a more accurate representation of DVH, regardless of target size than DPK convolution. Conclusion Using the Local Deposition Method, post-radioembolization Y90 PET/CT images can be transformed into 3D absorbed dose maps of the liver. An interventional radiologist or a Medical Physicist can perform this transformation in a clinical setting, allowing for rapid prediction of treatment efficacy by comparison to published tumoricidal thresholds.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

TH-E-BRE-01: A 3D Solver of Linear Boltzmann Transport Equation Based On a New Angular Discretization Method with Positivity for Photon Dose Calculation Benchmarked with Geant4

Purpose: The Linear Boltzmann Transport Equation (LBTE) solved through statistical Monte Carlo (MC) method provides the accurate dose calculation in radiotherapy. This work is to investigate the alternative way for accurately solving LBTE using deterministic numerical method due to its possible advantage in computational speed from MC. Methods: Instead of using traditional spherical harmonics to approximate angular scattering kernel, our deterministic numerical method directly computes angular scattering weights, based on a new angular discretization method that utilizes linear finite element method on the local triangulation of unit angular sphere. As a Result, our angular discretization method has the unique advantage in positivity, i.e., to maintain all scattering weights nonnegative all the time, which is physically correct. Moreover, our method is local in angular space, and therefore handles the anisotropic scattering well, such as the forward-peaking scattering. To be compatible with image-guided radiotherapy, the spatial variables are discretized on the structured grid with the standard diamond scheme. After discretization, the improved sourceiteration method is utilized for solving the linear system without saving the linear system to memory. The accuracy of our 3D solver is validated using analytic solutions and benchmarked with Geant4, a popular MC solver. Results: The differences between Geant4 solutions and our solutions were less than 1.5% for various testing cases that mimic the practical cases. More details are available in the supporting document. Conclusion: We have developed a 3D LBTE solver based on a new angular discretization method that guarantees the positivity of scattering weights for physical correctness, and it has been benchmarked with Geant4 for photon dose calculation.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

TH-E-BRE-07: Development of Dose Calculation Error Predictors for a Widely Implemented Clinical Algorithm

Purpose: Several shortcomings of the current implementation of the analytic anisotropic algorithm (AAA) may lead to dose calculation errors in highly modulated treatments delivered to highly heterogeneous geometries. Here we introduce a set of dosimetric error predictors that can be applied to a clinical treatment plan and patient geometry in order to identify high risk plans. Once a problematic plan is identified, the treatment can be recalculated with more accurate algorithm in order to better assess its viability. Methods: Here we focus on three distinct sources dosimetric error in the AAA algorithm. First, due to a combination of discrepancies in smallfield beam modeling as well as volume averaging effects, dose calculated through small MLC apertures can be underestimated, while that behind small MLC blocks can overestimated. Second, due the rectilinear scaling of the Monte Carlo generated pencil beam kernel, energy is not properly transported through heterogeneities near, but not impeding, the central axis of the beamlet. And third, AAA overestimates dose in regions very low density (< 0.2 g/cm{sup 3}). We have developed an algorithm to detect the location and magnitude of each scenario within the patient geometry, namely the field-size index (FSI), the heterogeneous scatter index (HSI), and the lowdensity index (LDI) respectively. Results: Error indices successfully identify deviations between AAA and Monte Carlo dose distributions in simple phantom geometries. Algorithms are currently implemented in the MATLAB computing environment and are able to run on a typical RapidArc head and neck geometry in less than an hour. Conclusion: Because these error indices successfully identify each type of error in contrived cases, with sufficient benchmarking, this method can be developed into a clinical tool that may be able to help estimate AAA dose calculation errors and when it might be advisable to use Monte Carlo calculations.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

Dose reconstruction for real-time patient-specific dose estimation in CT

Purpose: Many recent computed tomography (CT) dose reduction approaches belong to one of three categories: statistical reconstruction algorithms, efficient x-ray detectors, and optimized CT acquisition schemes with precise control over the x-ray distribution. The latter category could greatly benefit from fast and accurate methods for dose estimation, which would enable real-time patient-specific protocol optimization. Methods: The authors present a new method for volumetrically reconstructing absorbed dose on a per-voxel basis, directly from the actual CT images. The authors’ specific implementation combines a distance-driven pencil-beam approach to model the first-order x-ray interactions with a set of Gaussian convolution kernels to model the higher-order x-ray interactions. The authors performed a number of 3D simulation experiments comparing the proposed method to a Monte Carlo based ground truth. Results: The authors’ results indicate that the proposed approach offers a good trade-off between accuracy and computational efficiency. The images show a good qualitative correspondence to Monte Carlo estimates. Preliminary quantitative results show errors below 10%, except in bone regions, where the authors see a bigger model mismatch. The computational complexity is similar to that of a low-resolution filtered-backprojection algorithm. Conclusions: The authors present a method for analytic dose reconstruction in CT, similar to the techniques used in radiation therapy planning with megavoltage energies. Future work will include refinements of the proposed method to improve the accuracy as well as a more extensive validation study. The proposed method is not intended to replace methods that track individual x-ray photons, but the authors expect that it may prove useful in applications where real-time patient-specific dose estimation is required.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-D-201-02: Prediction of Delivered Dose Based On a Joint Histogram of CT and FDG PET Images

Purpose: To investigate whether pre-treatment images can be used in predicting microsphere distribution in tumors. When intra-arterial radioembolization using Y90 microspheres was performed, the microspheres were often delivered non-uniformly within the tumor, which could lead to an inefficient therapy. Therefore, it is important to estimate the distribution of microspheres. Methods: Early arterial phase CT and FDG PET images were acquired for patients with primary liver cancer prior to radioembolization (RE) using Y90 microspheres. Tumor volume was delineated on CT images and fused with FDG PET images. From each voxel (3.9×3.9×3.3 mm3) in the tumor, the Hounsfield unit (HU) from the CT and SUV values from the FDG PET were harvested. We binned both HU and SUV into 11 bins and then calculated a normalized joint-histogram in an 11×11 array.Patients also underwent a post-treatment Y90 PET imaging. Radiation dose for the tumor was estimated using convolution of the Y90 distribution with a dose-point kernel. We also calculated a fraction of the tumor volume that received a radiation dose great than 100Gy. Results: Averaged over 40 patients, 55% of tumor volume received a dose greater than 100Gy (range : 1.1 – 100%). The width of the joint histogram was narrower for patients with a high dose. For patients with a low dose, the width was wider and a larger fraction of tumor volume had low HU. Conclusion: We have shown the pattern of joint histogram of the HU and SUV depends on delivered dose. The patterns can predict the efficacy of uniform intra-arterial delivery of Y90 microspheres.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-E-J-175: Comparison of the Treatment Reproducibility of Tumors Affected by Breathing Motion

Purpose: The aim of the dose distribution simulations was to form a global idea of intensity-modulated radiation therapy (IMRT) realization, by its comparison to three-dimensional conformal radiation therapy (3DCRT) delivery for tumors affected by respiratory motion. Methods: In the group of 10patients both 3DCRT and IMRT plans were prepared.For each field the motion kernel was generated with the largest movement amplitude of 4;6 and 8mm.Additionally,the sets of reference measurements were made in no motion conditions(0 mm).The evaluation of plan delivery,using a diode array placed on moving platform,was based on the Gamma Index analysis with distance to agreement of 3mm and dose difference of 3%. Results: IMRT plans tended to spare doses delivered to lungs compared to 3DCRT.Nonetheless,analyzed volumes showed no significant difference between the static and dynamic techniques,except for the volumes of both lungs receiving 10 and 15Gy.After adding the components associated with the respiratory movement,all IMRT lung parameters evaluated for the ipsilateral,contralateral and both lungs together,revealed considerable differences between the 0vs.6, 0vs.8 and 4vs.8-mm amplitudes.Similar results were obtained for the 3DCRT lung measurements,but without significance between the 0vs.6-mm amplitude.Taking into account the CTV score parameter in 3DCRT and IMRT plans,there was no statistically significant difference between the motion patterns with the smallest amplitudes.The differences were found for the 8-mm amplitude when it was compared both with static conditions and 4-mm amplitude (for 3DCRT) and between 0vs.6, 0vs.8 and 4vs.8-mm amplitudes (for IMRT).All accepted and measured 3DCRT and IMRT doses to spinal cord,esophagus and heart were always below the QUANTEC limits. Conclusion: The application of IMRT technique in lung radiotherapy affords possibilities for reducing the lung doses.For maximal amplitudes of breathing trajectory below 4mm,the disagreement between CTV planned and delivered dose distribution can be neglected.Whereas respiratory motion with an amplitude above 5mm leads to significant changes in IMRT delivery.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-E-T-36: A GPU-Accelerated Monte-Carlo Dose Calculation Platform and Its Application Toward Validating a ViewRay Beam Model

Purpose: To build a fast, accurate and easily-deployable research platform for Monte-Carlo dose calculations. We port the dose calculation engine PENELOPE to C++, and accelerate calculations using GPU acceleration. Simulations of a Co-60 beam model provided by ViewRay demonstrate the capabilities of the platform. Methods: We built software that incorporates a beam model interface, CT-phantom model, GPU-accelerated PENELOPE engine, and GUI front-end. We rewrote the PENELOPE kernel in C++ (from Fortran) and accelerated the code on a GPU. We seamlessly integrated a Co-60 beam model (obtained from ViewRay) into our platform. Simulations of various field sizes and SSDs using a homogeneous water phantom generated PDDs, dose profiles, and output factors that were compared to experiment data. Results: With GPU acceleration using a dated graphics card (Nvidia Tesla C2050), a highly accurate simulation – including 100*100*100 grid, 3×3×3 mm3 voxels, <1% uncertainty, and 4.2×4.2 cm2 field size – runs 24 times faster (20 minutes versus 8 hours) than when parallelizing on 8 threads across a new CPU (Intel i7-4770). Simulated PDDs, profiles and output ratios for the commercial system agree well with experiment data measured using radiographic film or ionization chamber. Based on our analysis, this beam model is precise enough for general applications. Conclusions: Using a beam model for a Co-60 system provided by ViewRay, we evaluate a dose calculation platform that we developed. Comparison to measurements demonstrates the promise of our software for use as a research platform for dose calculations, with applications including quality assurance and treatment plan verification.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-E-T-74: A Simple Model of Dose Falloff for Highly Convergent SBRT Beams

Purpose: The purpose of this study was to create a simple model of dose falloff outside the target for a SBRT system employing a highly convergent beam geometry. With an estimate of the rate of reduction in dose away from a target of a given size, dose to tissues at a given distance from the target can be estimated. Our hypothesis is that dose at a given distance away from the edge of a target can be approximated using an inverse square model. Methods: With the GammaPod™ system used for this study, thirty-six rotating Co-60 beams with circular cross section converge at an isocenter and then diverge distal to the isocenter. Dose falloff beyond the target is mainly due to reduction in beam overlap, which in turn depends on projected area of all beams and projected beam area swept out during rotation. Beams also decrease in intensity beyond the isocenter. The GammaPod™ TPS calculates dose via superposition of Monte Carlo-generated kernels, each corresponding to the convergence of beams at an isocenter within a stereotactic breast cup. Results: The factors above yield a simple inverse square-based model that has been compared with TPS predictions and measurements for a variety of targets. Good agreement is seen considering the simple nature of the model. Fitting of the treatment planning and measured dose falloff data with a power law expression yields a negative exponent close to 2, confirming the inverse square nature of dose falloff. Conclusion: It is possible to apply a simple inverse square dose falloff model for SBRT or SRS systems such as the GammaPod which employ a highly-convergent beam geometry. This can be useful in estimating the “worst case scenario” for dose to critical organs at a known distance from the edge of the target volume. Authors are employees of Xcision Medical Systems.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-E-T-805: Verification of the Simplified Monte Carlo Method for Simulation in An Inhomogeneous Phantom

Purpose: A simplified Monte Carlo (SMC) method has been developed to obtain fast and accurate dose calculation in heterogeneous tissues to improve the accuracy of dose calculation. We have applied the SMC method to calculation of dose kernels for the pencil beam scanning. While the SMC method tracks individual primary protons in medium, it simplifies the dose calculation by using a measured depth-dose distribution instead of considering nuclear reactions and tracking secondary particles. To verify the accuracy of SMC calculation, we compared a dose-calculation Result using the SMC method with that using the Full Monte Carlo (FMC) method in an inhomogeneous phantom. Methods: As a model of the inhomogeneous media, we considered a phantom complied of a rectangular acrylic block of size 150*300*200 mm {sup 3} immersed in water within a virtual container with a size of 300*300*400 mm{sup 3}. Results: We found excellent agreement of overall dose distributions between the SMC and FMC methods. As for the laterally integrated depth-dose distributions, slight difference was found in front of the second Bragg-Peak between the two algorithms. While it took 25717.0 s on 2.7 GHz Intel Core i7 for the FMC method to complete the calculation, it took 15.4 s for the SMC method to complete it. The SMC method can calculate the dose distribution approximately 1675 times faster than the FMC method. Conclusion: The dose distribution obtained by SMC method agreed well that obtained by the FMC method in a simple inhomogeneous phantom. In contrast, calculation time by the SMC method has been reduced by three orders in magnitude compared with the FMC method.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-F-BRB-10: A Statistical Voxel Based Normal Organ Dose Prediction Model for Coplanar and Non-Coplanar Prostate Radiotherapy

Purpose: Knowledge learned from previous plans can be used to guide future treatment planning. Existing knowledge-based treatment planning methods study the correlation between organ geometry and dose volume histogram (DVH), which is a lossy representation of the complete dose distribution. A statistical voxel dose learning (SVDL) model was developed that includes the complete dose volume information. Its accuracy of predicting volumetric-modulated arc therapy (VMAT) and non-coplanar 4π radiotherapy was quantified. SVDL provided more isotropic dose gradients and may improve knowledge-based planning. Methods: 12 prostate SBRT patients originally treated using two full-arc VMAT techniques were re-planned with 4π using 20 intensity-modulated non-coplanar fields to a prescription dose of 40 Gy. The bladder and rectum voxels were binned based on their distances to the PTV. The dose distribution in each bin was resampled by convolving to a Gaussian kernel, resulting in 1000 data points in each bin that predicted the statistical dose information of a voxel with unknown dose in a new patient without triaging information that may be collectively important to a particular patient. We used this method to predict the DVHs, mean and max doses in a leave-one-out cross validation (LOOCV) test and compared its performance against lossy estimators including mean, median, mode, Poisson and Rayleigh of the voxelized dose distributions. Results: SVDL predicted the bladder and rectum doses more accurately than other estimators, giving mean percentile errors ranging from 13.35–19.46%, 4.81–19.47%, 22.49–28.69%, 23.35–30.5%, 21.05–53.93% for predicting mean, max dose, V20, V35, and V40 respectively, to OARs in both planning techniques. The prediction errors were generally lower for 4π than VMAT. Conclusion: By employing all dose volume information in the SVDL model, the OAR doses were more accurately predicted. 4π plans are better suited for knowledge-based planning than the VMAT plans that are strongly biased in its dose gradient orientation. This project is supported by Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

Iterative reconstruction for CT perfusion with a prior-image induced hybrid nonlocal means regularization: Phantom studies

Purpose: In computed tomography perfusion (CTP) imaging, an initial phase CT acquired with a high-dose protocol can be used to improve the image quality of later phase CT acquired with a low-dose protocol. For dynamic regions, signals in the later low-dose CT may not be completely recovered if the initial CT heavily regularizes the iterative reconstruction process. The authors propose a hybrid nonlocal means (hNLM) regularization model for iterative reconstruction of low-dose CTP to overcome the limitation of the conventional prior-image induced penalty. Methods: The hybrid penalty was constructed by combining the NLM of the initial phase high-dose CT in the stationary region and later phase low-dose CT in the dynamic region. The stationary and dynamic regions were determined by the similarity between the initial high-dose scan and later low-dose scan. The similarity was defined as a Gaussian kernel-based distance between the patch-window of the same pixel in the two scans, and its measurement was then used to weigh the influence of the initial high-dose CT. For regions with high similarity (e.g., stationary region), initial high-dose CT played a dominant role for regularizing the solution. For regions with low similarity (e.g., dynamic region), the regularization relied on a low-dose scan itself. This new hNLM penalty was incorporated into the penalized weighted least-squares (PWLS) for CTP reconstruction. Digital and physical phantom studies were performed to evaluate the PWLS-hNLM algorithm. Results: Both phantom studies showed that the PWLS-hNLM algorithm is superior to the conventional prior-image induced penalty term without considering the signal changes within the dynamic region. In the dynamic region of the Catphan phantom, the reconstruction error measured by root mean square error was reduced by 42.9% in PWLS-hNLM reconstructed image. Conclusions: The PWLS-hNLM algorithm can effectively use the initial high-dose CT to reconstruct low-dose CTP in the stationary region while reducing its influence in the dynamic region.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-I-43: A Software-Based Statistical Method to Compute Low Contrast Detectability in Computed Tomography Images

Purpose: The low contrast detectability (LCD) of a CT scanner is its ability to detect and display faint lesions. The current approach to quantify LCD is achieved using vendor-specific methods and phantoms, typically by subjectively observing the smallest size object at a contrast level above phantom background. However, this approach does not yield clinically applicable values for LCD. The current study proposes a statistical LCD metric using software tools to not only to assess scanner performance, but also to quantify the key factors affecting LCD. This approach was developed using uniform QC phantoms, and its applicability was then extended under simulated clinical conditions. Methods: MATLAB software was developed to compute LCD using a uniform image of a QC phantom. For a given virtual object size, the software randomly samples the image within a selected area, and uses statistical analysis based on Student’s t-distribution to compute the LCD as the minimal Hounsfield Unit’s that can be distinguished from the background at the 95% confidence level. Its validity was assessed by comparison with the behavior of a known QC phantom under various scan protocols and a tissue-mimicking phantom. The contributions of beam quality and scattered radiation upon the computed LCD were quantified by using various external beam-hardening filters and phantom lengths. Results: As expected, the LCD was inversely related to object size under all scan conditions. The type of image reconstruction kernel filter and tissue/organ type strongly influenced the background noise characteristics and therefore, the computed LCD for the associated image. Conclusion: The proposed metric and its associated software tools are vendor-independent and can be used to analyze any LCD scanner performance. Furthermore, the method employed can be used in conjunction with the relationships established in this study between LCD and tissue type to extend these concepts to patients’ clinical CT images.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-J-75: Accuracy and Stability of Electron Density Measurements Across Patient Size Using Dual Energy CT

Purpose: Dual energy (DE) CT can be used to characterize tissue composition. One application of DE CT is to measure electron density (ED, rho) and atomic number (Z) for use in radiation therapy treatment planning. This work evaluated the accuracy and stability of ED estimation as patient size varied for both single-energy (SE) and DE CT. Methods: An ED phantom (CIRS) and four torso-shaped water tanks (lateral widths 15, 25, 35 and 45 cm) containing 8 tissue-simulating cylinders of known ED were scanned on a dual-source CT system (Siemens Somatom Force) in SE (120 kV) and DE (90/150Sn) modes. Additional scans were performed on the 15 and 25 cm water tanks using DE techniques of 70/150Sn and 80/150Sn, respectively. CTDIvol was matched for all SE and DE scans for a given phantom size. Images were reconstructed using quantitative kernels to preserve CT number accuracy. ED was estimated in each test cylinder and in solid and liquid water using calibration measurements acquired in the CIRS phantom (SE) and a Rho-Z algorithm (DE). Results: ED estimates showed good agreement with the nominal ED values when using Rho-Z (slope = 1.0051, R2 = 0.9982). Mean percent error was similar between SE (1.21%) and DE (1.28%). Mean deviation across patient size decreased 34% (1.43% with SE, 0.95% with DE). When compared to 90/150Sn, DE techniques of 70/150Sn and 80/150Sn showed mean differences in ED of 0.43% and 0.15%, respectively. Conclusion: While both DE Rho-Z and SE CT number calibration methods are both accurate for estimating ED, Rho-Z offers the advantages of having less variability across patient size, not requiring a phantom calibration, and being able to distinguish between materials of similar attenuation, but different chemical composition. Low kV DE pairs are an option in small patients due to lack of effect on ED accuracy. This research was supported by Siemens Healthcare.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

WE-FG-207B-08: Dual-Energy CT Iodine Accuracy Across Vendors and Platforms

Purpose: Although a major benefit of dual-energy CT is its quantitative capabilities, it is critical to understand how results vary by scanner manufacturer and/or model before making clinical patient management decisions. Each manufacturer utilizes a specific dual-energy CT approach; cross-calibration may be required for facilities with more than one dual-energy CT scanner type. Methods: A solid dual-energy quality control phantom (Gammex, Inc.; Appleton, WI) representing a large body cross-section containing three Iodine inserts (2mg/ml, 5mg/ml, 15 mg/ml) was scanned on these CT systems: GE HD-750 (80/140kVp), prototype GE Revolution CT with GSI (80/140kVp), Siemens Flash (80/140kVp and 100/140kVp), and Philips IQon (120kVp and 140kVp). Iodine content was measured in units of concentration (mg/ml) from a single 5mm-thick central image. Three to five acquisitions were performed on each scanner platform in order to compute standard deviation. Scan acquisitions were approximately dose-matched (∼25mGy CTDIvol) and image parameters were as consistent as possible (thickness, kernel, no noise reduction applied). Results: Iodine measurement error ranges were −0.24-0.16 mg/ml for the 2mg/ml insert (−12.0 − 8.0%), −0.28–0.26 mg/ml for the 5mg/ml insert (−5.6 − 5.2%), and −1.16−0.99 mg/ml for the 15mg/ml insert (−7.7 − 6.6%). Standard deviations ranged from 0 to 0.19 mg/ml for the repeated acquisitions from each scanner. The average iodine measurement error and standard deviation across all systems and inserts was −0.21 ± 0.48 mg/ml (−1.5 ± 6.48%). The largest absolute measurement error was found in the 15mg/ml iodine insert. Conclusion: There was generally good agreement in Iodine quantification across 3 dual-energy CT manufacturers and 4 scanner models. This was unexpected given the widely different underlying dual-energy CT mechanisms employed. Future work will include additional scanner platforms, independent verification of the Iodine insert standard concentrations (especially the 15 mg/ml insert), and how much measurement variability can be clinically tolerated. This research has been supported by funds from Dr. William Murphy, Jr., the John S. Dunn, Sr. Distinguished Chair in Diagnostic Imaging at MD Anderson Cancer Center.

60 APPLIED LIFE SCIENCES↗