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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

WE-H-207A-02: Attenuation Correction in 4D-PET Using a Single-Phase Attenuation Map

Purpose: 4D-PET imaging has been proposed as a potential solution to the respiratory motion effect in thoracic region. CT-based attenuation correction (AC) is an essential step toward quantitative imaging for PET. However, due to the temporal difference of 4D-PET and a single breath-hold CT, motion artifacts are observed in the attenuation-corrected PET images that can lead to error in tumor shape and uptake. We introduce a practical method for aligning single-phase CT to all other 4D-PET phases using a penalized non-rigid demons registration. Methods: Individual 4D-PET frames were reconstructed without AC. Non-rigid Demons registration was used to derive deformation vector fields (DVFs) between the PET matched with CT phase and other 4D-PET images. While attenuated PET images provide enough useful data for organ borders such as lung and liver, tumors are not distinguishable from background due to loss of contrast. To preserve tumor shape in different phases, from CT image an ROI covering tumor was excluded from non-rigid transformation. Mean DVF of the central region of the tumor was assigned to all voxels in the ROI. This process mimics a rigid transformation of tumor along with a non-rigid transformation of other organs. 4D XCAT phantom with spherical tumors in lung with diameters ranging from 10 to 40 mm was used to evaluate the algorithm. Results: Motion related induced artifacts in attenuation-corrected 4D-PET images were significantly reduced. For tumors smaller than 20 mm, non-rigid transformation was capable to provide quantitative results. However, for larger tumors, where tumor self-attenuation is considerable, our combined method yields superior results. Conclusion: We introduced a practical method for deforming a single CT to match all 4D-PET images for accurate AC. Although 4D-PET data include insignificant anatomical information, we showed that they are still useful to estimate DVFs for aligning attenuation map and accurate AC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

True beam commissioning experience at Nordland Hospital Trust, Norway

To evaluate the measured of all photon beam data of first Varian True Beam version 2.0 slim model, recently commissioned at Nordland Hospital Trust, Bodø. To compare and evaluate the possibility of beam matching with the Clinac2300, for the energies of 6MV and 15 MV. Materials/Methods: Measurements of PDD, OAR, and Output factors were realized with the IBA Blue-phantom with different detectors and evaluated between them for all photon energies: 6MV, 15MV, 6MV FFF and 10MV FFF. The ionization chambers used were Pin Point CC01, CC04, Semiflex CC13 and photon diode by Iba dosimetry. The data were processed using Beizer algorithm with a resolution of 1 mm. The measured depth dose curves, diagonals, OAR, and output factors were imported into Eclipse in order to calculate beam data for the anisotropic analytical algorithm (AAA version 10.0.28) for both the dataset measured with CC04 and CC13 and compared. The model head of 23EX was selected as the most near model to True Beam as a restriction of our version of Aria. It was seen that better results were achieved with the CC04 measured data as a result of better resolution. For the biggest field after 10 cm depth a larger difference is seen between measured and calculated for both dataset, but it is within the criteria for acceptance. Results: The Beam analysis criteria of 2 mm at 50% dose is achieved for all the fields accept for 40x40 that is within 3%. Depth difference at maximum dose is within 1 mm for all the fields and dose difference at 100 mm and 200 mm is lower than 1% for or all the fields. The PDD between two machines for all the fields differ after Dmax with less than 1%. For profiles in the field zone and outside field the difference is within 1% for all the fields. In the penumbra region the difference is from 2% up to 12% for big fields. As for diagonals they differ as a result of the head construction at the edge of the field and the penumbra region. The output factors differ for big fields within 5% and for the small fields within 3%. MU and dose distribution does not change for plans recalculated with the new modeled machine.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRSDate not supplied

Total Variation Majorization Minimization (TV-MM) Approach to Radiometer Brightness Temperature Gridding and Reconstruction

This paper presents the implementation of an algorithm to enhance the image resolution of the Earth's surface brightness temperature (T B ) data measured by radiometers such as the one onboard of the Soil Moisture Active Passive (SMAP) mission. A key step in radiometer T B processing is the conversion of the swath-based calibrated antenna temperature (T A ) measurements to the Level 3 Earth-centered grid. The simplest algorithm to transform this data from swath to gridded format is called drop-in-the-bucket which simply averages surrounding noisy T A samples to form a T B value at the gridded location. This method reduces noise, however produces low resolution products. To obtain a higher resolution product, SMAP uses other techniques such the Backus-Gilbert (BG) algorithm, which is the conventional method used in microwave radiometry. Although this method performs the required interpolation, it is not effective in denoising and removing blurring effects due to antenna filtering of the radiometer image data. Our motivation for this development is to further improve the resolution through post-processing of the radiometer T B image, a highly cost-effective method of image enhancement. The approach adapted in this work is based on the minimization of the Total Variation (TV) regularized objective function that is used extensively in solving general ill-posed linear inverse problems in image processing. Since the TV-based objective function is convex but not everywhere differentiable, there exists many numerical algorithms that can estimate the solution and the one selected for this work is called Majorization- Minimization (MM). By applying this algorithm, simulation experiments were performed based on synthetic data from the Geophysical model as well as real SMAP data to demonstrate the effectiveness of the technique. Results were then compared against the BG method.

Wing Lee↗
DOE OSTI2016

SU-F-J-76: Evaluation of the Performance of Different Deformable Image Registration Algorithms in Helical, Axial and Cone-Beam CT Images of a Mobile Phantom

Purpose: To investigate quantitatively the performance of different deformable-image-registration algorithms (DIR) with helical (HCT), axial (ACT) and cone-beam CT (CBCT) by evaluating the variations in the CT-numbers and lengths of targets moving with controlled motion-patterns. Methods: Four DIR-algorithms including demons, fast-demons, Horn-Schunk and Locas-Kanade from the DIRART-software are used to register CT-images of a mobile-phantom. A mobile-phantom is scanned with different imaging techniques that include helical, axial and cone-beam CT. The phantom includes three targets with different lengths that are made from water-equivalent material and inserted in low-density-foam which is moved with adjustable motion-amplitudes and frequencies. Results: Most of the DIR-algorithms are able to produce the lengths of the stationary-targets, however, they do not produce the CT-number values in CBCT. The image-artifacts induced by motion are more regular in CBCT imaging where the mobile-target elongation increases linearly with motion-amplitude. In ACT and HCT, the motion-artifacts are irregular where some mobile -targets are elongated or shrunk depending on the motion-phase during imaging. The DIR-algorithms are successful in deforming the images of the mobile-targets to the images of the stationary-targets producing the CT-number values and length of the target for motion-amplitudes < 20 mm. Similarly in ACT, all DIR-algorithms produced the actual CT-number and length of the stationary-targets for motion-amplitudes < 15 mm. As stronger motion-artifacts are induced in HCT and ACT, DIR-algorithms fail to produce CT-values and shape of the stationary-targets and fast-demons-algorithm has worst performance. Conclusion: Most of DIR-algorithms produce the CT-number values and lengths of the stationary-targets in HCT and ACT images that has motion-artifacts induced by small motion-amplitudes. As motion-amplitudes increase, the DIR-algorithms fail to deform mobile-target images to the stationary-images in HCT and ACT. In CBCT, DIR-algorithms are successful in producing length and shape of the stationary-targets, however, they fail to produce the accurate CT-number level.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-D-BRB-04: Plan Quality Comparison of Intracranial Stereotactic Radiosurgery (SRS) for Gamma Knife and VMAT Treatments

Purpose: To compare treatment plan quality of intracranial stereotactic radiosurgery (SRS) for VMAT (RapidArc) and Gamma Knife (GK) systems. Methods: Ten patients with 24 tumors (seven with 1–2 and three with 4–6 lesions), previously treated with GK 4C (prescription doses ranging from 14–23 Gy) were re-planned for RapidArc. Identical contour sets were kept on MRI images for both plans with tissues assigned a CT number of zero. RapidArc plans were performed using 6 MV flattening-filter-free (FFF) beams with dose rate of 1400 MU/minute using two to eight arcs with the following combinations: 2 full coplanar arcs and the rest non-coplanar half arcs. Beam selection was based on target depth. Areas that penetrated more than 10 cm of tissue were avoided by creating smaller arcs or using avoidance sectors in optimization. Plans were optimized with jaw tracking and a high weighting to the normal-brain-tissue and Normal-Tissue-Objective without compromising PTV coverage. Plans were calculated on a 1 mm grid size using AAA algorithm and then normalized so that 99% of each target volume received the prescription dose. Plan quality was assessed by target coverage using Paddick Conformity Index (PCI), sparing of normal-brain-tissue through analysis of V4, V8, and V12 Gy, and integral dose. Results: In all cases critical structure dose criteria were met. RapidArc had a higher PCI than GK plans for 23 out of 24 lesions. The average PCI was 0.76±0.21 for RapidArc and 0.46±0.20 for GK plans (p≤0.001), respectively. Integral dose and normal-brain-tissue doses for all criteria were lower for RapidArc in nearly all patients. The average ratio of GK to RapidArc plans was 1.28±0.27 (p=0.018), 1.31±0.25 (p=0.017), 1.81±0.43 (p=0.005), and 1.50±0.61 (p=0.006) for V4, V8, and V12 Gy, and integral dose, respectively. Conclusion: VMAT was capable of producing higher quality treatment plans than GK when using optimal beam geometries and proper optimization techniques.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-G-JeP3-05: Geometry Based Transperineal Ultrasound Probe Positioning for Image Guided Radiotherapy

Purpose: The use of ultrasound (US) imaging in radiotherapy is not widespread, primarily due to the need for skilled operators performing the scans. Automation of probe positioning has the potential to remove this need and minimize operator dependence. We introduce an algorithm for obtaining a US probe position that allows good anatomical structure visualization based on clinical requirements. The first application is on 4D transperineal US images of prostate cancer patients. Methods: The algorithm calculates the probe position and orientation using anatomical information provided by a reference CT scan, always available in radiotherapy workflows. As initial test, we apply the algorithm on a CIRS pelvic US phantom to obtain a set of possible probe positions. Subsequently, five of these positions are randomly chosen and used to acquire actual US volumes of the phantom. Visual inspection of these volumes reveal if the whole prostate, and adjacent edges of bladder and rectum are fully visualized, as clinically required. In addition, structure positions on the acquired US volumes are compared to predictions of the algorithm. Results: All acquired volumes fulfill the clinical requirements as specified in the previous section. Preliminary quantitative evaluation was performed on thirty consecutive slices of two volumes, on which the structures are easily recognizable. The mean absolute distances (MAD) between actual anatomical structure positions and positions predicted by the algorithm were calculated. This resulted in MAD of 2.4±0.4 mm for prostate, 3.2±0.9 mm for bladder and 3.3±1.3 mm for rectum. Conclusion: Visual inspection and quantitative evaluation show that the algorithm is able to propose probe positions that fulfill all clinical requirements. The obtained MAD is on average 2.9 mm. However, during evaluation we assumed no errors in structure segmentation and probe positioning. In future steps, accurate estimation of these errors will allow for better evaluation of the achieved accuracy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-58: Comparison of Conformal Tracking Methods Using Initial, Adaptive and Preceding Image Frames for Image Registration

Purpose: Accounting for tumor motion during radiation therapy is important to ensure that the tumor receives the prescribed dose. Increasing the field size to account for this motion exposes the surrounding healthy tissues to unnecessary radiation. In contrast to using motion-encompassing techniques to treat moving tumors, conformal radiation therapy (RT) uses a smaller field to track the tumor and adapts the beam aperture according to the motion detected. This work investigates and compares the performance of three markerless, EPID based, optical flow methods to track tumor motion with conformal RT. Methods: Three techniques were used to track the motions of a 3D printed lung tumor programmed to move according to the tumor of seven lung cancer patients. These techniques utilized a multi-resolution optical flow algorithm as the core computation for image registration. The first method (DIR) registers the incoming images with an initial reference frame, while the second method (RFSF) uses an adaptive reference frame and the third method (CU) uses preceding image frames for registration. The patient traces and errors were evaluated for the seven patients. Results: The average position errors for all patient traces were 0.12 ± 0.33 mm, −0.05 ± 0.04 mm and −0.28 ± 0.44 mm for CU, DIR and RFSF method respectively. The position errors distributed within 1 standard deviation are 0.74 mm, 0.37 mm and 0.96 mm respectively. The CU and RFSF algorithms are sensitive to the characteristics of the patient trace and produce a wider distribution of errors amongst patients. Although the mean error for the DIR method is negatively biased (−0.05 mm) for all patients, it has the narrowest distribution of position error, which can be corrected using an offset calibration. Conclusion: Three techniques of image registration and position update were studied. Using direct comparison with an initial frame yields the best performance. The authors would like to thank Dr.YeLin Suh for making the Cyberknife dataset available to us. Scholarship funding from the Natural Sciences and Engineering Research Council of Canada (NSERC) and CancerCare Manitoba Foundation is acknowledged.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Investigating CT to CBCT image registration for head and neck proton therapy as a tool for daily dose recalculation

Purpose: Intensity modulated proton therapy (IMPT) of head and neck (H and N) cancer patients may be improved by plan adaptation. The decision to adapt the treatment plan based on a dose recalculation on the current anatomy requires a diagnostic quality computed tomography (CT) scan of the patient. As gantry-mounted cone beam CT (CBCT) scanners are currently being offered by vendors, they may offer daily or weekly updates of patient anatomy. CBCT image quality may not be sufficient for accurate proton dose calculation and it is likely necessary to perform CBCT CT number correction. In this work, the authors investigated deformable image registration (DIR) of the planning CT (pCT) to the CBCT to generate a virtual CT (vCT) to be used for proton dose recalculation. Methods: Datasets of six H and N cancer patients undergoing photon intensity modulated radiation therapy were used in this study to validate the vCT approach. Each dataset contained a CBCT acquired within 3 days of a replanning CT (rpCT), in addition to a pCT. The pCT and rpCT were delineated by a physician. A Morphons algorithm was employed in this work to perform DIR of the pCT to CBCT following a rigid registration of the two images. The contours from the pCT were deformed using the vector field resulting from DIR to yield a contoured vCT. The DIR accuracy was evaluated with a scale invariant feature transform (SIFT) algorithm comparing automatically identified matching features between vCT and CBCT. The rpCT was used as reference for evaluation of the vCT. The vCT and rpCT CT numbers were converted to stopping power ratio and the water equivalent thickness (WET) was calculated. IMPT dose distributions from treatment plans optimized on the pCT were recalculated with a Monte Carlo algorithm on the rpCT and vCT for comparison in terms of gamma index, dose volume histogram (DVH) statistics as well as proton range. The DIR generated contours on the vCT were compared to physician-drawn contours on the rpCT. Results: The DIR accuracy was better than 1.4 mm according to the SIFT evaluation. The mean WET differences between vCT (pCT) and rpCT were below 1 mm (2.6 mm). The amount of voxels passing 3%/3 mm gamma criteria were above 95% for the vCT vs rpCT. When using the rpCT contour set to derive DVH statistics from dose distributions calculated on the rpCT and vCT the differences, expressed in terms of 30 fractions of 2 Gy, were within [−4, 2 Gy] for parotid glands (D{sub mean}), spinal cord (D{sub 2%}), brainstem (D{sub 2%}), and CTV (D{sub 95%}). When using DIR generated contours for the vCT, those differences ranged within [−8, 11 Gy]. Conclusions: In this work, the authors generated CBCT based stopping power distributions using DIR of the pCT to a CBCT scan. DIR accuracy was below 1.4 mm as evaluated by the SIFT algorithm. Dose distributions calculated on the vCT agreed well to those calculated on the rpCT when using gamma index evaluation as well as DVH statistics based on the same contours. The use of DIR generated contours introduced variability in DVH statistics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-513: Investigating Dose of Internal Target Volume After Correcting for Tissue Heterogeneity in SBRT Lung Plans with Homogeneity Calculation

Purpose It was recommended to use the prescription of 54 Gy/3 with heterogeneity corrections for previously established dose scheme of 60 Gy/3 with homogeneity calculation. This study is to investigate dose coverage for the internal target volume (ITV) with and without heterogeneity correction. Methods Thirty patients who received stereotactic body radiotherapy (SBRT) to a dose of 60 Gy in 3 fractions with homogeneous planning for early stage non-small-cell lung cancer (NSCLC) were selected. ITV was created either from 4DCT scans or a fusion of multi-phase respiratory scans. Planning target volume (PTV) was a 5 mm expansion of the ITV. For this study, we recalculated homogeneous clinical plans using heterogeneity corrections with monitor units set as clinically delivered. All plans were calculated with 3 mm dose grids and collapsed cone convolution algorithm. To account for uncertainties from tumor delineation and image-guided radiotherapy, a structure ITV2mm was created by expanding ITV with 2 mm margins. Dose coverage to the PTV, ITV and ITV2mm were compared with a student paired t-test. Results With heterogeneity corrections, the PTV V60Gy decreased by 10.1% ± 18.4% (p<0.01) while the maximum dose to the PTV increased by 3.7 ± 4.3% (p<0.01). With and without corrections, D99% was 65.8 ± 4.0 Gy and 66.7 ± 4.8 Gy (p=0.15) for the ITV, and 63.9 ± 3.4 Gy and 62.9 ± 4.6 Gy for the ITV2mm (p=0.22), respectively. The mean dose to the ITV and ITV2mm increased 3.6% ± 4.7% (p<0.01) and 2.3% ± 5.2% (p=0.01) with heterogeneity corrections. Conclusion After heterogeneity correction, the peripheral coverage of the PTV decreased to approximately 54 Gy, but D99% of the ITV and ITV2mm was unchanged and the mean dose to the ITV and ITV2mm was increased. Clinical implication of these results requires more investigation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Experimental demonstration of passive acoustic imaging in the human skull cavity using CT-based aberration corrections

Purpose: Experimentally verify a previously described technique for performing passive acoustic imaging through an intact human skull using noninvasive, computed tomography (CT)-based aberration corrections Jones et al. [Phys. Med. Biol. 58, 4981–5005 (2013)]. Methods: A sparse hemispherical receiver array (30 cm diameter) consisting of 128 piezoceramic discs (2.5 mm diameter, 612 kHz center frequency) was used to passively listen through ex vivo human skullcaps (n = 4) to acoustic emissions from a narrow-band fixed source (1 mm diameter, 516 kHz center frequency) and from ultrasound-stimulated (5 cycle bursts, 1 Hz pulse repetition frequency, estimated in situ peak negative pressure 0.11–0.33 MPa, 306 kHz driving frequency) Definity™ microbubbles flowing through a thin-walled tube phantom. Initial in vivo feasibility testing of the method was performed. The performance of the method was assessed through comparisons to images generated without skull corrections, with invasive source-based corrections, and with water-path control images. Results: For source locations at least 25 mm from the inner skull surface, the modified reconstruction algorithm successfully restored a single focus within the skull cavity at a location within 1.25 mm from the true position of the narrow-band source. The results obtained from imaging single bubbles are in good agreement with numerical simulations of point source emitters and the authors’ previous experimental measurements using source-based skull corrections O’Reilly et al. [IEEE Trans. Biomed. Eng. 61, 1285–1294 (2014)]. In a rat model, microbubble activity was mapped through an intact human skull at pressure levels below and above the threshold for focused ultrasound-induced blood–brain barrier opening. During bursts that led to coherent bubble activity, the location of maximum intensity in images generated with CT-based skull corrections was found to deviate by less than 1 mm, on average, from the position obtained using source-based corrections. Conclusions: Taken together, these results demonstrate the feasibility of using the method to guide bubble-mediated ultrasound therapies in the brain. The technique may also have application in ultrasound-based cerebral angiography.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2004

A Bayesian approach to tracking patients having changing pharmacokinetic parameters

This paper considers the updating of Bayesian posterior densities for pharmacokinetic models associated with patients having changing parameter values. For estimation purposes it is proposed to use the Interacting Multiple Model (IMM) estimation algorithm, which is currently a popular algorithm in the aerospace community for tracking maneuvering targets. The IMM algorithm is described, and compared to the multiple model (MM) and Maximum A-Posteriori (MAP) Bayesian estimation methods, which are presently used for posterior updating when pharmacokinetic parameters do not change. Both the MM and MAP Bayesian estimation methods are used in their sequential forms, to facilitate tracking of changing parameters. Results indicate that the IMM algorithm is well suited for tracking time-varying pharmacokinetic parameters in acutely ill and unstable patients, incurring only about half of the integrated error compared to the sequential MM and MAP methods on the same example.

Bayes Theorem↗
DOE OSTI2016

SU-F-T-20: Novel Catheter Lumen Recognition Algorithm for Rapid Digitization

Purpose: Manual catheter recognition remains a time-consuming aspect of high-dose-rate brachytherapy (HDR) treatment planning. In this work, a novel catheter lumen recognition algorithm was created for accurate and rapid digitization. Methods: MatLab v8.5 was used to create the catheter recognition algorithm. Initially, the algorithm searches the patient CT dataset using an intensity based k-means filter designed to locate catheters. Once the catheters have been located, seed points are manually selected to initialize digitization of each catheter. From each seed point, the algorithm searches locally in order to automatically digitize the remaining catheter. This digitization is accomplished by finding pixels with similar image curvature and divergence parameters compared to the seed pixel. Newly digitized pixels are treated as new seed positions, and hessian image analysis is used to direct the algorithm toward neighboring catheter pixels, and to make the algorithm insensitive to adjacent catheters that are unresolvable on CT, air pockets, and high Z artifacts. The algorithm was tested using 11 HDR treatment plans, including the Syed template, tandem and ovoid applicator, and multi-catheter lung brachytherapy. Digitization error was calculated by comparing manually determined catheter positions to those determined by the algorithm. Results: he digitization error was 0.23 mm ± 0.14 mm axially and 0.62 mm ± 0.13 mm longitudinally at the tip. The time of digitization, following initial seed placement was less than 1 second per catheter. The maximum total time required to digitize all tested applicators was 4 minutes (Syed template with 15 needles). Conclusion: This algorithm successfully digitizes HDR catheters for a variety of applicators with or without CT markers. The minimal axial error demonstrates the accuracy of the algorithm, and its insensitivity to image artifacts and challenging catheter positioning. Future work to automatically place initial seed positions would improve the algorithm speed.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Retrievals of ice cloud microphysical properties of deep convective systems using radar measurements: Convective Cloud Microphysical Retrieval

This study presents new algorithms for retrieving ice cloud microphysical properties (ice water content (IWC) and median mass diameter (Dm)) for the stratiform and thick anvil regions of Deep Convective Systems (DCSs) using Next-Generation Radar (NEXRAD) reflectivity and recently developed empirical relationships from aircraft in situ measurements during the Midlatitude Continental Convective Clouds Experiment (MC3E). A classic DCS case on 20 May 2011 is used to compare the retrieved IWC profiles with other retrieval and cloud-resolving model simulations. The mean values of each retrieved and simulated IWC fall within one standard derivation of the other two. The statistical results from six selected cases during MC3E show that the aircraft in situ derived IWC and Dm are 0.47 ± 0.29 g m-3 and 2.02 ± 1.3 mm, while the mean values of retrievals have a positive bias of 0.16 g m-3 (34%) and a negative bias of 0.39 mm (19%). To validate the newly developed retrieval algorithms from this study, IWC and Dm are performed with other DCS cases during Bow Echo and Mesoscale Convective Vortex Experiment (BAMEX) field campaign using composite gridded NEXRAD reflectivity and compared with in situ IWC and Dm from aircraft. A total of 64 1-min collocated aircraft and radar samples are available for comparisons, and the averages of radar retrieved and aircraft in situ measured IWCs are 1.22 g m-3 and 1.26 g m-3 with a correlation of 0.5, and their averaged Dm values are 2.15 and 1.80 mm. These comparisons have shown that the retrieval algorithms 45 developed during MC3E can retrieve similar ice cloud microphysical properties of DCS to aircraft in situ measurements during BAMEX with median errors of ~40% and ~25% for IWC and Dm retrievals, respectively. This is indicating our retrieval algorithms are suitable for other midlatitude continental DCS ice clouds, especially at stratiform rain and thick anvil regions. In addition, based on the averaged IWC and Dm values during MC3E and BAMEX, the DCS IWC values over midlatitude are significantly different, while their Dm values are close to each other. On the other hand, these DCS IWC and Dm values are 1-2 orders of magnitude larger than those of single-layered cirrus clouds over midlatitudes.

Tian, Jingjing↗
DOE OSTI2015

SU-E-J-25: End-To-End (E2E) Testing On TomoHDA System Using a Real Pig Head for Intracranial Radiosurgery

Purpose: To determine the MVCT imaging uncertainty on the TomoHDA system for intracranial radiosurgery treatments. To determine the end-to-end (E2E) overall accuracy of the TomoHDA system for intracranial radiosurgery. Methods: A pig head was obtained from the butcher, cut coronally through the brain, and preserved in formaldehyde. The base of the head was fixed to a positioning plate allowing precise movement, i.e. translation and rotation, in all 6 axes. A repeatability test was performed on the pig head to determine uncertainty in the image bone registration algorithm. Furthermore, the test studied images with MVCT slice thicknesses of 1 and 3 mm in unison with differing scan lengths. A sensitivity test was performed to determine the registration algorithm’s ability to find the absolute position of known translations/rotations of the pig head. The algorithm’s ability to determine absolute position was compared against that of manual operators, i.e. a radiation therapist and radiation oncologist. Finally, E2E tests for intracranial radiosurgery were performed by measuring the delivered dose distributions within the pig head using Gafchromic films. Results: The repeatability test uncertainty was lowest for the MVCTs of 1-mm slice thickness, which measured less than 0.10 mm and 0.12 deg for all axes. For the sensitivity tests, the bone registration algorithm performed better than human eyes and a maximum difference of 0.3 mm and 0.4 deg was observed for the axes. E2E test results in absolute position difference measured 0.03 ± 0.21 mm in x-axis and 0.28 ± 0.18 mm in y-axis. A maximum difference of 0.32 and 0.66 mm was observed in x and y, respectively. The average peak dose difference between measured and calculated dose was 2.7 cGy or 0.4%. Conclusion: Our tests using a pig head phantom estimate the TomoHDA system to have a submillimeter overall accuracy for intracranial radiosurgery.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-T-236: Comparison of Two IMRT/VMAT QA Systems Using Gamma Index Analysis

Purpose: The goal of this study is to assess differences in the Gamma index pass rates when using two commercial QA systems and provide optimum Gamma index parameters for pre-treatment patient specific QA. Methods: Twenty-two VMAT cases that consisted of prostate, lung, head and neck, spine, brain and pancreas, were included in this study. The verification plans have been calculated using AcurosXB(V11) algorithm for different dose grids (1.5mm, 2.5mm, 3mm). The measurements were performed on TrueBeam(Varian) accelerator using both EPID(S1000) portal imager and ArcCheck(SunNuclearCorp) devices. Gamma index criteria variation of 3%/3mm, 2%/3mm, 2%/2mm and threshold (TH) doses of 5% to 50% were used in analysis. Results: The differences in Gamma pass rates between two devices are not statistically significant for 3%/3mm, yielding pass rate higher than 95%. Increase of lower dose TH showed reduced pass rates for both devices. ArcCheck’s more pronounced effect can be attributed to higher contribution of lower dose region spread. As expected, tightening criteria to 2%/2mm (TH: 10%) decreased Gamma pass rates below 95%. Higher EPID (92%) pass rates compared to ArcCheck (86%) probably due to better spatial resolution. Portal Dosimetry results showed lower Gamma pass rates for composite plans compared to individual field pass rates. This may be due to the expansion in the analyzed region which includes pixels not included in the separate field analysis. Decreasing dose grid size from 2.5mm to 1.5mm did not show statistically significant (p<0.05) differences in Gamma pass rates for both QA devices. Conclusion: Overall, both system measurements agree well with calculated dose when using gamma index criteria of 3%/3mm for a variety of VMAT cases. Variability between two systems increases using different dose GRID, TH and tighter gamma criteria and must be carefully assessed prior to clinical use.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2019

Version 4 of the SMAP Level-4 Soil Moisture Algorithm and Data Product

The NASA Soil Moisture Active Passive (SMAP) mission Level-4 Soil Moisture (L4_SM) product provides global, 3-hourly, 9-km resolution estimates of surface (0-5 cm) and root-zone (0-100 cm) soil moisture with a mean latency of ~2.5 days. The underlying L4_SM algorithm assimilates SMAP radiometer brightness temperature (Tb) observations into the NASA Catchment land surface model using a spatially-distributed ensemble Kalman filter. Version 4 of the L4_SM modeling system includes a reduction in the upward recharge of surface soil moisture from below under non-equilibrium conditions, resulting in reduced bias and improved dynamic range of L4_SM surface soil moisture compared to earlier versions. This change and additional technical modifications to the system reduce the mean and standard deviation of the observation-minus-forecast Tb residuals and overall soil moisture analysis increments while maintaining the skill of the L4_SM soil moisture estimates versus independent in situ measurements; the average, bias-adjusted RMSE in Version 4 is 0.039 m(exp 3) m(exp -3) for surface and 0.026 m(exp 3) m(exp -3) for root-zone soil moisture. Moreover, the coverage of assimilated SMAP observations in Version 4 is near-global owing to the use of additional satellite Tb records for algorithm calibration. L4_SM soil moisture uncertainty estimates are biased low (by 0.01-0.02 m(exp 3) m(exp -3)) against actual errors (computed versus in situ measurements). L4_SM runoff estimates, an additional product of the L4_SM algorithm, are biased low (by 35 mm year (exp -1)) against streamflow measurements. Compared to Version 3, bias in Version 4 is reduced by 46% for surface soil moisture uncertainty estimates and by 33% for runoff estimates.

RMSE↗
DOE OSTI2015

SU-E-T-806: Very Fast GPU-Based IMPT Dose Computation

Purpose: Designing particle therapy treatment plans is a dosimetrist-in-the-loop optimization wherein the conflicting constraints of achieving a desired tumor dose distribution must be balanced against the need to minimize the dose to nearby OARs. IMPT introduces an additional, inner, numerical optimization step in which the dosimetrist’s current set of constraints are used to determine the weighting of beam spots. Very fast dose calculations are needed to enable the dosimetrist to perform many iterations of the outer optimization in a commercially reasonable time. Methods: We have developed a GPU-based convolution-type dose computation algorithm that more accurately handles heterogeneities than earlier algorithms by redistributing energy from dose computed in a water volume. The depth dependence of the beam size is handled by pre-processing Bragg curves using a weighted superposition of Gaussian bases. Additionally, scattering, the orientation of treatment ports, and the non-parallel propagation of beams are handled by large, but sparse, energy-redistribution matrices that implement affine transforms. Results: We tested our algorithm using a brain tumor dataset with 1 mm voxels and a single treatment port from the patient’s anterior through the sinuses. The resulting dose volume is 100 × 100 × 230 mm with 66,200 beam spots on a 3 × 3 × 2 mm grid. The dose computation takes <1 msec on a GeForce GTX Titan GPU with the Gamma passing rate for 2mm/2% criterion of 99.1% compared to dose calculated by an alternative dose algorithm based on pencil beams. We will present comparisons to Monte Carlo dose calculations. Conclusion: Our high-speed dose computation method enables the IMPT spot weights to be optimized in <1 second, resulting in a nearly instantaneous response to user changes to dose constraints. This permits the creation of higher quality plans by allowing the dosimetrist to evaluate more alternatives in a short period of time.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TU-FG-BRB-03: Basis Vector Model Based Method for Proton Stopping Power Estimation From Experimental Dual Energy CT Data

Purpose: This work aims at reducing the uncertainty in proton stopping power (SP) estimation by a novel combination of a linear, separable basis vector model (BVM) for stopping power calculation (Med Phys 43:600) and a statistical, model-based dual-energy CT (DECT) image reconstruction algorithm (TMI 35:685). The method was applied to experimental data. Methods: BVM assumes the photon attenuation coefficients, electron densities, and mean excitation energies (I-values) of unknown materials can be approximated by a combination of the corresponding quantities of two reference materials. The DECT projection data for a phantom with 5 different known materials was collected on a Philips Brilliance scanner using two scans at 90 kVp and 140 kVp. The line integral alternating minimization (LIAM) algorithm was used to recover the two BVM coefficient images using the measured source spectra. The proton stopping powers are then estimated from the Bethe-Bloch equation using electron densities and I-values derived from the BVM coefficients. The proton stopping powers and proton ranges for the phantom materials estimated via our BVM based DECT method are compared to ICRU reference values and a post-processing DECT analysis (Yang PMB 55:1343) applied to vendorreconstructed images using the Torikoshi parametric fit model (tPFM). Results: For the phantom materials, the average stopping power estimations for 175 MeV protons derived from our method are within 1% of the ICRU reference values (except for Teflon with a 1.48% error), with an average standard deviation of 0.46% over pixels. The resultant proton ranges agree with the reference values within 2 mm. Conclusion: Our principled DECT iterative reconstruction algorithm, incorporating optimal beam hardening and scatter corrections, in conjunction with a simple linear BVM model, achieves more accurate and robust proton stopping power maps than the post-processing, nonlinear tPFM based DECT analysis applied to conventional reconstructions of low and high energy scans. Funding Support: NIH R01CA 75371; NCI grant R01 CA 149305.

60 APPLIED LIFE SCIENCES↗