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DOE OSTI2016

Soft-Collinear Mode for Jet Rates in Soft-Collinear Effective Theory

We propose the addition of a new "soft-collinear" mode to soft collinear effective theory (SCET) below the usual soft scale to factorize and resum logarithms of jet radii R in jet cross sections. We consider exclusive 2-jet cross sections in e + e - collisions with an energy veto Λ on additional jets. The key observation is that there are actually two pairs of energy scales whose ratio is R: the transverse momentum QR of the energetic particles inside jets and their total energy Q, and the transverse momentum ΛR of soft particles that are cut out of the jet cones and their energy Λ. The soft-collinear mode is necessary to factorize and resum logarithms of the latter hierarchy. We show how this factorization occurs in the jet thrust cross section for cone and k T -type algorithms at O(α s ) and using the thrust cone algorithm at O(α$2\atop{s}$). We identify the presence of hard-collinear, in-jet soft, global (veto) soft, and soft-collinear modes in the jet thrust cross section. We also observe here that the in-jet soft modes measured with thrust are actually the "csoft" modes of the theory SCET + . We dub the new theory with both csoft and soft-collinear modes "SCET ++ ". We go on to explain the relation between the "unmeasured" jet function appearing in total exclusive jet cross sections and the hard-collinear and csoft functions in measured jet thrust cross sections. We do not resum logs that are non-global in origin, arising from the ratio of the scales of soft radiation whose thrust is measured at Q${{\tau}}$/R and of the soft-collinear radiation at 2ΛR. Their resummation would require the introduction of additional operators beyond those we consider here. The steps we outline here are a necessary part of summing logs of R that are global in nature and have not been factorized and resummed beyond leading-log level previously.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Slow dynamics in a single bead with mechanical conditioning and transient heating

The contact stiffness of an aluminum bead confined between two slabs diminishes upon mechanical conditioning, and then recovers like log(t) after the conditioning ceases. Here that structure is evaluated for its response to transient heating and cooling, with and without accompanying conditioning vibrations. It is found that, under heating or cooling alone, stiffness changes are mostly consistent with temperature dependent material moduli; there is little or no slow dynamics. Hybrid tests in which vibration conditioning is followed by heating or cooling lead to recoveries that begin like log(t) and then become more complex. On subtracting the known response to heating or cooling alone we discern the influence of higher or lower temperatures on slow dynamic recovery from vibrations. It is found that heating accelerates the initial log(t) recovery, but by an amount more than predicted by an Arrhenius model of thermally activated barrier penetrations. Furthermore, transient cooling has no discernable effect, in contrast to the Arrhenius prediction that it slows recovery.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Rodeo Algorithm for Quantum Computing

We present a stochastic quantum computing algorithm that can prepare any eigenvector of a quantum Hamiltonian within a selected energy interval $\ [E-\epsilon, E+\epsilon]$. In order to reduce the spectral weight of all other eigenvectors by a suppression factor δ, the required computational effort scales as $\ O[|\log \delta|/(p \epsilon)]$, where p s the squared overlap of the initial state with the target eigenvector. The method, which we call the rodeo algorithm, uses auxiliary qubits to control the time evolution of the Hamiltonian minus some tunable parameter E . In this manner, we converge to the target eigenvector with exponential accuracy in the number of measurements. In addition to preparing eigenvectors, the method can also compute the full spectrum of the Hamiltonian. We illustrate the performance with several examples. For energy eigenvalue determination with error $\epsilon$, the computational scaling is $\ O[(\log \epsilon)^2/(p \epsilon)]$. For eigenstate preparation, the computational scaling is $\ O(\log \Delta/p)$, where $\Delta$ is the magnitude of the orthogonal component of the residual vector. The speed for eigenstate preparation is exponentially faster than that for phase estimation or adiabatic evolution.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Generalized Quantum Signal Processing

Quantum signal processing (QSP) and quantum singular value transformation (QSVT) currently stand as the most efficient techniques for implementing functions of block-encoded matrices, a central task that lies at the heart of most prominent quantum algorithms. However, current QSP approaches face several challenges, such as the restrictions imposed on the family of achievable polynomials and the difficulty of calculating the required phase angles for specific transformations. In this paper, we present a generalized quantum signal processing (GQSP) approach, employing general SU(2) rotations as our signal-processing operators, rather than relying solely on rotations in a single basis. Our approach lifts all practical restrictions on the family of achievable transformations, with the sole remaining condition being that | P | ≤ 1 , a restriction necessary due to the unitary nature of quantum computation. Furthermore, GQSP provides a straightforward recursive formula for determining the rotation angles needed to construct the polynomials in cases where P and Q are known. In cases where only P is known, we provide an efficient optimization algorithm capable of identifying in under a minute of GPU time, a corresponding Q for polynomials of degree on the order of 10 7 . We further illustrate GQSP simplifies QSP-based strategies for Hamiltonian simulation, offer an optimal solution to the ϵ -approximate fractional query problem that requires O ( ( 1 / δ ) + log ( 1 / ϵ ) ) queries to perform where O ( 1 / δ ) is a proved lower bound, and introduces novel approaches for implementing bosonic operators. Moreover, we propose a novel framework for the implementation of normal matrices, demonstrating its applicability through synthesis of diagonal matrices, as well as the development of a new algorithm for convolution through synthesis of circulant matrices using only O ( d log N + log 2 N ) 1 and 2-qubit gates for a filter of lengths d . Published by the American Physical Society 2024

Motlagh, Danial↗

DOE OSTI2023

Malicious Cyber Activity Detection using Zigzag Persistence

In this study we synthesize zigzag persistence from topological data analysis with autoencoder-based approaches to detect malicious cyber activity, and derive analytic insights. Cybersecurity aims to safeguard computers, networks, and servers from various forms of malicious attacks, including network damage, data theft, and activity monitoring. We focus on the cybersecurity domain and investigate the detection of malicious activity using log data. We consider the dynamics of the log data and explore the changing topology of a hypergraph representation of this data to gain insights into the underlying activity. These hypergraphs capture complex interactions between processes, together with their temporal information. To study the changing topology we use zigzag persistence, which captures how topological features persist at multiple dimensions over time. We observe that this detects malicious activity in a cyber data set. To automate this detection we implement an autoencoder trained on a vectorization of the resulting zigzag persistence barcodes. Our experimental results demonstrate the effectiveness of the autoencoder in detecting malicious activity. Overall, this study highlights the potential of zigzag persistence and its combination with temporal hypergraphs for analyzing cybersecurity log data and detecting malicious behavior.

hypergraphs, temporal hypergraph, topological data↗

DOE OSTI2019

Combining Tensor Decompositions and Graph Analytics to Provide Cyber Situational Awareness at HPC Scale

This paper describes MADHAT (Multidimensional Anomaly Detection fusing HPC, Analytics, and Tensors), an integrated workflow that demonstrates the applicability of HPC resources to the problem of maintaining cyber situational awareness. MADHAT combines two high-performance packages: ENSIGN for large-scale sparse tensor decompositions and HAGGLE for graph analytics. Tensor decompositions isolate coherent patterns of network behavior in ways that common clustering methods based on distance metrics cannot. Parallelized graph analysis then uses directed queries on a representation that combines the elements of identified patterns with other available information (such as additional log fields, domain knowledge, network topology, whitelists and blacklists, prior feedback, and published alerts) to confirm or reject a threat hypothesis, collect context, and raise alerts. MADHAT was developed using the collaborative HPC Architecture for Cyber Situational Awareness (HACSAW) research environment and evaluated on structured network sensor logs collected from Defense Research and Engineering Network (DREN) sites using HPC resources at the U.S. Army Engineer Research and Development Center DoD Supercomputing Resource Center (ERDC DSRC). To date, MADHAT has analyzed logs with over 650 million entries.

Cyber security, Tensor decomposition, graph analyt↗

DOE OSTI2020

Understanding the Interplay between Hardware Errors and User Job Characteristics on the Titan Supercomputer

Designing dependable supercomputers begins with an understanding of errors in real-world, large-scale systems. The Titan supercomputer at Oak Ridge National Laboratory provides a unique opportunity to investigate errors when an actual system is actively used by multiple concurrent users and workloads from diverse domains at varying scales. This study presents a thorough analysis of 6, 908, 497 hardware errors from 18, 688 compute nodes of Titan for 312, 215 user jobs over a 3-year time period. Through careful joining of two system logs – the Machine Check Architecture (MCA) log and the job scheduler log – we show the correlated pattern of hardware errors for each job and user, in addition to individual descriptive statistics of errors, jobs, and users. Since the majority of hardware errors are memory errors, this study also shows the importance of error correcting in memory systems.

Lim, Seung-Hwan↗

DOE OSTI2016

PATHA: Performance Analysis Tool for HPC Applications

Large science projects rely on complex workflows to analyze terabytes or petabytes of data. These jobs are often running over thousands of CPU cores and simultaneously performing data accesses, data movements, and computation. It is difficult to identify bottlenecks or to debug the performance issues in these large workflows. In order to address these challenges, we have developed Performance Analysis Tool for HPC Applications (PATHA) using the state-of-art open source big data processing tools. Our framework can ingest system logs to extract key performance measures, and apply the most sophisticated statistical tools and data mining methods on the performance data. Furthermore, it utilizes an efficient data processing engine to allow users to interactively analyze a large amount of different types of logs and measurements. To illustrate the functionality of PATHA, we conduct a case study on the workflows from an astronomy project known as the Palomar Transient Factory (PTF). This study processed 1.6 TB of system logs collected on the NERSC supercomputer Edison. Using PATHA, we were able to identify performance bottlenecks, which reside in three tasks of PTF workflow with the dependency on the density of celestial objects.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2017

Salmonella Inactivation During Extrusion of an Oat Flour Model Food

Abstract Little research exists on Salmonella inactivation during extrusion processing, yet many outbreaks associated with low water activity foods since 2006 were linked to extruded foods. The aim of this research was to study Salmonella inactivation during extrusion of a model cereal product. Oat flour was inoculated with Salmonella enterica serovar Agona, an outbreak strain isolated from puffed cereals, and processed using a single‐screw extruder at a feed rate of 75 kg/h and a screw speed of 500 rpm. Extrudate samples were collected from the barrel outlet in sterile bags and immediately cooled in an ice–water bath. Populations were determined using standard plate count methods or a modified most probable number when populations were low. Reductions in population were determined and analyzed using a general linear model. The regression model obtained for the response surface tested was Log ( N R / N O ) = 20.50 + 0.82 T − 141.16a w – 0.0039 T 2 + 87.91 a w 2 ( R 2 = 0.69). The model showed significant ( p < 0.05) linear and quadratic effects of a w and temperature and enabled an assessment of critical control parameters. Reductions of 0.67 ± 0.14 to 7.34 ± 0.02 log CFU/g were observed over ranges of a w (0.72 to 0.96) and temperature (65 to 100 °C) tested. Processing conditions above 82 °C and 0.89 a w achieved on average greater than a 5‐log reduction of Salmonella . Results indicate that extrusion is an effective means for reducing Salmonella as most processes commonly employed to produce cereals and other low water activity foods exceed these parameters. Thus, contamination of an extruded food product would most likely occur postprocessing as a result of environmental contamination or through the addition of coatings and flavorings.

Anderson, Nathan M.↗

DOE OSTI2015

Biofilm Detection in a Model Well-Bore Environment Using Low-Field NMR

This research addresses the challenges of the lack of non-invasive methods and poor spatiotemporal resolution associated with monitoring biogeochemical activity central to bioremediation of subsurface contaminants. Remediation efforts often include growth of biofilm to contain or degrade chemical contaminants, such as nitrates, hydrocarbons, heavy metals, and some chlorinated solvents. Previous research indicates that nuclear magnetic resonance (NMR) is sensitive to the biogeochemical processes of biofilm accumulation. The current research focuses on developing methods to use low-cost NMR technology to support in situ monitoring of biofilm growth and geochemical remediation processes in the subsurface. Biofilm was grown in a lab-scale radial flow bioreactor designed to model the near wellbore subsurface environment. The Vista Clara Javelin NMR logging device, a slim down-the-borehole probe, collected NMR measurements over the course of eight days while biofilm was cultivated in the sand-packed reactor. Measured NMR mean log T 2 relaxation times decreased from approximately 710 to 389 ms, indicating that the pore environment and bulk fluid properties were changing due to biofilm growth. Destructive sampling employing drop plate microbial population analysis and scanning electron and stereoscopic microscopy confirmed biofilm formation. Here our findings demonstrate that the NMR logging tool can detect small to moderate changes in T 2 distribution associated with environmentally relevant quantities of biofilm in quartz sand.

58 GEOSCIENCES↗

DOE OSTI2023

Morphological traits for allometric scaling of the European Sea Bass Dicentrarchus labrax (Linnaeus, 1758) from Southern Portugal population

Abstract The present study aimed to determine the allometric scaling among a selection of morphological traits in European sea bass ( Dicentrarchus labrax ) to estimate fish body weight. A set of morphological traits (fish body weight, length, height, and width) were directly measured in 146 fish of a recirculating aquaculture system, with body weights ranging from 17.11 to 652.21 g. In addition, a collection of digital imagery of each anesthetized fish from the side and top views were used to estimate other traits (indirect measures). Multiple regression analysis and regression coefficients were calculated using all possible combinations of biometric data (predictors) to estimate fish body weight, applying different numerical fitting models (linear, log‐linear, quadratic, exponential). The results showed that the best combination of traits for estimating fish body weight were fish body width, length and height, collected from direct measure ( R 2 = 0.995), for a log‐linear model fitting, which revealed more accurate determinations than the most commonly used length–weight relationship. Nevertheless, other combinations of morphological traits and fitting models were also found to be suitable in successfully predict fish body weight, with variability ranging between 92.5% and 98.5%. For indirect measures, the best predictor was a combination of traits from top view (width, eye distance and area without fins) fitted with a log‐linear function. These results comprise a relevant baseline in supporting the high potential of noninvasive methods to accurately follow the growth of European sea bass juveniles, recurring to imagery analysis of anesthetized fish. It has major potential applications in feeding consumption trials and fish growth models, as it allows for continuously following up fish growth under different experimental conditions without therein distress derived from manipulation.

Azevedo, Ana↗

DOE OSTI2025

Fate of Listeria monocytogenes Serotypes on Frozen Mixed Vegetables During Consumer‐Simulated Thawing and Storage

ABSTRACT Recent outbreaks and recalls associated with frozen vegetables in the United States and Europe have been linked to Listeria monocytogenes . This study aims to understand the extent to which frozen vegetables support the growth of L. monocytogenes once thawed and held at different temperatures. Six L. monocytogenes strains, two of each from serotypes 1/2a, 1/2b, and 4b, were individually inoculated onto frozen vegetables and stored at −18°C for 7 days. After 7 days, the vegetables were thawed and stored at 5°C or 10°C for up to 14 days or at 25°C for up to 7 days. L. monocytogenes was enumerated from the thawed vegetables throughout the storage period. Population data were fitted to the primary Baranyi model to estimate growth rates and lag phase durations; the secondary Ratkowsky square root model was used to model the relationship of the growth rates with storage temperature. Five of the L. monocytogenes strains survived and grew on the thawed vegetables (population increases of > 1 log CFU/g) stored at 5°C, and all six of the strains proliferated at 10°C and 25°C (population increases of > 3 log CFU/g after 14 days and > 4 log CFU/g after 7 days, respectively). A secondary model was successfully generated based on the growth rates of the six L. monocytogenes strains on the thawed vegetables ( r 2 = 0.8888, RMSE = 0.2057). Results from this study fill a data gap associated with L. monocytogenes survival on thawed vegetables and can be used to determine safe handling and storage practices for these products to protect public health.

Salazar, Joelle K. [Division of Food Processing Sc↗

DOE OSTI2010

Detailed analysis of latencies in image-based dynamic MLC tracking

Purpose: Previous measurements of the accuracy of image-based real-time dynamic multileaf collimator (DMLC) tracking show that the major contributor to errors is latency, i.e., the delay between target motion and MLC response. Therefore the purpose of this work was to develop a method for detailed analysis of latency contributions during image-based DMLC tracking. Methods: A prototype DMLC tracking system integrated with a linear accelerator was used for tracking a phantom with an embedded fiducial marker during treatment delivery. The phantom performed a sinusoidal motion. Real-time target localization was based on x-ray images acquired either with a portal imager or a kV imager mounted orthogonal to the treatment beam. Each image was stored in a file on the imaging workstation. A marker segmentation program opened the image file, determined the marker position in the image, and transferred it to the DMLC tracking program. This program estimated the three-dimensional target position by a single-imager method and adjusted the MLC aperture to the target position. Imaging intervals {Delta}T{sub image} from 150 to 1000 ms were investigated for both kV and MV imaging. After the experiments, the recorded images were synchronized with MLC log files generated by the MLC controller and tracking log files generated by the tracking program. This synchronization allowed temporal analysis of the information flow for each individual image from acquisition to completed MLC adjustment. The synchronization also allowed investigation of the MLC adjustment dynamics on a considerably finer time scale than the 50 ms time resolution of the MLC log files. Results: For {Delta}T{sub image}=150 ms, the total time from image acquisition to completed MLC adjustment was 380{+-}9 ms for MV and 420{+-}12 ms for kV images. The main part of this time was from image acquisition to completed image file writing (272 ms for MV and 309 ms for kV). Image file opening (38 ms), marker segmentation (4 ms), MLC position calculation (16 ms), and MLC adjustment (52 ms) were considerably faster. For {Delta}T{sub image}=1000 ms, the total time from image acquisition to completed MLC adjustment increased to 1030{+-}62 ms (MV) and 1330{+-}52 ms (kV) mainly because of delayed image file writing. The MLC adjustment duration was constant 52 ms ({+-}3 ms) for MLC adjustments below 1.1 mm and increased linearly for larger MLC adjustments. Conclusions: A method for detailed time analysis of each individual real-time position signal for DMLC tracking has been developed and applied to image-based tracking. The method allows identification of the major contributors to latency and therefore a focus for reducing this latency. The method could be an important tool for the reconstruction of the delivered target dose during DMLC tracking as it provides synchronization between target motion and MLC motion.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2013

Information-theoretic discrepancy based iterative reconstructions (IDIR) for polychromatic x-ray tomography

Purpose: X-ray photons generated from a typical x-ray source for clinical applications exhibit a broad range of wavelengths, and the interactions between individual particles and biological substances depend on particles' energy levels. Most existing reconstruction methods for transmission tomography, however, neglect this polychromatic nature of measurements and rely on the monochromatic approximation. In this study, we developed a new family of iterative methods that incorporates the exact polychromatic model into tomographic image recovery, which improves the accuracy and quality of reconstruction.Methods: The generalized information-theoretic discrepancy (GID) was employed as a new metric for quantifying the distance between the measured and synthetic data. By using special features of the GID, the objective function for polychromatic reconstruction which contains a double integral over the wavelength and the trajectory of incident x-rays was simplified to a paraboloidal form without using the monochromatic approximation. More specifically, the original GID was replaced with a surrogate function with two auxiliary, energy-dependent variables. Subsequently, the alternating minimization technique was applied to solve the double minimization problem. Based on the optimization transfer principle, the objective function was further simplified to the paraboloidal equation, which leads to a closed-form update formula. Numerical experiments on the beam-hardening correction and material-selective reconstruction were conducted to compare and assess the performance of conventional methods and the proposed algorithms.Results: The authors found that the GID determines the distance between its two arguments in a flexible manner. In this study, three groups of GIDs with distinct data representations were considered. The authors demonstrated that one type of GIDs that comprises “raw” data can be viewed as an extension of existing statistical reconstructions; under a particular condition, the GID is equivalent to the Poisson log-likelihood function. The newly proposed GIDs of the other two categories consist of log-transformed measurements, which have the advantage of imposing linearized penalties over multiple discrepancies. For all proposed variants of the GID, the aforementioned strategy was used to obtain a closed-form update equation. Even though it is based on the exact polychromatic model, the derived algorithm bears a structural resemblance to conventional methods based on the monochromatic approximation. The authors named the proposed approach as information-theoretic discrepancy based iterative reconstructions (IDIR). In numerical experiments, IDIR with raw data converged faster than previously known statistical reconstruction methods. IDIR with log-transformed data exhibited superior reconstruction quality and faster convergence speed compared with conventional methods and their variants.Conclusions: The authors' new framework for tomographic reconstruction allows iterative inversion of the polychromatic data model. The primary departure from the traditional iterative reconstruction was the employment of the GID as a new metric for quantifying the inconsistency between the measured and synthetic data. The proposed methods outperformed not only conventional methods based on the monochromatic approximation but also those based on the polychromatic model. The authors have observed that the GID is a very flexible means to design an objective function for iterative reconstructions. Hence, the authors expect that the proposed IDIR framework will also be applicable to other challenging tasks.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2013

A full-spectral Bayesian reconstruction approach based on the material decomposition model applied in dual-energy computed tomography

Purpose: Dual-energy computed tomography (DECT) makes it possible to get two fractions of basis materials without segmentation. One is the soft-tissue equivalent water fraction and the other is the hard-matter equivalent bone fraction. Practical DECT measurements are usually obtained with polychromatic x-ray beams. Existing reconstruction approaches based on linear forward models without counting the beam polychromaticity fail to estimate the correct decomposition fractions and result in beam-hardening artifacts (BHA). The existing BHA correction approaches either need to refer to calibration measurements or suffer from the noise amplification caused by the negative-log preprocessing and the ill-conditioned water and bone separation problem. To overcome these problems, statistical DECT reconstruction approaches based on nonlinear forward models counting the beam polychromaticity show great potential for giving accurate fraction images.Methods: This work proposes a full-spectral Bayesian reconstruction approach which allows the reconstruction of high quality fraction images from ordinary polychromatic measurements. This approach is based on a Gaussian noise model with unknown variance assigned directly to the projections without taking negative-log. Referring to Bayesian inferences, the decomposition fractions and observation variance are estimated by using the joint maximum a posteriori (MAP) estimation method. Subject to an adaptive prior model assigned to the variance, the joint estimation problem is then simplified into a single estimation problem. It transforms the joint MAP estimation problem into a minimization problem with a nonquadratic cost function. To solve it, the use of a monotone conjugate gradient algorithm with suboptimal descent steps is proposed.Results: The performance of the proposed approach is analyzed with both simulated and experimental data. The results show that the proposed Bayesian approach is robust to noise and materials. It is also necessary to have the accurate spectrum information about the source-detector system. When dealing with experimental data, the spectrum can be predicted by a Monte Carlo simulator. For the materials between water and bone, less than 5% separation errors are observed on the estimated decomposition fractions.Conclusions: The proposed approach is a statistical reconstruction approach based on a nonlinear forward model counting the full beam polychromaticity and applied directly to the projections without taking negative-log. Compared to the approaches based on linear forward models and the BHA correction approaches, it has advantages in noise robustness and reconstruction accuracy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2014

The use of strain tensor to estimate thoracic tumors deformation

Purpose: Respiration-induced kinematics of thoracic tumors suggests a simple analogy with elasticity, where a strain tensor is used to characterize the volume of interests. The application of the biomechanical framework allows for the objective determination of tumor characteristics. Methods: Four-dimensional computed tomography provides the snapshots of the patient's anatomy at the end of inspiration and expiration. Image registration was used to obtain the displacement vector fields and deformation fields, which allows one for the determination of the strain tensor. Its departure from the identity matrix gauges the departure of the medium from rigidity. The tensorial characteristic of each GTV voxel was determined and averaged. To this end, the standard Euclidean matrix norm as well as the Log-Euclidean norm were employed. Tensorial anisotropy was gauged with the fractional anisotropy measure which is based on the normalized variance of the tensors eigenvalues. Anisotropy was also evaluated with the geodesic distance in the Log-Euclidean framework of a given strain tensor to its closest isotropic counterpart. Results: The averaged strain tensor was determined for each of the 15 retrospectively analyzed thoracic GTVs. The amplitude of GTV motion varied from 0.64 to 4.21 with the average of 1.20 cm. The GTV size ranged from 5.16 to 149.99 cc with the average of 43.19 cc. The tensorial analysis shows that deformation is inconsiderable and that the tensorial anisotropy is small. The Log-Euclidean distance of averaged strain tensors from the identity matrix ranged from 0.06 to 0.31 with the average of 0.19. The Frobenius distance from the identity matrix is similar and ranged from 0.06 to 0.35 with the average of 0.21. Their fractional anisotropy ranged from 0.02 to 0.12 with the average of 0.07. Their geodesic anisotropy ranged from 0.03 to 0.16 with the average of 0.09. These values also indicate insignificant deformation. Conclusions: The tensorial framework allows for direct measurements of tissue deformation. It goes beyond the evaluation of deformation via comparison of shapes. It is an independent and objective determination of tissue properties. This methodology can be used to determine possible changes in lung properties due to radiation therapy and possible toxicities.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

TH-A-9A-10: Prostate SBRT Delivery with Flattening-Filter-Free Mode: Benefit and Accuracy

Purpose: Flattening-filter-free (FFF) beam mode offered on TrueBeam™ linac enables delivering IMRT at 2400 MU/min dose rate. This study investigates the benefit and delivery accuracy of using high dose rate in the context of prostate SBRT. Methods: 8 prostate SBRT patients were retrospectively studied. In 5 cases treated with 600-MU/min dose rate, continuous prostate motion data acquired during radiation-beam-on was used to analyze motion range. In addition, the initial 1/3 of prostate motion trajectories during each radiation-beam-on was separated to simulate motion range if 2400-MU/min were used. To analyze delivery accuracy in FFF mode, MLC trajectory log files from an additional 3 cases treated at 2400-MU/min were acquired. These log files record MLC expected and actual positions every 20ms, and therefore can be used to reveal delivery accuracy. Results: (1) Benefit. On average treatment at 600-MU/min takes 30s per beam; whereas 2400-MU/min requires only 11s. When shortening delivery time to ~1/3, the prostate motion range was significantly smaller (p<0.001). Largest motion reduction occurred in Sup-Inf direction, from [−3.3mm, 2.1mm] to [−1.7mm, 1.7mm], followed by reduction from [−2.1mm, 2.4mm] to [−1.0mm, 2.4mm] in Ant-Pos direction. No change observed in LR direction [−0.8mm, 0.6mm]. The combined motion amplitude (vector norm) confirms that average motion and ranges are significantly smaller when beam-on was limited to the 1st 1/3 of actual delivery time. (2) Accuracy. Trajectory log file analysis showed excellent delivery accuracy with at 2400 MU/min. Most leaf deviations during beam-on were within 0.07mm (99-percentile). Maximum leaf-opening deviations during each beam-on were all under 0.1mm for all leaves. Dose-rate was maintained at 2400-MU/min during beam-on without dipping. Conclusion: Delivery prostate SBRT with 2400 MU/min is both beneficial and accurate. High dose rates significantly reduced both treatment time and intra-beam prostate motion range. Excellent delivery accuracy was confirmed with very small leaf motion deviation.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2015

SU-E-I-58: Experiences in Setting Up An Online Fluoroscopy Tracking System in a Large Healthcare System

Purpose: Transitioning from a paper based to an online system for tracking fluoroscopic case information required by state regulation and to conform to NCRP patient dose tracking suggestions. Methods: State regulations require documentation of operator, equipment, and some metric of tube output for fluoroscopy exams. This information was previously collected in paper logs, which was cumbersome and inefficient for the large number of fluoroscopic units across multiple locations within the system. The “tech notes” feature within Siemens’ Syngo workflow RIS was utilized to create an entry form for technologists to input case information, which was sent to a third party vendor for archiving and display though an online web based portal. Results: Over 55k cases were logged in the first year of implementation, with approximately 6,500 cases per month once fully online. A system was built for area managers to oversee and correct data, which has increased the accuracy of inputted values. A high-dose report was built to automatically send notifications when patients exceed trigger levels. In addition to meeting regulatory requirements, the new system allows for larger scale QC in fluoroscopic cases by allowing comparison of data from specific procedures, locations, equipment, and operators so that instances that fall outside of reference levels can be identified for further evaluation. The system has also drastically improved identification of operators without documented equipment specific training. Conclusion: The transition to online fluoroscopy logs has improved efficiency in meeting state regulatory requirements as well as allowed for identification of particular procedures, equipment, and operators in need of additional attention in order to optimize patient and personnel doses, while high dose alerts improve patient care and follow up. Future efforts are focused on incorporating case information from outside of radiology, as well as on automating processes for increased efficiencies.

60 APPLIED LIFE SCIENCES↗