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SU-E-T-444: Gravity Effect On Maximum Leaf Speed in Dynamic IMRT Treatments

Purpose: A leaf sequencing algorithm has been recently developed in our department. Our purpose is to utilize this algorithm to reduce treatment time by studying the feasibility of using several maximum leaf speeds depending on gantry angle and leaf thickness (0.5 or 1 cm at isocenter). To do so, the gravity effect on MLC performance has been examined by means of analysing the dynalog files. Methods: Leaf position errors has been ascertained according to gantry angle and leaf speed in MLC Millenium120 (Varian). In order to do this, the following test has been designed: all leaves move in synchrony, with same speed and 1 cm gap between opposite leaves. This test is implemented for 18 different speeds: 0.25-0.5-0.75-1-1.25-1.5-1.75-2-2.1-2.2-2.3-2.4-2.5-2.6-2.7-2.8-2.9-3.0 cm/s and 8 gantry angles: 0-45-90-135-180-225-270-315. Collimator angle is 2 degrees in all cases since it is the most usual one in IMRT treatments in our department. Dynamic tolerance is 2 mm. Dynalogs files of 10 repetitions of the test are analysed with a Mathlab in-house developed software and RMS error and 95th percentiles are calculated. Varian recommends 2.5 cm/s as the maximum leaf speed for its segmentation algorithm. In our case, we accept this speed in the most restrictive situation: gantry angle 270 and 1 cm leaf thickness. Maximum speeds for the rest of the cases are calculated by keeping the difference between 95th percentile and dynamic tolerance. In this way, beam hold-off probability does not increase. Results: Maximum speeds every 45 degrees of gantry rotation have been calculated for both leaf thickness. These results are 2.9-2.9-2.9-2.9-2.7-2.6-2.6-2.7 cm/s for 0.5 cm leaf thickness and 2.7-2.7-2.7-2.7-2.6-2.5-2.5-2.6 cm/s for 1 cm leaf thickness. Conclusion: Gravity effect on MLC positioning has been studied. Maximum leaf speed according to leaf thickness and gantry angle have been calculated which reduces treatment time.

60 APPLIED LIFE SCIENCES↗

Intracore Natural Circulation Study in the High Temperature Test Facility

The development of the Modular High-Temperature Gas-Cooled Reactor is a significant milestone in advanced nuclear reactor technology. One of the concerns for the reactor’s safe operation is the effects of a loss-of-flow accident (LOFA) where the coolant circulators are tripped, and forced coolant flow through the core is lost. Depending on the steam generator placement, loop or intracore natural circulation develops to help transfer heat from the core to the reactor cavity, cooling system. This paper investigates the fundamental physical phenomena associated with intracore coolant natural circulation flow in a one-sixth Computational Fluid Dynamics (CFD) model of the Oregon State University High Temperature Test Facility (OSU HTTF) following a loss-of-flow accident transient. This study employs conjugate heat transfer and steady-state flow along with an SST k-ω turbulence model to characterize the phenomenon of core channel-to-channel natural convection. Previous studies have revealed the importance of complex flow distribution in the inlet and outlet plenums with the potential to generate hot coolant jets. For this reason, complete upper and lower plenum volumes are included in the analyzed computational domain. CFD results also include parametric studies performed for a mesh sensitivity analysis, generated using the STAR-CCM+ software. The resulting channel axial velocities and flow directions support the test facility scaling analysis and similarity group distortions calculation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Application of physiologically based pharmacokinetic modeling for sertraline dosing recommendations in pregnancy

Pregnancy is a period of significant change that impacts physiological and metabolic status leading to alterations in the disposition of drugs. Uncertainty in drug dosing in pregnancy can lead to suboptimal therapy, which can contribute to disease exacerbation. A few studies show there are increased dosing requirements for antidepressants in late pregnancy; however, the quantitative data to guide dose adjustments are sparse. We aimed to develop a physiologically based pharmacokinetic (PBPK) model that allows gestational-age dependent prediction of sertraline dosing in pregnancy. A minimal physiological model with defined gut, liver, plasma, and lumped placental-fetal compartments was constructed using the ordinary differential equation solver package, ‘mrgsolve’, in R. We extracted data from the literature to parameterize the model, including sertraline physicochemical properties, in vitro metabolism studies, disposition in nonpregnant women, and physiological changes during pregnancy. The model predicted the pharmacokinetic parameters from a clinical study with eight subjects for the second trimester and six subjects for the third trimester. Based on the model, gestational-dependent changes in physiology and metabolism account for increased clearance of sertraline (up to 143% at 40 weeks gestational age), potentially leading to under-dosing of pregnant women when nonpregnancy doses are used. The PBPK model was converted to a prototype web-based interactive dosing tool to demonstrate how the output of a PBPK model may translate into optimal sertraline dosing in pregnancy. Quantitative prediction of drug exposure using PBPK modeling in pregnancy will support clinically appropriate dosing and increase the therapeutic benefit for pregnant women.

60 APPLIED LIFE SCIENCES↗

Sparse thermal data for cellular automata modeling of grain structure in additive manufacturing

Grain growth in the wake of the melt pool formed during alloy-based additive manufacturing (AM) is complex and multifaceted, depending on parameters governing heat transport, fluid flow, and solidification itself. Cellular automata (CA) models have proven effective in providing computationally efficient and physically sound predictions of grain structure for several AM problems, but their efficiency is tied to the performance of heat transport models. CA models use only a small portion of the problem's temperature data (near the moving melt pool boundary), and much of the CA calculations do not affect the final result due to re-melting of material. Coupling of and communication between heat transport and solidification models, and eliminating operations irrelevant towards final grain structure prediction, will be necessary for using these methods for efficient simulation of large parts. In this work, we introduce a procedure of decoupling the CA from temperature field simulation, using files of relevant temperature data written by the heat transport model. This approach is validated against the standard coupling approach using data obtained through the computational fluid dynamics software OpenFOAM. Negligible differences are seen in grain size, volume, and texture distributions for multilayer simulation of test problems, while the quantity of temperature data for these test problems was reduced by four orders of magnitude (from 100s of GB to 10s of MB) and the code performance sped up by a factor of around 50. Furthermore, variability in microstructure as a function of cell size, substrate, time step, and nucleation parameters is studied, and it is found that cell sizes less than or equal to 1.67 μm and sufficiently small time steps yield Αstatistically equivalent microstructures. Finally, a potential use case for this CA approach—the layer-wise convergence in grain structure starting from extremes in initial grain size—is examined. This approach's ability to simulate expected trends in nucleation and epitaxial grain growth for large regions of microstructure, simulated independently of heat transport models themselves, should prove useful for investigation of various microstructure uncertainties and prediction of part-scale experimental results.

36 MATERIALS SCIENCE↗

Fungal and bacterial growth variation due to drought and nitrogen addition experimental treatments. Loma Ridge Experimental Project. 2010-2012

Terrestrial ecosystem models assume that microbial communities respond instantaneously, or are immediately resilient, to environmental change. Here we tested this assumption by quantifying the resilience of a leaf litter community to changes in precipitation or nitrogen availability. By manipulating composition within a global change experiment, we decoupled the legacies of abiotic parameters versus that of the microbial community itself. After one rainy season, more variation in fungal composition could be explained by the original microbial inoculum than the litterbag environment (18% versus 5.5% of total variation). This compositional legacy persisted for 3 years, when 6% of the variability in fungal composition was still explained by the microbial origin. In contrast, bacterial composition was generally more resilient than fungal composition. Microbial functioning (measured as decomposition rate) was not immediately resilient to the global change manipulations; decomposition depended on both the contemporary environment and rainfall the year prior. Finally, using metagenomic sequencing, we showed that changes in precipitation, but not nitrogen availability, altered the potential for bacterial carbohydrate degradation, suggesting why the functional consequences of the two experiments may have differed. Predictions of how terrestrial ecosystem processes respond to environmental change may thus be improved by considering the legacies of microbial communities. This data package includes ten csv files (five data files and their corresponding data dictionaries) and one file-level metadata excel file. Data files contains information about which plots were exposed to treatments related to drought and nitrogen, information about litter bags reciprocal transplants manipulation for water input and nitrogen, detail information about water addition, precipitation records, and litter variables collected. Data dictionary files include detail explanation for each column in the data files. The file-level metadata file describes each file mentioned above. All the analyses were done using the R software.

54 ENVIRONMENTAL SCIENCES↗

Validation Data Acquisition in HTTF during PCC Events

A validation experimental campaign was conducted in an Integral Effect Test (IET) facility of High Temperature Gas Reactors (HTGR), the High-Temperature Test Facility (HTTF) at Oregon State University (OSU). The HTTF simulates Depressurized and Pressurized Conduction Cooldowns (DCC and PCC). This campaign required the development of a new laser spectroscopic diagnostic to measure velocity in the challenging conditions of the HTTF: low speed (~1 m/s) gas flows at HTGR prototypical temperature and 1/10th pressure. This was a collaborative effort between co-PIs at The George Washington University (GW), Oregon State University (OSU), and NASA Langley Research Center. The main accomplishments of this project include the record for dynamic range for velocimetry, highest accuracy obtained with this technique, successful deployment in an IET leading to new validation matrix for CFD. These are detailed below and in manuscript appended to this executive summary. For this project, we introduced a new class of laser spectroscopic diagnostics to Thermal-Hydraulics to measure velocity of gases; furthermore, the diagnostic was demonstrated in-situ in an IET during DCC events. In such scenarios, particles used in mainstream techniques, like Particle Image Velocimetry (PIV) are not appropriate as they settle down too rapidly and also contaminate the experimental facility. Molecular tracers stay mixed within the working gas and can seed the flow in a technique called Molecular Tagging Velocimetry (MTV). In MTV a molecular tracer is photo-dissociated by a first (write) laser into radicals or molecules. The pattern created by the write laser is then interrogated with planar laser-induced fluorescence (PLIF), the read pulse(s), which are recorded with a camera. The pattern is probed and matched at two times (interval or probe time, dt), resulting in a time-of-flight velocimetry technique. This project demonstrated a new application range for MTV in gases. MTV has been extensively used for high-speed gas dynamics: molecules do not suffer from inertia associated with particles in regions of high accelerations (such as shock waves). For high-speed flows, the probe time is on the order of 0.1-10 µs. In time-of-flight techniques, the velocity is reconstructed from the recorded displacement, dx, between time interval dt: U = dx/dt. To first order, the resolution of the pattern matching is typically a (fixed) fraction of a pixel; therefore the resolution of the velocity measurement increases with dx and, for a given flow velocity, dt. For the low-speed flows of interest here, this requires long probe time, and therefore finding tracers that are stable for a long time. After an extensive literature survey we identified 6 tracers that would be suitable. We also worked with Spectra Physics to design a custom laser system that is flexible enough to probe these various tracers. The final instrument is made of 4 lasers that are integrated into a compact and movable cart to facilitate the deployment of the instrument off-site. One unique aspect of the laser system is the tunable dye laser (needed to do PLIF of the radicals). By being pumped by two Nd:YAG lasers, this laser is able to provide two pulses with any probe time (dt) for wavelengths between 200 and 900 nm with a linewidth of 3 pm. Accommodating the dual-pulse capability required customizing the pump lasers and the dye laser, making this system unique. Additionally, a custom UV-intensified CCD camera capable of frame-straddling and exposure time as short as 10 ns was acquired. More than two-third of the instrument cost (~$200k) was covered by a cost sharing from the PI’s startup funds. Of the 6 potential tracers identified, two were tested extensively (H2O and N2O) at high-temperature and elevated pressure at GW prior to conducting the tests at OSU. For both tracers, an Ar-F laser (193 nm, 10 ns, 10 mJ/pulse) photo-dissociates trace amounts (0.1 – 5% molar fraction) of the gases into OH and NO. OH is probed at 281.905 nm and NO at 226.186 nm (4-30mJ, 10 ns pulse). NO is very stable in inert environment and we could reconstruct velocities precisely with probe delay times as long at 40 ms, compared to 2 ms for OH, resulting in increased precision. Therefore, for the tests in the HTTF, N2O was selected as the final tracer and its optimal concentration was determined to be 0.5% molar. In the GW laboratory, we obtained a velocity measurement precision of 4 mm/s at conditions mimicking the HTTF tests. We also demonstrated the benefit of molecular tracers over particles and the flexibility of our instrument by continuously measuring velocity from 1000 to 0.1 m/s in a blow down test. This represents a dynamic range on velocity of 80 dB, which is unprecedented for velocimetry! Once the diagnostic was optimized, two two-week campaigns were conducted in the HTTF. This experimental campaign required numerous practical solutions to successfully and rapidly deploy this very sensitive table-top diagnostic in-situ. This was accomplished thanks to very extensive planning from all parties involved in the project. Due to constraints on availability of the HTTF, only adiabatic DCC tests were conducted. Specifically, the velocity was measured at the exit of the hot leg into the Reactor Cavity Simulation Tank (RCST). We were able to record the gas velocity associated with the air ingress for long times (up to one hour). Depending on the initial conditions (density of the gases in the Reactor Pressure Vessel and the RCST) the lock exchange lasted 30-60 s past the valve openings. Large vortices were identified within the shear layer at the interface of the cross flow. These vortices are an indication of shear-driven instability between the counter streams of different density. After the lock-exchange, a small residual flow was still present and its strength decayed exponentially. It finds its source in a buoyancy difference between the gases in both vessels due to the mixing and diffusion of the gases in the cross-over duct and the RPV lower plenum. We did not expect to capture this part of the transient, which would have been less significant (if not negligible) in the presence of a heated core; the precision of our measurement in the HTTF was 6 mm/s, which exceeded our expectations for such a complex test! Using commercial software (Fluent) we simulated the experiment with Computational Fluid Dynamic (CFD) using Reynolds Averaged Navier-Stokes (RANS) turbulence models. We were not able to accurately reproduce the shear layer instability, mixing, and diffusion captured in our experimental data, even with large 3D meshes (>10 M points). We attributed this to the inadequacy of the RANS models for the flow of interest: our experimental Reynolds number was too low and was outside the applicability range of the RANS models. Instead, we should have employed CFD with less modeling, such as Large Eddy (LES) or even Direct Numerical (DNS) simulations. Unfortunately, we did not have the computational resources to do so. Finally, it should be noted that this experimental technique holds great promises for measuring velocity in thermalhydraulics. MTV has an application domain (highlighted in the narrative) that is complimentary to more established (and simpler) techniques, such as PIV. It has attracted the attention of several thermalhydraulics researchers and sponsors to measure velocity in harsh environments. The spectroscopic nature of this technique also enables to expand it to measure temperature and concentration simultaneously to velocity. In lieu of a narrative, 4 detailed journal publications are appended to this executive summary to describe the various development and accomplishments during this project. They include 2 published manuscripts (Experiments in Fluids and Measurement Science and Technology), and two invited contributions following the NURETH-17 conference (Nuclear Science and Technology). Our current Nuclear Engineering and Design draft is not included at this time.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Baseflow Identification via Explainable AI With Kolmogorov‐Arnold Networks

Abstract Hydrological models often involve constitutive laws that may not be optimal in every application. We propose to replace such laws with the Kolmogorov‐Arnold networks (KANs), a class of neural networks designed to identify symbolic expressions. We demonstrate KAN's potential on the problem of baseflow identification, a notoriously challenging task plagued by significant uncertainty. KAN‐derived functional dependencies of the baseflow components on the aridity index outperform their original counterparts; they demonstrate that water availability, rather than potential evapotranspiration, drives baseflow by constraining actual evapotranspiration under arid conditions. On a test set, they increase the Nash‐Sutcliffe efficiency (NSE) by 65%, decrease the root mean squared error by 29%, and increase the Kling‐Gupta efficiency by 34%. This superior performance is achieved while reducing the number of fitting parameters from three to two. Next, we use data from 378 catchments across the continental United States to refine the water‐balance equation at the mean‐annual scale. The KAN‐derived equations based on the refined water balance outperform both the current aridity index model, with up to a 105% increase in NSE, and the KAN‐derived equations based on the original water balance. While the performance of our model and tree‐based machine learning methods is similar, KANs offer the advantage of simplicity and transparency and require no specific software or computational tools. This case study focuses on the aridity index formulation, but the approach is flexible and transferable to other hydrological processes. Plain Language Summary Equations used in hydrologic model are often suboptimal, resulting in reduced prediction accuracy and efficiency. We implemented Kolmogorov‐Arnold networks (KAN), a machine learning algorithm for deriving symbolic formulations, to estimate groundwater recharge and showed that it outperforms an existing state‐of‐the‐art semi‐empirical formulation. In hydrology, Nash‐Sutcliffe efficiency (NSE), root mean squared error (RMSE), and Kling‐Gupta efficiency (KGE) are commonly used to evaluate model performance. Higher NSE and KGE values indicate better performance, while lower RMSE values are preferable. Our results show that NSE increased by 71%, RMSE decreased by 32%, and KGE improved by 25%. In addition, KAN identifies an optimal functional form and can be used to derive new analytical formulas using the prior knowledge. The KAN‐inspired equation outperformed the original formulation and reduced the fitting parameters. Furthermore, we refined the water‐balance equation at the mean‐annual scale and showed that, based on the new water‐balance equation, KAN can derive new formulations that are superior to the original aridity index formulations (up to 105% increase in NSE) and KAN‐derived equations based on the original water balance. These findings highlight the significant potential of KAN to advance the scientific understanding of a wide range of hydrologic processes. Key Points Kolmogorov‐Arnold networks (KANs) enhance interpretability of machine‐learned hydrological models KAN‐derived symbolic formulations outperform state‐of‐the‐art semi‐empirical aridity indices KAN‐identified functional form yields an analytical index with fewer fitting parameters and improved performance

baseflow↗

Two excited-state datasets for quantum chemical UV-vis spectra of organic molecules

Abstract We present two open-source datasets that provide time-dependent density-functional tight-binding (TD-DFTB) electronic excitation spectra of organic molecules. These datasets represent predictions of UV-vis absorption spectra performed on optimized geometries of the molecules in their electronic ground state. The GDB-9-Ex dataset contains a subset of 96,766 organic molecules from the original open-source GDB-9 dataset. The ORNL_AISD-Ex dataset consists of 10,502,904 organic molecules that contain between 5 and 71 non-hydrogen atoms. The data reveals the close correlation between the magnitude of the gaps between the highest occupied molecular orbital (HOMO) and the lowest unoccupied molecular orbital (LUMO), and the excitation energy of the lowest singlet excited state energies quantitatively. The chemical variability of the large number of molecules was examined with a topological fingerprint estimation based on extended-connectivity fingerprints (ECFPs) followed by uniform manifold approximation and projection (UMAP) for dimension reduction. Both datasets were generated using the DFTB+ software on the “Andes” cluster of the Oak Ridge Leadership Computing Facility (OLCF).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Direct Modeling of Scintillator Thickness for Optimal Light Output and Spatial Resolution

It is common in x-ray radiography to use scintillators (e.g., BGO or LSO) to convert x-rays to visible light, which is then recorded by an imaging system. The response of the scintillator depends fundamentally on its thickness, with respect to both its visible light emittance and its spatial resolution. This is important for optimizing light output, signal to noise ratio, or optical response time. Given that it is often cost-prohibitive to procure a variety of scintillator samples and empirically test the performance, it is essential to be able to model and accurately simulate the performance of a scintillator with respect to thickness and other properties, and a direct way of doing this is using Monte Carlo-based radiation transport codes. Such simulations can be expensive in terms of computational time, and the codes are not easily obtained. In this work we first show such simulations, and demonstrate that there is a natural trade-off between light output of a scintillator and its spatial resolution. We then derive a first-principles model that accurately approximates the light output, using straightforward calculations that can be performed quickly with any basic computing software. We compare the results to those obtained from Monte Carlo simulations and show that our simplified model can be used to analyze the tradeoff between emittance and resolution nearly as well as using a full-scale radiation transport code.

Monte Carlo methods, X-ray imaging, scintillation ↗

SU-F-T-618: Evaluation of a Mono-Isocentric Treatment Planning Software for Stereotactic Radiosurgery of Multiple Brain Metastases

Purpose: To evaluate planning performance of an automated treatment planning software (BrainLAB; Elements) for stereotactic radiosurgery (SRS) of multiple brain metastases. Methods: Brainlab’s Multiple Metastases Elements (MME) uses single isocentric technique to treat up to 10 cranial planning target volumes (PTVs). The planning algorithm of the MME accounts for multiple PTVs overlapping with one another on the beam eyes view (BEV) and automatically selects a subset of all overlapping PTVs on each arc for sparing normal tissues in the brain. The algorithm also optimizes collimator angles, margins between multi-leaf collimators (MLCs) and PTVs, as well as monitor units (MUs) using minimization of conformity index (CI) for all targets. Planning performance was evaluated by comparing the MME-calculated treatment plan parameters with the same parameters calculated with the Volumetric Modulated Arc Therapy (VMAT) optimization on Varian’s Eclipse platform. Results: Figures 1 to 3 compare several treatment plan outcomes calculated between the MME and VMAT for 5 clinical multi-targets SRS patient plans. Prescribed target dose was volume-dependent and defined based on the RTOG recommendation. For a total number of 18 PTV’s, mean values for the CI, PITV, and GI were comparable between the MME and VMAT within one standard deviation (σ). However, MME-calculated MDPD was larger than the same VMAT-calculated parameter. While both techniques delivered similar maximum point doses to the critical cranial structures and total MU’s for the 5 patient plans, the MME required less treatment planning time by an order of magnitude compared to VMAT. Conclusion: The MME and VMAT produce similar plan qualities in terms of MUs, target dose conformation, and OAR dose sparing. While the selective use of PTVs for arc-optimization with the MME reduces significantly the total planning time in comparison to VMAT, the target dose homogeneity was also compromised due to its simplified inverse planning algorithm used.

60 APPLIED LIFE SCIENCES↗

BisQue for 3D Materials Science in the Cloud: Microstructure–Property Linkages

Accelerating the design and development of new advanced materials is one of the priorities in modern materials science. These efforts are critically dependent on the development of comprehensive materials cyber-infrastructures which enable effcient data storage, management, sharing, and collaboration as well as integration of computational tools that help establish processing{structure{property relationships. In this contribution, we present implementation of such computational tools into a cloud-based platform called BisQue (Kvilekval et al., 2010). We first describe the current state of BisQue as an open-source platform for multidisciplinary research in the cloud and its potential for 3D materials science. We then demonstrate how new computational tools, primarily aimed at processing{structure{property relationships, can be implemented into the system. Speci cally, in this work, we develop a module for BisQue that enables microstructure-sensitive predictions of effective yield strength of two-phase materials. Towards this end, we present an implementation of a computationally effcient data-driven model into the BisQue platform. The new module is made available online and can be used from a web browser without any special software and with minimal computational requirements on the user end. The capabilities of the module for rapid property screening are demonstrated in case studies with two different methodologies based on datasets containing 3D microstructure information from (i) synthetic generation and (ii) sampling large 3D volumes obtained in experiments.

36 MATERIALS SCIENCE↗

srlife : A software tool for estimating the life of high temperature concentrating solar receivers. Part II – Ceramic receivers

As Concentrating Solar Power (CSP) technologies aim for higher operating temperatures to enhance efficiency and meet industrial process heat demands, high-temperature metallic materials, including nickel-based superalloys, face challenges in maintaining structural integrity. Advanced ceramics offer a promising alternative due to their superior high-temperature strength. However, accurately assessing the performance of ceramic components requires a fundamentally different approach from that used for metallic components. This Part II of a two-part paper describes the integration of ceramic statistical failure models within srlife – an open-source tool for predicting the life of high-temperature CSP receivers. These models account for the inherent variability in ceramic strength, as well as the effects of subcritical crack growth (SCG) under high temperature cyclic loads. Here, the paper includes an example problem that demonstrate the process of evaluating ceramic receivers using srlife. Part I details the life estimation process for metallic receivers (i.e. creep-fatigue life) along with input and output data structure, thermohydraulic analysis, and structural analysis. The complete tool is available as open-source software at https://github.com/srlife-project/srlife and can be installed via the PyPi package manager (https://pypi.org). By supporting both ceramic and metallic receiver analyses, srlife facilitates fair comparisons between competing metallic and ceramic designs, enabling accurate evaluations of plant efficiency and the economic benefits of ceramic solar receivers and other components.

High temperature ceramic receivers↗

Validation of a deformable image registration technique for cone beam CT-based dose verification

Purpose: As radiation therapy evolves toward more adaptive techniques, image guidance plays an increasingly important role, not only in patient setup but also in monitoring the delivered dose and adapting the treatment to patient changes. This study aimed to validate a method for evaluation of delivered intensity modulated radiotherapy (IMRT) dose based on multimodal deformable image registration (DIR) for prostate treatments. Methods: A pelvic phantom was scanned with CT and cone-beam computed tomography (CBCT). Both images were digitally deformed using two realistic patient-based deformation fields. The original CT was then registered to the deformed CBCT resulting in a secondary deformed CT. The registration quality was assessed as the ability of the DIR method to recover the artificially induced deformations. The primary and secondary deformed CT images as well as vector fields were compared to evaluate the efficacy of the registration method and it’s suitability to be used for dose calculation. PLASTIMATCH, a free and open source software was used for deformable image registration. A B-spline algorithm with optimized parameters was used to achieve the best registration quality. Geometric image evaluation was performed through voxel-based Hounsfield unit (HU) and vector field comparison. For dosimetric evaluation, IMRT treatment plans were created and optimized on the original CT image and recomputed on the two warped images to be compared. The dose volume histograms were compared for the warped structures that were identical in both warped images. This procedure was repeated for the phantom with full, half full, and empty bladder. Results: The results indicated mean HU differences of up to 120 between registered and ground-truth deformed CT images. However, when the CBCT intensities were calibrated using a region of interest (ROI)-based calibration curve, these differences were reduced by up to 60%. Similarly, the mean differences in average vector field lengths decreased from 10.1 to 2.5 mm when CBCT was calibrated prior to registration. The results showed no dependence on the level of bladder filling. In comparison with the dose calculated on the primary deformed CT, differences in mean dose averaged over all organs were 0.2% and 3.9% for dose calculated on the secondary deformed CT with and without CBCT calibration, respectively, and 0.5% for dose calculated directly on the calibrated CBCT, for the full-bladder scenario. Gamma analysis for the distance to agreement of 2 mm and 2% of prescribed dose indicated a pass rate of 100% for both cases involving calibrated CBCT and on average 86% without CBCT calibration. Conclusions: Using deformable registration on the planning CT images to evaluate the IMRT dose based on daily CBCTs was found feasible. The proposed method will provide an accurate dose distribution using planning CT and pretreatment CBCT data, avoiding the additional uncertainties introduced by CBCT inhomogeneity and artifacts. This is a necessary initial step toward future image-guided adaptive radiotherapy of the prostate.

60 APPLIED LIFE SCIENCES↗

Monte Carlo reference data sets for imaging research: Executive summary of the report of AAPM Research Committee Task Group 195

The use of Monte Carlo simulations in diagnostic medical imaging research is widespread due to its flexibility and ability to estimate quantities that are challenging to measure empirically. However, any new Monte Carlo simulation code needs to be validated before it can be used reliably. The type and degree of validation required depends on the goals of the research project, but, typically, such validation involves either comparison of simulation results to physical measurements or to previously published results obtained with established Monte Carlo codes. The former is complicated due to nuances of experimental conditions and uncertainty, while the latter is challenging due to typical graphical presentation and lack of simulation details in previous publications. In addition, entering the field of Monte Carlo simulations in general involves a steep learning curve. It is not a simple task to learn how to program and interpret a Monte Carlo simulation, even when using one of the publicly available code packages. This Task Group report provides a common reference for benchmarking Monte Carlo simulations across a range of Monte Carlo codes and simulation scenarios. In the report, all simulation conditions are provided for six different Monte Carlo simulation cases that involve common x‐ray based imaging research areas. The results obtained for the six cases using four publicly available Monte Carlo software packages are included in tabular form. In addition to a full description of all simulation conditions and results, a discussion and comparison of results among the Monte Carlo packages and the lessons learned during the compilation of these results are included. This abridged version of the report includes only an introductory description of the six cases and a brief example of the results of one of the cases. This work provides an investigator the necessary information to benchmark his/her Monte Carlo simulation software against the reference cases included here before performing his/her own novel research. In addition, an investigator entering the field of Monte Carlo simulations can use these descriptions and results as a self‐teaching tool to ensure that he/she is able to perform a specific simulation correctly. Finally, educators can assign these cases as learning projects as part of course objectives or training programs.

Sechopoulos, Ioannis↗

Ab Initio Direct Dynamics

The reactivity and dynamics of molecular systems can be explored computationally by classical trajectory calculations. The traditional approach involves fitting a functional form of a potential energy surface (PES) to the energies from a large number of electronic structure calculations and then integrating numerous trajectories on this fitted PES to model the molecular dynamics. The ever-decreasing cost of computing and continuing advances in computational chemistry software have made it possible to use electronic structure calculations directly in molecular dynamics simulations without first having to construct a fitted PES. In this “on-the-fly” approach, every time the energy and its derivatives are needed for the integration of the equations of motion, they are obtained directly from quantum chemical calculations. This approach started to become practical in the mid-1990s as a result of increased availability of inexpensive computer resources and improved computational chemistry software. The application of direct dynamics calculations has grown rapidly over the last 25 years and would require a lengthy review article. The present Account is limited to some of our contributions to methods development and various applications. To improve the efficiency of direct dynamics calculations, we developed a Hessian-based predictor-corrector algorithm for integrating classical trajectories. Hessian updating made this even more efficient. Furthermore, this approach was also used to improve algorithms for following the steepest descent reaction paths. For larger molecular systems, we developed an extended Lagrangian approach in which the electronic structure is propagated along with the molecular structure. Strong field chemistry is a rapidly growing area, and to improve the accuracy of molecular dynamics in intense laser fields, we included the time-varying electric field in a novel predictor-corrector trajectory integration algorithm. Since intense laser fields can excite and ionize molecules, we extended our studies to include electron dynamics. Specifically, we developed code for time-dependent configuration interaction electron dynamics to simulate strong field ionization by intense laser pulses. Our initial application of ab initio direct dynamics in 1994 was to CH 2 O → H 2 + CO; the calculated vibrational distributions in the products were in very good agreement with experiment. In the intervening years, we have used direct dynamics to explore energy partitioning in various dissociation reactions, unimolecular dissociations yielding three fragments, reactions with branching after the transition state, nonstatistical dynamics of chemically activated molecules, dynamics of molecular fragmentation by intense infrared laser pulses, selective activation of specific dissociation channels by aligned intense infrared laser fields, angular dependence of strong field ionization, and simulation of sequential double ionization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A benchmark concept for simulation in radiographic testing

The new standard ISO 17636–2:2013 “NDT of welds: Radiographic testing - Part 2: X- and gamma ray techniques with digital detectors” describes a complex procedure for film replacement by phosphor imaging plates and digital detector arrays. RT modeling software should consider these detector types, X-ray film, and the standard requirements for image quality. Practitioners expect the same visibility of image quality indicators (IQI) in the simulated radiographs as in the experimental exposures. The proposed benchmark test is based on the comparison of experimental radiographs taken at BAM with modeled ones of participants. The experimental setup and the determination of the equivalent penetrameter sensitivity (EPS) as described in the procedure of ASTM E 746 are used for quantitative evaluation of the achievable contrast sensitivity for step hole IQIs as considered in Annex B of ISO 17636–2. System classification data for Computed Radiography (CR) and film systems will be provided by BAM according to ISO 11699–1 for selected film systems and according to ASTM E 2446 for selected CR systems. The classification of films and digital detectors is based on the measurement of the dose response function, the basic spatial resolution (SR{sub b}) of the image, and the measured image noise, which depends on the detector efficiency, the quantum statistics, and the detector fixed pattern noise.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Investigating ion recombination effects in a liquid-filled ionization chamber array used for IMRT QA measurements

Purpose: PTW’s Octavius 1000 SRS array performs IMRT quality assurance (QA) measurements with liquid-filled ionization chambers (LICs) to allow closer detector spacing and higher resolution, compared to air-filled QA devices. However, reduced ion mobility in LICs relative to air leads to increased ion recombination effects and reduced collection efficiencies that are dependent on Linac pulse frequency and pulse dose. These pulse parameters are variable during an IMRT delivery, which affects QA results. In this study, (1) 1000 SRS collection efficiencies were measured as a function of pulse frequency and pulse dose, (2) two methods were developed to correct changes in collection efficiencies during IMRT QA measurements, and the effects of these corrections on QA pass rates were compared. Methods: To obtain collection efficiencies, the OCTAVIUS 1000 SRS was used to measure open fields of varying pulse frequency, pulse dose, and beam energy with results normalized to air-filled chamber measurements. Changes in ratios of 1000 SRS to chamber measured dose were attributed to changing collection efficiencies, which were then correlated to pulse parameters using regression analysis. The usefulness of the derived corrections was then evaluated using 6 MV and 10FFF SBRT RapidArc plans delivered to the OCTAVIUS 4D system using a TrueBeam (Varian Medical Systems) linear accelerator equipped with a high definition multileaf collimator. For the first correction, MATLAB software was developed that calculates pulse frequency and pulse dose for each detector, using measurement and DICOM RT Plan files. Pulse information is converted to collection efficiency, and measurements are corrected by multiplying detector dose by ratios of calibration to measured collection efficiencies. For the second correction the MU/min in the daily 1000 SRS calibration was chosen to match the average MU/min of the volumetric modulated arc therapy plan. Effects of the two corrections on QA results were examined by performing 3D gamma analysis comparing predicted to measured dose, with and without corrections. Results: Collection efficiencies correlated linearly to pulse dose, while correlations with pulse frequency were less defined, generally increasing as pulse frequency decreased. After complex MATLAB corrections, average 3D gamma pass rates improved by [0.07%,0.40%,1.17%] for 6 MV and [0.29%,1.40%,4.57%] for 10FFF using [3%/3 mm,2%/2 mm,1%/1 mm] criteria. Maximum changes in gamma pass rates were [0.43%,1.63%,3.05%] for 6 MV and [1.00%,4.80%,11.2%] for 10FFF using [3%/3 mm,2%/2 mm,1%/1 mm] criteria. On average, pass rates of simple daily calibration corrections were within 1% of complex MATLAB corrections. Conclusions: OCTAVIUS 1000 SRS ion recombination effects have little effect on 6 MV measurements. However, the effect could potentially be clinically significant for higher pulse dose unflattened beams when using tighter gamma tolerances, especially when small aperture sizes are used, as is common for SRS/SBRT. In addition, ion recombination effects are strongly correlated to changing MU/min, therefore MU/min used in daily 1000 SRS calibrations should be matched to the expected average MU/min of the IMRT plan.

60 APPLIED LIFE SCIENCES↗

BinaRena: a dedicated interactive platform for human-guided exploration and binning of metagenomes

Background: Exploring metagenomic contigs and “binning” them into metagenome-assembled genomes (MAGs) are essential for the delineation of functional and evolutionary guilds within microbial communities. Despite the advances in automated binning algorithms, their capabilities in recovering MAGs with accuracy and biological relevance are so far limited. Researchers often find that human involvement is necessary to achieve representative binning results. This manual process however is expertise demanding and labor intensive, and it deserves to be supported by software infrastructure. Results: We present BinaRena, a comprehensive and versatile graphic interface dedicated to aiding human operators to explore metagenome assemblies via customizable visualization and to associate contigs with bins. Contigs are rendered as an interactive scatter plot based on various data types, including sequence metrics, coverage profiles, taxonomic assignments, and functional annotations. Various contig-level operations are permitted, such as selection, masking, highlighting, focusing, and searching. Binning plans can be conveniently edited, inspected, and compared visually or using metrics including silhouette coefficient and adjusted Rand index. Completeness and contamination of user-selected contigs can be calculated in real time. In demonstration of BinaRena’s usability, we show that it facilitated biological pattern discovery, hypothesis generation, and bin refinement in a complex tropical peatland metagenome. It enabled isolation of pathogenic genomes within closely related populations from the gut microbiota of diarrheal human subjects. It significantly improved overall binning quality after curating results of automated binners using a simulated marine dataset. Conclusions: BinaRena is an installation-free, dependency-free, client-end web application that operates directly in any modern web browser, facilitating ease of deployment and accessibility for researchers of all skill levels. The program is hosted at https://github.com/qiyunlab/binarena, together with documentation, tutorials, example data, and a live demo. It effectively supports human researchers in intuitive interpretation and fine tuning of metagenomic data.

59 BASIC BIOLOGICAL SCIENCES↗