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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Effect of MLC leaf width on treatment adaptation and accuracy for concurrent irradiation of prostate and pelvic lymph nodes

Purpose: The aim of the study was to evaluate the impact of multileaf collimator (MLC) leaf width on treatment adaptation and delivery accuracy for concurrent treatment of the prostate and pelvic lymph nodes with intensity modulated radiation therapy (IMRT). Methods: Seventy-five kilovoltage cone beam CTs (KV-CBCT) from six patients were included for this retrospective study. For each patient, three different IMRT plans were created based on a planning CT using three different MLC leaf widths of 2.5, 5, and 10 mm, respectively. For each CBCT, the prostate displacement was determined by a dual image registration. Adaptive plans were created by shifting selected MLC leaf pairs to compensate for daily prostate movements. To evaluate the impact of MLC leaf width on the adaptive plan for each daily CBCT, three MLC shifted plans were created using three different leaf widths of MLCs (a total of 225 adaptive treatment plans). Selective dosimetric endpoints for the tumor volumes and organs at risk (OARs) were evaluated for these adaptive plans. Using the planning CT from a selected patient, MLC shifted plans for three hypothetical longitudinal shifts of 2, 4, and 8 mm were delivered on the three linear accelerators to test the deliverability of the shifted plans and to compare the dose accuracy of the shifted plans with the original IMRT plans. Results: Adaptive plans from 2.5 and 5 mm MLCs had inadequate dose coverage to the prostate (D99 < 97%, or D{sub mean} < 99% of the planned dose) in 6%-8% of the fractions, while adaptive plans from 10 mm MLC led to inadequate dose coverage to the prostate in 25.3% of the fractions. The average V{sub 56Gy} of the prostate over the six patients was improved by 6.4% (1.6%-32.7%) and 5.8% (1.5%-35.7%) with adaptive plans from 2.5 and 5 mm MLCs, respectively, when compared with adaptive plans from 10 mm MLC. Pelvic lymph nodes were well covered for all MLC adaptive plans, as small differences were observed for D99, D{sub mean}, and V{sub 50.4Gy}. Similar OAR sparing could be achieved for the bladder and rectum with all three MLCs for treatment adaptation. The MLC shifted plans can be accurately delivered on all three linear accelerators with accuracy similar to their original IMRT plans, where gamma (3%/3 mm) passing rates were 99.6%, 93.0%, and 92.1% for 2.5, 5, and 10 mm MLCs, respectively. The percentages of pixels with dose differences between the measurement and calculation being less than 3% of the maximum dose were 85.9%, 82.5%, and 70.5% for the original IMRT plans from the three MLCs, respectively. Conclusions: Dosimetric advantages associated with smaller MLC leaves were observed in terms of the coverage to the prostate, when the treatment was adapted to account for daily prostate movement for concurrent irradiation of the prostate and pelvic lymph nodes. The benefit of switching the MLC from 10 to 5 mm was significant (p Much-Less-Than 0.01); however, switching the MLC from 5 to 2.5 mm would not gain significant (p= 0.15) improvement. IMRT plans with smaller MLC leaf widths achieved more accurate dose delivery.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

Benefits of adaptive radiation therapy in lung cancer as a function of replanning frequency

Purpose: To quantify the potential benefit associated with daily replanning in lung cancer in terms of normal tissue dose sparing and to characterize the tradeoff between adaptive benefit and replanning frequency. Methods: A set of synthetic images and contours, derived from weekly active breathing control images of 12 patients who underwent radiation therapy treatment for nonsmall cell lung cancer, is generated for each fraction of treatment using principal component analysis in a way that preserves temporal anatomical trends (e.g., tumor regression). Daily synthetic images and contours are used to simulate four different treatment scenarios: (1) a “no-adapt” scenario that simulates delivery of an initial plan throughout treatment, (2) a “midadapt” scenario that implements a single replan for fraction 18, (3) a “weekly adapt” scenario that simulates weekly adaptations, and (4) a “full-adapt” scenario that simulates daily replanning. An initial intensity modulated radiation therapy plan is created for each patient and replanning is carried out in an automated fashion by reoptimizing beam apertures and weights. Dose is calculated on each image and accumulated to the first in the series using deformable mappings utilized in synthetic image creation for comparison between simulated treatments. Results: Target coverage was maintained and cord tolerance was not exceeded for any of the adaptive simulations. Average reductions in mean lung dose (MLD) and volume of lung receiving 20 Gy or more (V20{sub lung}) were 65 ± 49 cGy (p = 0.000 01) and 1.1% ± 1.2% (p = 0.0006), respectively, for all patients. The largest reduction in MLD for a single patient was 162 cGy, which allowed an isotoxic escalation of the target dose of 1668 cGy. Average reductions in cord max dose, mean esophageal dose (MED), dose received by 66% of the heart (D66{sub heart}), and dose received by 33% of the heart (D33{sub heart}), were 158 ± 280, 117 ± 121, 37 ± 77, and 99 ± 120 cGy, respectively. Average incremental reductions in MLD for the midadapt, weekly adapt, and full-adapt treatments were 38, 18, and 8 cGy, respectively. Incremental reductions in MED for the same treatments were 57, 37, and 23 cGy. Reductions in MLD and MED for the full-adapt treatment were correlated with the absolute decrease in the planning target volume (r = 0.34 and r = 0.26). Conclusions: Adaptive radiation therapy for lung cancer yields clinically relevant reductions in normal tissue doses for frequencies of adaptation ranging from a single replan up to daily replanning. Increased frequencies of adaptation result in additional benefit while magnitude of benefit decreases.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TU-H-CAMPUS-JeP3-01: Towards Robust Adaptive Radiation Therapy Strategies

Purpose: To set up a framework combining robust treatment planning with adaptive reoptimization in order to maintain high treatment quality, to respond to interfractional variations and to identify those patients who will benefit the most from an adaptive fractionation schedule. Methods: We propose adaptive strategies based on stochastic minimax optimization for a series of simulated treatments on a one-dimensional patient phantom. The plan should be able to handle anticipated systematic and random errors and is applied during the first fractions. Information on the individual geometric variations is gathered at each fraction. At scheduled fractions, the impact of the measured errors on the delivered dose distribution is evaluated. For a patient that receives a dose that does not satisfy specified plan quality criteria, the plan is reoptimized based on these individual measurements using one of three different adaptive strategies. The reoptimized plan is then applied during future fractions until a new scheduled adaptation becomes necessary. In the first adaptive strategy the measured systematic and random error scenarios and their assigned probabilities are updated to guide the robust reoptimization. The focus of the second strategy lies on variation of the fraction of the worst scenarios taken into account during robust reoptimization. In the third strategy the uncertainty margins around the target are recalculated with the measured errors. Results: By studying the effect of the three adaptive strategies combined with various adaptation schedules on the same patient population, the group which benefits from adaptation is identified together with the most suitable strategy and schedule. Preliminary computational results indicate when and how best to adapt for the three different strategies. Conclusion: A workflow is presented that provides robust adaptation of the treatment plan throughout the course of treatment and useful measures to identify patients in need for an adaptive treatment strategy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Recommended Actions to Improve Adapter Safety

With the rapid advancement and acceleration in the electric vehicle (EV) industry within the United States, major automakers and EV charging companies are increasingly adopting the North American Charging Standard (NACS) connector style, now officially known as J3400. This shift is expected to enhance charging infrastructure, providing a better customer experience by making it easier for all EV drivers to access a wider network of direct-current (DC) fast chargers (DCFCs). However, the adoption of the J3400 standard presents challenges for many EVs already on the roads and some currently coming off production lines that are equipped with the Combined Charging System (CCS) connector, which this report will refer to as the North American standard, CCS1. These vehicles will need adapters to use new or existing J3400 infrastructure. During this transition, several issues have emerged. Firstly, there is a need to standardize the new connector type to ensure it is interoperable, safe, and reliable. Second, existing CCS EV drivers need a way to access the J3400 network, which will require electric vehicle supply equipment (EVSE) or sites with both connector types, driver-provided adapters to physically convert from CCS to J3400, or EVSE with retained adapters designed for use with the EVSE. Third, adapter standards will need to be written to specify how they will be designed and what evaluations will be needed to ensure safe and reliable performance. To address these challenges, adapters that support different types of charging connectors will be essential. These adapters will play a crucial role in supporting the transition and ensuring continued service for legacy EVs with CCS inlets as the J3400 standard becomes the predominant one in the United States. Consequently, the National Charging Experience (ChargeX) Consortium has investigated and performed a teardown analysis on the different adapter versions on the market. The aim is to create a failure mode and effects analysis (FMEA) on what are expected to be the most common adapter types used in this transition. In order to support this work, we executed an FMEA exercise with the main goal of identifying gaps in the existing adapters' performance and conformance to the most common safety requirements of high-power and high-voltage devices. This effort focused on adapters provided by the driver, as these may present the highest safety and reliability risks. The recommendations made here apply to both retained and driver-provided adapters.

25 ENERGY STORAGE↗
DOE OSTI2025

Evaluating How Climate Adaptation Measures Affect the Interconnected Water‐Energy Resource Systems of the Western United States

Abstract The Western US faces increasing water stress from the impacts of climate change, making it difficult to meet water demands for the region's cities, agriculture, and hydropower generators. Existing literature suggests that climate adaptation measures such as water conservation, cropland retirement, wastewater recycling, and managed aquifer recharge can alleviate some of these challenges. Few analyses, however, compare the relative efficacy and system‐wide effects of these adaptations under different climate projections across the entire Western United States. Here we use a Western US‐wide water systems model to evaluate, by sector and sub‐region, how the widespread implementation of these adaptive measures impacts water demands, water deliveries, and electricity use related to the water system for three different climate projections. We find that wastewater recycling has greater potential to lower unmet indoor water demands than urban indoor water conservation measures. However, when implemented at scale, indoor water conservation reduces electricity use by an average of 683 Terawatt hours while wastewater recycling increases energy use by an average of 721 Terawatt hours, cumulatively from 2020 to 2070. Cropland retirement and aquifer recharge adaptations increase the ability to meet agricultural water demand, increase groundwater storage, and reduce summertime electricity use. While most of these findings are consistent across different climate projections, the benefits of aquifer recharge are sensitive to spatial variation of precipitation. Given the limitations and tradeoffs of each individually, the results suggest that a portfolio of adaptation measures will be needed for a climate‐resilient water and energy future in the Western US. Plain Language Summary The Western US faces increased water stress from the impacts of climate change, making it difficult to meet demands for cities, agriculture, and hydropower facilities. Adaptation measures like water conservation, retiring agricultural lands, recycling wastewater, and storing water underground can address these challenges. However, there is little modeling to understand the impact of these adaptations if they were implemented across the entire Western US while also considering climate change. We use a Western US‐wide water systems model to evaluate how implementing adaptation measures impacts groundwater levels, the ability to meet water demands, and electricity use related to water in three different possible climate futures. We find that recycling wastewater to drinking water standards does a better job of meeting urban water demands than water conservation measures. However, indoor water conservation reduces energy use for water while recycling wastewater increases energy use for water. Retiring agricultural lands and storing water underground both increase the ability to meet agricultural water demands, increase underground water storage, and reduce summertime energy use. No adaptation measures provides benefits across every metric we track. Therefore, multiple adaptation measures will likely be needed to achieve a climate‐resilient future for energy and water in the Western US. Key Points Water‐related climate change adaptations have different benefits and tradeoffs for interconnected water‐energy systems in the Western U.S. Wastewater recycling most increases urban water coverage, but has a significant tradeoff in the form of greater electricity use Cropland retirement and aquifer recharge benefit water and electricity systems most in the summer when those systems are most stressed

Singhal, A↗
DOE OSTI2015

SU-E-J-78: Adaptive Planning Workflow in a Pencil Beam Scanning Proton Therapy Center

Purpose: The susceptibility of proton therapy to changes in patient setup and anatomy necessitates an adaptive planning process. With the right planning tools and clinical workflow, an adaptive plan can be created in a timely manner without adding significant workload to the treatment planning staff. Methods: In our center, a weekly QA CT is performed on most patients to assess setup, anatomy change, and tumor response. The QA CT is fused to the treatment planning CT, the contours are transferred via deformable registration, and the plan dose is recalculated on the QA CT. A physicist assesses the dose distribution, and an adaptive plan is requested based on tumor coverage or OAR dose changes. After the physician confirms or alters the deformed contours, a dosimetrist develops an adaptive plan using our TPS adaptation module. The plan is assessed for robustness and is then reviewed by the physician. Patient QA is performed within three days following the first adapted treatment. Results: Of the patients who received QA CTs, 19% required at least one adaptive plan (18.5% H&N, 18.5% brain, 11.1% breast, 14.8% chestwall, 14.8% lung, 18.5% pelvis and 3.8% abdomen). Of these patients, 14% went on a break, while the remainder was treated with the previous plan during the re-planning process. Adaptive plans were performed based on tumor shrinkage, anatomy change or positioning uncertainties for 37.9%, 44.8%, and 17.3% of the patients, respectively. On average, 3 full days are required between the QA CT and the first adapted plan treatment. Conclusion: Adaptive planning is a crucial component of proton therapy and should be applied to any site when the QA CT shows significant deviation from the plan. With an efficient workflow, an adaptive plan can be applied without delaying patient treatment or burdening the dosimetry and medical physics team.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

The beauty of simple adaptive control and new developments in nonlinear systems stability analysis

Although various adaptive control techniques have been around for a long time and in spite of successful proofs of stability and even successful demonstrations of performance, the eventual use of adaptive control methodologies in practical real world systems has met a rather strong resistance from practitioners and has remained limited. Apparently, it is difficult to guarantee or even understand the conditions that can guarantee stable operations of adaptive control systems under realistic operational environments. Besides, it is difficult to measure the robustness of adaptive control system stability and allow it to be compared with the common and widely used measure of phase margin and gain margin that is utilized by present, mainly LTI, controllers. Furthermore, customary stability analysis methods seem to imply that the mere stability of adaptive systems may be adversely affected by any tiny deviation from the pretty idealistic and assumably required stability conditions. This paper first revisits the fundamental qualities of customary direct adaptive control methodologies, in particular the classical Model Reference Adaptive Control, and shows that some of their basic drawbacks have been addressed and eliminated within the so-called Simple Adaptive Control methodology. Moreover, recent developments in the stability analysis methods of nonlinear systems show that prior conditions that were customarily assumed to be needed for stability are only apparent and can be eliminated. As a result, sufficient conditions that guarantee stability are clearly stated and lead to similarly clear proofs of stability. As many real-world applications show, once robust stability of the adaptive systems can be guaranteed, the added value of using Add-On Adaptive Control along with classical Control design techniques is pushing the desired performance beyond any previous limits.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Mutations in global regulators lead to metabolic selection during adaptation to complex environments

Adaptation to ecologically complex environments can provide insights into the evolutionary dynamics and functional constraints encountered by organisms during natural selection. Unlike adaptation to a single limiting resource, adaptation to a new environment with abundant and varied resources can be difficult to achieve by small incremental changes since many mutations are required to achieve even modest gains in fitness. Since changing complex environments are quite common in nature, we investigated how such an epistatic bottleneck can be avoided to allow rapid adaptation. We show that adaptive mutations arise repeatedly in independently evolved populations in the context of greatly increased genetic and phenotypic diversity. We go on to show that weak selection requiring substantial metabolic reprogramming can be readily achieved by mutations in the global response regulator arcA and the stress response regulator rpoS . We identified 46 unique single-nucleotide variants of arcA and 18 mutations in rpoS , nine of which resulted in stop codons or large deletions, suggesting that a subtle modulation of ArcA function and knockouts of rpoS are largely responsible for the metabolic shifts leading to adaptation. These mutations allow a higher order “metabolic selection” that eliminates epistatic bottlenecks, which could occur when many changes would be required. Proteomic and carbohydrate analysis of adapting E. coli populations revealed an up-regulation of enzymes associated with the TCA cycle and amino acid metabolism and an increase in the secretion of putrescine. The overall effect of adaptation across populations is to redirect and efficiently utilize uptake and catabolism of abundant amino acids. Concomitantly, there is a pronounced spread of more ecologically limited strains that results from specialization through metabolic erosion. Remarkably, the global regulators arcA and rpoS can provide a “one-step” mechanism of adaptation to a novel environment, which highlights the importance of global resource management as a powerful strategy to adaptation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Risk Inequality and the Food-Energy-Water (FEW) Nexus: A Study of 43 City Adaptation Plans

Goals aimed at adapting to climate change in sustainable and just ways are embedded in global agreements such as the Sustainable Development Goals and the New Urban Agenda. However, largely unexamined, are the ways that narrative understandings conveyed in adaptation plans consider and attempt to address inequality in climate risk to urban populations and FEW-systems. In this paper, we examine whether and how adaptation plans from C40 member cities address inequality in risk, by planning actions to reduce hazard exposure or tackling the drivers of social vulnerability. C40 is a network of 94 of the world's cities fostering policies to address climate change. We apply a mixed methods approach, including a discourse analysis and meta-analysis of adaptation plans. The discourse analysis helps to unpack framings of urban equity issues as they relate to policy actions, and the meta-analysis seeks to quantitatively investigate patterns of framing and policy across adaptation plans. Our findings suggest that FEW-nexus thinking is not yet embedded in narrative understandings of risk and planned adaptation actions, within the adaptation plans we studied. In the city adaptation plans we analyzed, we found multiple frames coexisting behind the broader adaptation visions (e.g., risk and resilience). Rather than converging, issues, and principles such as those of equality, coexist with economic issues in an imbalance of incongruent political movements and priorities. Techno-infrastructural and economic investments and concerns tend to take precedence over concerns and interests for inequality in climate risks. We discuss some of the institutional factors explaining this. Knowledge integration, for instance, is constrained by the existence of a plurality of sectors, levels of government, power, values, and ways of understanding and managing climate risk. We also suggest that the relatively low importance of equality considerations in the adaptation plans will likely limit the capacity of cities to support broader goals such as those of the New Urban Agenda and the Sustainable Development Goals.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

SU-D-BRB-05: Quantum Learning for Knowledge-Based Response-Adaptive Radiotherapy

Purpose: There is tremendous excitement in radiotherapy about applying data-driven methods to develop personalized clinical decisions for real-time response-based adaptation. However, classical statistical learning methods lack in terms of efficiency and ability to predict outcomes under conditions of uncertainty and incomplete information. Therefore, we are investigating physics-inspired machine learning approaches by utilizing quantum principles for developing a robust framework to dynamically adapt treatments to individual patient’s characteristics and optimize outcomes. Methods: We studied 88 liver SBRT patients with 35 on non-adaptive and 53 on adaptive protocols. Adaptation was based on liver function using a split-course of 3+2 fractions with a month break. The radiotherapy environment was modeled as a Markov decision process (MDP) of baseline and one month into treatment states. The patient environment was modeled by a 5-variable state represented by patient’s clinical and dosimetric covariates. For comparison of classical and quantum learning methods, decision-making to adapt at one month was considered. The MDP objective was defined by the complication-free tumor control (P{sup +}=TCPx(1-NTCP)). A simple regression model represented state-action mapping. Single bit in classical MDP and a qubit of 2-superimposed states in quantum MDP represented the decision actions. Classical decision selection was done using reinforcement Q-learning and quantum searching was performed using Grover’s algorithm, which applies uniform superposition over possible states and yields quadratic speed-up. Results: Classical/quantum MDPs suggested adaptation (probability amplitude ≥0.5) 79% of the time for splitcourses and 100% for continuous-courses. However, the classical MDP had an average adaptation probability of 0.5±0.22 while the quantum algorithm reached 0.76±0.28. In cases where adaptation failed, classical MDP yielded 0.31±0.26 average amplitude while the quantum approach averaged a more optimistic 0.57±0.4, but with high phase fluctuations. Conclusion: Our results demonstrate that quantum machine learning approaches provide a feasible and promising framework for real-time and sequential clinical decision-making in adaptive radiotherapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Accelerated basis adaptation in homogeneous chaos spaces

Polynomial chaos expansions (PCE) provide an efficient approach to uncertainty quantification (UQ) and have been adapted to diverse applications across the spectrum of science and engineering. For situations involving large stochastic parameterizations, the curse of dimensionality renders PCE-based methods computationally prohibitive. A basis adaptation approach for PCE was proposed by Tipireddy and Ghanem (2014) which transforms the input random variables through an isometry such that sufficient probabilistic characterization of specific quantities of interest (QoI) is concentrated in an algebraic manifold embedded in the linear span of the dominant transformed variables. While quite versatile, that original version of the PCE basis adaptation exhibited slow convergence for a number of problems of practical significance. In the present paper, we propose two novel methods to accelerate the convergence of the original basis adaptation approach, thus expanding its reach while also providing insight into its performance. In the first method, information gained from a pilot PCE representation is used to correct the mean and Gaussian coefficients in the adapted space. By taking advantages of probabilistic information in higher dimensional adaptation gleaned from an initial adaptation, the second method updates the rotation matrix used to identify the dominant transformed variables. In this manner, the new rotation matrix concentrates even more probabilistic information in its first few dimensions. These two method can be combined to achieve even better performance, the combined method is referred to as sequentially optimized adaptation method. Here, the methods are demonstrated on an analytical test function and a model of a space structure with several sub-components and a non-smooth quantity of interest representing the maximum acceleration over time. Both methods achieve accelerated convergence of the basis adaptation approach with negligible additional costs.

Accelerated convergence↗
DOE OSTI2021

hr-Adaptivity for nonconforming high-order meshes with the target matrix optimization paradigm

In this study, we present an \(hr\) -adaptivity framework for optimization of high-order meshes. This work extends the r -adaptivity method by Dobrev et al. (Comput Fluids, 2020), where we utilized the Target-Matrix Optimization Paradigm (TMOP) to minimize a functional that depends on each element’s current and target geometric parameters: element aspect-ratio , size , skew , and rotation . Since fixed mesh topology limits the ability to achieve the target size and aspect-ratio at each position, in this paper, we augment the r -adaptivity framework with nonconforming adaptive mesh refinement to further reduce the error with respect to the target geometric parameters. The proposed formulation, referred to as \(hr\) -adaptivity, introduces TMOP-based quality estimators to satisfy the aspect-ratio target via anisotropic refinements and size target via isotropic refinements in each element of the mesh. The methodology presented is purely algebraic, extends to both simplices and hexahedra/quadrilaterals of any order, and supports nonconforming isotropic and anisotropic refinements in 2D and 3D. Using a problem with a known exact solution, we demonstrate the effectiveness of \(hr\) -adaptivity over both r - and \(h\) -adaptivity in obtaining similar accuracy in the solution with significantly fewer mesh nodes. We also present several examples that show that \(hr\) -adaptivity can help satisfy geometric targets even when \(r\) -adaptivity fails to do so, due to the topology of the initial mesh.

42 ENGINEERING↗
DOE OSTI2014

Application of Low Dose Radiation Adaptive Response to Control Aging-Related Disease

Oxidative damage has been implicated in the pathogenesis of most aging-related diseases including neurodegenerative diseases. Antioxidant supplementation has been found to be ineffective in reducing such diseases, but increased endogenous production of antioxidants from the adaptive response due to physical and cognitive exercises (which increase oxidative metabolism and oxidative stress) has been effective in reducing some of the diseases. Low dose radiation (LDR), which increases oxidative stress and results in adaptive response of increased antioxidants, may provide an alternative method of controlling the aging-related diseases. We have studied the effect of LDR on the induction of adaptive response in rat brains and the effectiveness of the LDR in reducing the oxidative damage caused by subsequent high dose radiation. We have also investigated the effect of LDR on apomorphine-induced rotations in the 6-hydroxydopamine (6-OHDA) unilaterally-lesioned rat model of Parkinson's disease (PD). LDR was observed to initiate an adaptive response in the brain, and reduce the oxidative damage from subsequent high dose radiation exposure, confirming the effectiveness of LDR adaptive response in reducing the oxidative damage from the free radicals due to high dose radiation. LDR resulted in a slight improvement in Tyrosine hydroxylase expression on the lesioned side of substantia nigra (indicative of its protective effect on the dopaminergic neurons), and reduced the behavioral symptoms in the 6-OHDA rat model of PD. Translation of this concept to humans, if found to be applicable, may be a possible approach for controlling the progression of PD and other neurodegenerative diseases. Since any translation of the concept to humans would be hindered by the currently prevalent carcinogenic concerns regarding LDR based on the linear no-threshold (LNT) model, we have also studied the justifications for the use of the LNT model. One of the shortcomings of the LNT model is that it ignores the effects of any adaptive response of the body to the LDR. The importance of considering adaptive response becomes obvious when one considers the sharp contrast between (i) the failure of well-designed anti-angiogenesis therapies which resulted in aggressive tumors because of ignoring adaptive response and (ii) the occasional cure of untreated metastatic lesions likely due to the incidental adaptive response from the LDR exposure to parts of the body during radiation therapy of a primary tumor, known as the abscopal effect. Another shortcoming of the LNT model is that it pays exclusive attention to increase in mutations, which is not a decisive factor in the occurrence of clinical cancers, as the cause of excess cancers. On the other hand, LNT model ignores the immune system response, which plays a very important role in preventing occult cancers from becoming clinical cancers, as demonstrated by the large increase in cancers in organ transplant patients whose immune system is suppressed. There is also recent epidemiological evidence against the LNT model. A re-analysis of the latest update to the atomic bomb survivor data has shown that the data no longer support the LNT model but are consistent with the radiation hormesis hypothesis. A re-analysis of cancer incidence data of Taiwanese apartment dwellers that were exposed to LDR from contaminated building materials has also shown a reduction in cancers from the LDR. The present LDR carcinogenic concerns would preclude any human study of cancer prevention using LDR, since the study would require subjecting a large asymptomatic population to LDR. However, pilot studies of radiation hormesis in cancer patients may be more acceptable since these would require irradiation of limited numbers of patients in order to assess the effectiveness of the LDR treatments. Some of the LDR applications that may be considered for cancer patients are: LDR treatment of early stage cancers without the adverse side effects of current treatments such as radiation therapy or chemotherapy, adjuvant LDR treatment of cancer patients undergoing radiation therapy for better tumor control and reduced metastasis, and the use of LDR treatment following radiation therapy to reduce the risk of second cancers from the radiation therapy. Studies of LDR for the control of early-stage neurodegenerative diseases may also be more acceptable since currently there are no effective treatments available for controlling these diseases, and since such studies would require LDR exposure to limited parts of the brain, and the carcinogenic risk from such treatments would be very small due to the low radiation tissue-weighting factor for the brain. Success in these studies can lead to the study of LDR for preventing and controlling other aging-related diseases.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2021

Adaptive protection opportunities, gap assessments, and designs

This report provides a comprehensive overview of adaptive protection schemes in use by distribution systems for protection, switching and control on their systems. A significant focus is placed on how existing schemes can be impacted by increasing penetrations of DER as well as how these schemes can enable DER penetrations to increase. EPRI have conducted a survey of member utilities and performed a comprehensive literature review with the goal of baselining the research and identifying gaps with a focus on the issues that were encountered with adaptive protection on real systems. The five adaptive protection applications that are most prevalent on systems today are discussed in detail. These are weather-based fuse-saving, adaptive protection to reduce short-circuit current, adaptive protection for DER, adaptive protection for microgrids, and distribution automation. A broad overview of the technology is given for each scheme. Issues that have been encountered by utilities are highlighted and the safety and reliability impacts are also examined. As distribution systems, intelligent electronic devices, grid equipment and distribution management systems are rapidly evolving, adaptive protection techniques and technologies will become more widely adopted. This report proposes a framework for a conceptual automatic adaptive protection system. EPRI have ongoing research, development and demonstration projects in all of the constituent elements, however challenges remain to link the elements together in a secure and reliable way. EPRI will continue research into automated adaptive protection applications and challenges for the systems of today and future applications to assist system operators in managing the evolving system.

14 SOLAR ENERGY↗
DOE OSTI2016

Online Magnetic Resonance Image Guided Adaptive Radiation Therapy: First Clinical Applications

Purpose: To demonstrate the feasibility of online adaptive magnetic resonance (MR) image guided radiation therapy (MR-IGRT) through reporting of our initial clinical experience and workflow considerations. Methods and Materials: The first clinically deployed online adaptive MR-IGRT system consisted of a split 0.35T MR scanner straddling a ring gantry with 3 multileaf collimator-equipped {sup 60}Co heads. The unit is supported by a Monte Carlo–based treatment planning system that allows real-time adaptive planning with the patient on the table. All patients undergo computed tomography and MR imaging (MRI) simulation for initial treatment planning. A volumetric MRI scan is acquired for each patient at the daily treatment setup. Deformable registration is performed using the planning computed tomography data set, which allows for the transfer of the initial contours and the electron density map to the daily MRI scan. The deformed electron density map is then used to recalculate the original plan on the daily MRI scan for physician evaluation. Recontouring and plan reoptimization are performed when required, and patient-specific quality assurance (QA) is performed using an independent in-house software system. Results: The first online adaptive MR-IGRT treatments consisted of 5 patients with abdominopelvic malignancies. The clinical setting included neoadjuvant colorectal (n=3), unresectable gastric (n=1), and unresectable pheochromocytoma (n=1). Recontouring and reoptimization were deemed necessary for 3 of 5 patients, and the initial plan was deemed sufficient for 2 of the 5 patients. The reasons for plan adaptation included tumor progression or regression and a change in small bowel anatomy. In a subsequently expanded cohort of 170 fractions (20 patients), 52 fractions (30.6%) were reoptimized online, and 92 fractions (54.1%) were treated with an online-adapted or previously adapted plan. The median time for recontouring, reoptimization, and QA was 26 minutes. Conclusion: Online adaptive MR-IGRT has been successfully implemented with planning and QA workflow suitable for routine clinical application. Clinical trials are in development to formally evaluate adaptive treatments for a variety of disease sites.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2025

Local adaptation of both plant and pathogen: an arms‐race compromise in switchgrass rust

In coevolving species, parasites locally adapt to host populations as hosts locally adapt to resist parasites. Parasites often outpace host local adaptation since they have rapid life cycles, but host diversity, the strength of selection, and external environmental influence can result in complex outcomes. To better understand local adaptation in host–parasite systems, we examined locally adapted switchgrass (Panicum virgatum), and its leaf rust pathogen (Puccinia novopanici) across a latitudinal range in North America. We grew switchgrass genotypes in 10 replicated multiyear common gardens, measuring rust severity from natural infection in a ‘host reciprocal transplant’ framework for testing local adaptation. We conducted genome-wide association mapping to identify genetic loci associated with rust severity. Genetically differentiated rust populations were locally adapted to northern and southern switchgrass, despite host local adaptation to environmental conditions in the same regions. Rust resistance was polygenic, and distinct loci were associated with rust severity in the north and south. We narrowed a previously identified large-effect quantitative trait locus for rust severity to a candidate YELLOW STRIPE-LIKE gene and linked numerous other loci to defense-related genes. Overall, our results suggest that both hosts and parasites can be simultaneously locally adapted, especially when parasites impose less selection than other environmental factors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

WE-G-BRF-01: Adaptation to Intrafraction Tumor Deformation During Intensity-Modulated Radiotherapy: First Proof-Of-Principle Demonstration

Purpose: Intrafraction tumor deformation limits targeting accuracy in radiotherapy and cannot be adapted to by current motion management techniques. This study simulated intrafractional treatment adaptation to tumor deformations using a dynamic Multi-Leaf Collimator (DMLC) tracking system during Intensity-modulated radiation therapy (IMRT) treatment for the first time. Methods: The DMLC tracking system was developed to adapt to the intrafraction tumor deformation by warping the planned beam aperture guided by the calculated deformation vector field (DVF) obtained from deformable image registration (DIR) at the time of treatment delivery. Seven single phantom deformation images up to 10.4 mm deformation and eight tumor system phantom deformation images up to 21.5 mm deformation were acquired and used in tracking simulation. The intrafraction adaptation was simulated at the DMLC tracking software platform, which was able to communicate with the image registration software, reshape the instantaneous IMRT field aperture and log the delivered MLC fields.The deformation adaptation accuracy was evaluated by a geometric target coverage metric defined as the sum of the area incorrectly outside and inside the reference aperture. The incremental deformations were arbitrarily determined to take place equally over the delivery interval. The geometric target coverage of delivery with deformation adaptation was compared against the delivery without adaptation. Results: Intrafraction deformation adaptation during dynamic IMRT plan delivery was simulated for single and system deformable phantoms. For the two particular delivery situations, over the treatment course, deformation adaptation improved the target coverage by 89% for single target deformation and 79% for tumor system deformation compared with no-tracking delivery. Conclusion: This work demonstrated the principle of real-time tumor deformation tracking using a DMLC. This is the first step towards the development of an image-guided radiotherapy system to treat deforming tumors in real-time. The authors acknowledge funding support from the Australian NHMRC Australia Fellowship, Cure Cancer Australia Foundation, NHMRC Project Grant APP1042375 and US NIH/NCI R01CA93626.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Quantitative adaptation analytics for assessing dynamic systems of systems: LDRD Final Report

Our society is increasingly reliant on systems and interoperating collections of systems, known as systems of systems (SoS). These SoS are often subject to changing missions (e.g., nation- building, arms-control treaties), threats (e.g., asymmetric warfare, terrorism), natural environments (e.g., climate, weather, natural disasters) and budgets. How well can SoS adapt to these types of dynamic conditions? This report details the results of a three year Laboratory Directed Research and Development (LDRD) project aimed at developing metrics and methodologies for quantifying the adaptability of systems and SoS. Work products include: derivation of a set of adaptability metrics, a method for combining the metrics into a system of systems adaptability index (SoSAI) used to compare adaptability of SoS designs, development of a prototype dynamic SoS (proto-dSoS) simulation environment which provides the ability to investigate the validity of the adaptability metric set, and two test cases that evaluate the usefulness of a subset of the adaptability metrics and SoSAI for distinguishing good from poor adaptability in a SoS. Intellectual property results include three patents pending: A Method For Quantifying Relative System Adaptability, Method for Evaluating System Performance, and A Method for Determining Systems Re-Tasking.

99 GENERAL AND MISCELLANEOUS↗