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At least 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Spike-Free Adaptive Sliding Mode Control: Application to Permanent Magnet Synchronous Motors

A new methodology for adaptive sliding mode control (ASMC) has been widely used to improve the control performance in various systems. This method exhibits several advantages, including low sliding mode control (SMC) chattering, no knowledge of the system disturbance bound, and no overestimation of the control gain. Despite its advantages, this method can be hampered by the spike phenomenon, slow control gain convergence, and difficulty in achieving optimal performance under varying disturbances. Consequently, this article proposes a spike-free ASMC method with a disturbance observer (DOB) to address these problems. Previous ASMC methods have been analyzed via simulations to verify the aforementioned problems. Here, this analysis highlights the need for disturbance compensation and improvements in the SMC gain adaptation law. Therefore, a DOB is designed to mitigate the spike phenomenon by compensating for disturbances. Subsequently, an SMC gain adaptation law based on disturbance error estimation is designed to eliminate the spike phenomenon completely. The proposed adaptation law makes the SMC gain to converge to a slightly higher value than the disturbance estimation error. Consequently, the proposed method not only eliminates the spike phenomenon, but also ensures optimal performance under varying disturbances. The performance of the proposed method is experimen tally validated through a comparative study.

42 ENGINEERING↗
DOE OSTI2013

Adaptive Control Parameters for Dispersal of Multi-Agent Mobile Ad Hoc Network (MANET) Swarms

A mobile ad hoc network is a collection of independent nodes that communicate wirelessly with one another. This paper investigates nodes that are swarm robots with communications and sensing capabilities. Each robot in the swarm may operate in a distributed and decentralized manner to achieve some goal. This paper presents a novel approach to dynamically adapting control parameters to achieve mesh configuration stability. The presented approach to robot interaction is based on spring force laws (attraction and repulsion laws) to create near-optimal mesh like configurations. In prior work, we presented the extended virtual spring mesh (EVSM) algorithm for the dispersion of robot swarms. This paper extends the EVSM framework by providing the first known study on the effects of adaptive versus static control parameters on robot swarm stability. The EVSM algorithm provides the following novelties: 1) improved performance with adaptive control parameters and 2) accelerated convergence with high formation effectiveness. Simulation results show that 120 robots reach convergence using adaptive control parameters more than twice as fast as with static control parameters in a multiple obstacle environment.

42 ENGINEERING↗
DOE OSTI2025

LLM-Based Adaptive Distribution Voltage Regulation Under Frequent Topology Changes: An In-Context MPC Framework

This paper proposes a large language model (LLM) based adaptive inverter control for distribution voltage regulation under frequent topology changes. We leverage the ability of the LLM to perform in-context learning and create a topology-adaptive surrogate model for power flow calculation. The surrogate model is then integrated with a long short-term memory-based load forecaster and a model predictive control (MPC) scheme to achieve the optimal inverter control that adapts to frequent topology changes. Unlike many existing works that assume fixed-topology grids or require the knowledge of all possible topologies when training a model, the proposed in-context MPC method tackles the distribution voltage control problem under various topologies and adapts to unknown topologies with limited data requirement for fine-tuning. The effectiveness of our method is demonstrated on a modified IEEE 123-bus test system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Physiological and genomic signatures of evolutionary thermal adaptation in redband trout from extreme climates

Abstract Temperature is a master environmental factor that limits the geographical distribution of species, especially in ectotherms. To address challenges in biodiversity conservation under ongoing climate change, it is essential to characterize relevant functional limitations and adaptive genomic content at population and species levels. Here, we present evidence for adaptive divergence in cardiac function and genomic regions in redband trout ( Oncorhynchus mykiss gairdneri ) populations from desert and montane streams. Cardiac phenotypes of individual fish were measured in the field with a custom‐built electrocardiogram apparatus. Maximum heart rate and its rate limiting temperature during acute warming were significantly higher in fish that have evolved in the extreme of a desert climate compared to a montane climate. Association mapping with 526,301 single nucleotide polymorphisms ( SNP s) across the genome revealed signatures of thermal selection both within and among ecotypes. Among desert and montane populations, 435 SNP s were identified as putative outliers under natural selection and 20 of these loci showed significant association with average summer water temperatures among populations. Phenotypes for cardiac performance were variable within each ecotype, and 207 genomic regions were strongly associated with either maximum heart rate or rate limiting temperatures among individuals. Annotation of significant loci provided candidate genes that underlie thermal adaptation, including pathways associated with cardiac function ( IRX 5, CASQ 1, CAC 1D, and TITIN ), neuroendocrine system ( GPR 17 and NOS ), and stress response ( SERPH ). By integrating comparative physiology and population genomics, results here advance our knowledge on evolutionary processes of thermal adaptation in aquatic ectotherms.

Chen, Zhongqi↗
DOE OSTI2021

Divergence in heritable life history traits suggests potential for local adaptation and trade‐offs associated with a coal ash disposal site

Abstract Globally, human activities have resulted in rapid environmental changes that present unique challenges for wildlife. However, investigations of local adaptation in response to simultaneous exposure to multiple anthropogenic selection pressures are rare and often generate conflicting results. We used an in situ reciprocal transplant design within a quantitative genetic framework to examine how adaptive evolution and phenotypic plasticity contribute to the persistence of an amphibian population inhabiting an environment characterized by high levels of multiple toxic trace elements. We found evidence of phenotypic divergence that is largely consistent with local adaptation to an environment contaminated with multiple chemical stressors, tied to potential trade‐offs in the absence of contaminants. Specifically, the population derived from the contaminated environment had a reduced risk of mortality and greater larval growth and in the contaminated environment, relative to offspring from the naïve population. Further, while survival in the uncontaminated environment was not compromised in offspring from the contaminant‐exposed population, they did show delayed development and reduced growth rates over larval development, relative to the naïve population. We found no evidence of reduced additive genetic variation in the contaminant‐exposed population, suggesting long‐term selection in a novel environment has not reduced the evolutionary potential of that population. We also saw little evidence that past selection in the ASH environment had reduced trait plasticity in the resident population. Maternal effects were prominent in early development, but we did not detect any trends suggesting these effects were associated with the maternal transfer of toxic trace elements. Our results demonstrate the potential for adaptation to multiple contaminants in a wild amphibian population, which may have facilitated long‐term persistence in a heavily impacted environment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Genotype–environment associations across spatial scales reveal the importance of putative adaptive genetic variation in divergence

Abstract Identifying areas of high evolutionary potential is a judicious strategy for developing conservation priorities in the face of environmental change. For wide‐ranging species occupying heterogeneous environments, the evolutionary forces that shape distinct populations can vary spatially. Here, we investigate patterns of genomic variation and genotype–environment associations in the hermit thrush ( Catharus guttatus ), a North American songbird, at broad (across the breeding range) and narrow spatial scales (at a hybrid zone). We begin by building a genoscape or map of genetic variation across the breeding range and find five distinct genetic clusters within the species, with the greatest variation occurring in the western portion of the range. Genotype–environment association analyses indicate higher allelic turnover in the west than in the east, with measures of temperature surfacing as key predictors of putative adaptive genomic variation rangewide. Since broad patterns detected across a species' range represent the aggregate of many locally adapted populations, we investigate whether our broadscale analysis is consistent with a finer scale analysis. We find that top rangewide temperature‐associated loci vary in their clinal patterns (e.g., steep clines vs. fixed allele frequencies) across a hybrid zone in British Columbia, suggesting that the environmental predictors and the associated candidate loci identified in the rangewide analysis are of variable importance in this particular region. However, two candidate loci exhibit strong concordance with the temperature gradient in British Columbia, suggesting a potential role for temperature‐related barriers to gene flow and/or temperature‐driven ecological selection in maintaining putative local adaptation. This study demonstrates how patterns identified at the broad (macrogeographic) scale can be validated by investigating genotype–environment correlations at the local (microgeographic) scale. Furthermore, our results highlight the importance of considering the spatial distribution of putative adaptive variation when assessing population‐level sensitivity to climate change and other stressors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Natural variation in the C‐repeat binding factor cold response pathway correlates with local adaptation of Arabidopsis ecotypes

Summary The natural range of Arabidopsis thaliana (Arabidopsis) encompasses geographical regions that have greatly differing local climates, including harshness of winter temperatures. A question thus raised is whether differences in freezing tolerance might contribute to local adaptation in Arabidopsis. Consistent with this possibility is that Arabidopsis accessions differ in freezing tolerance and that those collected from colder northern latitudes are generally more tolerant to freezing than those collected from warmer southern latitudes. Moreover, recent studies with Arabidopsis genotypes collected from sites in Sweden ( SW ) and Italy ( IT ) have established that the two accessions are locally adapted, that the SW ecotype is more tolerant of freezing than the IT ecotype, and that genetic differences between the two ecotypes that condition local adaptation and freezing tolerance map to a region that includes the C‐repeat binding factor ( CBF ) locus. The CBF locus includes three genes – CBF 1 , CBF 2 and CBF 3 – that are induced by low temperature and encode transcription factors that regulate a group of more than 100 genes, the CBF regulon, which impart freezing tolerance. Here we show that cold induction of most CBF regulon genes is lower in IT plants compared with SW plants, and that this is due to the IT CBF 2 gene encoding a non‐functional CBF 2 protein. The non‐functional IT CBF 2 protein also contributes to the lower freezing tolerance of the IT plants compared with the SW plants. Taken together, studies on the SW and IT ecotypes provide evidence that natural variation in the CBF pathway has contributed to adaptive evolution in these Arabidopsis populations.

Gehan, Malia A.↗
DOE OSTI2019

A Comparison of Adaptive and Template Matching Techniques for Radio-Isotope Identification

We compare and contrast the effectiveness of a set of adaptive and non-adaptive algorithms for isotope identi cation based on gamma-ray spectra. One dimensional energy spectra are simulated for a variety of dwell-times and source to detector distances in order to reflect conditions typically encountered in radiological emergency response and environmental monitoring applications. We nd that adaptive methods are more accurate and computationally efficient than non-adaptive in cases of operational interest.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Organ sample generator for expected treatment dose construction and adaptive inverse planning optimization

Purpose: To create an organ sample generator (OSG) for expected treatment dose construction and adaptive inverse planning optimization. The OSG generates random samples of organs of interest from a distribution obeying the patient specific organ variation probability density function (PDF) during the course of adaptive radiotherapy. Methods: Principle component analysis (PCA) and a time-varying least-squares regression (LSR) method were used on patient specific geometric variations of organs of interest manifested on multiple daily volumetric images obtained during the treatment course. The construction of the OSG includes the determination of eigenvectors of the organ variation using PCA, and the determination of the corresponding coefficients using time-varying LSR. The coefficients can be either random variables or random functions of the elapsed treatment days depending on the characteristics of organ variation as a stationary or a nonstationary random process. The LSR method with time-varying weighting parameters was applied to the precollected daily volumetric images to determine the function form of the coefficients. Eleven h and n cancer patients with 30 daily cone beam CT images each were included in the evaluation of the OSG. The evaluation was performed using a total of 18 organs of interest, including 15 organs at risk and 3 targets. Results: Geometric variations of organs of interest during h and n cancer radiotherapy can be represented using the first 3 {approx} 4 eigenvectors. These eigenvectors were variable during treatment, and need to be updated using new daily images obtained during the treatment course. The OSG generates random samples of organs of interest from the estimated organ variation PDF of the individual. The accuracy of the estimated PDF can be improved recursively using extra daily image feedback during the treatment course. The average deviations in the estimation of the mean and standard deviation of the organ variation PDF for h and n cancer radiotherapy were less than 2 and 1 mm, respectively, for most organs after the second week of treatment. After the first three weeks of treatment, the mean discrepancy of the dose estimation accuracy was within 1% for most of organs, the corresponding standard deviation was within 2.5% for parotids, the brain stem and the cochleae, and within 1% for other organs. Conclusions: A patient specific OSG is feasible and can be used to generate random samples of organs of interest for the expected treatment dose construction and adaptive inverse planning. The accuracy of the OSG can be improved continuously and recursively during the adaptive treatment course using daily volumetric image feedback.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-J-229: Quantitative Assessment for Timely Adaptive Re-Planning Using Weekly Dose Monitoring for Head and Neck Cancer

Purpose: For patients with head and neck (HN) cancer, mid-course adaptive radiation therapy (ART) is a common practice in our institution to accommodate anatomic changes. The aim of the study is to evaluate whether dose re-calculation on weekly verification images can provide quantitative assessment for timely adaptive re-planning with daily image-guided intensity modulated radiotherapy (IMRT). Methods: We retrospectively selected sixty daily verification images acquired on CT-on-rail/CBCT from ten HN patients. These image sets were typically a week apart. Among these patients, six patients received a mid-course ART. Contours of the tumors and organ-at-risks (OARs) were manually delineated by a physician on each verification CT. After placing the treatment iso-center on the verification CTs according to the recorded clinical shifts, daily dose was re-calculated with the same beam configuration as the original plan. For the purpose of this study, electron densities for both verification CTs and planning CTs were set to 1.0 g/cm3. Results: Two patients had D99 of the CTV < 97% of the planned dose for more than three fractions due to remarkable tumor volume shrinkages. D-max of the spinal cord exceeded a tolerance of 45 Gy for four fractions in additional two patients. D-mean of the parotid increased within 25% of the planned value. D-max of the brainstem and D-mean of the oral cavity did not show significant variation. If the re-planning criteria included D99 of the CTV < 97% of the planned dose and D-max of the spinal cord > 45 Gy, two out ten patients required ART at week 2 and two patients required ART at week 3, respectively. Conclusion: Weekly dose monitoring with re-calculation on verification images can provide quantitative dose guidance for timely adaptive re-planning. Future work will include accumulative dose analysis for the decision of adaptive re-planning. The study is supported in part by Siemens Medical Solutions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

MO-E-BRD-01: Adapt-A-Thon - Texas Hold’em Invitational

Software tools for image-based adaptive radiotherapy such as deformable image registration, contour propagation and dose mapping have progressed beyond the research setting and are now commercial products available as part of both treatment planning systems and stand-alone applications. These software tools are used together to create clinical workflows to detect, track and evaluate changes in the patient and to accumulate dose. Deviations uncovered in this process are used to guide decisions about replanning/adaptation with the goal of keeping the delivery of prescribed dose “on target” throughout the entire course of radiotherapy. Since the output from one step of the adaptive process is used as an input for another, it is essential to understand and document the uncertainty associated with each of the step and how these uncertainties are propagated. This in turn requires an understanding how the underlying tools work. Unfortunately, important details about the algorithms used to implement these tools are scarce or incomplete, too often for competitive reasons. This is in contrast to the situation involving other basic treatment planning algorithms such as dose calculations, where the medical physics community essentially requires vendors to provide physically important details about their underlying theory and clinical implementation. Vendors should adopt this same level of information sharing when it comes to the tools and techniques for image guided adaptive radiotherapy. The goal of this session is to start this process by inviting vendors and medical physicists to discuss and demonstrate the available tools and describe how they are intended to be used in clinical practice. The format of the session will involve a combination of formal presentations, interactive demonstrations, audience participation and some friendly “Texas style” competition. Learning Objectives: Understand the components of the image-based adaptive radiotherapy process. Understand the how these components are implemented in various commercial systems. Understand the different use cases and workflows currently supported these tools.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-80: A Comparative Analysis of MIM and Pinnacle Software for Adaptive Planning

Purpose: IMRT treatment is often administered with image guidance and small PTV margins. Change in body habitus such as weight loss and tumor response during the course of a treatment could be significant, thus warranting re-simulation and re-planning. Adaptive planning is challenging and places significant burden on the staff, as such some commercial vendors are now offering adaptive planning software to stream line the process of re-planning and dose accumulation between different CT data set. The purpose of this abstract is to compare the adaptive planning tools between Pinnacle version 9.8 and MIM 6.4 software. Methods: Head and Neck cases of previously treated patients that experienced anatomical changes during the course of their treatment were chosen for evaluation. The new CT data set from the re-simulation was imported to Pinnacle and MIM software. The dynamic planning tool in pinnacle was used to calculate the old plan with fixed MU setting on the new CT data. In MIM, the old CT was registered to the new data set, followed by a dose transformation to the new CT. The dose distribution to the PTV and critical structures from each software were analyzed and compared. Results: 9% difference was observed between the Global maximum doses reported by both software. Mean doses to organs at risk and PTV’s were within 6 % however pinnacle showed greater difference in PTV coverage change. Conclusion: MIM software adaptive planning corrects for geometrical changes without consideration for the effect of radiological path length on dose distribution; however Pinnacle corrects for both geometric and radiological effect on the dose distribution. Pinnacle gives a better estimate of the dosimetric impact due to anatomical changes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-135: Feasibility of Using Quantitative Cone Beam CT for Proton Adaptive Planning

Purpose: To investigate the feasibility of using scatter corrected cone beam CT (CBCT) for proton adaptive planning. Methods: Phantom study was used to evaluate the CT number difference between the planning CT (pCT), quantitative CBCT (qCBCT) with scatter correction and calibrated Hounsfield units using adaptive scatter kernel superposition (ASKS) technique, and raw CBCT (rCBCT). After confirming the CT number accuracy, prostate patients, each with a pCT and several sets of weekly CBCT, were investigated for this study. Spot scanning proton treatment plans were independently generated on pCT, qCBCT and rCBCT. The treatment plans were then recalculated on all images. Dose-volume-histogram (DVH) parameters and gamma analysis were used to compare between dose distributions. Results: Phantom study suggested that Hounsfield unit accuracy for different materials are within 20 HU for qCBCT and over 250 HU for rCBCT. For prostate patients, proton dose could be calculated accurately on qCBCT but not on rCBCT. When the original plan was recalculated on qCBCT, tumor coverage was maintained when anatomy was consistent with pCT. However, large dose variance was observed when patient anatomy change. Adaptive plan using qCBCT was able to recover tumor coverage and reduce dose to normal tissue. Conclusion: It is feasible to use qu antitative CBCT (qCBCT) with scatter correction and calibrated Hounsfield units for proton dose calculation and adaptive planning in proton therapy. Partly supported by Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Technical Note: A fast online adaptive replanning method for VMAT using flattening filter free beams

Purpose: To develop a fast replanning algorithm based on segment aperture morphing (SAM) for online replanning of volumetric modulated arc therapy (VMAT) with flattening filter free (FFF) beams. Methods: A software tool was developed to interface with a VMAT research planning system, which enables the input and output of beam and machine parameters of VMAT plans. The SAM algorithm was used to modify multileaf collimator positions for each segment aperture based on the changes of the target from the planning (CT/MR) to daily image [CT/CBCT/magnetic resonance imaging (MRI)]. The leaf travel distance was controlled for large shifts to prevent the increase of VMAT delivery time. The SAM algorithm was tested for 11 patient cases including prostate, pancreatic, and lung cancers. For each daily image set, three types of VMAT plans, image-guided radiation therapy (IGRT) repositioning, SAM adaptive, and full-scope reoptimization plans, were generated and compared. Results: The SAM adaptive plans were found to have improved the plan quality in target and/or critical organs when compared to the IGRT repositioning plans and were comparable to the reoptimization plans based on the data of planning target volume (PTV)-V100 (volume covered by 100% of prescription dose). For the cases studied, the average PTV-V100 was 98.85% ± 1.13%, 97.61% ± 1.45%, and 92.84% ± 1.61% with FFF beams for the reoptimization, SAM adaptive, and repositioning plans, respectively. The execution of the SAM algorithm takes less than 10 s using 16-CPU (2.6 GHz dual core) hardware. Conclusions: The SAM algorithm can generate adaptive VMAT plans using FFF beams with comparable plan qualities as those from the full-scope reoptimization plans based on daily CT/CBCT/MRI and can be used for online replanning to address interfractional variations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-J-105: Towards a Novel Treatment Planning Pipeline Delivering Pareto- Optimal Plans While Enabling Inter- and Intrafraction Plan Adaptation

Purpose: To develop a new IMRT treatment planning methodology suitable for the new generation of MR-linear accelerator machines. The pipeline is able to deliver Pareto-optimal plans and can be utilized for conventional treatments as well as for inter- and intrafraction plan adaptation based on real-time MR-data. Methods: A Pareto-optimal plan is generated using the automated multicriterial optimization approach Erasmus-iCycle. The resulting dose distribution is used as input to the second part of the pipeline, an iterative process which generates deliverable segments that target the latest anatomical state and gradually converges to the prescribed dose. This process continues until a certain percentage of the dose has been delivered. Under a conventional treatment, a Segment Weight Optimization (SWO) is then performed to ensure convergence to the prescribed dose. In the case of inter- and intrafraction adaptation, post-processing steps like SWO cannot be employed due to the changing anatomy. This is instead addressed by transferring the missing/excess dose to the input of the subsequent fraction. In this work, the resulting plans were delivered on a Delta4 phantom as a final Quality Assurance test. Results: A conventional static SWO IMRT plan was generated for two prostate cases. The sequencer faithfully reproduced the input dose for all volumes of interest. For the two cases the mean relative dose difference of the PTV between the ideal input and sequenced dose was 0.1% and −0.02% respectively. Both plans were delivered on a Delta4 phantom and passed the clinical Quality Assurance procedures by achieving 100% pass rate at a 3%/3mm gamma analysis. Conclusion: We have developed a new sequencing methodology capable of online plan adaptation. In this work, we extended the pipeline to support Pareto-optimal input and clinically validated that it can accurately achieve these ideal distributions, while its flexible design enables inter- and intrafraction plan adaptation. This research is financially supported by Elekta AB, Stockholm, Sweden.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-J-108: TMR Correction Factor Based Online Adaptive Radiotherapy for Stereotactic Radiosurgery (SRS) of L-Spine Tumors Using Cone Beam CT

Purpose: To investigate the feasibility of using TMR ratio correction factors for a fast online adaptive plan to compensate for anatomical changes in stereotactic radiosurgery (SRS) of L-spine tumors. Methods: Three coplanar treatment plans were made for 11 patients: Uniform (9 IMRT beams equally distributed around the patient); Posterior (IMRT with 9 posterior beams every 20 degree) and VMAT (2 360° arcs). For each patient, the external body and bowel gas were contoured on the planning CT and pre-treatment CBCT. After registering CBCT and the planning CT by aligning to the tumor, the CBCT contours were transferred to the planning CT. To estimate the actual delivered dose while considering patient’s anatomy of the treatment day, a hybrid CT was created by overriding densities in planning CT using the differences between CT and CBCT external and bowel gas contours. Correction factors (CF) were calculated using the effective depth information obtained from the planning system using the hybrid CT: CF = TMR (delivery)/TMR (planning). The adaptive plan was generated by multiplying the planned Monitor Units with the CFs. Results: The mean absolute difference (MAD) in V16Gy of the target between planned and estimated delivery with and without TMR correction was 0.8 ± 0.7% vs. 2.4 ± 1.3% for Uniform and 1.0 ± 0.9% vs. 2.6 ± 1.3% for VMAT plans(p<0.05), respectively. For V12Gy of cauda-equina with and without TMR correction, MAD was 0.24 ± 0.19% vs. 1.2 ± 1.02% for Uniform and 0.23 ± 0.20% vs. 0.78 ± 0.79% for VMAT plans(p<0.05), respectively. The differences between adaptive and original plans were not significant for posterior plans. Conclusion: The online adaptive strategy using TMR ratios and pre-treatment CBCT information was feasible strategy to compensate for anatomical changes for the patients treated for L-spine tumors, particularly for equally spaced IMRT and VMAT plans.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-J-197: A Novel Intra-Beam Range Detection and Adaptation Strategy for Particle Therapy

Purpose: In-vivo range detection/verification is crucial in particle therapy for effective and safe delivery. The state-of-art techniques are not sufficient for in-vivo on-line range verification due to conflicts among patient dose, signal statistics and imaging time. We propose a novel intra-beam range detection and adaptation strategy for particle therapy. Methods: This strategy uses the planned mid-range spots as probing beams without adding extra radiation to patients. Such choice of probing beams ensures the Bragg peaks to remain inside the tumor even with significant range variation from the plan. It offers sufficient signal statistics for in-beam positron emission tomography (PET) due to high positron activity of therapeutic dose. The probing beam signal can be acquired and reconstructed using in-beam PET that allows for delineation of the Bragg peaks and detection of range shift with ease of detection enabled by single-layered spots. If the detected range shift is within a pre-defined tolerance, the remaining spots will be delivered as the original plan. Otherwise, a fast re-optimization using range-shifted beamlets and accounting for the probing beam dose is applied to consider the tradeoffs posed by the online anatomy. Simulated planning and delivery studies were used to demonstrate the effectiveness of the proposed techniques. Results: Simulations with online range variations due to shifts of various foreign objects into the beam path showed successful delineation of the Bragg peaks as a result of delivering probing beams. Without on-line delivery adaptation, dose distribution was significantly distorted. In contrast, delivery adaptation incorporating detected range shift recovered well the planned dose. Conclusion: The proposed intra-beam range detection and adaptation utilizing the planned mid-range spots as probing beams, which illuminate the beam range with strong and accurate PET signals, is a safe, practical, yet effective approach to address range uncertainty issues in particle therapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-AB-209-08: Novel Beam-Specific Adaptive Margins for Reducing Organ-At-Risk Doses

Purpose: Current practice of using 3D margins in radiotherapy with high-energy photon beams provides larger-than-required target coverage. According to the photon depth-dose curve, target displacements in beam direction result in minute changes in dose delivered. We exploit this behavior by generating margins on a per-beam basis which simultaneously account for the relative distance of the target and adjacent organs-at-risk (OARs). Methods: For each beam, we consider only geometrical uncertainties of the target location perpendicular to beam direction. By weighting voxels based on its proximity to an OAR, we generate adaptive margins that yield similar overall target coverage probability and reduced OAR dose-burden, at the expense of increased target volume. Three IMRT plans, using 3D margins and 2D per-beam margins with and without adaptation, were generated for five prostate patients with a prescription dose Dpres of 78Gy in 2Gy fractions using identical optimisation constraints. Systematic uncertainties of 1.1, 1.1, 1.5mm in the LR, SI, and AP directions, respectively, and 0.9, 1.1, 1.0mm for the random uncertainties, were assumed. A verification tool was employed to simulate the effects of systematic and random errors using a population size of 50,000. The fraction of the population that satisfies or violates a given DVH constraint was used for comparison. Results: We observe similar target coverage across all plans, with at least 97.5% of the population meeting the D98%>95%Dpres constraint. When looking at the probability of the population receiving D5<70Gy for the rectum, we observed median absolute increases of 23.61% (range, 2.15%–27.85%) and 6.97% (range, 0.65%–17.76%) using per-beam margins with and without adaptation, respectively, relative to using 3D margins. Conclusion: We observed sufficient and similar target coverage using per-beam margins. By adapting each per-beam margin away from an OAR, we can further reduce OAR dose without significantly lowering target coverage probability by irradiating more less-important tissues. This work is supported by Cancer Research UK under Programme C33589/A19908. Research at ICR is also supported by Cancer Research UK under Programme C33589/A19727 and NHS funding to the NIHR Biomedical Research Centre at RMH and ICR.

07 ISOTOPE AND RADIATION SOURCES↗