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At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

ATEQ: Adaptive toroidal equilibrium code

A radially adaptive numerical scheme is developed to solve the Grad–Shafranov equation for axisymmetric magnetohydrodynamic equilibrium. Here, a decomposition with independent solutions is employed in the radial direction, and Fourier decomposition is used in the poloidal direction. The independent solutions are then obtained using an adaptive shooting scheme together with the multi-region matching technique in the radial direction. Accordingly, the adaptive toroidal equilibrium (ATEQ) code is constructed for axisymmetric equilibrium studies. The adaptive numerical scheme in the radial direction improves considerably the accuracy of the equilibrium solution. The decomposition with independent solutions effectively reduces the matrix size in solving the magnetohydrodynamic equilibrium problem. The reduction of the matrix size is about an order of magnitude as compared with the conventional radially grid-based numerical schemes. Also, in this ATEQ numerical scheme, no matter how accuracy in the radial direction is imposed, the size of matrices basically does not change. The small matrix size scheme gives ATEQ more flexibility to address the requirement of the number of Fourier components in the poloidal direction in tough equilibrium problems. These two unique features, the adaptive shooting and small matrix size, make ATEQ useful to improve tokamak equilibrium solutions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Possibilities of joint application of adaptive optics technique and nonlinear optical phase conjugation to compensate for turbulent distortions

The efficiency of integrating the nonlinear optical technique based on forming a reverse wavefront and the conventional adaptive optics into a unified complex (for example, for adaptive focusing of quasi-cw laser radiation) is demonstrated. Nonlinear optical phase conjugation may provide more exact information about the phase fluctuations in the corrected wavefront in comparison with the adaptive optics methods. At the same time, the conventional methods of adaptive optics provide an efficient control of a laser beam projected onto a target for a rather long time. (adaptive optics)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2012

Mechanisms of Host Receptor Adaptation by Severe Acute Respiratory Syndrome Coronavirus

The severe acute respiratory syndrome coronavirus (SARS-CoV) from palm civets has twice evolved the capacity to infect humans by gaining binding affinity for human receptor angiotensin-converting enzyme 2 (ACE2). Numerous mutations have been identified in the receptor-binding domain (RBD) of different SARS-CoV strains isolated from humans or civets. Why these mutations were naturally selected or how SARS-CoV evolved to adapt to different host receptors has been poorly understood, presenting evolutionary and epidemic conundrums. In this study, we investigated the impact of these mutations on receptor recognition, an important determinant of SARS-CoV infection and pathogenesis. Using a combination of biochemical, functional, and crystallographic approaches, we elucidated the molecular and structural mechanisms of each of these naturally selected RBD mutations. These mutations either strengthen favorable interactions or reduce unfavorable interactions with two virus-binding hot spots on ACE2, and by doing so, they enhance viral interactions with either human (hACE2) or civet (cACE2) ACE2. Therefore, these mutations were viral adaptations to either hACE2 or cACE2. To corroborate the above analysis, we designed and characterized two optimized RBDs. The human-optimized RBD contains all of the hACE2-adapted residues (Phe-442, Phe-472, Asn-479, Asp-480, and Thr-487) and possesses exceptionally high affinity for hACE2 but relative low affinity for cACE2. The civet-optimized RBD contains all of the cACE2-adapted residues (Tyr-442, Pro-472, Arg-479, Gly-480, and Thr-487) and possesses exceptionally high affinity for cACE2 and also substantial affinity for hACE2. These results not only illustrate the detailed mechanisms of host receptor adaptation by SARS-CoV but also provide a molecular and structural basis for tracking future SARS-CoV evolution in animals.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Sequential Kalman tuning of the t -preconditioned Crank-Nicolson algorithm: efficient, adaptive and gradient-free inference for Bayesian inverse problems

Ensemble Kalman Inversion (EKI) has been proposed as an efficient method for the approximate solution of Bayesian inverse problems with expensive forward models. However, when applied to the Bayesian inverse problem EKI is only exact in the regime of Gaussian target measures and linear forward models. Here, in this work we propose embedding EKI and Flow Annealed Kalman Inversion, its normalizing flow (NF) preconditioned variant, within a Bayesian annealing scheme as part of an adaptive implementation of the t-preconditioned Crank-Nicolson (tpCN) sampler. The tpCN sampler differs from standard pCN in that its proposal is reversible with respect to the multivariate t-distribution. The more flexible tail behaviour allows for better adaptation to sampling from non-Gaussian targets. Within our Sequential Kalman Tuning (SKT) adaptation scheme, EKI is used to initialize and precondition the tpCN sampler for each annealed target. The subsequent tpCN iterations ensure particles are correctly distributed according to each annealed target, avoiding the accumulation of errors that would otherwise impact EKI. We demonstrate the performance of SKT for tpCN on three challenging numerical benchmarks, showing significant improvements in the rate of convergence compared to adaptation within standard SMC with importance weighted resampling at each temperature level, and compared to similar adaptive implementations of standard pCN. The SKT scheme applied to tpCN offers an efficient, practical solution for solving the Bayesian inverse problem when gradients of the forward model are not available. Code implementing the SKT schemes for tpCN is available at https://github.com/RichardGrumitt/KalmanMC.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Nonlinear burn control in ITER using adaptive allocation of actuators with uncertain dynamics

Abstract ITER will be the first tokamak to sustain a fusion-producing, or burning, plasma. If the plasma temperature were to inadvertently rise in this burning regime, the positive correlation between temperature and the fusion reaction rate would establish a destabilizing positive feedback loop. Careful regulation of the plasma’s temperature and density, or burn control, is required to prevent these potentially reactor-damaging thermal excursions, neutralize disturbances and improve performance. In this work, a Lyapunov-based burn controller is designed using a full zero-dimensional nonlinear model. An adaptive estimator manages destabilizing uncertainties in the plasma confinement properties and the particle recycling conditions (caused by plasma–wall interactions). The controller regulates the plasma density with requests for deuterium and tritium particle injections. In ITER-like plasmas, the fusion-born alpha particles will primarily heat the plasma electrons, resulting in different electron and ion temperatures in the core. By considering separate response models for the electron and ion energies, the proposed controller can independently regulate the electron and ion temperatures by requesting that different amounts of auxiliary power be delivered to the electrons and ions. These two commands for a specific control effort (electron and ion heating) are sent to an actuator allocation module that optimally maps them to the heating actuators available to ITER: an electron cyclotron heating system (20 MW), an ion cyclotron heating system (20 MW), and two neutral beam injectors (16.5 MW each). Two different actuator allocators are presented in this work. The first actuator allocator finds the optimal mapping by solving a convex quadratic program that includes actuator saturation and rate limits. It is nonadaptive and assumes that the mapping between the commanded control efforts and the allocated actuators (i.e. the effector model) contains no uncertainties. The second actuator allocation module has an adaptive estimator to handle uncertainties in the effector model. This uncertainty includes actuator efficiencies, the fractions of neutral beam heating that are deposited into the plasma electrons and ions, and the tritium concentration of the fueling pellets. Furthermore, the adaptive allocator considers actuator dynamics (actuation lag) that contain uncertainty. This adaptive allocation algorithm is more computationally efficient than the aforementioned nonadaptive allocator because it is computed using dynamic update laws so that finding the solution to a static optimization problem is not required at every time step. A simulation study assesses the performance of the proposed adaptive burn controller augmented with each of the actuator allocation modules.

Physics↗
DOE OSTI2021

Genomic Signatures of a Major Adaptive Event in the Pathogenic Fungus Melampsora larici-populina

The recent availability of genome-wide sequencing techniques has allowed systematic screening for molecular signatures of adaptation, including in nonmodel organisms. Host–pathogen interactions constitute good models due to the strong selective pressures that they entail. We focused on an adaptive event which affected the poplar rust fungus Melampsora larici-populina when it overcame a resistance gene borne by its host, cultivated poplar. Based on 76 virulent and avirulent isolates framing narrowly the estimated date of the adaptive event, we examined the molecular signatures of selection. Using an array of genome scan methods based on different features of nucleotide diversity, we detected a single locus exhibiting a consistent pattern suggestive of a selective sweep in virulent individuals (excess of differentiation between virulent and avirulent samples, linkage disequilibrium, genotype–phenotype statistical association, and long-range haplotypes). Our study pinpoints a single gene and further a single amino acid replacement which may have allowed the adaptive event. Although our samples are nearly contemporary to the selective sweep, it does not seem to have affected genome diversity further than the immediate vicinity of the causal locus, which can be explained by a soft selective sweep (where selection acts on standing variation) and by the impact of recombination in mitigating the impact of selection. Therefore, it seems that properties of the life cycle of M. larici-populina, which entails both high genetic diversity and outbreeding, has facilitated its adaptation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

The Adaptive Potential of the Middle Domain of Yeast Hsp90

Abstract The distribution of fitness effects (DFEs) of new mutations across different environments quantifies the potential for adaptation in a given environment and its cost in others. So far, results regarding the cost of adaptation across environments have been mixed, and most studies have sampled random mutations across different genes. Here, we quantify systematically how costs of adaptation vary along a large stretch of protein sequence by studying the distribution of fitness effects of the same ≈2,300 amino-acid changing mutations obtained from deep mutational scanning of 119 amino acids in the middle domain of the heat shock protein Hsp90 in five environments. This region is known to be important for client binding, stabilization of the Hsp90 dimer, stabilization of the N-terminal-Middle and Middle-C-terminal interdomains, and regulation of ATPase–chaperone activity. Interestingly, we find that fitness correlates well across diverse stressful environments, with the exception of one environment, diamide. Consistent with this result, we find little cost of adaptation; on average only one in seven beneficial mutations is deleterious in another environment. We identify a hotspot of beneficial mutations in a region of the protein that is located within an allosteric center. The identified protein regions that are enriched in beneficial, deleterious, and costly mutations coincide with residues that are involved in the stabilization of Hsp90 interdomains and stabilization of client-binding interfaces, or residues that are involved in ATPase–chaperone activity of Hsp90. Thus, our study yields information regarding the role and adaptive potential of a protein sequence that complements and extends known structural information.

Cote-Hammarlof, Pamela A.↗
DOE OSTI2021

Museomics Dissects the Genetic Basis for Adaptive Seasonal Coloration in the Least Weasel

Abstract Dissecting the link between genetic variation and adaptive phenotypes provides outstanding opportunities to understand fundamental evolutionary processes. Here, we use a museomics approach to investigate the genetic basis and evolution of winter coat coloration morphs in least weasels (Mustela nivalis), a repeated adaptation for camouflage in mammals with seasonal pelage color moults across regions with varying winter snow. Whole-genome sequence data were obtained from biological collections and mapped onto a newly assembled reference genome for the species. Sampling represented two replicate transition zones between nivalis and vulgaris coloration morphs in Europe, which typically develop white or brown winter coats, respectively. Population analyses showed that the morph distribution across transition zones is not a by-product of historical structure. Association scans linked a 200-kb genomic region to coloration morph, which was validated by genotyping museum specimens from intermorph experimental crosses. Genotyping the wild populations narrowed down the association to pigmentation gene MC1R and pinpointed a candidate amino acid change cosegregating with coloration morph. This polymorphism replaces an ancestral leucine residue by lysine at the start of the first extracellular loop of the protein in the vulgaris morph. A selective sweep signature overlapped the association region in vulgaris, suggesting that past adaptation favored winter-brown morphs and can anchor future adaptive responses to decreasing winter snow. Using biological collections as valuable resources to study natural adaptations, our study showed a new evolutionary route generating winter color variation in mammals and that seasonal camouflage can be modulated by changes at single key genes.

Miranda, Inês↗
DOE OSTI2017

On the Adaptive Protection of Microgrids: A Review on How to Mitigate Cyber Attacks and Communication Failures

One main challenge in the practical implementation of a microgrid is the design of an adequate protection scheme in both grid connected and islanded modes. Conventional overcurrent protection schemes face selectivity and sensitivity issues during grid and microgrid faults since the fault current level is different in both cases for the same relay. Various approaches have been implemented in the past to deal with this problem, yet the most promising ones are the implementation of adaptive protection techniques abiding by the IEC 61850 communication standard. This paper presents a critical review of existing adaptive protection schemes, the technical challenges for the use of classical protection techniques and the need for an adaptive, smart protection system. However, the risk of communication link failures and cyber security threats still remain a challenge in implementing a reliable adaptive protection scheme. A contingency is needed where a communication issue prevents the relay from adjusting to a lower current level during islanded mode. An adaptive protection scheme is proposed that utilizes energy storage (ES) and hybrid ES (HESS) already available in the network as a mechanism to source the higher fault current. Four common grid ES and HESS are reviewed for their suitability in feeding the fault while some solutions are proposed.

25 ENERGY STORAGE↗
DOE OSTI2023

Improving Signal-to-Noise Ratio (SNR) for Readout Signals Using Adaptive Filters on Reconfigurable Controls Hardware

This study investigates the optimization of Signal-to-Noise Ratio (SNR) in superconducting quantum computing readout signals through adaptive filtering. Quantum computing technology has the potential to revolutionize various fields by delivering exponential speedup in solving certain computational problems. However, the technology's practical implementation is hindered by the difficulty of extracting clean, reliable signals during the readout phase, with various sources of noise presenting a significant barrier to clean signals. This noise, often present in readout profiles due to imperfect isolation, degrades the system's overall SNR, thus impeding the ability to extract the quantum state accurately. The research leverages the power of adaptive filtering to improve the SNR of quantum computing readout signals. Specifically, an adaptive filter is implemented in a PYNQ overlay on an FPGA, and eventually will be connected to a quantum computing system. The system models the noise with a Least Mean Squares (LMS) adaptive filter, and then subtracts the estimated noise from the received signal to improve the SNR. A Direct Memory Access (DMA) channel is used to handle the signal processing, delivering efficient, high-speed data transfer between the PYNQ system and the hardware. The study explores the benefits of this adaptive filtering technique, potentially providing a significant contribution to practical and fast quantum computing.

Johnson, Hans↗
DOE OSTI2025

Adaptation and Plasticity of Nannochloropsis sp. in Response to Seasonal and Geographic Climate Variation

Phytoplankton respond to their environment through genetic adaptation and plasticity to maintain fitness. This poses challenges when growing microalgae for industrial applications because, inherently, outdoor mass cultivation may lead to adaptations that alter desirable phenotypic traits and environmental niches. Here, we used common garden experiments to quantify the plasticity and adaptive responses to seasonal and geographic climate variation of Nannochloropsis, a microalga commonly used in biotechnology. An initially monoclonal strain was grown outdoors across four locations in Hawaii, Texas, California, and New Mexico. Following 17 and 22 months of cultivation outdoors, we collected samples during winter and summer, respectively, and we compared strains' growth from the four sites across temperature and light gradients in the laboratory. Despite hundreds of generations of exposure to divergent climates, with ~20°C and three-fold differences in daily light intensity, strains showed only minor differences in performance. Thermal performance varied more among seasons than sites, whereas light performance varied with both season and site. Our study indicates that Nannochloropsis exhibits broad plasticity in response to light and temperature, which may inhibit genetic adaptation in space or time. Highly variable field conditions, with daily and seasonal climate fluctuations, may favor plasticity and prevent the rapid adaptation often seen in laboratory studies of microorganisms in constant environments.

common garden experiment↗
DOE OSTI2016

Climate variables explain neutral and adaptive variation within salmonid metapopulations: the importance of replication in landscape genetics

Abstract Understanding how environmental variation influences population genetic structure is important for conservation management because it can reveal how human stressors influence population connectivity, genetic diversity and persistence. We used riverscape genetics modelling to assess whether climatic and habitat variables were related to neutral and adaptive patterns of genetic differentiation (population‐specific and pairwise F ST ) within five metapopulations (79 populations, 4583 individuals) of steelhead trout ( Oncorhynchus mykiss ) in the Columbia River Basin, USA . Using 151 putatively neutral and 29 candidate adaptive SNP loci, we found that climate‐related variables (winter precipitation, summer maximum temperature, winter highest 5% flow events and summer mean flow) best explained neutral and adaptive patterns of genetic differentiation within metapopulations, suggesting that climatic variation likely influences both demography (neutral variation) and local adaptation (adaptive variation). However, we did not observe consistent relationships between climate variables and F ST across all metapopulations, underscoring the need for replication when extrapolating results from one scale to another (e.g. basin‐wide to the metapopulation scale). Sensitivity analysis (leave‐one‐population‐out) revealed consistent relationships between climate variables and F ST within three metapopulations; however, these patterns were not consistent in two metapopulations likely due to small sample sizes ( N = 10). These results provide correlative evidence that climatic variation has shaped the genetic structure of steelhead populations and highlight the need for replication and sensitivity analyses in land and riverscape genetics.

Hand, Brian K.↗
DOE OSTI2020

Adaptive noise canceling for transient absorption microscopy

Significance: Ultrafast fiber lasers are an attractive alternative to bulk lasers for nonlinear optical microscopy for their compactness and low cost. The high relative intensity noise (RIN) of these lasers poses a challenge for pump-probe measurements such as transient absorption and stimulated Raman scattering, along with modalities that provide label-free contrast from the vibrational and electronic structure of molecules. Aim: Digital adaptive filtering was applied to determine the applicability for canceling laser RIN in a transient absorption microscope with an ultrafast fiber laser source. Approach: Digitized signals from the transmitted probe and reference photodetectors were fed to an adaptive filter in MATLAB, running in a noise canceling configuration. This result was then fed to a software lock-in algorithm to demodulate the pump-probe signal. Images were built up one line scan at a time with a 3.5-kHz resonant scanner, with 100× averaging. The imaging target was Bi4Ge3O12, which exhibits nondegenerate two-photon absorption at the pump/probe wavelengths used (530-nm pump and 490-nm probe). Results: Without adaptive noise cancellation, the lock-in output primarily passes the laser RIN within its detection bandwidth, resulting in images that closely follow the linear transmissivity and lack sensitivity to pump-probe time delay. With adaptive noise cancellation in front of the lock-in, the RIN rejection is enough to restore the z-sectioning and sensitivity to pump-probe delay, as expected for transient absorption. Results were limited primarily by noise from the photodetector and analog-to-digital converter. Conclusions: Digital adaptive noise cancellation, even when limited by electronics noise, can recover pump-probe signals by removal of laser RIN, under conditions where averaging alone fails.

42 ENGINEERING↗
DOE OSTI2025

Deep-learning-based domain adaptation for cavity fault prediction at Jefferson Laboratory

Superconducting radio-frequency (SRF) cavities are the core components of the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab, providing high-power electron beams for nuclear physics experiments. The facility comprises 418 SRF cavities, and any fault in these cavities can lead to interruptions in the electron beam supply. Cavity faults are the leading cause of beam trips in CEBAF. Predicting and mitigating those faults before onset can help maintain normal operation. Existing models face challenges in distinguishing between normal and fault signals when changes occur in the underlying time-series data, from changes in control software, operational parameters, or the environment. This work proposes a deep learning domain adaptation model that leverages transfer learning to address fault prediction challenges by improving accuracy. The model is trained and fine-tuned using a dataset collected for faulty and normal operation using a data acquisition system in CEBAF. Our deep learning-based domain adaptation model achieves a prediction accuracy of 89.61% of the fault and normal signals. The developed model effectively predicts normal running signals compared to the baseline approach without domain adaptation. This capacity is essential for the fault prediction task in the CEBAF because of heavily imbalanced data containing vast amounts of normal signals. The model performs well for predicting faults several hundred milliseconds before the fault onset compared to other models where no adaptation is applied. Incorporating deep learning-based domain adaptation techniques will significantly improve the fault prediction performance.

Rahman, Md Monibor [Old Dominion Univ., Norfolk, V↗
DOE OSTI2013

Quantification of organ motion based on an adaptive image-based scale invariant feature method

Purpose: The availability of corresponding landmarks in IGRT image series allows quantifying the inter and intrafractional motion of internal organs. In this study, an approach for the automatic localization of anatomical landmarks is presented, with the aim of describing the nonrigid motion of anatomo-pathological structures in radiotherapy treatments according to local image contrast.Methods: An adaptive scale invariant feature transform (SIFT) was developed from the integration of a standard 3D SIFT approach with a local image-based contrast definition. The robustness and invariance of the proposed method to shape-preserving and deformable transforms were analyzed in a CT phantom study. The application of contrast transforms to the phantom images was also tested, in order to verify the variation of the local adaptive measure in relation to the modification of image contrast. The method was also applied to a lung 4D CT dataset, relying on manual feature identification by an expert user as ground truth. The 3D residual distance between matches obtained in adaptive-SIFT was then computed to verify the internal motion quantification with respect to the expert user. Extracted corresponding features in the lungs were used as regularization landmarks in a multistage deformable image registration (DIR) mapping the inhale vs exhale phase. The residual distances between the warped manual landmarks and their reference position in the inhale phase were evaluated, in order to provide a quantitative indication of the registration performed with the three different point sets.Results: The phantom study confirmed the method invariance and robustness properties to shape-preserving and deformable transforms, showing residual matching errors below the voxel dimension. The adapted SIFT algorithm on the 4D CT dataset provided automated and accurate motion detection of peak to peak breathing motion. The proposed method resulted in reduced residual errors with respect to standard SIFT, providing a motion description comparable to expert manual identification, as confirmed by DIR.Conclusions: The application of the method to a 4D lung CT patient dataset demonstrated adaptive-SIFT potential as an automatic tool to detect landmarks for DIR regularization and internal motion quantification. Future works should include the optimization of the computational cost and the application of the method to other anatomical sites and image modalities.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

SU-E-J-20: Adaptive Aperture Morphing for Online Correction for Prostate Cancer Radiotherapy

Purpose: Online adaptive aperture morphing is desirable over translational couch shifts to accommodate not only the target position variation but also anatomic changes (rotation, deformation, and relation of target to organ-atrisks). We proposed quick and reliable method for adapting segment aperture leaves for IMRT treatment of prostate. Methods: The proposed method consists of following steps: (1) delineate the contours of prostate, SV, bladder and rectum on kV-CBCT; (2) determine prostate displacement from the rigid body registration of the contoured prostate manifested on the reference CT and the CBCT; (3) adapt the MLC segment apertures obtained from the pre-treatment IMRT planning to accommodate the shifts as well as anatomic changes. The MLC aperture adaptive algorithm involves two steps; first move the whole aperture according to prostate translational/rotational shifts, and secondly fine-tune the aperture shape to maintain the spatial relationship between the planning target contour and the MLC aperture to the daily target contour. Feasibility of this method was evaluated retrospectively on a seven-field IMRT treatment of prostate cancer patient by comparing dose volume histograms of the original plan and the aperture-adjusted plan, with/without additional segments weight optimization (SWO), on two daily treatment CBCTs selected with relative large motion and rotation. Results: For first daily treatment, the prostate rotation was significant (12degree around lateral-axis). With apertureadjusted plan, the D95 to the target was improved 25% and rectum dose (D30, D40) was reduced 20% relative to original plan on daily volumes. For second treatment-fraction, (lateral shift = 6.7mm), after adjustment target D95 improved by 3% and bladder dose (D30, maximum dose) was reduced by 1%. For both cases, extra SWO did not provide significant improvement. Conclusion: The proposed method of adapting segment apertures is promising in treatment position correction, including target translational displacement, rotation and deformation. Additional SWO could improve ROIs dose distribution.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

MO-C-17A-06: Online Adaptive Re-Planning to Account for Independent Motions Between Multiple Targets During Radiotherapy of Lung Cancer

Purpose: To quantify interfractional independent motions between multiple targets in radiotherapy (RT) of lung cancer, and to study the dosimetric benefits of an online adaptive replanning method to account for these variations. Methods: Ninety five diagnostic-quality daily CTs acquired for 9 lung cancer patients treated with IGRT using an in-room CT (CTVision, Siemens) were analyzed. On each daily CT set, contours of the targets (GTV, CTV, or involved nodes) and organs at risk were generated by populating the planning contours using an auto-segmentation tool (ABAS, Elekta) with manual editing. For each patient, an IMRT plan was generated based on the planning CT with a prescription dose of 60 Gy in 2Gy fractions. Three plans were generated and compared for each daily CT set: an IGRT (repositioning) plan by copying the original plan with the required shifts, an online adaptive plan by rapidly modifying the aperture shapes and segment weights of the original plan to conform to the daily anatomy, and a new fully re-optimized plan based on the daily CT using a planning system (Panther, Prowess). Results: The daily deviations of the distance between centers of masses of the targets from the plans varied daily from -10 to 8 mm with an average −0.9±4.1 mm (one standard deviation). The average CTV V100 are 99.0±0.7%, 97.9±2.8%, 99.0±0.6%, and 99.1±0.6%, and the lung V20 Gy 928±332 cc, 944±315 cc, 917±300 cc, and 891±295 cc for the original, repositioning, adaptive, and re-optimized plans, respectively. Wilcoxon signed-rank tests show that the adaptive plans are statistically significantly better than the repositioning plans and comparable with the reoptimized plans. Conclusion: There exist unpredictable, interfractional, relative volume changes and independent motions between multiple targets during lung cancer RT which cannot be accounted for by the current IGRT repositioning but can be corrected by the online adaptive replanning method.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-57: First Development of Adapting to Intrafraction Relative Motion Between Prostate and Pelvic Lymph Nodes Targets

Purpose Large intrafraction relative motion of multiple targets is common in advanced head and neck, lung, abdominal, gynaecological and urological cancer, jeopardizing the treatment outcomes. The objective of this study is to develop a real-time adaptation strategy, for the first time, to accurately correct for the relative motion of multiple targets by reshaping the treatment field using the multi-leaf collimator (MLC). Methods The principle of tracking the simultaneously treated but differentially moving tumor targets is to determine the new aperture shape that conforms to the shifted targets. Three dimensional volumes representing the individual targets are projected to the beam’s eye view. The leaf openings falling inside each 2D projection will be shifted according to the measured motion of each target to form the new aperture shape. Based on the updated beam shape, new leaf positions will be determined with optimized trade-off between the target underdose and healthy tissue overdose, and considerations of the physical constraints of the MLC. Taking a prostate cancer patient with pelvic lymph node involvement as an example, a preliminary dosimetric study was conducted to demonstrate the potential treatment improvement compared to the state-of- art adaptation technique which shifts the whole beam to track only one target. Results The world-first intrafraction adaptation system capable of reshaping the beam to correct for the relative motion of multiple targets has been developed. The dose in the static nodes and small bowel are closer to the planned distribution and the V45 of small bowel is decreased from 110cc to 75cc, corresponding to a 30% reduction by this technique compared to the state-of-art adaptation technique. Conclusion The developed adaptation system to correct for intrafraction relative motion of multiple targets will guarantee the tumour coverage and thus enable PTV margin reduction to minimize the high target dose to the adjacent organs-at-risk. The authors acknowledge funding support from the Australian NHMRC Australia Fellowship and NHMRC Project Grant No. APP1042375.

60 APPLIED LIFE SCIENCES↗