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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Beam’s-eye-view imaging during non-coplanar lung SBRT

Purpose: Beam’s-eye-view (BEV) imaging with an electronic portal imaging device (EPID) can be performed during lung stereotactic body radiation therapy (SBRT) to monitor the tumor location in real-time. Image quality for each patient and treatment field depends on several factors including the patient anatomy and the gantry and couch angles. The authors investigated the angular dependence of automatic tumor localization during non-coplanar lung SBRT delivery. Methods: All images were acquired at a frame rate of 12 Hz with an amorphous silicon EPID. A previously validated markerless lung tumor localization algorithm was employed with manual localization as the reference. From ten SBRT patients, 12 987 image frames of 123 image sequences acquired at 48 different gantry–couch rotations were analyzed. δ was defined by the position difference of the automatic and manual localization. Results: Regardless of the couch angle, the best tracking performance was found in image sequences with a gantry angle within 20° of 250° (δ = 1.40 mm). Image sequences acquired with gantry angles of 150°, 210°, and 350° also led to good tracking performances with δ = 1.77–2.00 mm. Overall, the couch angle was not correlated with the tracking results. Among all the gantry–couch combinations, image sequences acquired at (θ = 30°, ϕ = 330°), (θ = 210°, ϕ = 10°), and (θ = 250°, ϕ = 30°) led to the best tracking results with δ = 1.19–1.82 mm. The worst performing combinations were (θ = 90° and 230°, ϕ = 10°) and (θ = 270°, ϕ = 30°) with δ > 3.5 mm. However, 35% (17/48) of the gantry–couch rotations demonstrated substantial variability in tracking performances between patients. For example, the field angle (θ = 70°, ϕ = 10°) was acquired for five patients. While the tracking errors were ≤1.98 mm for three patients, poor performance was found for the other two patients with δ ≥ 2.18 mm, leading to average tracking error of 2.70 mm. Only one image sequence was acquired for all other gantry–couch rotations (δ = 1.18–10.29 mm). Conclusions: Non-coplanar beams with gantry–couch rotation of (θ = 30°, ϕ = 330°), (θ = 210°, ϕ = 10°), and (θ = 250°, ϕ = 30°) have the highest accuracy for BEV lung tumor localization. Additionally, gantry angles of 150°, 210°, 250°, and 350° also offer good tracking performance. The beam geometries (θ = 90° and 230°, ϕ = 10°) and (θ = 270°, ϕ = 30°) are associated with substantial automatic localization errors. Overall, lung tumor visibility and tracking performance were patient dependent for a substantial number of the gantry–couch angle combinations studied.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TH-AB-202-05: BEST IN PHYSICS (JOINT IMAGING-THERAPY): First Online Ultrasound-Guided MLC Tracking for Real-Time Motion Compensation in Radiotherapy

Purpose: While MLC tracking has been successfully used for motion compensation of moving targets, current real-time target localization methods rely on correlation models with x-ray imaging or implanted electromagnetic transponders rather than direct target visualization. In contrast, ultrasound imaging yields volumetric data in real-time (4D) without ionizing radiation. We report the first results of online 4D ultrasound-guided MLC tracking in a phantom. Methods: A real-time tracking framework was installed on a 4D ultrasound station (Vivid7 dimension, GE) and used to detect a 2mm spherical lead marker inside a water tank. The volumetric frame rate was 21.3Hz (47ms). The marker was rigidly attached to a motion stage programmed to reproduce nine tumor trajectories (five prostate, four lung). The 3D marker position from ultrasound was used for real-time MLC aperture adaption. The tracking system latency was measured and compensated by prediction for lung trajectories. To measure geometric accuracy, anterior and lateral conformal fields with 10cm circular aperture were delivered for each trajectory. The tracking error was measured as the difference between marker position and MLC aperture in continuous portal imaging. For dosimetric evaluation, 358° VMAT fields were delivered to a biplanar diode array dosimeter using the same trajectories. Dose measurements with and without MLC tracking were compared to a static reference dose using a 3%/3 mm γ-test. Results: The tracking system latency was 170ms. The mean root-mean-square tracking error was 1.01mm (0.75mm prostate, 1.33mm lung). Tracking reduced the mean γ-failure rate from 13.9% to 4.6% for prostate and from 21.8% to 0.6% for lung with high-modulation VMAT plans and from 5% (prostate) and 18% (lung) to 0% with low modulation. Conclusion: Real-time ultrasound tracking was successfully integrated with MLC tracking for the first time and showed similar accuracy and latency as other methods while holding the potential to measure target motion non-invasively. SI was supported by the Graduate School for Computing in Medicine and Life Science, German Excellence Initiative [grant DFG GSC 235/1].

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Iterative Learning Control for High-Speed Rosette Trajectory Tracking

We demonstrate high-speed tracking of a selfrepeating non-raster scan AFM pattern known as rosette. To generate this pattern, the lateral axes of the scanner trace a sum of two sinusoids with different frequencies but identical amplitudes. A feedback controller is combined with an iterative learning controller (ILC) to track this repetitive pattern. The feedback controller is designed based on the internal model principle and incorporates the fundamental reference frequencies. The ILC eliminates the repeating deterministic disturbances that appear in the tracking error. To verify the efficacy of the control approach, an experiment is conducted using a two degrees-of-freedom microelectromechanical system nanopositioner to track a rosette pattern sequentially at the rate= of five frames per second. The experimental results show that the root-mean-square value of tracking error has been reduced by more than 50% owing to the ILC

42 ENGINEERING↗
DOE OSTI2022

Evaluation of dynamic testing of full-scale wind turbine drivetrains with hardware-in-the-loop

Dynamometer testing of full-scale wind turbine drivetrains involves subjecting integrated components to extreme static loads, fatigue loads, or dynamic loads to replicate field conditions. This paper provides a detailed evaluation of the uncertainty and errors in applied loads and measured responses, and their magnitude relative to established repeatability bounds for a drivetrain subjected to static and dynamic loads on the 7.5 MW test bench at the Clemson University Wind Turbine Drivetrain Testing Facility. An ideal drivetrain simulation model is utilized to isolate the influence of load tracking errors on test article responses. It is shown that the test article response variations are mainly driven by run out and clearances inherent to the drivetrain. For the dynamic profiles, the load tracking errors are within acceptable limits. Furthermore, a frequency analysis is used to show that the test bench controller tracking performance is acceptable for profiles with frequency content up to 1.5 Hz.

17 WIND ENERGY↗
DOE OSTI2015

SU-D-207-05: Real-Time Intrafractional Motion Tracking During VMAT Delivery Using a Conventional Elekta CBCT System

Purpose: Real-time kV projection streaming capability has become recently available for Elekta XVI version 5.0. This study aims to investigate the feasibility and accuracy of real-time fiducial marker tracking during CBCT acquisition with or without simultaneous VMAT delivery using a conventional Elekta linear accelerator. Methods: A client computer was connected to an on-board kV imaging system computer, and receives and processes projection images immediately after image acquisition. In-house marker tracking software based on FFT normalized cross-correlation was developed and installed in the client computer. Three gold fiducial markers with 3 mm length were implanted in a pelvis-shaped phantom with 36 cm width. The phantom was placed on a programmable motion platform oscillating in anterior-posterior and superior-inferior directions simultaneously. The marker motion was tracked in real-time for (1) a kV-only CBCT scan with treatment beam off and (2) a kV CBCT scan during a 6-MV VMAT delivery. The exposure parameters per projection were 120 kVp and 1.6 mAs. Tracking accuracy was assessed by comparing superior-inferior positions between the programmed and tracked trajectories. Results: The projection images were successfully transferred to the client computer at a frequency of about 5 Hz. In the kV-only scan, highly accurate marker tracking was achieved over the entire range of cone-beam projection angles (detection rate / tracking error were 100.0% / 0.6±0.5 mm). In the kV-VMAT scan, MV-scatter degraded image quality, particularly for lateral projections passing through the thickest part of the phantom (kV source angle ranging 70°-110° and 250°-290°), resulting in a reduced detection rate (90.5%). If the lateral projections are excluded, tracking performance was comparable to the kV-only case (detection rate / tracking error were 100.0% / 0.8±0.5 mm). Conclusion: Our phantom study demonstrated a promising Result for real-time motion tracking using a conventional Elekta linear accelerator. MV-scatter suppression is needed to improve tracking accuracy during MV delivery. This research is funded by Motion Management Research Grant from Elekta.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-G-BRA-02: Development of a Learning Based Block Matching Algorithm for Ultrasound Tracking in Radiotherapy

Purpose: To develop an ultrasound learning-based tracking algorithm with the potential to provide real-time motion traces of anatomy-based fiducials that may aid in the effective delivery of external beam radiation. Methods: The algorithm was developed in Matlab R2015a and consists of two main stages: reference frame selection, and localized block matching. Immediately following frame acquisition, a normalized cross-correlation (NCC) similarity metric is used to determine a reference frame most similar to the current frame from a series of training set images that were acquired during a pretreatment scan. Segmented features in the reference frame provide the basis for the localized block matching to determine the feature locations in the current frame. The boundary points of the reference frame segmentation are used as the initial locations for the block matching and NCC is used to find the most similar block in the current frame. The best matched block locations in the current frame comprise the updated feature boundary. The algorithm was tested using five features from two sets of ultrasound patient data obtained from MICCAI 2014 CLUST. Due to the lack of a training set associated with the image sequences, the first 200 frames of the image sets were considered a valid training set for preliminary testing, and tracking was performed over the remaining frames. Results: Tracking of the five vessel features resulted in an average tracking error of 1.21 mm relative to predefined annotations. The average analysis rate was 15.7 FPS with analysis for one of the two patients reaching real-time speeds. Computations were performed on an i5-3230M at 2.60 GHz. Conclusion: Preliminary tests show tracking errors comparable with similar algorithms at close to real-time speeds. Extension of the work onto a GPU platform has the potential to achieve real-time performance, making tracking for therapy applications a feasible option. This work is partially funded by NIH grant R01CA190298.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

A Technique for Generating Volumetric Cine-Magnetic Resonance Imaging

Purpose: The purpose of this study was to develop a techique to generate on-board volumetric cine-magnetic resonance imaging (VC-MRI) using patient prior images, motion modeling, and on-board 2-dimensional cine MRI. Methods and Materials: One phase of a 4-dimensional MRI acquired during patient simulation is used as patient prior images. Three major respiratory deformation patterns of the patient are extracted from 4-dimensional MRI based on principal-component analysis. The on-board VC-MRI at any instant is considered as a deformation of the prior MRI. The deformation field is represented as a linear combination of the 3 major deformation patterns. The coefficients of the deformation patterns are solved by the data fidelity constraint using the acquired on-board single 2-dimensional cine MRI. The method was evaluated using both digital extended-cardiac torso (XCAT) simulation of lung cancer patients and MRI data from 4 real liver cancer patients. The accuracy of the estimated VC-MRI was quantitatively evaluated using volume-percent-difference (VPD), center-of-mass-shift (COMS), and target tracking errors. Effects of acquisition orientation, region-of-interest (ROI) selection, patient breathing pattern change, and noise on the estimation accuracy were also evaluated. Results: Image subtraction of ground-truth with estimated on-board VC-MRI shows fewer differences than image subtraction of ground-truth with prior image. Agreement between normalized profiles in the estimated and ground-truth VC-MRI was achieved with less than 6% error for both XCAT and patient data. Among all XCAT scenarios, the VPD between ground-truth and estimated lesion volumes was, on average, 8.43 ± 1.52% and the COMS was, on average, 0.93 ± 0.58 mm across all time steps for estimation based on the ROI region in the sagittal cine images. Matching to ROI in the sagittal view achieved better accuracy when there was substantial breathing pattern change. The technique was robust against noise levels up to SNR = 20. For patient data, average tracking errors were less than 2 mm in all directions for all patients. Conclusions: Preliminary studies demonstrated the feasibility of generating real-time VC-MRI for on-board localization of moving targets in radiation therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Asynchronous and Distributed Tracking of Time-Varying Fixed Points

NREL researcher Andrey Bernstein discusses asynchronous and distributed tracking of time-varying fixed points as part of the Innovative Optimization and Control Methods for Highly Distributed Autonomous Systems workshop. NREL hosted the workshop to exchange ideas on state-of-the-art control and optimization strategies as well as get feedback on work being done at NREL.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

The impact of cine EPID image acquisition frame rate on markerless soft-tissue tracking

Purpose: Although reduction of the cine electronic portal imaging device (EPID) acquisition frame rate through multiple frame averaging may reduce hardware memory burden and decrease image noise, it can hinder the continuity of soft-tissue motion leading to poor autotracking results. The impact of motion blurring and image noise on the tracking performance was investigated. Methods: Phantom and patient images were acquired at a frame rate of 12.87 Hz with an amorphous silicon portal imager (AS1000, Varian Medical Systems, Palo Alto, CA). The maximum frame rate of 12.87 Hz is imposed by the EPID. Low frame rate images were obtained by continuous frame averaging. A previously validated tracking algorithm was employed for autotracking. The difference between the programmed and autotracked positions of a Las Vegas phantom moving in the superior-inferior direction defined the tracking error (δ). Motion blurring was assessed by measuring the area change of the circle with the greatest depth. Additionally, lung tumors on 1747 frames acquired at 11 field angles from four radiotherapy patients are manually and automatically tracked with varying frame averaging. δ was defined by the position difference of the two tracking methods. Image noise was defined as the standard deviation of the background intensity. Motion blurring and image noise are correlated with δ using Pearson correlation coefficient (R). Results: For both phantom and patient studies, the autotracking errors increased at frame rates lower than 4.29 Hz. Above 4.29 Hz, changes in errors were negligible withδ < 1.60 mm. Motion blurring and image noise were observed to increase and decrease with frame averaging, respectively. Motion blurring and tracking errors were significantly correlated for the phantom (R = 0.94) and patient studies (R = 0.72). Moderate to poor correlation was found between image noise and tracking error with R −0.58 and −0.19 for both studies, respectively. Conclusions: Cine EPID image acquisition at the frame rate of at least 4.29 Hz is recommended. Motion blurring in the images with frame rates below 4.29 Hz can significantly reduce the accuracy of autotracking.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

A Generic Two-Vector Model Predictive Control for Hybrid Multilevel Converters

In this article, a generic two-vector model predictive control (TV-MPC) strategy is proposed for the hybrid multilevel converters (HMCs). The proposed method selects two optimal voltage vectors among all the vector candidates using a geometric positioning approach to reduce the computational burden, which is a common issue in the existing MPC methods for HMC. Then duty cycles of the two selected vectors are optimized to minimize the current tracking error, such that the current tracking performance can be enhanced compared with the conventional MPC. In addition, the voltages of the floating dc capacitors can be balanced by evaluating all switching sequences that belong to the optimal voltage vectors with optimal duty cycles. Here, the concept of the proposed TV-MPC is generic and applicable for any HMCs. A typical HMC based on active neutral-point-clamped topology is adopted as a case study in this work. Comprehensive simulation and experimental studies are performed on an all silicon-carbide HMC prototype to validate the effectiveness of the proposed control scheme.

42 ENGINEERING↗
DOE OSTI2026

Optimisation of the Kaplan hydropower system via PID 2 and digital twin

Here, this paper proposes a proportional–integral-double–derivative (PID 2 ) optimisation method for the Kaplan hydropower system by building a digital twin. The study first uses one multilayer perceptron (MLP) to model the hydroturbine dynamic and then adopts three connected MLPs to model the generator dynamic, both in an open-loop fashion. Inspired by stochastic distribution control (SDC) theory, we regard the training of the turbine's neural network model as a process control problem, and we propose minimising entropy loss to update the network parameters. The next step is to build the digital twin by connecting the neural network models with a PID 2 controller and a lead-lag exciter and run the whole model in a closed-loop fashion. After that, a binary search approach is applied to optimise the PID 2 parameters based on the obtained digital twin model. The simulation results show that the proposed method can reduce the mean square tracking error by more than 90%. Furthermore, the method is extended to jointly optimise the PID 2 controller and excitation system gains through multiobjective optimisation, leveraging Pareto frontier analysis to balance active power and voltage tracking performance. Simulation results confirm the effectiveness of the proposed method, achieving a 83.46% reduction in relative mean square error of active power, a 47.13% reduction in terminal voltage tracking error, and an 82.78% improvement in the overall scalarized objective.

Hydropower system↗
DOE OSTI2021

Five-day track forecast skills of WRF model for the western North Pacific tropical cyclones

In this study, the characteristics of simulated tropical cyclones (TCs) over the western North Pacific by a regional model (the WRF Model) are verified. We utilize 12-km horizontal grid spacing, and simulations are integrated for 5 days from model initialization. A total of 125 forecasts are divided into five clusters through the k-means clustering method. The TCs in the cluster 1 and 2 (group 1), which includes many TCs moving northward in the subtropical region, generally have larger track errors than for TCs in cluster 3 and 4 (group 2). The optimal steering vector is used to examine the difference in the track forecast skill between these two groups. The bias in the steering vector between the model and analysis data is found to be more substantial for group 1 TCs than group 2 TCs. The larger steering vector difference for group 1 TCs indicates that environmental fields tend to be poorly simulated in group 1 TC cases. Furthermore, the residual terms, including the storm-scale process, asymmetric convection distribution, or beta-related effect, are also larger for group 1 TCs than group 2 TCs. Therefore, it is probable that the large track forecast error for group 1 TCs is a result of unreasonable simulations of environmental wind fields and residual processes in the midlatitudes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Performance of the first mechanically-coupled twisting heliostat: encircled energy vs angle of incidence, and closed loop tracking

The first automatic twisting heliostat, with 8 m2 reflector, was completed and tested on-sun in January 2024. It was set up on a target-oriented dual-axis mount, with the target-axis aimed at a target 113 m to the west. The shape-twisting is purely automatic, made by a mechanical cam coupling to the cross-axis, which turns as the angle of incidence of the sun’s rays on the reflector. Three unsaturated images taken at different times of day were recorded of the sun on the target, reflected at angles of incidence of 5°, 49° and 68°. The measured FWHM of three images is very similar, about 1.09 m or 9.5 mrad, only slightly larger than an ideal solar disc, indicating that the different twisted reflector shapes are close to the ideal biconics needed to image the sun. The encircled energy measured for all three images was similar, 87% within approximately 1.30 m diameter. We report here also on a novel, tracking camera that employs a semitransparent beamsplitter fixed perpendicular to the mirror surface and to the plane of incidence. Over 2.5 hours of measurement of closed loop tracking, errors were ≤ 0.36 mrad rms, in both tracking axes.

14 SOLAR ENERGY↗
DOE OSTI2014

Iso-uncertainty control in an experimental fluoroscopy system

Purpose: X-ray fluoroscopy remains an important imaging modality in a number of image-guided procedures due to its real-time nature and excellent spatial detail. However, the radiation dose delivered raises concerns about its use particularly in lengthy treatment procedures (>0.5 h). The authors have previously presented an algorithm that employs feedback of geometric uncertainty to control dose while maintaining a desired targeting uncertainty during fluoroscopic tracking of fiducials. The method was tested using simulations of motion against controlled noise fields. In this paper, the authors embody the previously reported method in a physical prototype and present changes to the controller required to function in a practical setting. Methods: The metric for feedback used in this study is based on the trace of the covariance of the state of the system, tr(C). The state is defined here as the 2D location of a fiducial on a plane parallel to the detector. A relationship between this metric and the tube current is first developed empirically. This relationship is extended to create a manifold that incorporates a latent variable representing the estimated background attenuation. The manifold is then used within the controller to dynamically adjust the tube current and maintain a specified targeting uncertainty. To evaluate the performance of the proposed method, an acrylic sphere (1.6 mm in diameter) was tracked at tube currents ranging from 0.5 to 0.9 mA (0.033 s) at a fixed energy of 80 kVp. The images were acquired on a Varian Paxscan 4030A (2048 × 1536 pixels, ∼100 cm source-to-axis distance, ∼160 cm source-to-detector distance). The sphere was tracked using a particle filter under two background conditions: (1) uniform sheets of acrylic and (2) an acrylic wedge. The measured tr(C) was used in conjunction with a learned manifold to modulate the tube current in order to maintain a specified uncertainty as the sphere traversed regions of varying thickness corresponding to the acrylic sheets in the background. Results: With feedback engaged, the tracking error was found to correlate well with the specified targeting uncertainty. Tracking of the fiducial was found to be robust to changes in the attenuation presented by the varying background conditions. For a desired uncertainty of 5.0 mm, comparison of the feedback framework with a comparable system employing fixed exposure demonstrated dose savings of 29%. Conclusions: This work presents a relation between a state descriptor, tr(C), the x-ray tube current used, and an estimate of the background attenuation. This relation is leveraged to modulate the tube current in order to maintain a desired geometric uncertainty during fluoroscopy. The authors’ work demonstrates the use of the method in a real x-ray fluoroscopy system with physical motion against varying backgrounds. The method offers potential savings in imaging dose to patients and staff while maintaining tracking uncertainty during fluoroscopy-guided treatment procedures.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Biomimetic model-based advanced control strategy integrated with multi-agent optimization for nonlinear chemical processes

Here, a novel framework is proposed for integrating biomimetic-based advanced control and multi-agent optimization approaches for nonlinear chemical process applications. In particular, a Biologically-Inspired Optimal Control Strategy, denoted as BIO-CS, is combined with multi-agent optimization (MAO) techniques to provide optimal solutions for dynamic systems. In this combined framework, the BIO-CS algorithm employs gradient-based optimal control solvers for the intermediate problems associated with the leader-follower agents’ local interactions. Also, the MAO uses the capabilities of heuristic-based optimization techniques by sharing process information to obtain optimal operating setpoints for the controller considering an overall process objective. The applicability of the proposed method is demonstrated using a nonlinear, multivariable, process model of a fermentation system. Specifically, the optimal operating points are computed by the MAO implementation for setpoint tracking, trajectory tracking and plant-model mismatch scenarios for BIO-CS application. Results of the developed framework are compared to a gradient-based Sequential Quadratic Programming (SQP) technique and a classical proportional-integral (PI) controller in terms of optimization and control studies, respectively. As an additional contribution, BIO-CS is also cast as a model predictive controller (MPC) for the first time and compared to the agent-based BIO-CS approach in terms of computational time and tracking error. Closed-loop control results show up to 46% improvement in tracking performance during transient for the multi-agent BIO-CS when compared to BIO-CS as MPC for additional computational expense. The obtained results illustrate the capabilities of this novel integrated framework including BIO-CS as MPC to achieve desired nonlinear system performance for various scenarios.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Poster - 49: Assessment of Synchrony respiratory compensation error for CyberKnife liver treatment

The goal of this work is to quantify respiratory motion compensation errors for liver tumor patients treated by the CyberKnife system with Synchrony tracking, to identify patients with the smallest tracking errors and to eventually help coach patient’s breathing patterns to minimize dose delivery errors. The accuracy of CyberKnife Synchrony respiratory motion compensation was assessed for 37 patients treated for liver lesions by analyzing data from system logfiles. A predictive model is used to modulate the direction of individual beams during dose delivery based on the positions of internally implanted fiducials determined using an orthogonal x-ray imaging system and the current location of LED external markers. For each x-ray pair acquired, system logfiles report the prediction error, the difference between the measured and predicted fiducial positions, and the delivery error, which is an estimate of the statistical error in the model overcoming the latency between x-ray acquisition and robotic repositioning. The total error was calculated at the time of each x-ray pair, for the number of treatment fractions and the number of patients, giving the average respiratory motion compensation error in three dimensions. The 99{sup th} percentile for the total radial error is 3.85 mm, with the highest contribution of 2.79 mm in superior/inferior (S/I) direction. The absolute mean compensation error is 1.78 mm radially with a 1.27 mm contribution in the S/I direction. Regions of high total error may provide insight into features predicting groups of patients with larger or smaller total errors.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SIFT-based dense pixel tracking on 0.35 T cine-MR images acquired during image-guided radiation therapy with application to gating optimization

Purpose: To first demonstrate the viability of applying an image processing technique for tracking regions on low-contrast cine-MR images acquired during image-guided radiation therapy, and then outline a scheme that uses tracking data for optimizing gating results in a patient-specific manner. Methods: A first-generation MR-IGRT system—treating patients since January 2014—integrates a 0.35 T MR scanner into an annular gantry consisting of three independent Co-60 sources. Obtaining adequate frame rates for capturing relevant patient motion across large fields-of-view currently requires coarse in-plane spatial resolution. This study initially (1) investigate the feasibility of rapidly tracking dense pixel correspondences across single, sagittal plane images (with both moderate signal-to-noise and spatial resolution) using a matching objective for highly descriptive vectors called scale-invariant feature transform (SIFT) descriptors associated to all pixels that describe intensity gradients in local regions around each pixel. To more accurately track features, (2) harmonic analysis was then applied to all pixel trajectories within a region-of-interest across a short training period. In particular, the procedure adjusts the motion of outlying trajectories whose relative spectral power within a frequency bandwidth consistent with respiration (or another form of periodic motion) does not exceed a threshold value that is manually specified following the training period. To evaluate the tracking reliability after applying this correction, conventional metrics—including Dice similarity coefficients (DSCs), mean tracking errors (MTEs), and Hausdorff distances (HD)—were used to compare target segmentations obtained via tracking to manually delineated segmentations. Upon confirming the viability of this descriptor-based procedure for reliably tracking features, the study (3) outlines a scheme for optimizing gating parameters—including relative target position and a tolerable margin about this position—derived from a probability density function that is constructed using tracking results obtained just prior to treatment. Results: The feasibility of applying the matching objective for SIFT descriptors toward pixel-by-pixel tracking on cine-MR acquisitions was first retrospectively demonstrated for 19 treatments (spanning various sites). Both with and without motion correction based on harmonic analysis, sub-pixel MTEs were obtained. A mean DSC value spanning all patients of 0.916 ± 0.001 was obtained without motion correction, with DSC values exceeding 0.85 for all patients considered. While most patients show accurate tracking without motion correction, harmonic analysis does yield substantial gain in accuracy (defined using HDs) for three particularly challenging subjects. An application of tracking toward a gating optimization procedure was then demonstrated that should allow a physician to balance beam-on time and tissue sparing in a patient-specific manner by tuning several intuitive parameters. Conclusions: Tracking results show high fidelity in assessing intrafractional motion observed on cine-MR acquisitions. Incorporating harmonic analysis during a training period improves the robustness of the tracking for challenging targets. The concomitant gating optimization procedure should allow for physicians to quantitatively assess gating effectiveness quickly just prior to treatment in a patient-specific manner.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2015

Reference respiratory waveforms by minimum jerk model analysis

Purpose: CyberKnife{sup ®} robotic surgery system has the ability to deliver radiation to a tumor subject to respiratory movements using Synchrony{sup ®} mode with less than 2 mm tracking accuracy. However, rapid and rough motion tracking causes mechanical tracking errors and puts mechanical stress on the robotic joint, leading to unexpected radiation delivery errors. During clinical treatment, patient respiratory motions are much more complicated, suggesting the need for patient-specific modeling of respiratory motion. The purpose of this study was to propose a novel method that provides a reference respiratory wave to enable smooth tracking for each patient. Methods: The minimum jerk model, which mathematically derives smoothness by means of jerk, or the third derivative of position and the derivative of acceleration with respect to time that is proportional to the time rate of force changed was introduced to model a patient-specific respiratory motion wave to provide smooth motion tracking using CyberKnife{sup ®}. To verify that patient-specific minimum jerk respiratory waves were being tracked smoothly by Synchrony{sup ®} mode, a tracking laser projection from CyberKnife{sup ®} was optically analyzed every 0.1 s using a webcam and a calibrated grid on a motion phantom whose motion was in accordance with three pattern waves (cosine, typical free-breathing, and minimum jerk theoretical wave models) for the clinically relevant superior–inferior directions from six volunteers assessed on the same node of the same isocentric plan. Results: Tracking discrepancy from the center of the grid to the beam projection was evaluated. The minimum jerk theoretical wave reduced the maximum-peak amplitude of radial tracking discrepancy compared with that of the waveforms modeled by cosine and typical free-breathing model by 22% and 35%, respectively, and provided smooth tracking for radial direction. Motion tracking constancy as indicated by radial tracking discrepancy affected by respiratory phase was improved in the minimum jerk theoretical model by 7.0% and 13% compared with that of the waveforms modeled by cosine and free-breathing model, respectively. Conclusions: The minimum jerk theoretical respiratory wave can achieve smooth tracking by CyberKnife{sup ®} and may provide patient-specific respiratory modeling, which may be useful for respiratory training and coaching, as well as quality assurance of the mechanical CyberKnife{sup ®} robotic trajectory.

60 APPLIED LIFE SCIENCES↗