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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Blind identification of full-field vibration modes of output-only structures from uniformly-sampled, possibly temporally-aliased (sub-Nyquist), video measurements

Enhancing the spatial and temporal resolution of vibration measurements and modal analysis could significantly benefit dynamic modelling, analysis, and health monitoring of structures. For example, spatially high-density mode shapes are critical for accurate vibration-based damage localization. In experimental or operational modal analysis, higher (frequency) modes, which may be outside the frequency range of the measurement, contain local structural features that can improve damage localization as well as the construction and updating of the modal-based dynamic model of the structure. In general, the resolution of vibration measurements can be increased by enhanced hardware. Traditional vibration measurement sensors such as accelerometers have high-frequency sampling capacity; however, they are discrete point-wise sensors only providing sparse, low spatial sensing resolution measurements, while dense deployment to achieve high spatial resolution is expensive and results in the mass-loading effect and modification of structure's surface. Non-contact measurement methods such as scanning laser vibrometers provide high spatial and temporal resolution sensing capacity; however, they make measurements sequentially that requires considerable acquisition time. As an alternative non-contact method, digital video cameras are relatively low-cost, agile, and provide high spatial resolution, simultaneous, measurements. Combined with vision based algorithms (e.g., image correlation or template matching, optical flow, etc.), video camera based measurements have been successfully used for experimental and operational vibration measurement and subsequent modal analysis. However, the sampling frequency of most affordable digital cameras is limited to 30–60 Hz, while high-speed cameras for higher frequency vibration measurements are extremely costly. This work develops a computational algorithm capable of performing vibration measurement at a uniform sampling frequency lower than what is required by the Shannon-Nyquist sampling theorem for output-only modal analysis. In particular, the spatio-temporal uncoupling property of the modal expansion of structural vibration responses enables a direct modal decoupling of the temporally-aliased vibration measurements by existing output-only modal analysis methods, yielding (full-field) mode shapes estimation directly. Then the signal aliasing properties in modal analysis is exploited to estimate the modal frequencies and damping ratios. Furthermore, the proposed method is validated by laboratory experiments where output-only modal identification is conducted on temporally-aliased acceleration responses and particularly the temporally-aliased video measurements of bench-scale structures, including a three-story building structure and a cantilever beam.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Short-Term Precipitation Forecast Based on the PERSIANN System and LSTM Recurrent Neural Networks

Short-term Quantitative Precipitation Forecasting is important for flood forecasting, early flood warning, and natural hazard management. This study proposes a precipitation forecast model by extrapolating Cloud-Top Brightness Temperature (CTBT) using advanced Deep Neural Networks, and applying the forecasted CTBT into an effective rainfall retrieval algorithm to obtain the Short-term Quantitative Precipitation Forecasting (0–6 hr). To achieve such tasks, we propose a Long Short-Term Memory (LSTM) and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), respectively. The precipitation forecasts obtained from our proposed framework, (i.e., LSTM combined with PERSIANN) are compared with a Recurrent Neural Network (RNN), Persistency method, and Farneback optical flow each combined with PERSIANN algorithm and the numerical model results from the first version of Rapid Refresh (RAPv1.0) over three regions in the United States, including the states of Oregon, Oklahoma, and Florida. We report our experiments indicate better statistics, such as correlation coefficient and root-mean-square error, for the CTBT forecasts from the proposed LSTM compared to the RNN, Persistency, and the Farneback method. The precipitation forecasts from the proposed LSTM and PERSIANN framework has demonstrated better statistics compared to the RAPv1.0 numerical forecasts and PERSIANN estimations from RNN, Persistency, and Farneback projections in terms of Probability of Detection, False Alarm Ratio, Critical Success Index, correlation coefficient, and root-mean-square error, especially in predicting the convective rainfalls. The proposed method shows superior capabilities in short-term forecasting over compared methods, and has the potential to be implemented globally as an alternative short-term forecast product.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Endoperoxide formation by an α-ketoglutarate-dependent mononuclear non-haem iron enzyme

Many peroxy-containing secondary metabolites have been isolated and shown to provide beneficial effects to human health. Yet, the mechanisms of most endoperoxide biosyntheses are not well understood. Although endoperoxides have been suggested as key reaction intermediates in several cases, the only well-characterized endoperoxide biosynthetic enzyme is prostaglandin H synthase, a haem-containing enzyme9. Fumitremorgin B endoperoxidase (FtmOx1) from Aspergillus fumigatus is the first reported α-ketoglutarate-dependent mononuclear non-haem iron enzyme that can catalyse an endoperoxide formation reaction. To elucidate the mechanistic details for this unique chemical transformation, we report the X-ray crystal structures of FtmOx1 and the binary complexes it forms with either the co-substrate (α-ketoglutarate) or the substrate (fumitremorgin B). Uniquely, after α-ketoglutarate has bound to the mononuclear iron centre in a bidentate fashion, the remaining open site for oxygen binding and activation is shielded from the substrate or the solvent by a tyrosine residue (Y224). Upon replacing Y224 with alanine or phenylalanine, the FtmOx1 catalysis diverts from endoperoxide formation to the more commonly observed hydroxylation. Subsequent characterizations by a combination of stopped-flow optical absorption spectroscopy and freeze-quench electron paramagnetic resonance spectroscopy support the presence of transient radical species in FtmOx1 catalysis. Furthermore, our results help to unravel the novel mechanism for this endoperoxide formation reaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Image registration for accurate electrode deformation analysis in operando microscopy of battery materials

Operando imaging techniques have become increasingly valuable in both battery research and manufacturing. However, the reliability of these methods can be compromised by instabilities in the imaging setup and operando cells, particularly when utilizing high-resolution imaging systems. The acquired imaging data often include features arising from both undesirable system vibrations and drift, as well as the scientifically relevant deformations occurring in the battery sample during cell operation. For meaningful analysis, it is crucial to distinguish and separately evaluate these two factors. To address these challenges, we employ a suite of advanced image-processing techniques. These include fast Fourier transform analysis in the frequency domain, power spectrum-based assessments for image quality, as well as rigid and non-rigid image-registration methods. These techniques allow us to identify and exclude blurred images, correct for displacements caused by motor vibrations and sample holder drift and, thus, prevent unwanted image artifacts from affecting subsequent analyses and interpretations. Additionally, we apply optical flow analysis to track the dynamic deformation of battery electrode materials during electrochemical cycling. This enables us to observe and quantify the evolving mechanical responses of the electrodes, offering deeper insights into battery degradation. Together, these methods ensure more accurate image analysis and enhance our understanding of the chemomechanical interplay in battery performance and longevity.

Sun, Tianxiao↗
DOE OSTI2014

Validation of deformable image registration algorithms on CT images of ex vivo porcine bladders with fiducial markers

Purpose: The spatial accuracy of deformable image registration (DIR) is important in the implementation of image guided adaptive radiotherapy techniques for cancer in the pelvic region. Validation of algorithms is best performed on phantoms with fiducial markers undergoing controlled large deformations. Excised porcine bladders, exhibiting similar filling and voiding behavior as human bladders, provide such an environment. The aim of this study was to determine the spatial accuracy of different DIR algorithms on CT images ofex vivo porcine bladders with radiopaque fiducial markers applied to the outer surface, for a range of bladder volumes, using various accuracy metrics. Methods: Five excised porcine bladders with a grid of 30–40 radiopaque fiducial markers attached to the outer wall were suspended inside a water-filled phantom. The bladder was filled with a controlled amount of water with added contrast medium for a range of filling volumes (100–400 ml in steps of 50 ml) using a luer lock syringe, and CT scans were acquired at each filling volume. DIR was performed for each data set, with the 100 ml bladder as the reference image. Six intensity-based algorithms (optical flow or demons-based) implemented in theMATLAB platform DIRART, a b-spline algorithm implemented in the commercial software package VelocityAI, and a structure-based algorithm (Symmetric Thin Plate Spline Robust Point Matching) were validated, using adequate parameter settings according to values previously published. The resulting deformation vector field from each registration was applied to the contoured bladder structures and to the marker coordinates for spatial error calculation. The quality of the algorithms was assessed by comparing the different error metrics across the different algorithms, and by comparing the effect of deformation magnitude (bladder volume difference) per algorithm, using the Independent Samples Kruskal-Wallis test. Results: The authors found good structure accuracy without dependency on bladder volume difference for all but one algorithm, and with the best result for the structure-based algorithm. Spatial accuracy as assessed from marker errors was disappointing for all algorithms, especially for large volume differences, implying that the deformations described by the registration did not represent anatomically correct deformations. The structure-based algorithm performed the best in terms of marker error for the large volume difference (100–400 ml). In general, for the small volume difference (100–150 ml) the algorithms performed relatively similarly. The structure-based algorithm exhibited the best balance in performance between small and large volume differences, and among the intensity-based algorithms, the algorithm implemented in VelocityAI exhibited the best balance. Conclusions: Validation of multiple DIR algorithms on a novel physiological bladder phantom revealed that the structure accuracy was good for most algorithms, but that the spatial accuracy as assessed from markers was low for all algorithms, especially for large deformations. Hence, many of the available algorithms exhibit sufficient accuracy for contour propagation purposes, but possibly not for accurate dose accumulation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-D-17A-07: Development and Evaluation of a Prototype Ultrasonography Respiratory Monitoring System for 4DCT Reconstruction

Purpose: Respiratory motion artifacts are commonly seen in the abdominal and thoracic CT images. A Real-time Position Management (RPM) system is integrated with CT simulator using abdominal surface as a surrogate for tracking the patient respiratory motion. The respiratory-correlated four-dimensional computed tomography (4DCT) is then reconstructed by GE advantage software. However, there are still artifacts due to inaccurate respiratory motion detecting and sorting methods. We developed an Ultrasonography Respiration Monitoring (URM) system which can directly monitor diaphragm motion to detect respiratory cycles. We also developed a new 4DCT sorting and motion estimation method to reduce the respiratory motion artifacts. The new 4DCT system was compared with RPM and the GE 4DCT system. Methods: Imaging from a GE CT scanner was simultaneously correlated with both the RPM and URM to detect respiratory motion. A radiation detector, Blackcat GM-10, recorded the X-ray on/off and synchronized with URM. The diaphragm images were acquired with Ultrasonix RP system. The respiratory wave was derived from diaphragm images and synchronized with CT scanner. A more precise peaks and valleys detection tool was developed and compared with RPM. The motion is estimated for the slices which are not in the predefined respiratory phases by using block matching and optical flow method. The CT slices were then sorted into different phases and reconstructed, compared with the images reconstructed from GE Advantage software using respiratory wave produced from RPM system. Results: The 4DCT images were reconstructed for eight patients. The discontinuity at the diaphragm level due to an inaccurate identification of phases by the RPM was significantly improved by URM system. Conclusion: Our URM 4DCT system was evaluated and compared with RPM and GE 4DCT system. The new system is user friendly and able to reduce motion artifacts. It also has the potential to monitor organ motion during therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

SU-E-J-173: Evaluation of Deformable Registration for Correcting Respiratory Motion in 4DCT Lung Images

Purpose: Deformable Image Registration (DIR) is gaining wider clinical acceptance in radiation oncology. The aim of this work is to characterise a DIR algorithm on publically available 4DCT lung images, such that comparison can be performed against other algorithms. We propose an evaluation method of registration accuracy that takes into account the initial misregistration of the datasets. Methods: The “DIR Validation dataset” ( http://www.creatis.insa-lyon.fr/rio/dir{sub v}alidation{sub d}ata ) provides benchmark data for evaluating 3D CT registration algorithms. It consists of six 4DCT lung datasets (1x1x2mm resolution) with 100 landmarks identified on the end-exhalation and end-inhalation phases. Images were registered to end-inhalation using proprietary form of optical flow in commercial software (Mirada RTx, Mirada Medical, UK). Target registration error was measured before and after DIR, referred to as Initial Registration Error (IRE) and Final Registration Error (FRE). Results: The mean FRE over all landmarks was 1.37±1.81mm. FRE increased with IRE. Mean FRE of 0.86, 0.86, 1.53, 3.38, 4.45, 7.58mm was observed for IRE in the ranges 0–5, 5–10, 10–15, 15–20, 20–25, >25 mm. Higher FRE was observed at the inferior lung, where IRE was greater. Out-of-plane motion contributed more to IRE, and therefore to FRE. Maximum FRE of 20.6mm was observed for IRE of 32.1mm, located at the posterior of the middle lobe for dataset 2. Sub-voxel registration accuracy was achieved for up to 10mm IRE, and increased linearly at 0.3mm FRE/mm IRE thereafter. Conclusion: Publicly available clinical datasets enable algorithms to be compared objectively between publications. However, only reporting average TRE after registration can be misleading as the ability of an algorithm to correct for displacements varies with the IRE or position within the patient. Consequently, algorithms should be characterized using the entire range of initial displacements. For the algorithm assessed, clinically acceptable error within one voxel was achieved for IRE of up to 15mm. TK, AL, and MG are employees of Mirada Medical.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

MO-C-17A-03: A GPU-Based Method for Validating Deformable Image Registration in Head and Neck Radiotherapy Using Biomechanical Modeling

Purpose: Deformable image registration (DIR) plays a pivotal role in head and neck adaptive radiotherapy but a systematic validation of DIR algorithms has been limited by a lack of quantitative high-resolution groundtruth. We address this limitation by developing a GPU-based framework that provides a systematic DIR validation by generating (a) model-guided synthetic CTs representing posture and physiological changes, and (b) model-guided landmark-based validation. Method: The GPU-based framework was developed to generate massive mass-spring biomechanical models from patient simulation CTs and contoured structures. The biomechanical model represented soft tissue deformations for known rigid skeletal motion. Posture changes were simulated by articulating skeletal anatomy, which subsequently applied elastic corrective forces upon the soft tissue. Physiological changes such as tumor regression and weight loss were simulated in a biomechanically precise manner. Synthetic CT data was then generated from the deformed anatomy. The initial and final positions for one hundred randomly-chosen mass elements inside each of the internal contoured structures were recorded as ground truth data. The process was automated to create 45 synthetic CT datasets for a given patient CT. For instance, the head rotation was varied between +/− 4 degrees along each axis, and tumor volumes were systematically reduced up to 30%. Finally, the original CT and deformed synthetic CT were registered using an optical flow based DIR. Results: Each synthetic data creation took approximately 28 seconds of computation time. The number of landmarks per data set varied between two and three thousand. The validation method is able to perform sub-voxel analysis of the DIR, and report the results by structure, giving a much more in depth investigation of the error. Conclusions: We presented a GPU based high-resolution biomechanical head and neck model to validate DIR algorithms by generating CT equivalent 3D volumes with simulated posture changes and physiological regression.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

MO-G-18C-03: Evaluation of Deformable Image Registration for Lung Motion Estimation Using Hyperpolarized Gas Tagging MRI

Purpose: Hyperpolarized gas (HP) tagging MRI is a novel imaging technique for direct measurement of lung motion during breathing. This study aims to quantitatively evaluate the accuracy of deformable image registration (DIR) in lung motion estimation using HP tagging MRI as references. Methods: Three healthy subjects were imaged using the HP MR tagging, as well as a high-resolution 3D proton MR sequence (TrueFISP) at the end-of-inhalation (EOI) and the end-of-exhalation (EOE). Ground truth of lung motion and corresponding displacement vector field (tDVF) was derived from HP tagging MRI by manually tracking the displacement of tagging grids between EOI and EOE. Seven different DIR methods were applied to the high-resolution TrueFISP MR images (EOI and EOE) to generate the DIR-based DVFs (dDVF). The DIR methods include Velocity (VEL), MIM, Mirada, multi-grid B-spline from Elastix (MGB) and 3 other algorithms from DIRART toolbox (Double Force Demons (DFD), Improved Lucas-Kanade (ILK), and Iterative Optical Flow (IOF)). All registrations were performed by independent experts. Target registration error (TRE) was calculated as tDVF – dDVF. Analysis was performed for the entire lungs, and separately for the upper and lower lungs. Results: Significant differences between tDVF and dDVF were observed. Besides the DFD and IOF algorithms, all other dDVFs showed similarity in deformation magnitude distribution but away from the ground truth. The average TRE for entire lung ranged 2.5−23.7mm (mean=8.8mm), depending on the DIR method and subject's breathing amplitude. Larger TRE (13.3–23.7mm) was found in subject with larger breathing amplitude of 45.6mm. TRE was greater in lower lung (2.5−33.9 mm, mean=12.4mm) than that in upper lung (2.5−11.9 mm, mean=5.8mm). Conclusion: Significant differences were observed in lung motion estimation between the HP gas tagging MRI method and the DIR methods, especially when lung motion is large. Large variation among different DIR methods was also observed.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

TU-F-BRF-07: Accuracy of Routine Treatment Planning 4D and DIBH CT Delineation of the Left Anterior Descending Artery in Radiotherapy

Purpose: To assess the feasibility of routine treatment planning 4DCT and deep inspiration breath-hold (DIBH) to accurately contour the left anterior descending artery (LAD), a primary indicator of cardiac toxicity, for radiotherapy treatment planning of breast cancer. Methods: Ten subjects were imaged with a cardiac-gated MRI protocol to determine the displacement of a ROI that included the LAD. The subjects performed a series of breath-hold maneuvers to obtain short-axis and radial views, which were resampled to create a 3D-volume. Tissue motion was determined using a multi-resolution 3D optical flow deformable image registration algorithm. The ROI motion was then used as a spatial boundary to characterize the blurring motion of the LAD in ten patients during clinical 4DCT and DIBH protocols. A radiologist contoured the LAD. Coronary motion-induced blurring artifacts were quantified by applying an unsharp filter to accentuate the LAD despite motion-blurring. The 4DCT maximum inhalation and exhalation respiratory phases were co-registered to determine the LAD displacement during tidal respiration, as visualized in 4DCT. Results: The average 90{sup th} percentile heart motion for the ROI was 0.7±0.1mm(LR), 1.3±0.6mm(SI), 0.6±0.2mm(AP) in the cardiac-gated MRI cohort. The average relative increase in the number of voxels comprising the LAD contour was 69.4±4.5% for the DIBH. During tidal respiration, the average relative increase in the LAD contour was 69.3±5.9% and 67.9±4.6% for inhalation and exhalation respiratory phases respectively. The average 90{sup th} percentile LAD motion was 4.8±1.1mm(LR), 0.9±0.4mm(SI), 1.9±0.6mm(AP) for the 4DCT cohort, in the absence of cardiac-gating. Conclusion: Uncompensated coronary motion was the dominant form of motion blurring present in the CT images due to the high frequency of the cardiac cycle relative to the respiratory cycle. The 4D and DIBH CT contour delineation of the LAD was consistently overestimated without cardiac-gating, which could have led to inaccurate dose volume histogram indicators in clinical practice.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

A framework for the correction of slow physiological drifts during MR-guided HIFU therapies: Proof of concept

Purpose: While respiratory motion compensation for magnetic resonance (MR)-guided high intensity focused ultrasound (HIFU) interventions has been extensively studied, the influence of slow physiological motion due to, for example, peristaltic activity, has so far been largely neglected. During lengthy interventions, the magnitude of the latter can exceed acceptable therapeutic margins. The goal of the present study is to exploit the episodic workflow of these therapies to implement a motion correction strategy for slow varying drifts of the target area and organs at risk over the entire duration of the intervention. Methods: The therapeutic workflow of a MR-guided HIFU intervention is in practice often episodic: Bursts of energy delivery are interleaved with periods of inactivity, allowing the effects of the beam on healthy tissues to recede and/or during which the plan of the intervention is reoptimized. These periods usually last for at least several minutes. It is at this time scale that organ drifts due to slow physiological motion become significant. In order to capture these drifts, the authors propose the integration of 3D MR scans in the therapy workflow during the inactivity intervals. Displacements were estimated using an optical flow algorithm applied on the 3D acquired images. A preliminary study was conducted on ten healthy volunteers. For each volunteer, 3D MR images of the abdomen were acquired at regular intervals of 10 min over a total duration of 80 min. Motion analysis was restricted to the liver and kidneys. For validating the compatibility of the proposed motion correction strategy with the workflow of a MR-guided HIFU therapy, an in vivo experiment on a porcine liver was conducted. A volumetric HIFU ablation was completed over a time span of 2 h. A 3D image was acquired before the first sonication, as well as after each sonication. Results: Following the volunteer study, drifts larger than 8 mm for the liver and 5 mm for the kidneys prove that slow physiological motion can exceed acceptable therapeutic margins. In the animal experiment, motion tracking revealed an initial shift of up to 4 mm during the first 10 min and a subsequent continuous shift of ∼2 mm/h until the end of the intervention. This leads to a continuously increasing mismatch of the initial shot planning, the thermal dose measurements, and the true underlying anatomy. The estimated displacements allowed correcting the planned sonication cell cluster positions to the true target position, as well as the thermal dose estimates during the entire intervention and to correct the nonperfused volume measurement. A spatial coherence of all three is particularly important to assure a confluent ablation volume and to prevent remaining islets of viable malignant tissue. Conclusions: This study proposes a motion correction strategy for displacements resulting from slowly varying physiological motion that might occur during a MR-guided HIFU intervention. The authors have shown that such drifts can lead to a misalignment between interventional planning, energy delivery, and therapeutic validation. The presented volunteer study and in vivo experiment demonstrate both the relevance of the problem for HIFU therapies and the compatibility of the proposed motion compensation framework with the workflow of a HIFU intervention under clinical conditions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-104: Evaluation of Accuracy for Various Deformable Image Registrations with Virtual Deformation QA Software

Purpose: The accuracy of deformable image registration (DIR) has a significant dosimetric impact in radiation treatment planning. We evaluated accuracy of various DIR algorithms using virtual deformation QA software (ImSimQA, Oncology System Limited, UK). Methods: The reference image (Iref) and volume (Vref) was first generated with IMSIMQA software. We deformed Iref with axial movement of deformation point and Vref depending on the type of deformation that are the deformation1 is to increase the Vref (relaxation) and the deformation 2 is to decrease the Vref (contraction) .The deformed image (Idef) and volume (Vdef) were inversely deformed to Iref and Vref using DIR algorithms. As a Result, we acquired deformed image (Iid) and volume (Vid). The DIR algorithms were optical flow (HS, IOF) and demons (MD, FD) of the DIRART. The image similarity evaluation between Iref and Iid was calculated by Normalized Mutual Information (NMI) and Normalized Cross Correlation (NCC). The value of Dice Similarity Coefficient (DSC) was used for evaluation of volume similarity. Results: When moving distance of deformation point was 4 mm, the value of NMI was above 1.81 and NCC was above 0.99 in all DIR algorithms. Since the degree of deformation was increased, the degree of image similarity was decreased. When the Vref increased or decreased about 12%, the difference between Vref and Vid was within ±5% regardless of the type of deformation. The value of DSC was above 0.95 in deformation1 except for the MD algorithm. In case of deformation 2, that of DSC was above 0.95 in all DIR algorithms. Conclusion: The Idef and Vdef have not been completely restored to Iref and Vref and the accuracy of DIR algorithms was different depending on the degree of deformation. Hence, the performance of DIR algorithms should be verified for the desired applications.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-115: Correlation of Displacement Vector Fields Calculated by Deformable Image Registration Algorithms with Motion Parameters of CT Images with Well-Defined Targets and Controlled-Motion

Purpose: To investigate correlation of displacement vector fields (DVF) calculated by deformable image registration algorithms with motion parameters in helical axial and cone-beam CT images with motion artifacts. Methods: A mobile thorax phantom with well-known targets with different sizes that were made from water-equivalent material and inserted in foam to simulate lung lesions. The thorax phantom was imaged with helical, axial and cone-beam CT. The phantom was moved with a cyclic motion with different motion amplitudes and frequencies along the superior-inferior direction. Different deformable image registration algorithms including demons, fast demons, Horn-Shunck and iterative-optical-flow from the DIRART software were used to deform CT images for the phantom with different motion patterns. The CT images of the mobile phantom were deformed to CT images of the stationary phantom. Results: The values of displacement vectors calculated by deformable image registration algorithm correlated strongly with motion amplitude where large displacement vectors were calculated for CT images with large motion amplitudes. For example, the maximal displacement vectors were nearly equal to the motion amplitudes (5mm, 10mm or 20mm) at interfaces between the mobile targets lung tissue, while the minimal displacement vectors were nearly equal to negative the motion amplitudes. The maximal and minimal displacement vectors matched with edges of the blurred targets along the Z-axis (motion-direction), while DVF’s were small in the other directions. This indicates that the blurred edges by phantom motion were shifted largely to match with the actual target edge. These shifts were nearly equal to the motion amplitude. Conclusions: The DVF from deformable-image registration algorithms correlated well with motion amplitude of well-defined mobile targets. This can be used to extract motion parameters such as amplitude. However, as motion amplitudes increased, image artifacts increased significantly and that limited image quality and poor correlation between the motion amplitude and DVF was obtained.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-237: Real-Time 3D Anatomy Estimation From Undersampled MR Acquisitions

Recent developments made MRI guided radiotherapy feasible. Performing simultaneous imaging during fractions can provide information about changing anatomy by means of deformable image registration for either immediate plan adaptations or accurate dose accumulation on the changing anatomy. In 3D MRI, however, acquisition time is considerable and scales with resolution. Furthermore, intra-scan motion degrades image quality.In this work, we investigate the sensitivity of registration quality on imageresolution: potentially, by employing spatial undersampling, the acquisition timeof MR images for the purpose of deformable image registration can be reducedsignificantly.On a volunteer, 3D-MR imaging data was sampled in a navigator-gated manner, acquiring one axial volume (360×260×100mm{sup 3}) per 3s during exhale phase. A T1-weighted FFE sequence was used with an acquired voxel size of (2.5mm{sup 3}) for a duration of 17min. Deformation vector fields were evaluated for 100 imaging cycles with respect to the initial anatomy using deformable image registration based on optical flow. Subsequently, the imaging data was downsampled by a factor of 2, simulating a fourfold acquisition speed. Displacements of the downsampled volumes were then calculated by the same process.In kidneyliver boundaries and the region around stomach/duodenum, prominent organ drifts could be observed in both the original and the downsampled imaging data. An increasing displacement of approximately 2mm was observed for the kidney, while an area around the stomach showed sudden displacements of 4mm. Comparison of the motile points over time showed high reproducibility between the displacements of high-resolution and downsampled volumes: over a 17min acquisition, the componentwise RMS error was not more than 0.38mm.Based on the synthetic experiments, 3D nonrigid image registration shows little sensitivity to image resolution and the displacement information is preserved even when halving the resolution. This can be employed to greatly reduce image acquisition times for interventional applications in real-time. This work was funded by the SoRTS consortium, which includes the industry partners Elekta, Philips and Technolution.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-430: Feasibility Study On Using Overlap Volume Histogram to Predict the Dose Difference by Respiratory Motion

Purpose: The dose difference between three-dimensional dose (3D dose) and 4D dose which considers motion due to respiratory can be varied according to geometrical relationship between planning target volume (PTV) and organ at risk (OAR). The purpose of the study is to investigate the dose difference between 3D and 4D dose using overlap volume histogram (OVH) which is an indicator that quantify geometrical relationship between a PTV and an OAR. Methods: Five liver cancer patients who previously treated stereotactic body radiotherapy (SBRT) were investigated. Four-dimensional computed tomography (4DCT) images were acquired for all patients. ITV-based treatment planning was performed. 3D dose was calculated on the end-exhale phase image as a reference phase image. 4D dose accumulation was implemented from all phase images using dose warping technique used deformable image registration (DIR) algorithm (Horn and Schunck optical flow) in DIRART. In this study OVH was used to quantify geometrical relationship between a PTV and an OAR. OVH between a PTV and a selected OAR was generated for each patient case and compared for all cases. The dose difference between 3D and 4D dose for normal organ was calculated and compared for all cases according to OVH. Results: The 3D and 4D dose difference for OAR was analyzed using dose-volume histogram (DVH). On the basis of a specific point which corresponds to 10% of OAR volume overlapped with expanded PTV, mean dose difference was 34.56% in minimum OVH distance case and 13.36% in maximum OVH distance case. As the OVH distance increased, mean dose difference between 4D and 3D dose was decreased. Conclusion: The tendency of dose difference variation was verified according to OVH. OVH is seems to be indicator that has a potential to predict the dose difference between 4D and 3D dose. This work was supported by the Radiation Technology R&D program (No. 2013M2A2A7043498) and the Mid-career Researcher Program (2014R1A2A1A10050270) through the National Research Foundation of Korea funded by the Ministry of Science, ICT&Future Planning.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

TU-EF-304-04: A Heart Motion Model for Proton Scanned Beam Chest Radiotherapy

Purpose: To model fast-moving heart surface motion as a function of cardiac-phase in order to compensate for the lack of cardiac-gating in evaluating accurate dose to coronary structures. Methods: Ten subjects were prospectively imaged with a breath-hold, cardiac-gated MRI protocol to determine heart surface motion. Radial and planar views of the heart were resampled into a 3-dimensional volume representing one heartbeat. A multi-resolution optical flow deformable image registration algorithm determined tissue displacement during the cardiac-cycle. The surface of the heart was modeled as a thin membrane comprised of voxels perpendicular to a pencil beam scanning (PBS) beam. The membrane’s out-of-plane spatial displacement was modeled as a harmonic function with Lame’s equations. Model accuracy was assessed with the root mean squared error (RMSE). The model was applied to a cohort of six chest wall irradiation patients with PBS plans generated on phase-sorted 4DCT. Respiratory motion was separated from the cardiac motion with a previously published technique. Volumetric dose painting was simulated and dose accumulated to validate plan robustness (target coverage variation accepted within 2%). Maximum and mean heart surface dose assessed the dosimetric impact of heart and coronary artery motion. Results: Average and maximum heart surface displacements were 2.54±0.35mm and 3.6mm from the end-diastole phase to the end-systole cardiac-phase respectively. An average RMSE of 0.11±0.04 showed the model to be accurate. Observed errors were greatest between the circumflex artery and mitral valve level of the heart anatomy. Heart surface displacements correspond to a 3.6±1.0% and 5.1±2.3% dosimetric impact on the maximum and mean heart surface DVH indicators respectively. Conclusion: Although heart surface motion parallel to beam’s direction was substantial, its maximum dosimetric impact was 5.1±2.3%. Since PBS delivers low doses to coronary structures relative to photon radiotherapy, it is unknown whether this variation would be clinically significant for late effects.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

WE-AB-BRA-11: Development of Physiological-Based Virtual Thorax Phantoms for Evaluation of Deformable Image Registration

Purpose: To develop a methodology of constructing physiological-based virtual thorax phantom based on hyperpolarized (HP) gas tagging MRI for evaluating deformable image registration (DIR). Methods: Three healthy subjects were imaged at both the end-of-inhalation (EOI) and the end-of-exhalation (EOE) phases using a high-resolution (2.5mm isovoxel) 3D proton MRI, as well as a hybrid MRI which combines HP gas tagging MRI and a low-resolution (4.5mm isovoxel) proton MRI. A sparse tagging displacement vector field (tDVF) was derived from the HP gas tagging MRI by tracking the displacement of tagging grids between EOI and EOE. Using the tDVF and the high-resolution MR images, we determined the motion model of the entire thorax in the following two steps: 1) the DVF inside of lungs was estimated based on the sparse tDVF using a novel multi-step natural neighbor interpolation method; 2) the DVF outside of lungs was estimated from the DIR between the EOI and EOE images (Velocity AI). The derived motion model was then applied to the high-resolution EOI image to create a deformed EOE image, forming the virtual phantom where the motion model provides the ground truth of deformation. Five DIR methods were evaluated using the developed virtual phantom. Errors in DVF magnitude (Em) and angle (Ea) were determined and compared for each DIR method. Results: Among the five DIR methods, free form deformation produced DVF results that are most closely resembling the ground truth (Em=1.04mm, Ea=6.63°). The two DIR methods based on B-spline produced comparable results (Em=2.04mm, Ea=13.66°; and Em =2.62mm, Ea=17.67°), and the two optical-flow methods produced least accurate results (Em=7.8mm; Ea=53.04°; Em=4.45mm, Ea=31.02°). Conclusion: A methodology for constructing physiological-based virtual thorax phantom based on HP gas tagging MRI has been developed. Initial evaluation demonstrated its potential as an effective tool for robust evaluation of DIR in the lung.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-G-BRA-04: Simulation of Errors in Maximal Intensity Projection (MIP)-Based Lung Tumor Internal Target Volumes (ITV) Using Real-Time 2D MRI and Deformable Image Registration Based Lung Tumor Tracking

Purpose: To evaluate the effect of inter- and intra-fractional tumor motion on the error in four-dimensional computed tomography (4DCT) maximal intensity projection (MIP)–based lung tumor internal target volumes (ITV), using deformable image registration of real-time 2D-sagital cine-mode MRI acquired during lung SBRT treatments. Methods: Five lung tumor patients underwent free breathing SBRT treatment on the ViewRay, with dose prescribed to PTV (4DCT MIP-based ITV+3–6mm margin). Sagittal slice cine-MR images (3.5×3.5mm pixels) were acquired through the center of the tumor at 4 frames per second throughout the treatments (3–4 fractions of 21–32 minutes duration). Tumor GTVs were contoured on the first frame of the cine and tracked throughout the treatment using off-line optical-flow based deformable registration implemented on a GPU cluster. Pseudo-4DCT MIP-based ITVs were generated from MIPs of the deformed GTV contours limited to short segments of image data. All possible pseudo-4DCT MIP-based ITV volumes were generated with 1s resolution and compared to the ITV volume of the entire treatment course. Varying pseudo-4DCT durations from 10-50s were analyzed. Results: Tumors were covered in their entirety by PTV in the patients analysed here. However, pseudo-4DCT based ITV volumes were observed that were as small as 29% of the entire treatment-ITV, depending on breathing irregularity and the duration of pseudo-4DCT. With an increase in duration of pseudo-4DCT from 10–50s the minimum volume acquired from 95% of all pseudo-4DCTs increased from 62%–81% of the treatment ITV. Conclusion: A 4DCT MIP-based ITV offers a ‘snap-shot’ of breathing motion for the brief period of time the tumor is imaged on a specific day. Real time MRI over prolonged periods of time and over multiple treatment fractions shows that the accuracy of this snap-shot varies according to inter- and intra-fractional tumor motion. Further work is required to investigate the dosimetric effect of these results.

60 APPLIED LIFE SCIENCES↗