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At least 397 records · Page 22
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DOE OSTI2014

SU-D-17A-03: 5D Respiratory Motion Model Based Iterative Reconstruction Method for 4D Cone-Beam CT

Purpose: The purpose of this work is to develop a new iterative reconstruction method for 4D cone-beam CT (CBCT) based on a published time-independent 5D respiratory motion model. The proposed method will offer a single high-resolution image at a user-selected breathing phase and the 5D motion model parameters, which could be used to generate the breathing pattern during the CT acquisition. Methods: 5D respiratory motion model was proposed for accurately modeling the motion of lung and lung tumor tissues. 4D images are then parameterized by a reference image, measured breathing amplitude, breathing rate, two time-independent vector fields that describe the 5D model parameters, and a scalar field that describes the change in HU as a function of breathing amplitude. In contrast with the traditional method of reconstructing multiple temporal image phases to reduce respiratory artifact, 5D model based method simplify the problem into the reconstruction of a single reference image and the 5D motion model parameters. The reconstruction formulation of the reference image and scalar and vector fields is a nonlinear least-square optimization problem that consists of solving the reference image and fields alternately, in which the reference image is regularized with the total variation sparsity transform and the vector fields are solved through linearizations regularized by the H1 norm. 2D lung simulations were performed in this proof-of-concept study. Results: The breathing amplitude, its rate, and the corresponding scalar and vector fields were generated from a patient case. Compared with filtered backprojection method and sparsity regularized iterative method for the phase-by-phase reconstruction, the proposed 5D motion model based method yielded improved image quality. Conclusion: Based on 5D respiratory motion model, we have developed a new iterative reconstruction method for 4D CBCT that has the potential for improving image quality while providing needed on-table motion information.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-J-79: Internal Tumor Volume Motion and Volume Size Assessment Using 4D CT Lung Data

Purpose: To assess internal tumor volume change through breathing cycle and associated tumor motion using the 4DCT data. Methods: Respiration induced volume change through breathing cycle and associated motion was analyzed for nine patients that were scanned during the different respiratory phases. The examined datasets were the maximum and average intensity projections (MIP and AIP) and the 10 phases of the respiratory cycle. The internal target volume (ITV) was delineated on each of the phases and the planning target volume (PTV) was then created by adding setup margins to the ITV. Tumor motion through the phases was assessed using the acquired 4DCT dataset, which was then used to determine if the margins used for the ITV creation successfully encompassed the tumor in three dimensions. Results: Results showed that GTV motion along the superior inferior axes was the largest in all the cases independent of the tumor location and/or size or the use of abdomen compression. The extent of the tumor motion was found to be connected with the size of the GTV. The smallest GTVs exhibited largest motion vector independent of the tumor location. The motion vector size varied through the phases depending on the tumor size and location and it was smallest for phases 20 and 30. The smaller the volume of the delineated GTV, the greater its volume difference through the different respiratory phases was. The average GTV volume change was largest for the phases 60 and 70. Conclusion: Even if GTV is delineated using both AIP and MIP datasets, its motion extent will exceed the used margins especially for the very small GTV volumes. When the GTV size is less than 10 cc it is recommended to use fusion of the GTVs through all the phases to create the planning ITV.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-T-452: Impact of Respiratory Motion On Robustly-Optimized Intensity-Modulated Proton Therapy to Treat Lung Cancers

Purpose: We compared conventionally optimized intensity-modulated proton therapy (IMPT) treatment plans against the worst-case robustly optimized treatment plans for lung cancer. The comparison of the two IMPT optimization strategies focused on the resulting plans' ability to retain dose objectives under the influence of patient set-up, inherent proton range uncertainty, and dose perturbation caused by respiratory motion. Methods: For each of the 9 lung cancer cases two treatment plans were created accounting for treatment uncertainties in two different ways: the first used the conventional Method: delivery of prescribed dose to the planning target volume (PTV) that is geometrically expanded from the internal target volume (ITV). The second employed the worst-case robust optimization scheme that addressed set-up and range uncertainties through beamlet optimization. The plan optimality and plan robustness were calculated and compared. Furthermore, the effects on dose distributions of the changes in patient anatomy due to respiratory motion was investigated for both strategies by comparing the corresponding plan evaluation metrics at the end-inspiration and end-expiration phase and absolute differences between these phases. The mean plan evaluation metrics of the two groups were compared using two-sided paired t-tests. Results: Without respiratory motion considered, we affirmed that worst-case robust optimization is superior to PTV-based conventional optimization in terms of plan robustness and optimality. With respiratory motion considered, robust optimization still leads to more robust dose distributions to respiratory motion for targets and comparable or even better plan optimality [D95% ITV: 96.6% versus 96.1% (p=0.26), D5% - D95% ITV: 10.0% versus 12.3% (p=0.082), D1% spinal cord: 31.8% versus 36.5% (p =0.035)]. Conclusion: Worst-case robust optimization led to superior solutions for lung IMPT. Despite of the fact that robust optimization did not explicitly account for respiratory motion it produced motion-resistant treatment plans. However, further research is needed to incorporate respiratory motion into IMPT robust optimization.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

TH-E-17A-04: Geometric Validation of K-Space Self-Gated 4D-MRI Vs. 4D-CT Using A Respiratory Motion Phantom

Purpose: 4D-CT is often limited by motion artifacts, low temporal resolution, and poor phase-based target definition. We recently developed a novel k-space self-gated 4D-MRI technique with high spatial and temporal resolution. The goal here is to geometrically validate 4D-MRI using a MRI-CT compatible respiratory motion phantom and comparison to 4D-CT. Methods: 4D-MRI was acquired using 3T spoiled gradient echo-based 3D projection sequences. Respiratory phases were resolved using self-gated k-space lines as the motion surrogate. Images were reconstructed into 10 temporal bins with 1.56×1.56×1.56mm3. A MRI-CT compatible phantom was designed with a 23mm diameter ball target filled with highconcentration gadolinium(Gd) gel embedded in a 35×40×63mm3 plastic box stabilized with low-concentration Gd gel. The whole phantom was driven by an air pump. Human respiratory motion was mimicked using the controller from a commercial dynamic phantom (RSD). Four breathing settings (rates/depths: 10s/20mm, 6s/15mm, 4s/10mm, 3s/7mm) were scanned with 4D-MRI and 4D-CT (slice thickness 1.25mm). Motion ground-truth was obtained from input signals and real-time video recordings. Reconstructed images were imported into Eclipse(Varian) for target contouring. Volumes and target positions were compared with ground-truth. Initial human study was investigated on a liver patient. Results: 4D-MRI and 4D-CT scans for the different breathing cycles were reconstructed with 10 phases. Target volume in each phase was measured for both 4D-CT and 4D-MRI. Volume percentage difference for the 6.37ml target ranged from 6.67±5.33 to 11.63±5.57 for 4D-CT and from 1.47±0.52 to 2.12±1.60 for 4D-MRI. The Mann-Whitney U-test shows the 4D-MRI is significantly superior to 4D-CT (p=0.021) for phase-based target definition. Centroid motion error ranges were 1.35–1.25mm (4D-CT), and 0.31–0.12mm (4D-MRI). Conclusion: The k-space self-gated 4D-MRI we recently developed can accurately determine phase-based target volume while avoiding typical motion artifacts found in 4D-CT, and is being further studied for use in GI targeting and motion management. This work supported in part by grant 1R03CA173273-01.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Motion tracking in the liver: Validation of a method based on 4D ultrasound using a nonrigid registration technique

Purpose: Treatments like radiotherapy and focused ultrasound in the abdomen require accurate motion tracking, in order to optimize dosage delivery to the target and minimize damage to critical structures and healthy tissues around the target. 4D ultrasound is a promising modality for motion tracking during such treatments. In this study, the authors evaluate the accuracy of motion tracking in the liver based on deformable registration of 4D ultrasound images. Methods: The offline analysis was performed using a nonrigid registration algorithm that was specifically designed for motion estimation from dynamic imaging data. The method registers the entire 4D image data sequence in a groupwise optimization fashion, thus avoiding a bias toward a specifically chosen reference time point. Three healthy volunteers were scanned over several breathing cycles (12 s) from three different positions and angles on the abdomen; a total of nine 4D scans for the three volunteers. Well-defined anatomic landmarks were manually annotated in all 96 time frames for assessment of the automatic algorithm. The error of the automatic motion estimation method was compared with interobserver variability. The authors also performed experiments to investigate the influence of parameters defining the deformation field flexibility and evaluated how well the method performed with a lower temporal resolution in order to establish the minimum frame rate required for accurate motion estimation. Results: The registration method estimated liver motion with an error of 1 mm (75% percentile over all datasets), which was lower than the interobserver variability of 1.4 mm. The results were only slightly dependent on the degrees of freedom of the deformation model. The registration error increased to 2.8 mm with an eight times lower temporal resolution. Conclusions: The authors conclude that the methodology was able to accurately track the motion of the liver in the 4D ultrasound data. The authors believe that the method has potential in interventions on moving abdominal organs such as MR or ultrasound guided focused ultrasound therapy and radiotherapy, pending the method is enabled to run in real-time. The data and the annotations used for this study are made publicly available for those who would like to test other methods on 4D liver ultrasound data.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-D-210-06: Feasibility for Monitoring the Head of the Pancreas Motion Through a Surrogate Using Ultrasound During Radiation Therapy Delivery

Purpose: Substantial target motion during the delivery of radiation therapy (RT) for pancreatic cancer is well recognized as a major limiting factor on RT effectiveness. The aim of this work is to monitor intra-fractional motion of the pancreas using ultrasound during RT delivery. Methods: Transabdominal Ultrasound B-mode images were collected from 5 volunteers using a research version of the Clarity Autoscan System (Elekta). The autoscan transducer with center frequency of 5 MHz was utilized for the scans. Imaging parameters were adjusted to acquire images at the desired depth with good contrast and a wide sweep angle. Since well-defined boundaries of the pancreas can be difficult to find on ultrasound B-mode images, the portal vein was selected as a surrogate for motion estimation of the head of the pancreas. The selection was due to its anatomical location posterior to the neck of the pancreas and close proximity to the pancreas head. The portal vein was contoured on the ultrasound images acquired during simulation using the Clarity Research AFC Workstation software. Volunteers were set up in a similar manner to the simulation for their monitoring session and the ultrasound transducer was mounted on an arm fixed to the couch. A video segment of the portal vein motion was captured. Results: The portal vein was visualized and segmented. Successful monitoring sessions of the portal vein were observed. In addition, our results showed that the ultrasound transducer itself reduces breathing related motion. This is analogous to the use of a compression plate to suppress respiration motion during thorax or abdominal irradiation. Conclusion: We demonstrate the feasibility of tracking the pancreas through the localization of the portal vein using abdominal ultrasound. This will allow for real-time tracking of the intra-fractional motion to justify PTV-margin and to account for unusual motions, thus, improving normal tissue sparing. This research was funding in part by Elekta Inc.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-P-13: Quantifying the Geometric Error Due to Irregular Motion in Four-Dimensional Computed Tomography (4DCT)

Purpose: Respiratory correlated 4DCT images are generated under the assumption of a regular breathing cycle. This study evaluates the error in 4DCT-based target position estimation in the presence of irregular respiratory motion. Methods: A custom-made programmable externally-and internally-deformable lung motion phantom was placed inside the CT bore. An abdominal pressure belt was placed around the phantom to mimic clinical 4DCT acquisitio and the motion platform was programmed with a sinusoidal (±10mm, 10 cycles per minute) motion trace and 7 motion traces recorded from lung cancer patients. The same setup and motion trajectories were repeated in the linac room and kV fluoroscopic images were acquired using the on-board imager. Positions of 4 internal markers segmented from the 4DCT volumes were overlaid upon the motion trajectories derived from the fluoroscopic time series to calculate the difference between estimated (4DCT) and “actual” (kV fluoro) positions. Results: With a sinusoidal trace, absolute errors of the 4DCT estimated markers positions vary between 0.78mm and 5.4mm and RMS errors are between 0.38mm to 1.7mm. With irregular patient traces, absolute errors of the 4DCT estimated markers positions increased significantly by 100 to 200 percent, while the corresponding RMS error values have much smaller changes. Significant mismatches were frequently found at peak-inhale or peak-exhale phase. Conclusion: As expected, under conditions of well-behaved, periodic sinusoidal motion, the 4DCT yielded much better estimation of marker positions. When an actual patient trace is used 4DCT-derived positions showed significant mismatches with the fluoroscopic trajectories, indicating the potential for geometric and therefore dosimetric errors in the presence of cycle-to-cycle respiratory variations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-I-80: Quantification of Respiratory and Cardiac Motion Effect in SPECT Acquisitions Using Anthropomorphic Models: A Monte Carlo Simulation Study

Purpose: The purpose of the present study was to quantify, evaluate the impact of cardiac and respiratory motion on clinical nuclear imaging protocols. Common SPECT and scintigraphic scans are studied using Monte Carlo (MC) simulations, comparing the resulted images with and without motion. Methods: Realistic simulations were executed using the GATE toolkit and the XCAT anthropomorphic phantom as a reference model for human anatomy. Three different radiopharmaceuticals based on 99mTc were studied, namely 99mTc-MDP, 99mTc—N—DBODC and 99mTc—DTPA-aerosol for bone, myocardium and lung scanning respectively. The resolution of the phantom was set to 3.5 mm{sup 3}. The impact of the motion on spatial resolution was quantified using a sphere with 3.5 mm diameter and 10 separate time frames, in the ECAM modeled SPECT scanner. Finally, respiratory motion impact on resolution and imaging of lung lesions was investigated. The MLEM algorithm was used for data reconstruction, while the literature derived biodistributions of the pharmaceuticals were used as activity maps in the simulations. Results: FWHM was extracted for a static and a moving sphere which was ∼23 cm away from the entrance of the SPECT head. The difference in the FWHM was 20% between the two simulations. Profiles in thorax were compared in the case of bone scintigraphy, showing displacement and blurring of the bones when respiratory motion was inserted in the simulation. Large discrepancies were noticed in the case of myocardium imaging when cardiac motion was incorporated during the SPECT acquisition. Finally the borders of the lungs are blurred when respiratory motion is included resulting to a dislocation of ∼2.5 cm. Conclusion: As we move to individualized imaging and therapy procedures, quantitative and qualitative imaging is of high importance in nuclear diagnosis. MC simulations combined with anthropomorphic digital phantoms can provide an accurate tool for applications like motion correction techniques’ optimization. This research has been co-funded by the European Union (European Social Fund) and Greek national resources under the framework of the ‘Archimedes III: Funding of Research Groups in TEI of Athens’ project of the ‘Education & Lifelong Learning’ Operational Programme.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-191: Motion Prediction Using Extreme Learning Machine in Image Guided Radiotherapy

Purpose: Real-time motion tracking is a critical issue in image guided radiotherapy due to the time latency caused by image processing and system response. It is of great necessity to fast and accurately predict the future position of the respiratory motion and the tumor location. Methods: The prediction of respiratory position was done based on the positioning and tracking module in ARTS-IGRT system which was developed by FDS Team (www.fds.org.cn). An approach involving with the extreme learning machine (ELM) was adopted to predict the future respiratory position as well as the tumor’s location by training the past trajectories. For the training process, a feed-forward neural network with one single hidden layer was used for the learning. First, the number of hidden nodes was figured out for the single layered feed forward network (SLFN). Then the input weights and hidden layer biases of the SLFN were randomly assigned to calculate the hidden neuron output matrix. Finally, the predicted movement were obtained by applying the output weights and compared with the actual movement. Breathing movement acquired from the external infrared markers was used to test the prediction accuracy. And the implanted marker movement for the prostate cancer was used to test the implementation of the tumor motion prediction. Results: The accuracy of the predicted motion and the actual motion was tested. Five volunteers with different breathing patterns were tested. The average prediction time was 0.281s. And the standard deviation of prediction accuracy was 0.002 for the respiratory motion and 0.001 for the tumor motion. Conclusion: The extreme learning machine method can provide an accurate and fast prediction of the respiratory motion and the tumor location and therefore can meet the requirements of real-time tumor-tracking in image guided radiotherapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-562: Motion Tracking Optimization for Conformal Arc Radiotherapy Plans: A QUASAR Phantom Based Study

Purpose: This study is to use plan parameters optimization (Dose rate, collimator angle, couch angle, initial starting phase) to improve the performance of conformal arc radiotherapy plans with motion tracking by increasing the plan performance score (PPS). Methods: Two types of 3D conformal arc plans were created based on QUASAR respiratory motion phantom with spherical and cylindrical targets. Sinusoidal model was applied to the MLC leaves to generate motion tracking plans. A MATLAB program was developed to calculate PPS of each plan (ranges from 0–1) and optimize plan parameters. We first selected the dose rate for motion tracking plans and then used simulated annealing algorithm to search for the combination of the other parameters that resulted in the plan of the maximal PPS. The optimized motion tracking plan was delivered by Varian Truebeam Linac. In-room cameras and stopwatch were used for starting phase selection and synchronization between phantom motion and plan delivery. Gaf-EBT2 dosimetry films were used to measure the dose delivered to the target in QUASAR phantom. Dose profiles and Truebeam trajectory log files were used for plan delivery performance evaluation. Results: For spherical target, the maximal PPS (PPSsph) of the optimized plan was 0.79: (Dose rate: 500MU/min, Collimator: 90°, Couch: +10°, starting phase: 0.83π). For cylindrical target, the maximal PPScyl was 0.75 (Dose rate: 300MU/min, Collimator: 87°, starting phase: 0.97π) with couch at 0°. Differences of dose profiles between motion tracking plans (with the maximal and the minimal PPS) and 3D conformal plans were as follows: PPSsph=0.79: %ΔFWHM: 8.9%, %Dmax: 3.1%; PPSsph=0.52: %ΔFWHM: 10.4%, %Dmax: 6.1%. PPScyl=0.75: %ΔFWHM: 4.7%, %Dmax: 3.6%; PPScyl=0.42: %ΔFWHM: 12.5%, %Dmax: 9.6%. Conclusion: By achieving high plan performance score through parameters optimization, we can improve target dose conformity of motion tracking plan by decreasing total MLC leaf travel distance and leaf speed.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2015

MO-DE-210-05: Improved Accuracy of Liver Feature Motion Estimation in B-Mode Ultrasound for Image-Guided Radiation Therapy

Purpose: In similarity-measure based motion estimation incremental tracking (or template update) is challenging due to quantization, bias and accumulation of tracking errors. A method is presented which aims to improve the accuracy of incrementally tracked liver feature motion in long ultrasound sequences. Methods: Liver ultrasound data from five healthy volunteers under free breathing were used (15 to 17 Hz imaging rate, 2.9 to 5.5 minutes in length). A normalised cross-correlation template matching algorithm was implemented to estimate tissue motion. Blood vessel motion was manually annotated for comparison with three tracking code implementations: (i) naive incremental tracking (IT), (ii) IT plus a similarity threshold (ST) template-update method and (iii) ST coupled with a prediction-based state observer, known as the alpha-beta filter (ABST). Results: The ABST method produced substantial improvements in vessel tracking accuracy for two-dimensional vessel motion ranging from 7.9 mm to 40.4 mm (with mean respiratory period: 4.0 ± 1.1 s). The mean and 95% tracking errors were 1.6 mm and 1.4 mm, respectively (compared to 6.2 mm and 9.1 mm, respectively for naive incremental tracking). Conclusions: High confidence in the output motion estimation data is required for ultrasound-based motion estimation for radiation therapy beam tracking and gating. The method presented has potential for monitoring liver vessel translational motion in high frame rate B-mode data with the required accuracy. This work is support by Cancer Research UK Programme Grant C33589/A19727.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Lung motion estimation using dynamic point shifting: An innovative model based on a robust point matching algorithm

Purpose: Image-guided radiotherapy is an advanced 4D radiotherapy technique that has been developed in recent years. However, respiratory motion causes significant uncertainties in image-guided radiotherapy procedures. To address these issues, an innovative lung motion estimation model based on a robust point matching is proposed in this paper. Methods: An innovative robust point matching algorithm using dynamic point shifting is proposed to estimate patient-specific lung motion during free breathing from 4D computed tomography data. The correspondence of the landmark points is determined from the Euclidean distance between the landmark points and the similarity between the local images that are centered at points at the same time. To ensure that the points in the source image correspond to the points in the target image during other phases, the virtual target points are first created and shifted based on the similarity between the local image centered at the source point and the local image centered at the virtual target point. Second, the target points are shifted by the constrained inverse function mapping the target points to the virtual target points. The source point set and shifted target point set are used to estimate the transformation function between the source image and target image. Results: The performances of the authors’ method are evaluated on two publicly available DIR-lab and POPI-model lung datasets. For computing target registration errors on 750 landmark points in six phases of the DIR-lab dataset and 37 landmark points in ten phases of the POPI-model dataset, the mean and standard deviation by the authors’ method are 1.11 and 1.11 mm, but they are 2.33 and 2.32 mm without considering image intensity, and 1.17 and 1.19 mm with sliding conditions. For the two phases of maximum inhalation and maximum exhalation in the DIR-lab dataset with 300 landmark points of each case, the mean and standard deviation of target registration errors on the 3000 landmark points of ten cases by the authors’ method are 1.21 and 1.04 mm. In the EMPIRE10 lung registration challenge, the authors’ method ranks 24 of 39. According to the index of the maximum shear stretch, the authors’ method is also efficient to describe the discontinuous motion at the lung boundaries. Conclusions: By establishing the correspondence of the landmark points in the source phase and the other target phases combining shape matching and image intensity matching together, the mismatching issue in the robust point matching algorithm is adequately addressed. The target registration errors are statistically reduced by shifting the virtual target points and target points. The authors’ method with consideration of sliding conditions can effectively estimate the discontinuous motion, and the estimated motion is natural. The primary limitation of the proposed method is that the temporal constraints of the trajectories of voxels are not introduced into the motion model. However, the proposed method provides satisfactory motion information, which results in precise tumor coverage by the radiation dose during radiotherapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Temporal regularization of ultrasound-based liver motion estimation for image-guided radiation therapy

Purpose: Ultrasound-based motion estimation is an expanding subfield of image-guided radiation therapy. Although ultrasound can detect tissue motion that is a fraction of a millimeter, its accuracy is variable. For controlling linear accelerator tracking and gating, ultrasound motion estimates must remain highly accurate throughout the imaging sequence. This study presents a temporal regularization method for correlation-based template matching which aims to improve the accuracy of motion estimates. Methods: Liver ultrasound sequences (15–23 Hz imaging rate, 2.5–5.5 min length) from ten healthy volunteers under free breathing were used. Anatomical features (blood vessels) in each sequence were manually annotated for comparison with normalized cross-correlation based template matching. Five sequences from a Siemens Acuson™ scanner were used for algorithm development (training set). Results from incremental tracking (IT) were compared with a temporal regularization method, which included a highly specific similarity metric and state observer, known as the α–β filter/similarity threshold (ABST). A further five sequences from an Elekta Clarity™ system were used for validation, without alteration of the tracking algorithm (validation set). Results: Overall, the ABST method produced marked improvements in vessel tracking accuracy. For the training set, the mean and 95th percentile (95%) errors (defined as the difference from manual annotations) were 1.6 and 1.4 mm, respectively (compared to 6.2 and 9.1 mm, respectively, for IT). For each sequence, the use of the state observer leads to improvement in the 95% error. For the validation set, the mean and 95% errors for the ABST method were 0.8 and 1.5 mm, respectively. Conclusions: Ultrasound-based motion estimation has potential to monitor liver translation over long time periods with high accuracy. Nonrigid motion (strain) and the quality of the ultrasound data are likely to have an impact on tracking performance. A future study will investigate spatial uniformity of motion and its effect on the motion estimation errors.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

SU-F-J-80: Deformable Image Registration for Residual Organ Motion Estimation in Respiratory Gated Treatments with Scanned Carbon Ion Beams

Purpose: At the Centro Nazionale di Adroterapia Oncologica (CNAO, Pavia, Italy) C-ions respiratory gated treatments of patients with abdominal tumours started in 2014. In these cases, the therapeutic dose is delivered around end-exhale. We propose the use of a respiratory motion model to evaluate residual tumour motion. Such a model requires motion fields obtained from deformable image registration (DIR) between 4DCT phases, estimating anatomical motion through interpolation. The aim of this work is to identify the optimal DIR technique to be integrated in the modeling pipeline. Methods: We used 4DCT datasets from 4 patients to test 4 DIR algorithms: Bspline, demons, log-domain and symmetric log domain diffeomorphic demons. We evaluate DIR performance in terms of registration accuracy (RMSE between registered images) and anatomical consistency of the motion field (Jacobian) when registering end-inhale to end-exhale. We subsequently employed the model to estimate the tumour trajectory within the ideal gating window. Results: Within the liver contour, the RMSE is in the range 31–46 HU for the best performing algorithm (Bspline) and 43–145 HU for the worst one (demons). The Jacobians featured zero negative voxels (which indicate singularities in the motion field) for the Bspline fields in 3 of 4 patients, whereas diffeomorphic demons fields showed a non-null number of negative voxels in every case. GTV motion in the gating window measured less than 7 mm for every patient, displaying a predominant superior-inferior (SI) component. Conclusion: The Bspline algorithm allows for acceptable DIR results in the abdominal region, exhibiting the property of anatomical consistency of the computed field. Computed trajectories are in agreement with clinical expectations (small and prevalent SI displacements), since patients lie wearing semi-rigid immobilizing masks. In future, the model could be used for retrospective estimation of organ motion during treatment, as guided by the breathing surrogate signal.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-J-158: Respiratory Motion Resolved, Self-Gated 4D-MRI Using Rotating Cartesian K-Space Sampling

Purpose: Dynamic MRI has been used to quantify respiratory motion of abdominal organs in radiation treatment planning. Many existing 4D-MRI methods based on 2D acquisitions suffer from limited slice resolution and additional stitching artifacts when evaluated in 3D{sup 1}. To address these issues, we developed a 4D-MRI (3D dynamic) technique with true 3D k-space encoding and respiratory motion self-gating. Methods: The 3D k-space was acquired using a Rotating Cartesian K-space (ROCK) pattern, where the Cartesian grid was reordered in a quasi-spiral fashion with each spiral arm rotated using golden angle{sup 2}. Each quasi-spiral arm started with the k-space center-line, which were used as self-gating{sup 3} signal for respiratory motion estimation. The acquired k-space data was then binned into 8 respiratory phases and the golden angle ensures a near-uniform k-space sampling in each phase. Finally, dynamic 3D images were reconstructed using the ESPIRiT technique{sup 4}. 4D-MRI was performed on 6 healthy volunteers, using the following parameters (bSSFP, Fat-Sat, TE/TR=2ms/4ms, matrix size=500×350×120, resolution=1×1×1.2mm, TA=5min, 8 respiratory phases). Supplemental 2D real-time images were acquired in 9 different planes. Dynamic locations of the diaphragm dome and left kidney were measured from both 4D and 2D images. The same protocol was also performed on a MRI-compatible motion phantom where the motion was programmed with different amplitude (10–30mm) and frequency (3–10/min). Results: High resolution 4D-MRI were obtained successfully in 5 minutes. Quantitative motion measurements from 4D-MRI agree with the ones from 2D CINE (<5% error). The 4D images are free of the stitching artifacts and their near-isotropic resolution facilitates 3D visualization and segmentation of abdominal organs such as the liver, kidney and pancreas. Conclusion: Our preliminary studies demonstrated a novel ROCK 4D-MRI technique with true 3D k-space encoding and respiratory motion self-gating. The technique leads to high-resolution and artifacts-free 4D images for improved abdominal organ motion studies. K.S acknowledges funding support from NIH R01CA188300.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-G-JeP1-06: Correlation of Lung Tumor Motion with Tumor Location Using Electromagnetic Tracking

Purpose: It is well known that lung tumors move with respiration. However, most measurements of lung tumor motion have studied long treatment times with intermittent imaging; those populations may not necessarily represent conventional LINAC patients. We summarized the correlation between tumor motion and location in a multi-institutional trial with electromagnetic tracking, and identified the patient cohort that would most benefit from respiratory gating. Methods: Continuous electromagnetic transponder data (Varian Medical, Seattle, WA) of lung tumor motion was collected from 14 patients (214 total fractions) across 3 institutions during external beam radiation therapy in a prospective clinical trial (NCT01396551). External intervention from the clinician, such as couch shifts, instructed breath-holds, and acquisition pauses, were manually removed from the 10 Hz tracking data according to recorded notes. The average three-dimensional displacement from the breathing cycle’s end-expiratory to end-inhalation phases (peak-to-peak distance) of the transponders’ isocenter was calculated for each patient’s treatment. A weighted average of each isocenter was used to assess the effects of location on motion. A total of 14 patients were included in this analysis, grouped by their transponders’ location in the lung: upper, medial, and lower. Results: 8 patients had transponders in the upper lung, and 3 patients each in the medial lobe and lower lung. The weighted average ± standard deviation of all peak-to-peak distances for each group was: 1.04 ± 0.39 cm in the lower lung, 0.56 ± 0.14 cm in the medial lung, and 0.30 ± 0.06 cm in the upper lung. Conclusion: Tumors in the lower lung are most susceptible to excessive motion and daily variation, and would benefit most from continuous motion tracking and gating. Those in the medial lobe might be at moderate risk. The upper lobes have limited motion. These results can guide different motion management strategies between lung tumor locations. This is part of an NIH-funded prospective clinical trial (NCT01396551), using an electromagnetic transponder tracking system and additional funding from Varian Medical (Seattle, WA).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-G-JeP4-12: Real-Time Organ Motion Monitoring Using Ultrasound and KV Fluoroscopy During Lung SBRT Delivery

Purpose: Real-time ultrasound monitoring during SBRT is advantageous in understanding and identifying motion irregularities which may cause geometric misses. In this work, we propose to utilize real-time ultrasound to track the diaphragm in conjunction with periodical kV fluoroscopy to monitor motion of tumor or landmarks during SBRT delivery. Methods: Transabdominal Ultrasound (TAUS) b-mode images were collected from 10 healthy volunteers using the Clarity Autoscan System (Elekta). The autoscan transducer, which has a center frequency of 5 MHz, was utilized for the scans. The acquired images were contoured using the Clarity Automatic Fusion and Contouring workstation software. Monitoring sessions of 5 minute length were observed and recorded. The position correlation between tumor and diaphragm could be established with periodic kV fluoroscopy periodically acquired during treatment with Elekta XVI. We acquired data using a tissue mimicking ultrasound phantom with embedded spheres placed on a motion stand using ultrasound and kV Fluoroscopy. MIM software was utilized for image fusion. Correlation of diaphragm and target motion was also validated using 4D-MRI and 4D-CBCT. Results: The diaphragm was visualized as a hyperechoic region on the TAUS b-mode images. Volunteer set-up can be adjusted such that TAUS probe will not interfere with treatment beams. A segment of the diaphragm was contoured and selected as our tracking structure. Successful monitoring sessions of the diaphragm were recorded. For some volunteers, diaphragm motion over 2 times larger than the initial motion has been observed during tracking. For the phantom study, we were able to register the 2D kV Fluoroscopy with the US images for position comparison. Conclusion: We demonstrated the feasibility of tracking the diaphragm using real-time ultrasound. Real-time tracking can help in identifying such irregularities in the respiratory motion which is correlated to tumor motion. We also showed the feasibility of acquiring 2D KV Fluoroscopy and registering the images with Ultrasound.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

WE-DE-BRA-11: A Study of Motion Tracking Accuracy of Robotic Radiosurgery Using a Novel CCD Camera Based End-To-End Test System

Purpose: A novel end-to-end test system using a CCD camera and a scintillator based phantom (XRV-124, Logos Systems Int’l) capable of measuring the beam-by-beam delivery accuracy of Robotic Radiosurgery (CyberKnife) was developed and reported in our previous work. This work investigates its application in assessing the motion tracking (Synchrony) accuracy for CyberKnife. Methods: A QA plan with Anterior and Lateral beams (with 4 different collimator sizes) was created (Multiplan v5.3) for the XRV-124 phantom. The phantom was placed on a motion platform (superior and inferior movement), and the plans were delivered on the CyberKnife M6 system using four motion patterns: static, Sine- wave, Sine with 15° phase shift, and a patient breathing pattern composed of 2cm maximum motion with 4 second breathing cycle. Under integral recording mode, the time-averaged beam vectors (X, Y, Z) were measured by the phantom and compared with static delivery. In dynamic recording mode, the beam spots were recorded at a rate of 10 frames/second. The beam vector deviation from average position was evaluated against the various breathing patterns. Results: The average beam position of the six deliveries with no motion and three deliveries with Synchrony tracking on ideal motion (sinewave without phase shift) all agree within −0.03±0.00 mm, 0.10±0.04, and 0.04±0.03 in the X, Y, and X directions. Radiation beam width (FWHM) variations are within ±0.03 mm. Dynamic video record showed submillimeter tracking stability for both regular and irregular breathing pattern; however the tracking error up to 3.5 mm was observed when a 15 degree phase shift was introduced. Conclusion: The XRV-124 system is able to provide 3D and 4D targeting accuracy for CyberKnife delivery with Synchrony. The experimental results showed sub-millimeter delivery in phantom with excellent correlation in target to breathing motion. The accuracy was degraded when irregular motion and phase shift was introduced.

60 APPLIED LIFE SCIENCES↗