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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A Sheaf Theoretical Approach to Uncertainty Quantification of Heterogeneous Geolocation Information

Integration of multiple, heterogeneous sensors is a challenging problem across a range of applications. Prominent among these are multi-target tracking, where one must combine observations from different sensor types in a meaningful and efficient way to track multiple targets. Because different sensors have differing error models, we seek a theoretically justified quantification of the agreement among ensembles of sensors, both overall for a sensor collection, and also at a fine-grained level specifying pairwise and multi-way interactions among sensors. We demonstrate that the theory of mathematical sheaves provides a unified answer to this need, supporting both quantitative and qualitative data. Furthermore, the theory provides algorithms to globalize data across the network of deployed sensors, and to diagnose issues when the data do not globalize cleanly. We demonstrate and illustrate the utility of sheaf-based tracking models based on experimental data of a wild population of black bears in Asheville, North Carolina. A measurement model involving four sensors deployed among the bears and the team of scientists charged with tracking their location is deployed. This provides a sheaf-based integration model which is small enough to fully interpret, but of sufficient complexity to demonstrate the sheaf’s ability to recover a holistic picture of the locations and behaviors of both individual bears and the bear-human tracking system. A statistical approach was developed in parallel for comparison, a dynamic linear model which was estimated using a Kalman filter. This approach also recovered bear and human locations and sensor accuracies. When the observations are normalized into a common coordinate system, the structure of the dynamic linear observation model recapitulates the structure of the sheaf model, demonstrating the canonicity of the sheaf-based approach. However, when the observations are not so normalized, the sheaf model still remains valid.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Benchmarking sensor fusion capabilities of an integrated instrumentation package

Quantifying and mitigating environmental risks introduced by marine energy conversion systems requires a variety of sensors (active acoustic, passive acoustic, and optical). The operation of these sensors must satisfy three directives to be effective: (1) do not alter the environment through operation of sensors; (2) capture rare events; and (3) do not accrue unmanageable volumes of low-value data. This requires integrating sensors into a single package, rather than operating them independently. The Adaptable Monitoring Package is an integrated instrumentation package that combines a multibeam sonar, acoustic camera, current profiler, optical cameras, and an array of hydrophones. The capabilities and limitations of the AMP sensors were benchmarked using cooperative targets, and real-time target tracking and detection was used to detect opportunistic targets (e.g., diving birds, seals). During an initial deployment, automatic detection of opportunistic targets achieved a 58% true positive rate and a 99% true negative rate (100% corresponding to an ideal system in both cases). In post-processing, target tracking data were used to evaluate automatic target classification capabilities using a k-nearest neighbor algorithm. Findings suggest that real-time target classification should be possible and enable integrated instrumentation systems to meet the monitoring needs of marine energy deployments.

16 TIDAL AND WAVE POWER↗
DOE OSTI2016

Effect of retransmission and retrodiction on estimation and fusion in long-haul sensor networks

In a long-haul sensor network, sensors are remotely deployed over a large geographical area to perform certain tasks, such as target tracking. In this work, we study the scenario where sensors take measurements of one or more dynamic targets and send state estimates of the targets to a fusion center via satellite links. The severe loss and delay inherent over the satellite channels reduce the number of estimates successfully arriving at the fusion center, thereby limiting the potential fusion gain and resulting in suboptimal accuracy performance of the fused estimates. In addition, the errors in target-sensor data association can also degrade the estimation performance. To mitigate the effect of imperfect communications on state estimation and fusion, we consider retransmission and retrodiction. The system adopts certain retransmission-based transport protocols so that lost messages can be recovered over time. Besides, retrodiction/smoothing techniques are applied so that the chances of incurring excess delay due to retransmission are greatly reduced. We analyze the extent to which retransmission and retrodiction can improve the performance of delay-sensitive target tracking tasks under variable communication loss and delay conditions. Lastly, simulation results of a ballistic target tracking application are shown in the end to demonstrate the validity of our analysis.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

Performance Tradeoffs of Spectrum Sensing and Target State Estimation and Fusion

We consider a scenario where a cognitive radio sensor performs spectrum sensing and target tracking alternately. Both tasks may impose certain performance guarantee requirements that necessitate considerations of how to schedule these tasks over time. In addition, multiple such cognitive radio sensors can perform collaborative spectrum sensing and target tracking, where a fusion center serves to collect the sensor estimates and their covariances to generate fused target state estimates. We study the performance tradeoffs of these two tasks from variable scheduling intervals. The effect of sensing errors on the target tracking performance due to induced loss from perceived channel unavailability is investigated and conclusions are drawn based on the observed performance tradeoffs.

Liu, Qiang↗
DOE OSTI2014

Multi-target camera tracking, hand-off and display LDRD 158819 final report

Modern security control rooms gather video and sensor feeds from tens to hundreds of cameras. Advanced camera analytics can detect motion from individual video streams and convert unexpected motion into alarms, but the interpretation of these alarms depends heavily upon human operators. Unfortunately, these operators can be overwhelmed when a large number of events happen simultaneously, or lulled into complacency due to frequent false alarms. This LDRD project has focused on improving video surveillance-based security systems by changing the fundamental focus from the cameras to the targets being tracked. If properly integrated, more cameras shouldn't lead to more alarms, more monitors, more operators, and increased response latency but instead should lead to better information and more rapid response times. For the course of the LDRD we have been developing algorithms that take live video imagery from multiple video cameras, identifies individual moving targets from the background imagery, and then displays the results in a single 3D interactive video. In this document we summarize the work in developing this multi-camera, multi-target system, including lessons learned, tools developed, technologies explored, and a description of current capability.

47 OTHER INSTRUMENTATION↗
DOE OSTI2014

Multi-Target Camera Tracking, Hand-off and Display LDRD 158819 Final Report

Modern security control rooms gather video and sensor feeds from tens to hundreds of cameras. Advanced camera analytics can detect motion from individual video streams and convert unexpected motion into alarms, but the interpretation of these alarms depends heavily upon human operators. Unfortunately, these operators can be overwhelmed when a large number of events happen simultaneously, or lulled into complacency due to frequent false alarms. This LDRD project has focused on improving video surveillance-based security systems by changing the fundamental focus from the cameras to the targets being tracked. If properly integrated, more cameras shouldn’t lead to more alarms, more monitors, more operators, and increased response latency but instead should lead to better information and more rapid response times. For the course of the LDRD we have been developing algorithms that take live video imagery from multiple video cameras, identify individual moving targets from the background imagery, and then display the results in a single 3D interactive video. In this document we summarize the work in developing this multi-camera, multi-target system, including lessons learned, tools developed, technologies explored, and a description of current capability.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

A Topological Approach for Motion Track Discrimination

Detecting small targets at range is difficult because there is not enough spatial information present in an image sub-region containing the target to use correlation-based methods to differentiate it from dynamic confusers present in the scene. Moreover, this lack of spatial information also disqualifies the use of most state-of-the-art deep learning image-based classifiers. Here, we use characteristics of target tracks extracted from video sequences as data from which to derive distinguishing topological features that help robustly differentiate targets of interest from confusers. In particular, we calculate persistent homology from time-delayed embeddings of dynamic statistics calculated from motion tracks extracted from a wide field-of-view video stream. In short, we use topological methods to extract features related to target motion dynamics that are useful for classification and disambiguation and show that small targets can be detected at range with high probability.

Emerson, Tegan H.↗
DOE OSTI2014

WE-G-BRF-09: Force- and Image-Adaptive Strategies for Robotised Placement of 4D Ultrasound Probes

Purpose: To allow continuous acquisition of high quality 4D ultrasound images for non-invasive live tracking of tumours for IGRT, image- and force-adaptive strategies for robotised placement of 4D ultrasound probes are developed and evaluated. Methods: The developed robotised ultrasound system is based on a 6-axes industrial robot (adept Viper s850) carrying a 4D ultrasound transducer with a mounted force-torque sensor. The force-adaptive placement strategies include probe position control using artificial potential fields and contact pressure regulation by a PD controller strategy. The basis for live target tracking is a continuous minimum contact pressure to ensure good image quality and high patient comfort. This contact pressure can be significantly disturbed by respiratory movements and has to be compensated. All measurements were performed on human subjects under realistic conditions. When performing cardiac ultrasound, rib- and lung shadows are a common source of interference and can disrupt the tracking. To ensure continuous tracking, these artefacts had to be detected to automatically realign the probe. The detection is realised by multiple algorithms based on entropy calculations as well as a determination of the image quality. Results: Through active contact pressure regulation it was possible to reduce the variance of the contact pressure by 89.79% despite respiratory motion of the chest. The results regarding the image processing clearly demonstrate the feasibility to detect image artefacts like rib shadows in real-time. Conclusion: In all cases, it was possible to stabilise the image quality by active contact pressure control and automatically detected image artefacts. This fact enables the possibility to compensate for such interferences by realigning the probe and thus continuously optimising the ultrasound images. This is a huge step towards fully automated transducer positioning and opens the possibility for stable target tracking in ultrasoundguided radiation therapy requiring contact pressure of 5–10 N. This work was supported by the Graduate School for Computing in Medicine and Life Sciences funded by Germany's Excellence Initiative [DFG GSC 235/1].

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Detection and classification capabilities of two multibeam sonars

Multibeam sonars can be used to detect and classify marine fauna under conditions when optical sensors are ineffective. In this work, we compare the detection and classification capabilities of two multibeam sonars with different operating frequencies, the Tritech Gemini 720is (720 kHz) and the Teledyne BlueView M900-2250 (2250 kHz). The two sonars were deployed with overlapping swaths in a narrow tidal channel with peak currents of approximately 2 m/s where seals, schools of fish, and diving birds were intermittently present. In comparing data concurrently acquired by both sonars, we observe differences in the appearance of detected targets and detection capabilities. The detected target tracks are classified using a random forest model as either individual biological targets (flora and fauna, including fish, diving birds, seals, and plant matter), fish schools, or nonbiological targets (including entrained air and sonar artifacts). Despite the observed differences in detection capabilities for the two sonars, automatic classification distinguishes between target classes with precision and recall above 0.7 and 0.9, respectively. Furthermore, these results suggest that while similar methodologies can be used for data analysis, some outcomes from environmental studies using multibeam sonars may be instrument-specific.

16 TIDAL AND WAVE POWER↗
DOE OSTI2014

SU-E-J-194: Dynamic Tumor Tracking End-To-End Testing Using a 4D Thorax Phantom and EBT3 Films

Purpose: To quantify the Vero linac dosimetric accuracy of the tumor dynamic tracking treatment using EBT3 film embedded in a 4D thorax phantom. Methods: A dynamic thorax phantom with tissue equivalent materials and a film insert were used in this study. The thorax phantom was scanned in 4DCT mode with a viscoil embedded in its film insert composed of lung equivalent material. Dynamic tracking planning was performed using the 50% phase CT set with 5 conformal beams at gantry angles of 330, 15, 60, 105 and 150 degrees. Each field is a 3cm by 3cm square centered at viscoil since there was no solid mass target. Total 3 different 1–2cos4 motion profiles were used with varied motion magnitude and cycle frequency. Before treatment plan irradiation, a 4D motion model of the target was established using a series of acquired fluoroscopic images and infrared markers motion positions. During irradiation, fluoroscopic image monitoring viscoil motion was performed to verify model validity. The irradiated films were scanned and the dose maps were compared to the planned Monte Carlo dose distributions. Gamma analyses using 3%–3mm, 2%–3mm, 3%–2mm, 2%–2mm criteria were performed and presented. Results: For each motion pattern, a 4D motion model was built successfully and the target tracking performance was verified with fluoroscopic monitoring of the viscoil motion and its model predicted locations. The film gamma analysis showed the average pass rates among the 3 motion profiles are 98.14%, 96.2%, 91.3% and 85.61% for 3%–3mm, 2%–3mm, 3%–2mm, 2%–2mm criteria. Conclusion: Target dynamic tracking was performed using patient-like breathing patterns in a 4D thorax phantom with EBT3 film insert and a viscoil. There was excellent agreement between acquired and planned dose distributions for all three target motion patterns. This study performed end-to-end testing and verified the treatment accuracy of tumor dynamic tracking.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Verification of Accuracy of CyberKnife Tumor-tracking Radiation Therapy Using Patient-specific Lung Phantoms

Purpose: To investigate the accuracy of the CyberKnife Xsight Lung Tracking System (XLTS) compared with that of a fiducial-based target tracking system (FTTS) using patient-specific lung phantoms. Methods and Materials: Three-dimensional printing technology was used to make individualized lung phantoms that closely mimicked the lung anatomy of actual patients. Based on planning computed tomographic data from 6 lung cancer patients who underwent stereotactic ablative radiation therapy using the CyberKnife, the volume above a certain Hounsfield unit (HU) was assigned as the structure to be filled uniformly with polylactic acid material by a 3-dimensional printer (3D Edison, Lokit, Korea). We evaluated the discrepancies between the measured and modeled target positions, representing the total tracking error, using 3 log files that were generated during each treatment for both the FTTS and the XLTS. We also analyzed the γ index between the film dose measured under the FTTS and XLTS. Results: The overall mean values and standard deviations of total tracking errors for the FTTS were 0.36 ± 0.39 mm, 0.15 ± 0.64 mm, and 0.15 ± 0.62 mm for the craniocaudal (CC), left–right (LR), and anteroposterior (AP) components, respectively. Those for the XLTS were 0.38 ± 0.54 mm, 0.13 ± 0.18 mm, and 0.14 ± 0.37 mm for the CC, LR, and AP components, respectively. The average of γ passing rates was 100% for the criteria of 3%, 3 mm; 99.6% for the criteria of 2%, 2 mm; and 86.8% for the criteria of 1%, 1 mm. Conclusions: The XLTS has segmentation accuracy comparable with that of the FTTS and small total tracking errors.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

SU-G-JeP3-08: Robotic System for Ultrasound Tracking in Radiation Therapy

Purpose: For safe and accurate real-time tracking of tumors for IGRT using 4D ultrasound, it is necessary to make use of novel, high-end force-sensitive lightweight robots designed for human-machine interaction. Such a robot will be integrated into an existing robotized ultrasound system for non-invasive 4D live tracking, using a newly developed real-time control and communication framework. Methods: The new KUKA LWR iiwa robot is used for robotized ultrasound real-time tumor tracking. Besides more precise probe contact pressure detection, this robot provides an additional 7th link, enhancing the dexterity of the kinematic and the mounted transducer. Several integrated, certified safety features create a safe environment for the patients during treatment. However, to remotely control the robot for the ultrasound application, a real-time control and communication framework has to be developed. Based on a client/server concept, client-side control commands are received and processed by a central server unit and are implemented by a client module running directly on the robot’s controller. Several special functionalities for robotized ultrasound applications are integrated and the robot can now be used for real-time control of the image quality by adjusting the transducer position, and contact pressure. The framework was evaluated looking at overall real-time capability for communication and processing of three different standard commands. Results: Due to inherent, certified safety modules, the new robot ensures a safe environment for patients during tumor tracking. Furthermore, the developed framework shows overall real-time capability with a maximum average latency of 3.6 ms (Minimum 2.5 ms; 5000 trials). Conclusion: The novel KUKA LBR iiwa robot will advance the current robotized ultrasound tracking system with important features. With the developed framework, it is now possible to remotely control this robot and use it for robotized ultrasound tracking applications, including image quality control and target tracking.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-J-156: Preclinical Inverstigation of Dynamic Tumor Tracking Using Vero SBRT Linear Accelerator: Motion Phantom Dosimetry Study

Purpose: Following the ‘end-to-end testing’ paradigm of Dynamic Target Tracking option in our Image-Guided dedicated SBRT VeroTM linac, we verify the capability of the system to deliver planned dose to moving targets in the heterogeneous thorax phantom (CIRSTM). The system includes gimbaled C-band linac head, robotic 6 degree of freedom couch and a tumor tracking method based on predictive modeling of target position using fluoroscopically tracked implanted markers and optically tracked infrared reflecting external markers. Methods: 4DCT scan of the motion phantom with the VisicoilTM implanted marker in the close vicinity of the target was acquired, the ‘exhale’=most prevalent phase was used for planning (iPlan by BrainLabTM). Typical 3D conformal SBRT treatment plans aimed to deliver 6-8Gy/fx to two types of targets: a)solid water-equivalent target 3cm in diameter; b)single VisicoilTM marker inserted within lung equivalent material. The planning GTV/CTV-to-PTV margins were 2mm, the block margins were 3 mm. The dose calculated by MonteCarlo algorithm with 1% variance using option Dose-to-water was compared to the ion chamber (CC01 by IBA Dosimetry) measurements in case (a) and GafchromicTM EBT3 film measurements in case (b). During delivery, the target 6 motion patterns available as a standard on CIRSTM motion phantom were investigated: in case (a), the target was moving along the designated sine or cosine4 3D trajectory; in case (b), the inserted marker was moving sinusoidally in 1D. Results: The ion chamber measurements have shown the agreement with the planned dose within 1% under all the studied motion conditions. The film measurements show 98.1% agreement with the planar calculated dose (gamma criteria: 3%/3mm). Conclusion: We successfully verified the capability of the SBRT VeroTM linac to perform real-time tumor tracking and accurate dose delivery to the target, based on predictive modeling of the correlation between implanted marker motion and external surrogate of breathing motion.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Projection-Based Linear Constrained Estimation and Fusion over Long-Haul Links

In this work, we study estimation and fusion with linear dynamics in long-haul sensor networks, wherein a number of sensors are remotely deployed over a large geographical area for performing tasks such as target tracking, and a remote fusion center serves to combine the information provided by these sensors in order to improve the overall tracking accuracy. In reality, the motion of a dynamic target might be subject to certain constraints, for instance, those defined by a road network. We explore the accuracy performance of projection-based constrained estimation and fusion methods that is affected by information loss over the long-haul links. We use a tracking example to compare the tracking errors under various implementations of centralized and distributed projection-based estimation and fusion methods.

Rao, Nageswara S↗
DOE OSTI2016

Projection-Based linear constrained estimation and fusion over long-haul links

We study estimation and fusion with linear dynamics in long-haul sensor networks, wherein a number of sensors are remotely deployed over a large geographical area for performing tasks such as target tracking, and a remote fusion center serves to combine the information provided by these sensors in order to improve the overall tracking accuracy. In reality, the motion of a dynamic target might be subject to certain constraints, for instance, those defined by a road network. We explore the accuracy performance of projection-based constrained estimation and fusion methods that is affected by information loss over the long-haul links. We use an example to compare the tracking errors under various implementations of centralized and distributed projection-based estimation and fusion methods and demonstrate the effectiveness of using projection-based methods in these settings.

Rao, Nageswara S↗
DOE OSTI2016

A Synchronized Sensor Array for Remote Monitoring of Avian and Bat Interactions with Offshore Renewable Energy Facilities

Wind energy production in the U.S. is projected to increase to 35% of our nation’s energy by 2050. This substantial increase in the U.S. is only a portion of the global wind industry growth, as many countries strive to reduce greenhouse gas emissions. A major environmental concern and potential market barrier for expansion of wind energy is bird and bat mortality from impacts with turbine blades, towers, and nacelles. Carcass surveys are the standard protocol for quantifying mortality at onshore sites. This method is imperfect, however, due to survey frequency at remote sites, removal of carcasses by scavengers between surveys, searcher efficiency, and other biases as well as delays of days to weeks or more in obtaining information on collision events. Furthermore, carcass surveys are not feasible at offshore wind energy sites. Near-real-time detection and quantification of interaction rates is possible at both onshore and offshore wind facilities using an onboard, integrated sensor package with data transmitted to central processing centers. We developed and experimentally tested an array of sensors that continuously monitors for interactions (including impacts) of birds and bats with wind turbines. The synchronized array includes three sensor nodes: (1) vibration (accelerometers and contact microphones), (2) optical (visual and infrared spectrum cameras), and (3) bioacoustics (acoustic and ultrasonic microphones). Accelerometers and contact acoustic microphones are placed at the root of each blade to detect impact vibrations and sound waves propagating through the structure. On-board data processing algorithms using wavelet analysis detect impact signals exceeding background vibration. Stereo-visual and infrared cameras were placed on the nacelle to allow target tracking, distance, and size calculations. On-board image processing and target detection algorithms identify moving targets within the camera field of view. Bioacoustic recorders monitor vocalizations and echolocations to aid in identifying organisms involved in interactions. Data from all sensors are temporarily stored in ring (i.e., circular) buffers with a duration varying by sensor type. Detection of target presence or impact by any of the sensors can trigger the archiving of data from all buffers for transmission to a central data processing center for evaluation and post-processing. This mitigates the risk of “data mortgages” posed by continual recording and minimizes personnel time required to manually review event data. We first conducted individual component tests at laboratories and field sites in Corvallis and Newport, Oregon, and Seattle and Sequim, Washington. We conducted additional component tests on research wind turbines at the North American Wind Research and Training Center, Mesalands Community College (MCC; General Electric 1.5 MW turbine), New Mexico, and the National Wind Technology Center, National Renewable Energy Laboratory (NREL; Controls Advanced Research Turbines 3 [CART 3] 600 kW Westinghouse turbine), Colorado. We conducted fully integrated system tests at NREL in October 2014 and April 2015. We used only research wind turbines so that we could conduct controlled, experimentally generated impacts using empty and water-filled tennis balls shot from a compressed air cannon on the ground. The approx. 57-140 g tennis balls (depending on water content) were at the upper mass range for bats, but lower mass range for marine birds. Therefore, the ability to detect collisions of most seabirds is likely greater than our experiments demonstrate, but possibly lower for some bats depending on the background signal of a given turbine. Vibration data demonstrated that background signals of operating turbines varied markedly among the CART 3 under normal operation (greatest), GE (moderate), and CART 3 during idle rotation (generator not engaged; least). In total, we measured 63 experimental blade impacts on the two research turbines. Impaction detection was dependent on background signals, position of impact on the blade (a tip strike resulted in the strongest impact signal), and impact kinetics (velocity of ball and whether the ball struck the surface of the blade or the leading edge of the blade struck the ball). Overall detection percentage ranged from 100% for the “quietest” conditions (CART 3 idle rotation), down to 35% for the noisiest (CART 3 normal operation). Impact signals were detected from sensors on more than one blade (i.e., blades other than the blade struck) 50% - 75% of the time. Stereo imaging provided valuable metrics, but increased data processing and equipment cost. Given the cost of cameras with sufficient resolution for target identification, we suggest mounting cameras directly on the blades to continuously view the entire rotor swept area with the fewest number of cameras. Bioacoustic microphones provide taxonomic identification, as well as information on ambient noise levels. They also assist in identifying environmental conditions such as hail storms, high winds, thunder, lightning, etc., that may contribute to a collision or a false positive detection. We demonstrated a proof of concept for an integrated sensor array to detect and identify bird and bat collisions with wind turbines. The next phase of research and development for this system will miniaturize and integrate sensors from all three nodes into a single wireless package that can be attached directly to the blade. This next generation system would use all “smart” sensors capable of onboard data processing to drastically reduce data streams and processing time on a central computer. A provisional patent for the blade mounted system was submitted by Oregon State University and recorded by the U.S. Patent and Trademark Office (application no. 62313028). Eventually, technology and industry advances will allow this low cost monitoring system to be designed into materials during manufacturing so that all turbines could be monitored with either a subset or full suite of sensors. As standard equipment on all commercial turbines, the sensor suite would allow the industry to effectively monitor whether individual turbines were causing mortalities or not and under what circumstances. It would also provide real-time evaluation of mechanical and structural integrity of a turbine via vibration, image, and acoustic data streams, thereby permitting modifications in operation to limit environmental or mechanical damage.

17 WIND ENERGY↗
DOE OSTI2015

SU-E-T-300: Dosimetric Comparision of 4D Radiation Therapy and 3D Radiation Therapy for the Liver Tumor Based On 4D Medical Image

Purpose: The purpose of this work was to determine the dosimetric benefit to normal tissues by tracking liver tumor dose in four dimensional radiation therapy (4DRT) on ten phases of four dimensional computer tomagraphy(4DCT) images. Methods: Target tracking each phase with the beam aperture for ten liver cancer patients were converted to cumulative plan and compared to the 3D plan with a merged target volume based on 4DCT image in radiation treatment planning system (TPS). The change in normal tissue dose was evaluated in the plan by using the parameters V5, V10, V15, V20,V25, V30, V35 and V40 (volumes receiving 5, 10, 15, 20, 25, 30, 35 and 40Gy, respectively) in the dose-volume histogram for the liver; mean dose for the following structures: liver, left kidney and right kidney; and maximum dose for the following structures: bowel, duodenum, esophagus, stomach and heart. Results: There was significant difference between 4D PTV(average 115.71cm3 )and ITV(169.86 cm3). When the planning objective is 95% volume of PTV covered by the prescription dose, the mean dose for the liver, left kidney and right kidney have an average decrease 23.13%, 49.51%, and 54.38%, respectively. The maximum dose for bowel, duodenum,esophagus, stomach and heart have an average decrease 16.77%, 28.07%, 24.28%, 4.89%, and 4.45%, respectively. Compared to 3D RT, radiation volume for the liver V5, V10, V15, V20, V25, V30, V35 and V40 by using the 4D plans have a significant decrease(P≤0.05). Conclusion: The 4D plan method creates plans that permit better sparing of the normal structures than the commonly used ITV method, which delivers the same dosimetric effects to the target.

60 APPLIED LIFE SCIENCES↗