Target Localization Accuracy Research Articles

Assessment of Brain Tumor Displacements after Skull-based Registration: A CT/MRI Fusion Study

Purpose: To assess brain tumor displacements between skull based and soft-tissue based matching during CTMRI fusion for a total of 35 brain lesions. Methods: Twenty-five patients who underwent CT and MRI scans in the same day were retrospectively recruited into the study. Semi-automatic skull based fusion was first performed and reviewed on a Treatment Planning System (TPS). A secondary fine-tuning of the fusion was then performed, if mismatch was observed in the tumor or neighboring soft-tissue, using nearby visible soft-tissue, such as gyri, sulci, and fissures. Two physicists fine-tuned the secondary fusion until the best match could be agreed upon. The resulting rotations and translations between the two fusions were recorded, which indicated local displacements between skull based and soft-tissue based matching. We further created a PTV by expanding a 2 mm margin around the GTV after skull-based fusion, and then evaluated the coverage of the GTV within the PTV after fine tuning with soft-tissue based fusion. Results: In 29 of the 35 lesions, minor to no mismatch was found between the soft-tissue and skull based fusions. The corresponding translational and rotational shifts were 0.05 ± 0.63 mm (LR), 0.01 ± 0.79 mm (AP), 0.37 ± 1.01 mm (SI); -0.15 ± 0.67° (pitch), -0.19 ± 0.34° (yaw), and -0.12 ± 0.49° (roll). Thus the GTV, after soft-tissue based fusion, was 100% covered by the PTV. However, in the remaining 6 lesions in the study, noticeable displacements were observed between the skull and soft-tissue based fusions. Excluding an outlier lesion, the mean translational and rotational shifts for 5 of the 6 remaining lesions were 0.90 ± 2.15 mm (LR), 1.50 ± 2.27 mm (AP), -1.01 ± 1.83 mm (SI); -1.42 ± 3.12°(pitch), 0.02 ± 0.83°(yaw), and -0.17 ± 0.68°(roll). For the outlier lesion, the GTV was nearly missed by the PTV, and for the rest of the 5 lesions, the mean coverage of the GTV was 98.9% within the PTV. Conclusion: In a small portion of lesions, our study showed noticeable brain tumor displacement with typical patient setup in CT and MRI scans when using skull based fusion in comparison with soft-tissue fusion. Careful review of the skull based fusion is recommended by examining the match with nearby soft-tissue and/or tumors. If fusion deviations are found, it is also recommended to consider adding a margin to the GTV to account for such variations, since such variations could potentially affect target localization accuracy at the time of treatment.

A Robust and Efficient Algorithm for Tool Recognition and Localization for Space Station Robot

This paper studies a robust target recognition and localization method for a maintenance robot in a space station, and its main goal is to solve the target affine transformation caused by microgravity and the strong reflection and refraction of sunlight and lamplight in the cabin, as well as the occlusion of other objects. In this method, an Affine Scale Invariant Feature Transform (Affine-SIFT) algorithm is proposed to extract enough local feature points with a fully affine invariant, and the stable matching point is obtained from the above point for target recognition by the selected Random Sample Consensus (RANSAC) algorithm. Then, in order to localize the target, the effective and appropriate 3D grasping scope of the target is defined, and we determine and evaluate the grasping precision with the estimated affine transformation parameters presented in this paper. Finally, the threshold of RANSAC is optimized to enhance the accuracy and efficiency of target recognition and localization, and the scopes of illumination, vision distance and viewpoint angle for robot are evaluated to obtain effective image data by Root-Mean-Square Error (RMSE). An experimental system to simulate the illumination environment in a space station is established. Enough experiments have been carried out, and the experimental results show both the validity of the proposed definition of the grasping scope and the feasibility of the proposed recognition and localization method.

Analysis of the targeting uncertainty of a stereotactic frameless radiosurgery technique for arteriovenous malformation

In order to target arteriovenous malformations (AVM) in a frameless approach, registration of two-dimensional (2D) digital-subtracted-angiographs (DSA) with three-dimensional (3D) computed tomography (CT) is required. Targeting accuracy and delineation of a frameless 2D-DSA and 3D-CT image registration tool based on bony anatomy of the skull was evaluated. This frameless approach assures accurate target localization and can be used in a clinical setting.

Transorbital target localization with augmented ophthalmologic surgical endoscopy

Access to the space behind the eyeball is limited by the position of the globe anteriorly, the neurovascular structures embedded in fat posteriorly, and the tight bony confine of the orbit. These anatomical relationships have impeded application of minimally invasive procedures to the region, such as foreign body removal, tumor biopsy, or the administration of medical therapy directly to the optic nerve. An image-guided system was developed using a magnetically tracked flexible endoscope to navigate behind the eye, with the aim of enabling accurate transorbital surgery to user-specified target locations. Targets were defined by microspherical bulbs containing water or gadolinium contrast, with differing visible coloring agent. Six living pigs were anesthetized and two microspheres of differing color and contrast content were implanted in the fat tissue of each orbit. Preoperative T1-weighted MRI volumes were obtained and registered intraoperatively. The system capabilities were tested with a series of targeted surgical interventions. The surgeon was required to navigate the endoscope to each lucent microsphere and identify it by color. For three pigs, 3D/2D registration was performed such that the target's image volume coordinates were used to display its location on real-time endoscope video. The ophthalmologic surgeon was able to correctly identify every target by color, with average intervention time of 24.2 min without enhancement and 3.2 min with enhancement. This difference is highly statistically significant [Formula: see text] for reduction in localization time. Accurate transorbital target localization is possible in-vivo using image-guided transorbital endoscopy, while endoscopic enhancement through the use of video augmentation significantly reduces procedure time.

Assessment of Volumetric and Dosimetric Variations for Image Guided Stereotactic Body Radiation Therapy Treatment

Assessment of Volumetric and Dosimetric Variations for Image Guided Stereotactic Body Radiation Therapy Treatment

The application of micro-vacuo-certo-contacting ophthalmophanto in X-ray radiosurgery for tumors in an eyeball.

The large errors of routine localization for eyeball tumors restricted X-ray radiosurgery application, just for the eyeball to turn around. To localize the accuracy site, the micro-vacuo-certo-contacting ophthalmophanto (MVCCOP) method was used. Also, the outcome of patients with tumors in the eyeball was evaluated. In this study, computed tomography (CT) localization accuracy was measured by repeating CT scan using MVCCOP to fix the eyeball in radiosurgery. This study evaluated the outcome of the tumors and the survival of the patients by follow-up. The results indicated that the accuracy of CT localization of Brown-Roberts-Wells (BRW) head ring was 0.65 mm and maximum error was 1.09 mm. The accuracy of target localization of tumors in the eyeball using MVCCOP was 0.87 mm averagely, and the maximum error was 1.19 mm. The errors of fixation of the eyeball were 0.84 mm averagely and 1.17 mm maximally. The total accuracy was 1.34 mm, and 95% confidence accuracy was 2.09 mm. The clinical application of this method in 14 tumor patients showed satisfactory results, and all of the tumors showed the clear rims. The site of ten retinoblastomas was decreased significantly. The local control interval of tumors were 6 ∼ 24 months, median of 10.5 months. The survival of ten patients was 7 ∼ 30 months, median of 16.5 months. Also, the tumors were kept stable or shrank in the other four patients with angioma and melanoma. In conclusion, the MVCCOP is suitable and dependable for X-ray radiosurgery for eyeball tumors. The tumor control and survival of patients are satisfactory, and this method can effectively postpone or avoid extirpation of eyeball.

Cramér‐Rao lower bound with P d < 1 for target localisation accuracy in multistatic passive radar

By exploiting the sources of opportunity not designed for radar applications, the passive radar system often operates with a P d in the range from 60 to 85% for acceptable false alarm rates. Multistatic radar networks can be used to both increase detection capability and localisation accuracy. The standard Cramer-Rao lower bound (CRLB) cannot be used for a realistic assessment of the target localisation accuracy in a surveillance area since it provides optimistic predictions. In this study, the authors derive the CRLB with missing observations, namely for P d < 1, for the multisensory case. The results are illustrated for the case study of a multistatic passive radar exploiting FM radio transmissions where each bistatic pair within the network is assigned with a detection probability for each target position in the surveillance area. The obtained CRLB with P d < 1 is then employed to compare the localisation performance achievable by a multistatic passive radar when using different sets of measurements: (A) only range measurements, (B) range and Doppler frequency measurements and (C) Doppler frequency measurements only. The reported results show that the proposed CRLB with P d < 1 yields a more reliable prediction of the achievable performance thus allowing a fair comparison of the above different strategies for target localisation.

The potential role of respiratory motion management and image guidance in the reduction of severe toxicities following stereotactic ablative radiation therapy for patients with centrally located early stage non-small cell lung cancer or lung metastases.

Image guidance allows delivery of very high doses of radiation over a few fractions, known as stereotactic ablative radiotherapy (SABR). This treatment is associated with excellent outcome for early stage non-small cell lung cancer and metastases to the lungs. In the delivery of SABR, central location constantly poses a challenge due to the difficulty of adequately sparing critical thoracic structures that are immediately adjacent to the tumor if an ablative dose of radiation is to be delivered to the tumor target. As of current, various respiratory motion management and image guidance strategies can be used to ensure accurate tumor target localization prior and/or during daily treatment, which allows for maximal and safe reduction of set up margins. The incorporation of both may lead to the most optimal normal tissue sparing and the most accurate SABR delivery. Here, the clinical outcome, treatment related toxicities, and the pertinent respiratory motion management/image guidance strategies reported in the current literature on SABR for central lung tumors are reviewed.

SU‐E‐T‐268: Proton Radiosurgery End‐To‐End Testing Using Lucy 3D QA Phantom

Purpose:To check the overall accuracy of proton radiosurgery treatment delivery using ready‐made circular collimator inserts and fixed thickness compensating boluses.Methods:Lucy 3D QA phantom (Standard Imaging Inc. WI, USA) inserted with GaFchromicTM film was irradiated with laterally scattered and longitudinally spread‐out 126.8 MeV proton beams. The tests followed every step in the proton radiosurgery treatment delivery process: CT scan (GE Lightspeed VCT), target contouring, treatment planning (Odyssey 5.0, Optivus, CA), portal calibration, target localization using robotic couch with image guidance and dose delivery at planned gantry angles. A 2 cm diameter collimator insert in a 4 cm diameter radiosurgery cone and a 1.2 cm thick compensating flat bolus were used for all beams. Film dosimetry (RIT114 v5.0, Radiological Imaging Technology, CO, USA) was used to evaluate the accuracy of target localization and relative dose distributions compared to those calculated by the treatment planning system.Results:The localization accuracy was estimated by analyzing the GaFchromic films irradiated at gantry 0, 90 and 270 degrees. We observed 0.5 mm shift in lateral direction (patient left), ±0.9 mm shift in AP direction and ±1.0 mm shift in vertical direction (gantry dependent). The isodose overlays showed good agreement (&lt;2mm, 50% isodose lines) between measured and calculated doses.Conclusion:Localization accuracy depends on gantry sag, CT resolution and distortion, DRRs from treatment planning computer, localization accuracy of image guidance system, fabrication of ready‐made aperture and cone housing. The total deviation from the isocenter was 1.4 mm. Dose distribution uncertainty comes from distal end error due to bolus and CT density, in addition to localization error. The planned dose distribution was well matched (&gt;90%) to the measured values 2%/2mm criteria. Our test showed the robustness of our proton radiosurgery treatment delivery system using ready‐made collimator inserts and fixed thickness compensating boluses.

SU-E-J-231: Comparison of 3D Angiogram and MRI in Delineating the AVM Target for Frameless Stereotactic Radiosurgery

Purpose: Stereotactic radiation therapy (SRT) provides an excellent alternative to embolization and surgical excision for the management of appropriately selected cerebral arteriovenous malformations (AVMs). The currently accepted standard for delineating AVMs is planar digital subtraction angiography (DSA). DSA can be used to acquire a 3D data set that preserves osseous structures (3D-DA) at the time of the angiography for SRT planning. Magnetic resonance imaging (MRI) provides an alternative noninvasive method of visualizing the AVM nidus with comparable spatial resolution. We utilized 3D-DA and T1 post-contrast MRI data to evaluate the differences in SRT target volumes. Methods: Four patients underwent 3D-DA and high-resolution MRI. 3D T1 post-contrast images were obtained in all three reconstruction planes. A planning CT was fused with MRI and 3D-DA data sets. The AVMs were contoured utilizing one of the image sets at a time. Target volume, centroid, and maximum and minimum dimensions were analyzed for each patient. Results: Targets delineated using post-contrast MRI demonstrated a larger mean volume. AVMs >2 cc were found to have a larger difference between MRI and 3D-DA volumes. Larger AVMs also demonstrated a smaller relative uncertainty in contour centroid position (1 mm). AVM targets 2 cc. The greater centroid stability for AVMs >2 cc ensures accurate target localization during image fusion. The larger MRI target volumes did not result in prohibitively greater volumes of normal brain tissue receiving the prescription dose. The larger centroid instability for AVMs <2 cc precludes the use of MRI alone for target delineation. We recommend incorporating a 3D-DA for these patients.« less

An Engineering Approach for Observer Trajectory Optimization in Passive Target Tracking System

In passive target tracking system, the observer trajectories have an important effect on the accuracy of target localization and tracking. This paper addressed an engineering approach to optimize the trajectory altitude of observer platform for airborne ESM surveillance system. The method proposed is based on Monte-Carlo run, which avoid complicated theoretical deduction and make the observer path easy-to-practice. By the analysis, the general principle of observer trajectory altitude optimization can be obtained. Within the range of allowed flying altitudes for observer, the measurements of elevation should be maintain or close to 45 degrees as much as possible.

Propagator Method-Based Joint Estimation of Angle and Polarization for Bistatic MIMO Radar with Polarization Sensitive Array

This paper links the parameter estimation problem of polarization diversity bistatic multiple-input multiple-output (MIMO) radar to propagator method (PM), and proposes an algorithm for joint estimation of direction-of-departure (DOD), direction-of-arrival (DOA) and polarization information for bistatic MIMO radars. PM algorithm is a low complexity algorithm since it requires no eigen-value decomposition (EVD) of the covariance matrix of the received data. The proposed algorithm can estimate the multiple parameter accurately, while achieve paired parameters estimation automatically. Through obtaining polarization information, MIMO radars can further increase the target location and identification accuracy. Simulation results verify the feasibility and effectiveness of the proposed algorithm.

Resource Allocation in MIMO Radar With Multiple Targets for Non-Coherent Localization

In an MIMO radar network, the multiple transmit elements may emit waveforms that differ on power and bandwidth. In this paper, we are asking, given that these two resources are limited, what is the optimal power, optimal bandwidth, and optimal joint power and bandwidth allocation for best localization of multiple targets. The well-known Crámer–Rao lower bound for target localization accuracy is used as a figure of merit and approximate solutions are found by minimizing a sequence of convex problems. Their quality is assessed through extensive numerical simulations and with the help of a lower-bound on the true solution. Simulations results reveal that bandwidth allocation policies have a definitely stronger impact on performance than power.

A stationary wavelet transform based approach to registration of planning CT and setup cone beam-CT images in radiotherapy.

Image registration between planning CT images and cone beam-CT (CBCT) images is one of the key technologies of image guided radiotherapy (IGRT). Current image registration methods fall roughly into two categories: geometric features-based and image grayscale-based. Mutual information (MI) based registration, which belongs to the latter category, has been widely applied to multi-modal and mono-modal image registration. However, the standard mutual information method only focuses on the image intensity information and overlooks spatial information, leading to the instability of intensity interpolation. Due to its use of positional information, wavelet transform has been applied to image registration recently. In this study, we proposed an approach to setup CT and cone beam-CT (CBCT) image registration in radiotherapy based on the combination of mutual information (MI) and stationary wavelet transform (SWT). Firstly, SWT was applied to generate gradient images and low frequency components produced in various levels of image decomposition were eliminated. Then inverse SWT was performed on the remaining frequency components. Lastly, the rigid registration of gradient images and original images was implemented using a weighting function with the normalized mutual information (NMI) being the similarity measure, which compensates for the lack of spatial information in mutual information based image registration. Our experiment results showed that the proposed method was highly accurate and robust, and indicated a significant clinical potential in improving the accuracy of target localization in image guided radiotherapy (IGRT).

Model-guided respiratory organ motion prediction of the liver from 2D ultrasound.

With the availability of new and more accurate tumour treatment modalities such as high-intensity focused ultrasound or proton therapy, accurate target location prediction has become a key issue. Various approaches for diverse application scenarios have been proposed over the last decade. Whereas external surrogate markers such as a breathing belt work to some extent, knowledge about the internal motion of the organs inherently provides more accurate results. In this paper, we combine a population-based statistical motion model and information from 2d ultrasound sequences in order to predict the respiratory motion of the right liver lobe. For this, the motion model is fitted to a 3d exhalation breath-hold scan of the liver acquired before prediction. Anatomical landmarks tracked in the ultrasound images together with the model are then used to reconstruct the complete organ position over time. The prediction is both spatial and temporal, can be computed in real-time and is evaluated on ground truth over long time scales (5.5 min). The method is quantitatively validated on eight volunteers where the ultrasound images are synchronously acquired with 4D-MRI, which provides ground-truth motion. With an average spatial prediction accuracy of 2.4 mm, we can predict tumour locations within clinically acceptable margins.

A Practical Method of Observer Velocity Optimization with Airborne ESM Sensor

In bearings-only target motion analysis, the observer trajectory has an important effect on the accuracy of target localization and tracking. This paper presented a practical method of observer velocity optimization based on Monte-Carlo run for airborne ESM measurement system. For verifying the validity of our method, the geometric dilution of precision (GDOP) is taken as the performance index. Finally, three scenarios are given and the GDOP values of the ESM measurement system in scenarios are calculated to illustrate the observer velocity optimization strategy.

A limited‐angle intrafraction verification (LIVE) system for radiation therapy

Currently, no 3D or 4D volumetric x-ray imaging techniques are available for intrafraction verification of target position during actual treatment delivery or in-between treatment beams, which is critical for stereotactic radiosurgery (SRS) and stereotactic body radiation therapy (SBRT) treatments. This study aims to develop a limited-angle intrafraction verification (LIVE) system to use prior information, deformation models, and limited angle kV-MV projections to verify target position intrafractionally. The LIVE system acquires limited-angle kV projections simultaneously during arc treatment delivery or in-between static 3D/IMRT treatment beams as the gantry moves from one beam to the next. Orthogonal limited-angle MV projections are acquired from the beam's eye view (BEV) exit fluence of arc treatment beam or in-between static beams to provide additional anatomical information. MV projections are converted to kV projections using a linear conversion function. Patient prior planning CT at one phase is used as the prior information, and the on-board patient volume is considered as a deformation of the prior images. The deformation field is solved using the data fidelity constraint, a breathing motion model extracted from the planning 4D-CT based on principal component analysis (PCA) and a free-form deformation (FD) model. LIVE was evaluated using a 4D digital extended cardiac torso phantom (XCAT) and a CIRS 008A dynamic thoracic phantom. In the XCAT study, patient breathing pattern and tumor size changes were simulated from CT to treatment position. In the CIRS phantom study, the artificial target in the lung region experienced both size change and position shift from CT to treatment position. Varian Truebeam research mode was used to acquire kV and MV projections simultaneously during the delivery of a dynamic conformal arc plan. The reconstruction accuracy was evaluated by calculating the 3D volume percentage difference (VPD) and the center of mass (COM) difference of the tumor in the true on-board images and reconstructed images. In both simulation and phantom studies, LIVE achieved substantially better reconstruction accuracy than reconstruction using PCA or FD deformation model alone. In the XCAT study, the average VPD and COM differences among different patient scenarios for LIVE system using orthogonal 30° scan angles were 4.3% and 0.3 mm when using kV+BEV MV. Reducing scan angle to 15° increased the average VPD and COM differences to 15.1% and 1.7 mm. In the CIRS phantom study, the VPD and COM differences for the LIVE system using orthogonal 30° scan angles were 6.4% and 1.4 mm. Reducing scan angle to 15° increased the VPD and COM differences to 51.9% and 3.8 mm. The LIVE system has the potential to substantially improve intrafraction target localization accuracy by providing volumetric verification of tumor position simultaneously during arc treatment delivery or in-between static treatment beams. With this improvement, LIVE opens up a new avenue for margin reduction and dose escalation in both fractionated treatments and SRS and SBRT treatments.

Echolocation behaviour of the big brown bat (Eptesicus fuscus) in an obstacle avoidance task of increasing difficulty.

Four big brown bats (Eptesicus fuscus) were challenged in an obstacle avoidance experiment to localize vertically stretched wires requiring progressively greater accuracy by diminishing the wire-to-wire distance from 50 to 10 cm. The performance of the bats decreased with decreasing gap size. The avoidance task became very difficult below a wire separation of 30 cm, which corresponds to the average wingspan of E. fuscus. Two of the bats were able to pass without collisions down to a gap size of 10 cm in some of the flights. The other two bats only managed to master gap sizes down to 20 and 30 cm, respectively. They also performed distinctly worse at all other gap sizes. With increasing difficulty of the task, the bats changed their flight and echolocation behaviour. Especially at gap sizes of 30 cm and below, flight paths increased in height and flight speed was reduced. In addition, the bats emitted approach signals that were arranged in groups. At all gap sizes, the largest numbers of pulses per group were observed in the last group before passing the obstacle. The more difficult the obstacle avoidance task, the more pulses there were in the groups and the shorter the within-group pulse intervals. In comparable situations, the better-performing bats always emitted groups with more pulses than the less well-performing individuals. We hypothesize that the accuracy of target localization increases with the number of pulses per group and that each group is processed as a package.

Two-tier target tracking framework in distributed sensor networks

A distributive two–tier tracking framework is developed to track mobile targets in sensor networks. The algorithm utilises the efficiency of binary sensor reading to ensure fast isolation of the target, and then it uses a small cluster of sensors around the target to compute accurate target location. The framework has two tiers, in tier–one, binary sensor reading and Viterbi algorithm are used, it is a fast and distributed way of roughly locate the target. In tier–two, a detailed localisation using maximum likelihood estimation is done within a small cluster of sensors to compute the accurate location of the target. By dividing the framework into two tiers, scaling the size of the network only affects the computation cost in tier one, where binary data are used. The computation cost in tier 2 remains unchanged. The framework is first implemented in a chained–form network with sensors deployed in a regular pattern, it is then extended to other regularly deployed network in full 2D space. The two–tier tracking framework is implemented using ultrasonic sensor network in a real–world hallway–room environment in our lab.

Maximizing Water Surface Target Localization Accuracy Under Sunlight Reflection with an Autonomous Unmanned Aerial Vehicle

Reflected sunlight can significantly impact the effectiveness of vision-based object detection and tracking algorithms, especially ones developed for an aerial platform operating over a marine envi...