In vivoliver tracking with a high volume rate 4D ultrasound scanner and a 2D matrix array probe

Landmark tracking in liver US images using cascade convolutional neural networks with long short-term memory

Accurate tracking of anatomic landmarks is critical for motion management in liver radiation therapy. Ultrasound (US) is a safe, low-cost technology that is broadly available and offer real-time imaging capability. This study proposed a deep learning-based tracking method for the US image-guided radiation therapy. The proposed cascade deep learning model is composed of an attention network, a mask region-based convolutional neural network (mask R-CNN), and a long short-term memory (LSTM) network. The attention network learns a mapping from an US image to a suspected area of landmark motion in order to reduce the search region. The mask R-CNN then produces multiple region-of-interest proposals in the reduced region and identifies the proposed landmark via three network heads: bounding box regression, proposal classification, and landmark segmentation. The LSTM network models the temporal relationship among the successive image frames for bounding box regression and proposal classification. To consolidate the final proposal, a selection method is designed according to the similarities between sequential frames. The proposed method was tested on the liver US tracking datasets used in the medical image computing and computer assisted interventions 2015 challenges, where the landmarks were annotated by three experienced observers to obtain their mean positions. Five-fold cross validation on the 24 given US sequences with ground truths shows that the mean tracking error for all landmarks is 0.65 ± 0.56 mm, and the errors of all landmarks are within 2 mm. We further tested the proposed model on 69 landmarks from the testing dataset that have the similar image pattern with the training pattern, resulting in a mean tracking error of 0.94 ± 0.83 mm. The proposed deep-learning model was implemented on a graphics processing unit (GPU), tracking 47-81 frames s-1. Our experimental results have demonstrated the feasibility and accuracy of our proposed method in tracking liver anatomic landmarks using US images, providing a potential solution for real-time liver tracking for active motion management during radiation therapy.

A phantom-based analysis for tracking intra-fraction pancreatic tumor motion by ultrasound imaging during radiation therapy

Purpose

In this study, we aim to further evaluate the accuracy of ultrasound tracking for intra-fraction pancreatic tumor motion during radiotherapy by a phantom-based study.

Methods

Twelve patients with pancreatic cancer who were treated with stereotactic body radiation therapy were enrolled in this study. The displacement points of the respiratory cycle were acquired from 4DCT and transferred to a motion platform to mimic realistic breathing movements in our phantom study. An ultrasound abdominal phantom was placed and fixed in the motion platform. The ground truth of phantom movement was recorded by tracking an optical tracker attached to this phantom. One tumor inside the phantom was the tracking target. In the evaluation of the results, the monitoring results from the ultrasound system were compared with the phantom motion results from the infrared camera. Differences between infrared monitoring motion and ultrasound tracking motion were analyzed by calculating the root-mean-square error.

Results

The 82.2% ultrasound tracking motion was within a 0.5 mm difference value between ultrasound tracking displacement and infrared monitoring motion. 0.7% ultrasound tracking failed to track accurately (a difference value > 2.5 mm). These differences between ultrasound tracking motion and infrared monitored motion do not correlate with respiratory displacements, respiratory velocity, or respiratory acceleration by linear regression analysis.

Conclusions

The highly accurate monitoring results of this phantom study prove that the ultrasound tracking system may be a potential method for real-time monitoring targets, allowing more accurate delivery of radiation doses.

Systematic analysis of volumetric ultrasound parameters for markerless 4D motion tracking

OBJECTIVES

Motion compensation is an interesting approach to improve treatments of moving structures. For example, target motion can substantially affect dose delivery in radiation therapy, where methods to detect and mitigate the motion are widely used. Recent advances in fast, volumetric ultrasound have rekindled the interest in ultrasound for motion tracking. We present a setup to evaluate ultrasound based motion tracking and we study the effect of imaging rate and motion artifacts on its performance.

METHODS

We describe an experimental setup to acquire markerless 4D ultrasound data with precise ground truth from a robot and evaluate different real-world trajectories and system settings toward accurate motion estimation. We analyze motion artifacts in continuously acquired data by comparing to data recorded in a step-and-shoot fashion. Furthermore, we investigate the trade-off between the imaging frequency and resolution.

RESULTS

The mean tracking errors show that continuously acquired data leads to similar results as data acquired in a step-and-shoot fashion. We report mean tracking errors up to 2.01 mm and 1.36 mm on the continuous data for the lower and higher resolution, respectively, while step-and-shoot data leads to mean tracking errors of 2.52 mm and 0.98 mm.

CONCLUSIONS

We perform a quantitative analysis of different system settings for motion tracking with 4D ultrasound. We can show that precise tracking is feasible and additional motion in continuously acquired data does not impair the tracking. Moreover, the analysis of the frequency resolution trade-off shows that a high imaging resolution is beneficial in ultrasound tracking.

An Upgraded Siamese Neural Network for Motion Tracking in Ultrasound Image Sequences

Deep learning is heavily being borrowed to solve problems in medical imaging applications, and Siamese neural networks are the front runners of motion tracking. In this article, we propose to upgrade one such Siamese architecture-based neural network for robust and accurate landmark tracking in ultrasound images to improve the quality of image-guided radiation therapy. Although several researchers have improved the Siamese architecture-based networks with sophisticated detection modules and by incorporating transfer learning, the inherent assumptions of the constant position model and the missing motion model remain unaddressed limitations. In our proposed model, we overcome these limitations by introducing two modules into the original architecture. We employ a reference template update to resolve the constant position model and a linear Kalman filter (LKF) to address the missing motion model. Moreover, we demonstrate that the proposed architecture provides promising results without transfer learning. The proposed model was submitted to an open challenge organized by MICCAI and was evaluated exhaustively on the Liver US Tracking (CLUST) 2D dataset. Experimental results proved that the proposed model tracked the landmarks with promising accuracy. Furthermore, we also induced synthetic occlusions to perform a qualitative analysis of the proposed approach. The evaluations were performed on the training set of the CLUST 2D dataset. The proposed method outperformed the original Siamese architecture by a significant margin.

Deep learning-based motion tracking using ultrasound images

PURPOSE

Ultrasound (US) imaging is an established imaging modality capable of offering video-rate volumetric images without ionizing radiation. It has the potential for intra-fraction motion tracking in radiation therapy. In this study, a deep learning-based method has been developed to tackle the challenges in motion tracking using US imaging.

METHODS

We present a Markov-like network, which is implemented via generative adversarial networks, to extract features from sequential US frames (one tracked frame followed by untracked frames) and thereby estimate a set of deformation vector fields (DVFs) through the registration of the tracked frame and the untracked frames. The positions of the landmarks in the untracked frames are finally determined by shifting landmarks in the tracked frame according to the estimated DVFs. The performance of the proposed method was evaluated on the testing dataset by calculating the tracking error (TE) between the predicted and ground truth landmarks on each frame.

RESULTS

The proposed method was evaluated using the MICCAI CLUST 2015 dataset which was collected using seven US scanners with eight types of transducers and the Cardiac Acquisitions for Multi-structure Ultrasound Segmentation (CAMUS) dataset which was acquired using GE Vivid E95 ultrasound scanners. The CLUST dataset contains 63 2D and 22 3D US image sequences respectively from 42 and 18 subjects, and the CAMUS dataset includes 2D US images from 450 patients. On CLUST dataset, our proposed method achieved a mean tracking error of 0.70 ± 0.38 mm for the 2D sequences and 1.71 ± 0.84 mm for the 3D sequences for those public available annotations. And on CAMUS dataset, a mean tracking error of 0.54 ± 1.24 mm for the landmarks in the left atrium was achieved.

CONCLUSIONS

A novel motion tracking algorithm using US images based on modern deep learning techniques has been demonstrated in this study. The proposed method can offer millimeter-level tumor motion prediction in real time, which has the potential to be adopted into routine tumor motion management in radiation therapy.

Block-matching-based registration to evaluate ultrasound visibility of percutaneous needles in liver-mimicking phantoms

Purpose

To present a novel methodical approach to compare visibility of percutaneous needles in ultrasound images.

Methods

A motor‐driven rotation platform was used to gradually change the needle angle while capturing image data. Data analysis was automated using block‐matching‐based registration, with a tracking and refinement step. Every 25 frames, a Hough transform was used to improve needle alignments after large rotations. The method was demonstrated by comparing three commercial needles (14G radiofrequency ablation, RFA; 18G Trocar; 22G Chiba) and six prototype needles with different sizes, materials, and surface conditions (polished, sand‐blasted, and kerfed), within polyvinyl alcohol phantom tissue and ex vivo bovine liver models. For each needle and angle, a contrast‐to‐noise ratio (CNR) was determined to quantify visibility. CNR values are presented as a function of needle type and insertion angle. In addition, the normalized area under the (CNR‐angle) curve was used as a summary metric to compare needles.

Results

In phantom tissue, the first kerfed needle design had the largest normalized area of visibility and the polished 1 mm diameter stainless steel needle the smallest (0.704 ± 0.199 vs. 0.154 ± 0.027, p < 0.01). In the ex vivo model, the second kerfed needle design had the largest normalized area of visibility, and the sand‐blasted stainless steel needle the smallest (0.470 ± 0.190 vs. 0.127 ± 0.047, p < 0.001). As expected, the analysis showed needle visibility peaks at orthogonal insertion angles. For acute or obtuse angles, needle visibility was similar or reduced. Overall, the variability in needle visibility was considerably higher in livers.

Conclusion

The best overall visibility was found with kerfed needles and the commercial RFA needle. The presented methodical approach to quantify ultrasound visibility allows comparisons of (echogenic) needles, as well as other technological innovations aiming to improve ultrasound visibility of percutaneous needles, such as coatings, material treatments, and beam steering approaches.

Target tracking accuracy and latency with different 4D ultrasound systems – a robotic phantom study

Ultrasound (US) imaging, in contrast to other image guidance techniques, offers the distinct advantage of providing volumetric image data in real-time (4D) without using ionizing radiation. The goal of this study was to perform the first quantitative comparison of three different 4D US systems with fast matrix array probes and real-time data streaming regarding their target tracking accuracy and system latency. Sinusoidal motion of varying amplitudes and frequencies was used to simulate breathing motion with a robotic arm and a static US phantom. US volumes and robot positions were acquired online and stored for retrospective analysis. A template matching approach was used for target localization in the US data. Target motion measured in US was compared to the reference trajectory performed by the robot to determine localization accuracy and system latency. Using the robotic setup, all investigated 4D US systems could detect a moving target with sub-millimeter accuracy. However, especially high system latency increased tracking errors substantially and should be compensated with prediction algorithms for respiratory motion compensation.

2D ultrasound imaging based intra-fraction respiratory motion tracking for abdominal radiation therapy using machine learning

We have previously developed a robotic ultrasound imaging system for motion monitoring in abdominal radiation therapy. Owing to the slow speed of ultrasound image processing, our previous system could only track abdominal motions under breath-hold. To overcome this limitation, a novel 2D-based image processing method for tracking intra-fraction respiratory motion is proposed. Fifty-seven different anatomical features acquired from 27 sets of 2D ultrasound sequences were used in this study. Three 2D ultrasound sequences were acquired with the robotic ultrasound system from three healthy volunteers. The remaining datasets were provided by the 2015 MICCAI Challenge on Liver Ultrasound Tracking. All datasets were preprocessed to extract the feature point, and a patient-specific motion pattern was extracted by principal component analysis and slow feature analysis (SFA). The tracking finds the most similar frame (or indexed frame) by a k-dimensional-tree-based nearest neighbor search for estimating the tracked object location. A template image was updated dynamically through the indexed frame to perform a fast template matching (TM) within a learned smaller search region on the incoming frame. The mean tracking error between manually annotated landmarks and the location extracted from the indexed training frame is 1.80  ±  1.42 mm. Adding a fast TM procedure within a small search region reduces the mean tracking error to 1.14  ±  1.16 mm. The tracking time per frame is 15 ms, which is well below the frame acquisition time. Furthermore, the anatomical reproducibility was measured by analyzing the location's anatomical landmark relative to the probe; the position-controlled probe has better reproducibility and yields a smaller mean error across all three volunteer cases, compared to the force-controlled probe (2.69 versus 11.20 mm in the superior-inferior direction and 1.19 versus 8.21 mm in the anterior-posterior direction). Our method reduces the processing time for tracking respiratory motion significantly, which can reduce the delivery uncertainty.

Evaluation of 2D and 3D ultrasound tracking algorithms and impact on ultrasound-guided liver radiotherapy margins

PURPOSE

Compensation for respiratory motion is important during abdominal cancer treatments. In this work we report the results of the 2015 MICCAI Challenge on Liver Ultrasound Tracking and extend the 2D results to relate them to clinical relevance in form of reducing treatment margins and hence sparing healthy tissues, while maintaining full duty cycle.

METHODS

We describe methodologies for estimating and temporally predicting respiratory liver motion from continuous ultrasound imaging, used during ultrasound-guided radiation therapy. Furthermore, we investigated the trade-off between tracking accuracy and runtime in combination with temporal prediction strategies and their impact on treatment margins.

RESULTS

Based on 2D ultrasound sequences from 39 volunteers, a mean tracking accuracy of 0.9 mm was achieved when combining the results from the 4 challenge submissions (1.2 to 3.3 mm). The two submissions for the 3D sequences from 14 volunteers provided mean accuracies of 1.7 and 1.8 mm. In combination with temporal prediction, using the faster (41 vs 228 ms) but less accurate (1.4 vs 0.9 mm) tracking method resulted in substantially reduced treatment margins (70% vs 39%) in contrast to mid-ventilation margins, as it avoided non-linear temporal prediction by keeping the treatment system latency low (150 vs 400 ms). Acceleration of the best tracking method would improve the margin reduction to 75%.

CONCLUSIONS

Liver motion estimation and prediction during free-breathing from 2D ultrasound images can substantially reduce the in-plane motion uncertainty and hence treatment margins. Employing an accurate tracking method while avoiding non-linear temporal prediction would be favorable. This approach has the potential to shorten treatment time compared to breath-hold and gated approaches, and increase treatment efficiency and safety.

Using needle orientation sensing as surrogate signal for respiratory motion estimation in percutaneous interventions

PURPOSE

To develop and evaluate an approach to estimate the respiratory-induced motion of lesions in the chest and abdomen.

MATERIALS AND METHODS

The proposed approach uses the motion of an initial reference needle inserted into a moving organ to estimate the lesion (target) displacement that is caused by respiration. The needles position is measured using an inertial measurement unit (IMU) sensor externally attached to the hub of an initially placed reference needle. Data obtained from the IMU sensor and the target motion are used to train a learning-based approach to estimate the position of the moving target. An experimental platform was designed to mimic respiratory motion of the liver. Liver motion profiles of human subjects provided inputs to the experimental platform. Variables including the insertion angle, target depth, target motion velocity and target proximity to the reference needle were evaluated by measuring the error of the estimated target position and processing time.

RESULTS

The mean error of estimation of the target position ranged between 0.86 and 1.29 mm. The processing maximum training and testing time was 5 ms which is suitable for real-time target motion estimation using the needle position sensor.

CONCLUSION

The external motion of an initially placed reference needle inserted into a moving organ can be used as a surrogate, measurable and accessible signal to estimate in real-time the position of a moving target caused by respiration; this technique could then be used to guide the placement of subsequently inserted needles directly into the target.

A block matching based approach with multiple simultaneous templates for the real-time 2D ultrasound tracking of liver vessels

PURPOSE

The implementation of motion management techniques in radiation therapy can aid in mitigating uncertainties and reducing margins. For motion management to be effective, it is necessary to track key structures both accurately and at a real-time speed. Therefore, the focus of this work was to develop a 2D algorithm for the real-time tracking of ultrasound features to aid in radiation therapy motion management.

MATERIALS AND METHODS

The developed algorithm utilized a similarity measure-based block matching algorithm incorporating training methods and multiple simultaneous templates. The algorithm is broken down into three primary components, all of which use normalized cross-correlation (NCC) as a similarity metric. First, a global feature shift to account for gross displacements from the previous frame is determined using large block sizes which encompass the entirety of the feature. Second, the most similar reference frame is chosen from a series of training images that are accumulated during the first K frames of tracking to aid in contour consistency and provide a starting point for the localized template initialization. Finally, localized block matching is performed through the simultaneous use of both a training frame and the previous frame. The localized block matching utilizes a series of templates positioned at the boundary points of the training and previous contours. The weighted final boundary points from both the previous and the training frame are ultimately combined and used to determine an affine transformation from the previous frame to the current frame.

RESULTS

A mean tracking error of 0.72 ± 1.25 mm was observed for 85 point-landmarks across 39 ultrasound sequences relative to manual ground truth annotations. The image processing speed per landmark with the GPU implementation was between 41 and 165 frames per second (fps) during the training set accumulation, and between 73 and 234 fps after training set accumulation. Relative to a comparable multithreaded CPU approach using OpenMP, the GPU implementation resulted in speedups between -30% and 355% during training set accumulation, and between -37% and 639% postaccumulation.

CONCLUSIONS

Initial implementations indicated an accuracy that was comparable to or exceeding those achieved by alternative 2D tracking methods, with a computational speed that is more than sufficient for real-time applications in a radiation therapy environment. While the overall performance reached levels suitable for implementation in radiation therapy, the observed increase in failures for smaller features, as well as the algorithm's inability to be applied to nonconvex features warrants additional investigation to address the shortcomings observed.

Feasibility study of ultrasound imaging for stereotactic body radiation therapy with active breathing coordinator in pancreatic cancer

PURPOSE

Stereotactic body radiation therapy (SBRT) allows for high radiation doses to be delivered to the pancreatic tumors with limited toxicity. Nevertheless, the respiratory motion of the pancreas introduces major uncertainty during SBRT. Ultrasound imaging is a non-ionizing, non-invasive, and real-time technique for intrafraction monitoring. A configuration is not available to place the ultrasound probe during pancreas SBRT for monitoring.

METHODS AND MATERIALS

An arm-bridge system was designed and built. A CT scan of the bridge-held ultrasound probe was acquired and fused to ten previously treated pancreatic SBRT patient CTs as virtual simulation CTs. Both step-and-shoot intensity-modulated radiation therapy (IMRT) and volumetric-modulated arc therapy (VMAT) planning were performed on virtual simulation CT. The accuracy of our tracking algorithm was evaluated by programmed motion phantom with simulated breath-hold 3D movement. An IRB-approved volunteer study was also performed to evaluate feasibility of system setup. Three healthy subjects underwent the same patient setup required for pancreas SBRT with active breath control (ABC). 4D ultrasound images were acquired for monitoring. Ten breath-hold cycles were monitored for both phantom and volunteers. For the phantom study, the target motion tracked by ultrasound was compared with motion tracked by the infrared camera. For the volunteer study, the reproducibility of ABC breath-hold was assessed.

RESULTS

The volunteer study results showed that the arm-bridge system allows placement of an ultrasound probe. The ultrasound monitoring showed less than 2 mm reproducibility of ABC breath-hold in healthy volunteers. The phantom monitoring accuracy is 0.14 ± 0.08 mm, 0.04 ± 0.1 mm, and 0.25 ± 0.09 mm in three directions. On dosimetry part, 100% of virtual simulation plans passed protocol criteria.

CONCLUSIONS

Our ultrasound system can be potentially used for real-time monitoring during pancreas SBRT without compromising planning quality. The phantom study showed high monitoring accuracy of the system, and the volunteer study showed feasibility of the clinical workflow.

Online 4D ultrasound guidance for real-time motion compensation by MLC tracking

PURPOSE

With the trend in radiotherapy moving toward dose escalation and hypofractionation, the need for highly accurate targeting increases. While MLC tracking is already being successfully used for motion compensation of moving targets in the prostate, current real-time target localization methods rely on repeated x-ray imaging and implanted fiducial markers or electromagnetic transponders rather than direct target visualization. In contrast, ultrasound imaging can yield volumetric data in real-time (3D + time = 4D) without ionizing radiation. The authors report the first results of combining these promising techniques-online 4D ultrasound guidance and MLC tracking-in a phantom.

METHODS

A software framework for real-time target localization was installed directly on a 4D ultrasound station and used to detect a 2 mm spherical lead marker inside a water tank. The lead marker was rigidly attached to a motion stage programmed to reproduce nine characteristic tumor trajectories chosen from large databases (five prostate, four lung). The 3D marker position detected by ultrasound was transferred to a computer program for MLC tracking at a rate of 21.3 Hz and used for real-time MLC aperture adaption on a conventional linear accelerator. The tracking system latency was measured using sinusoidal trajectories and compensated for by applying a kernel density prediction algorithm for the lung traces. To measure geometric accuracy, static anterior and lateral conformal fields as well as a 358° arc with a 10 cm circular aperture were delivered for each trajectory. The two-dimensional (2D) geometric tracking error was measured as the difference between marker position and MLC aperture center in continuously acquired portal images. For dosimetric evaluation, VMAT treatment plans with high and low modulation were delivered to a biplanar diode array dosimeter using the same trajectories. Dose measurements with and without MLC tracking were compared to a static reference dose using 3%/3 mm and 2%/2 mm γ-tests.

RESULTS

The overall tracking system latency was 172 ms. The mean 2D root-mean-square tracking error was 1.03 mm (0.80 mm prostate, 1.31 mm lung). MLC tracking improved the dose delivery in all cases with an overall reduction in the γ-failure rate of 91.2% (3%/3 mm) and 89.9% (2%/2 mm) compared to no motion compensation. Low modulation VMAT plans had no (3%/3 mm) or minimal (2%/2 mm) residual γ-failures while tracking reduced the γ-failure rate from 17.4% to 2.8% (3%/3 mm) and from 33.9% to 6.5% (2%/2 mm) for plans with high modulation.

CONCLUSIONS

Real-time 4D ultrasound tracking was successfully integrated with online MLC tracking for the first time. The developed framework showed an accuracy and latency comparable with other MLC tracking methods while holding the potential to measure and adapt to target motion, including rotation and deformation, noninvasively.

System Integration and In Vivo Testing of a Robot for Ultrasound Guidance and Monitoring During Radiotherapy

We are developing a cooperatively controlled robot system for image-guided radiation therapy (IGRT) in which a clinician and robot share control of a 3-D ultrasound (US) probe. IGRT involves two main steps: 1) planning/simulation and 2) treatment delivery. The goals of the system are to provide guidance for patient setup and real-time target monitoring during fractionated radiotherapy of soft tissue targets, especially in the upper abdomen. To compensate for soft tissue deformations created by the probe, we present a novel workflow where the robot holds the US probe on the patient during acquisition of the planning computerized tomography image, thereby ensuring that planning is performed on the deformed tissue. The robot system introduces constraints (virtual fixtures) to help to produce consistent soft tissue deformation between simulation and treatment days, based on the robot position, contact force, and reference US image recorded during simulation. This paper presents the system integration and the proposed clinical workflow, validated by an in vivo canine study. The results show that the virtual fixtures enable the clinician to deviate from the recorded position to better reproduce the reference US image, which correlates with more consistent soft tissue deformation and the possibility for more accurate patient setup and radiation delivery.

An improved tracking framework for ultrasound probe localization in image-guided radiosurgery

Real-time target localization with ultrasound holds high potential for image guidance and motion compensation in radiosurgery due to its non-invasive image acquisition free from ionizing radiation. However, a two-step localization has to be performed when integrating ultrasound into the existing radiosurgery workflow. In addition to target localization inside the ultrasound volume, the probe itself has to be localized in order to transform the target position into treatment room coordinates. By adapting existing camera calibration tools, we have developed a method to extend the stereoscopic X-ray tracking system of a radiosurgery platform in order to locate objects such as marker geometries with six degrees of freedom. The calibration was performed with 0.1 mm reprojection error. By using the full area of the flat-panel detectors without pre-processing the extended software increased the tracking volume and resolution by up to 80%, substantially improving patient localization and marker detectability. Furthermore, marker-tracking showed sub-millimeter accuracy and rotational errors below 0.1°. This demonstrates that the developed extension framework can accurately localize marker geometries using an integrated X-ray system, establishing the link for the integration of real-time ultrasound image guidance into the existing system.

First evaluation of the feasibility of MLC tracking using ultrasound motion estimation

PURPOSE

To quantify the performance of the Clarity ultrasound (US) imaging system (Elekta AB, Stockholm, Sweden) for real-time dynamic multileaf collimator (MLC) tracking.

METHODS

The Clarity calibration and quality assurance phantom was mounted on a motion platform moving with a periodic sine wave trajectory. The detected position of a 30 mm hypoechogenic sphere within the phantom was continuously reported via Clarity's real-time streaming interface to an in-house tracking and delivery software and subsequently used to adapt the MLC aperture. A portal imager measured MV treatment field/MLC apertures and motion platform positions throughout each experiment to independently quantify system latency and geometric error. Based on the measured range of latency values, a prostate stereotactic body radiation therapy (SBRT) delivery was performed with three realistic motion trajectories. The dosimetric impact of system latency on MLC tracking was directly measured using a 3D dosimeter mounted on the motion platform.

RESULTS

For 2D US imaging, the overall system latency, including all delay times from the imaging and delivery chain, ranged from 392 to 424 ms depending on the lateral sector size. For 3D US imaging, the latency ranged from 566 to 1031 ms depending on the elevational sweep. The latency-corrected geometric root-mean squared error was below 0.75 mm (2D US) and below 1.75 mm (3D US). For the prostate SBRT delivery, the impact of a range of system latencies (400-1000 ms) on the MLC tracking performance was minimal in terms of gamma failure rate.

CONCLUSIONS

Real-time MLC tracking based on a noninvasive US input is technologically feasible. Current system latencies are higher than those for x-ray imaging systems, but US can provide full volumetric image data and the impact of system latency was measured to be small for a prostate SBRT case when using a US-like motion input.

Review of ultrasound image guidance in external beam radiotherapy part II: intra-fraction motion management and novel applications

Imaging has become an essential tool in modern radiotherapy (RT), being used to plan dose delivery prior to treatment and verify target position before and during treatment. Ultrasound (US) imaging is cost-effective in providing excellent contrast at high resolution for depicting soft tissue targets apart from those shielded by the lungs or cranium. As a result, it is increasingly used in RT setup verification for the measurement of inter-fraction motion, the subject of Part I of this review (Fontanarosa et al 2015 Phys. Med. Biol. 60 R77-114). The combination of rapid imaging and zero ionising radiation dose makes US highly suitable for estimating intra-fraction motion. The current paper (Part II of the review) covers this topic. The basic technology for US motion estimation, and its current clinical application to the prostate, is described here, along with recent developments in robust motion-estimation algorithms, and three dimensional (3D) imaging. Together, these are likely to drive an increase in the number of future clinical studies and the range of cancer sites in which US motion management is applied. Also reviewed are selections of existing and proposed novel applications of US imaging to RT. These are driven by exciting developments in structural, functional and molecular US imaging and analytical techniques such as backscatter tissue analysis, elastography, photoacoustography, contrast-specific imaging, dynamic contrast analysis, microvascular and super-resolution imaging, and targeted microbubbles. Such techniques show promise for predicting and measuring the outcome of RT, quantifying normal tissue toxicity, improving tumour definition and defining a biological target volume that describes radiation sensitive regions of the tumour. US offers easy, low cost and efficient integration of these techniques into the RT workflow. US contrast technology also has potential to be used actively to assist RT by manipulating the tumour cell environment and by improving the delivery of radiosensitising agents. Finally, US imaging offers various ways to measure dose in 3D. If technical problems can be overcome, these hold potential for wide-dissemination of cost-effective pre-treatment dose verification and in vivo dose monitoring methods. It is concluded that US imaging could eventually contribute to all aspects of the RT workflow.

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.

4D Ultrasound Tracking of Liver and its Verification for TIPS Guidance

In this work we describe a 4D registration method for on the fly stabilization of ultrasound volumes for improving image guidance for transjugular intrahepatic portosystemic shunt (TIPS) interventions. The purpose of the method is to enable a continuous visualization of the relevant anatomical planes (determined in a planning stage) in a free breathing patient during the intervention. This requires registration of the planning information to the interventional images, which is achieved in two steps. In the first step tracking is performed across the streaming input. An approximate transformation between the reference image and the incoming image is estimated by composing the intermediate transformations obtained from the tracking. In the second step a subsequent registration is performed between the reference image and the approximately transformed incoming image to account for the accumulation of error. The two step approach helps in reducing the search range and is robust under rotation. We additionally present an approach to initialize and verify the registration. Verification is required when the reference image (containing planning information) is acquired in the past and is not part of the (interventional) 4D ultrasound sequence. The verification score will help in invalidating the registration outcome, for instance, in the case of insufficient overlap or information between the registering images due to probe motion or loss of contact, respectively. We evaluate the method over thirteen 4D US sequences acquired from eight subjects. A graphics processing unit implementation runs the 4D tracking at 9 Hz with a mean registration error of 1.7 mm.

Toward Standardized Acoustic Radiation Force (ARF)-Based Ultrasound Elasticity Measurements With Robotic Force Control

OBJECTIVE

Acoustic radiation force (ARF)-based approaches to measure tissue elasticity require transmission of a focused high-energy acoustic pulse from a stationary ultrasound probe and ultrasound-based tracking of the resulting tissue displacements to obtain stiffness images or shear wave speed estimates. The method has established benefits in biomedical applications such as tumor detection and tissue fibrosis staging. One limitation, however, is the dependence on applied probe pressure, which is difficult to control manually and prohibits standardization of quantitative measurements. To overcome this limitation, we built a robot prototype that controls probe contact forces for shear wave speed quantification.

METHODS

The robot was evaluated with controlled force increments applied to a tissue-mimicking phantom and in vivo abdominal tissue from three human volunteers.

RESULTS

The root-mean-square error between the desired and measured forces was 0.07 N in the phantom and higher for the fatty layer of in vivo abdominal tissue. The mean shear wave speeds increased from 3.7 to 4.5 m/s in the phantom and 1.0 to 3.0 m/s in the in vivo fat for compressive forces ranging from 2.5 to 30 N. The standard deviation of shear wave speeds obtained with the robotic approach were low in most cases ( 0.2 m/s) and comparable to that obtained with a semiquantitative landmark-based method.

CONCLUSION

Results are promising for the introduction of robotic systems to control the applied probe pressure for ARF-based measurements of tissue elasticity.

SIGNIFICANCE

This approach has potential benefits in longitudinal studies of disease progression, comparative studies between patients, and large-scale multidimensional elasticity imaging.

[Ultrasound motion tracking for radiation therapy]

BACKGROUND

In modern radiotherapy the radiation dose can be applied with an accuracy in the range of 1-2 mm provided that the exact position of the target is known. If, however, the target (the tumor) is located in the lungs or the abdomen, respiration or peristalsis can cause substantial movement of the target.

METHODS

Various methods for intrafractional motion detection and compensation are currently under consideration or are already applied in clinical practice. Sonography is one promising option, which is now on the brink of clinical implementation. Ultrasound is particularly suited for this purpose due to the high soft tissue contrast, real-time capability, the absence of ionizing radiation and low acquisition costs. Ultrasound motion tracking is an image-based approach, i.e. the target volume or an adjacent structure is directly monitored and the motion is tracked automatically on the ultrasound image. Diverse algorithms are presently available that provide the real-time target coordinates from 2D as well as 3D images. Definition of a suitable sonographic window is not, however, trivial and a gold standard for positioning and mounting of the transducer has not yet been developed. Furthermore, processing of the coordinate information in the therapy unit and the dynamic adaptation of the radiation field are challenging tasks.

CONCLUSION

It is not clear whether ultrasound motion tracking will become established in the clinical routine although all technical prerequisites can be considered as fulfilled, such that exciting progress in this field of research is still to be expected.

Spatial and Temporal Control of Hyperthermia Using Real Time Ultrasonic Thermal Strain Imaging with Motion Compensation, Phantom Study

Mild hyperthermia has been successfully employed to induce reversible physiological changes that can directly treat cancer and enhance local drug delivery. In this approach, temperature monitoring is essential to avoid undesirable biological effects that result from thermal damage. For thermal therapies, Magnetic Resonance Imaging (MRI) has been employed to control real-time Focused Ultrasound (FUS) therapies. However, combined ultrasound imaging and therapy systems offer the benefits of simple, low-cost devices that can be broadly applied. To facilitate such technology, ultrasound thermometry has potential to reliably monitor temperature. Control of mild hyperthermia was previously achieved using a proportional-integral-derivative (PID) controller based on thermocouple measurements. Despite accurate temporal control of heating, this method is limited by the single position at which the temperature is measured. Ultrasound thermometry techniques based on exploiting the thermal dependence of acoustic parameters (such as longitudinal velocity) can be extended to create thermal maps and allow an accurate monitoring of temperature with good spatial resolution. However, in vivo applications of this technique have not been fully developed due to the high sensitivity to tissue motion. Here, we propose a motion compensation method based on the acquisition of multiple reference frames prior to treatment. The technique was tested in the presence of 2-D and 3-D physiological-scale motion and was found to provide effective real-time temperature monitoring. PID control of mild hyperthermia in presence of motion was then tested with ultrasound thermometry as feedback and temperature was maintained within 0.3°C of the requested value.

Spatial and Temporal Control of Hyperthermia Using Real Time Ultrasonic Thermal Strain Imaging with Motion Compensation, Phantom Study

Mild hyperthermia has been successfully employed to induce reversible physiological changes that can directly treat cancer and enhance local drug delivery. In this approach, temperature monitoring is essential to avoid undesirable biological effects that result from thermal damage. For thermal therapies, Magnetic Resonance Imaging (MRI) has been employed to control real-time Focused Ultrasound (FUS) therapies. However, combined ultrasound imaging and therapy systems offer the benefits of simple, low-cost devices that can be broadly applied. To facilitate such technology, ultrasound thermometry has potential to reliably monitor temperature. Control of mild hyperthermia was previously achieved using a proportional-integral-derivative (PID) controller based on thermocouple measurements. Despite accurate temporal control of heating, this method is limited by the single position at which the temperature is measured. Ultrasound thermometry techniques based on exploiting the thermal dependence of acoustic parameters (such as longitudinal velocity) can be extended to create thermal maps and allow an accurate monitoring of temperature with good spatial resolution. However, in vivo applications of this technique have not been fully developed due to the high sensitivity to tissue motion. Here, we propose a motion compensation method based on the acquisition of multiple reference frames prior to treatment. The technique was tested in the presence of 2-D and 3-D physiological-scale motion and was found to provide effective real-time temperature monitoring. PID control of mild hyperthermia in presence of motion was then tested with ultrasound thermometry as feedback and temperature was maintained within 0.3°C of the requested value.

Respiratory gating based on internal electromagnetic motion monitoring during stereotactic liver radiation therapy: First results

BACKGROUND

Intrafraction motion may compromise the target dose in stereotactic body radiation therapy (SBRT) of tumors in the liver. Respiratory gating can improve the treatment delivery, but gating based on an external surrogate signal may be inaccurate. This is the first paper reporting on respiratory gating based on internal electromagnetic monitoring during liver SBRT.

MATERIAL AND METHODS

Two patients with solitary liver metastases were treated with respiratory-gated SBRT guided by three implanted electromagnetic transponders. The treatment was delivered in end-exhale with beam-on when the centroid of the three transponders deviated less than 3 mm [left-right (LR) and anterior-posterior (AP) directions] and 4mm [cranio-caudal (CC)] from the planned position. For each treatment fraction, log files were used to determine the transponder motion during beam-on in the actual gated treatments and in simulated treatments without gating. The motion was used to reconstruct the dose to the clinical target volume (CTV) with and without gating. The reduction in D95 (minimum dose to 95% of the CTV) relative to the plan was calculated for both treatment courses.

RESULTS

With gating the maximum course mean (standard deviation) geometrical error in any direction was 1.2 mm (1.8 mm). Without gating the course mean error would mainly increase for Patient 1 [to -2.8 mm (1.6 mm) (LR), 7.1 mm (5.8 mm) (CC), -2.6 mm (2.8mm) (AP)] due to a large systematic cranial baseline drift at each fraction. The errors without gating increased only slightly for Patient 2. The reduction in CTV D95 was 0.5% (gating) and 12.1% (non-gating) for Patient 1 and 0.3% (gating) and 1.7% (non-gating) for Patient 2. The mean duty cycle was 55%.

CONCLUSION

Respiratory gating based on internal electromagnetic motion monitoring was performed for two liver SBRT patients. The gating added robustness to the dose delivery and ensured a high CTV dose even in the presence of large intrafraction motion.

The 2014 liver ultrasound tracking benchmark

The Challenge on Liver Ultrasound Tracking (CLUST) was held in conjunction with the MICCAI 2014 conference to enable direct comparison of tracking methods for this application. This paper reports the outcome of this challenge, including setup, methods, results and experiences. The database included 54 2D and 3D sequences of the liver of healthy volunteers and tumor patients under free breathing. Participants had to provide the tracking results of 90% of the data (test set) for pre-defined point-landmarks (healthy volunteers) or for tumor segmentations (patient data). In this paper we compare the best six methods which participated in the challenge. Quantitative evaluation was performed by the organizers with respect to manual annotations. Results of all methods showed a mean tracking error ranging between 1.4 mm and 2.1 mm for 2D points, and between 2.6 mm and 4.6 mm for 3D points. Fusing all automatic results by considering the median tracking results, improved the mean error to 1.2 mm (2D) and 2.5 mm (3D). For all methods, the performance is still not comparable to human inter-rater variability, with a mean tracking error of 0.5–0.6 mm (2D) and 1.2–1.8 mm (3D). The segmentation task was fulfilled only by one participant, resulting in a Dice coefficient ranging from 76.7% to 92.3%. The CLUST database continues to be available and the online leader-board will be updated as an ongoing challenge.

System Integration and Preliminary In-Vivo Experiments of a Robot for Ultrasound Guidance and Monitoring during Radiotherapy

We are developing a cooperatively-controlled robot system in which a clinician and robot share control of a 3D ultrasound (US) probe. The goals of the system are to provide guidance for patient setup and real-time target monitoring during fractionated radiotherapy. Currently, there is limited use of realtime US image feedback during radiotherapy for lower abdominal organs and it has not yet been clinically applied for upper abdominal organs. One challenge is that placing an US probe on the patient produces tissue deformation around the target organ, leading to displacement of the target. Our solution is to perform treatment planning on the deformed organ and then to reproduce this deformation during radiotherapy. We therefore introduce a robot system to hold the US probe on the patient. In order to create a consistent deformation, the system records the robot position, contact force, and reference US image during simulation and then introduces virtual constraints (soft virtual fixtures) to guide the clinician to correctly place the probe during the fractionated treatments. Because the robot is under-actuated (5 motorized and 6 passive degrees-of-freedom), the guidance also involves a graphical user interface (adjustment GUI) to achieve the desired probe orientation. This paper presents the integrated system, a proposed clinical workflow, the results of an initial in-vivo canine study with a 3-DOF robot, and the results of phantom experiments with an improved 5-DOF robotic system. The results suggest that the guidance may enable the clinician to more consistently and accurately place the US probe.

Ultrasound Imaging in Radiation Therapy: From Interfractional to Intrafractional Guidance

External beam radiation therapy (EBRT) is included in the treatment regimen of the majority of cancer patients. With the proliferation of hypofractionated radiotherapy treatment regimens, such as stereotactic body radiation therapy (SBRT), interfractional and intrafractional imaging technologies are becoming increasingly critical to ensure safe and effective treatment delivery. Ultrasound (US)-based image guidance systems offer real-time, markerless, volumetric imaging with excellent soft tissue contrast, overcoming the limitations of traditional X-ray or computed tomography (CT)-based guidance for abdominal and pelvic cancer sites, such as the liver and prostate. Interfractional US guidance systems have been commercially adopted for patient positioning but suffer from systematic positioning errors induced by probe pressure. More recently, several research groups have introduced concepts for intrafractional US guidance systems leveraging robotic probe placement technology and real-time soft tissue tracking software. This paper reviews various commercial and research-level US guidance systems used in radiation therapy, with an emphasis on hardware and software technologies that enable the deployment of US imaging within the radiotherapy environment and workflow. Previously unpublished material on tissue tracking systems and robotic probe manipulators under development by our group is also included.

A new method for tracking organ motion on diagnostic ultrasound images

PURPOSE

Respiratory-gated irradiation is effective in reducing the margins of a target in the case of abdominal organs, such as the liver, that change their position as a result of respiratory motion. However, existing technologies are incapable of directly measuring organ motion in real-time during radiation beam delivery. Hence, the authors proposed a novel quantitative organ motion tracking method involving the use of diagnostic ultrasound images; it is noninvasive and does not entail radiation exposure. In the present study, the authors have prospectively evaluated this proposed method.

METHODS

The method involved real-time processing of clinical ultrasound imaging data rather than organ monitoring; it comprised a three-dimensional ultrasound device, a respiratory sensing system, and two PCs for data storage and analysis. The study was designed to evaluate the effectiveness of the proposed method by tracking the gallbladder in one subject and a liver vein in another subject. To track a moving target organ, the method involved the control of a region of interest (ROI) that delineated the target. A tracking algorithm was used to control the ROI, and a large number of feature points and an error correction algorithm were used to achieve long-term tracking of the target. Tracking accuracy was assessed in terms of how well the ROI matched the center of the target.

RESULTS

The effectiveness of using a large number of feature points and the error correction algorithm in the proposed method was verified by comparing it with two simple tracking methods. The ROI could capture the center of the target for about 5 min in a cross-sectional image with changing position. Indeed, using the proposed method, it was possible to accurately track a target with a center deviation of 1.54±0.9 mm. The computing time for one frame image using our proposed method was 8 ms. It is expected that it would be possible to track any soft-tissue organ or tumor with large deformations and changing cross-sectional position using this method.

CONCLUSIONS

The proposed method achieved real-time processing and continuous tracking of the target organ for about 5 min. It is expected that our method will enable more accurate radiation treatment than is the case using indirect observational methods, such as the respiratory sensor method, because of direct visualization of the tumor. Results show that this tracking system facilitates safe treatment in clinical practice.

In vivo reproducibility of robotic probe placement for a novel ultrasound-guided radiation therapy system

Ultrasound can provide real-time image guidance of radiation therapy, but the probe-induced tissue deformations cause local deviations from the treatment plan. If placed during treatment planning, the probe causes streak artifacts in required computed tomography (CT) images. To overcome these challenges, we propose robot-assisted placement of an ultrasound probe, followed by replacement with a geometrically identical, CT-compatible model probe. In vivo reproducibility was investigated by implanting a canine prostate, liver, and pancreas with three 2.38-mm spherical markers in each organ. The real probe was placed to visualize the markers and subsequently replaced with the model probe. Each probe was automatically removed and returned to the same position or force. Under position control, the median three-dimensional reproducibility of marker positions was 0.6 to 0.7 mm, 0.3 to 0.6 mm, and 1.1 to 1.6 mm in the prostate, liver, and pancreas, respectively. Reproducibility was worse under force control. Probe substitution errors were smallest for the prostate (0.2 to 0.6 mm) and larger for the liver and pancreas (4.1 to 6.3 mm), where force control generally produced larger errors than position control. Results indicate that position control is better than force control for this application, and the robotic approach has potential, particularly for relatively constrained organs and reproducibility errors that are smaller than established treatment margins.

4D ultrasound speckle tracking of intra-fraction prostate motion: a phantom-based comparison with x-ray fiducial tracking using CyberKnife

This study investigates the use of a mechanically-swept 3D ultrasound (3D-US) probe for soft-tissue displacement monitoring during prostate irradiation, with emphasis on quantifying the accuracy relative to CyberKnife® x-ray fiducial tracking. An US phantom, implanted with x-ray fiducial markers was placed on a motion platform and translated in 3D using five real prostate motion traces acquired using the Calypso system. Motion traces were representative of all types of motion as classified by studying Calypso data for 22 patients. The phantom was imaged using a 3D swept linear-array probe (to mimic trans-perineal imaging) and, subsequently, the kV x-ray imaging system on CyberKnife. A 3D cross-correlation block-matching algorithm was used to track speckle in the ultrasound data. Fiducial and US data were each compared with known phantom displacement. Trans-perineal 3D-US imaging could track superior-inferior (SI) and anterior-posterior (AP) motion to ≤0.81 mm root-mean-square error (RMSE) at a 1.7 Hz volume rate. The maximum kV x-ray tracking RMSE was 0.74 mm, however the prostate motion was sampled at a significantly lower imaging rate (mean: 0.04 Hz). Initial elevational (right-left; RL) US displacement estimates showed reduced accuracy but could be improved (RMSE <2.0 mm) using a correlation threshold in the ultrasound tracking code to remove erroneous inter-volume displacement estimates. Mechanically-swept 3D-US can track the major components of intra-fraction prostate motion accurately but exhibits some limitations. The largest US RMSE was for elevational (RL) motion. For the AP and SI axes, accuracy was sub-millimetre. It may be feasible to track prostate motion in 2D only. 3D-US also has the potential to improve high tracking accuracy for all motion types. It would be advisable to use US in conjunction with a small (∼2.0 mm) centre-of-mass displacement threshold in which case it would be possible to take full advantage of the accuracy and high imaging rate capability.

Detecting hepatic steatosis using ultrasound-induced thermal strain imaging: an ex vivo animal study

Hepatic steatosis or fatty liver disease occurs when lipids accumulate within the liver and can lead to steatohepatitis, cirrhosis, liver cancer and eventual liver failure requiring liver transplant. Conventional brightness mode (B-mode) ultrasound (US) is the most common noninvasive diagnostic imaging modality used to diagnose hepatic steatosis in clinics. However, it is mostly subjective or requires a reference organ such as the kidney or spleen with which to compare. This comparison can be problematic when the reference organ is diseased or absent. The current work presents an alternative approach to noninvasively detecting liver fat content using US-induced thermal strain imaging (US-TSI). This technique is based on the difference in the change in the speed of sound as a function of temperature between water- and lipid-based tissues. US-TSI was conducted using two system configurations including a mid-frequency scanner with a single linear array transducer (5-14 MHz) for both imaging and heating and a high-frequency (13-24 MHz) small animal imaging system combined with a separate custom-designed US heating transducer array. Fatty livers (n = 10) with high fat content (45.6 ± 11.7%) from an obese mouse model and control livers (n = 10) with low fat content (4.8 ± 2.9%) from wild-type mice were embedded in gelatin. Then, US imaging was performed before and after US induced heating. Heating time periods of ∼ 3 s and ∼ 9.2 s were used for the mid-frequency imaging and high-frequency imaging systems, respectively, to induce temperature changes of approximately 1.5 °C. The apparent echo shifts that were induced as a result of sound speed change were estimated using 2D phase-sensitive speckle tracking. Following US-TSI, histology was performed to stain lipids and measure percentage fat in the mouse livers. Thermal strain measurements in fatty livers (-0.065 ± 0.079%) were significantly (p < 0.05) higher than those measured in control livers (-0.124 ± 0.037%). Using histology as a gold standard to classify mouse livers, US-TSI had a sensitivity and specificity of 70% and 90%, respectively. The area under the receiver operating characteristic curve was 0.775. This ex vivo study demonstrates the feasibility of using US-TSI to detect fatty livers and warrants further investigation of US-TSI as a diagnostic tool for hepatic steatosis.

Histotripsy cardiac therapy system integrated with real-time motion correction

Histotripsy has shown promise in non-invasive cardiac therapy for neonatal and fetal applications. However, for cardiac applications in general, and especially in the adult heart, cardiac and respiratory motion may affect treatment accuracy and efficacy. In this article, we describe a histotripsy-mediated cardiac therapy system integrated with a fast motion tracking algorithm and treatment monitoring using ultrasound imaging. Motion tracking is performed by diamond search block matching in real-time ultrasound images using a reference image of the moving target, refined by Kalman filtering. As proof of feasibility, this algorithm was configured to track 2-D target motion and then electronically adjust the focus of a 1-MHz annular therapy array to correct for axial motion. This integrated motion tracking system is capable of sub-millimeter accuracy for displacements of 0-15 mm and velocities of 0-80 mm/s, with a maximum error less than 3 mm. Tissue phantom tests indicated that treatment efficiency and lesion size using motion tracking over displacements of 0-15 mm and velocities of 0-42 mm/s are comparable to those achieved when treating stationary targets. In vivo validation was conducted in an open-chest canine model, where the system provided 24 min of motion-corrected histotripsy therapy in the live beating heart, generating a targeted lesion on the atrial septum. Based on this proof of feasibility and the natural extension of these techniques to three dimensions, we anticipate a full motion correction system would be feasible and beneficial for non-invasive cardiac therapy.

Automatic needle detection and tracking in 3D ultrasound using an ROI-based RANSAC and Kalman method

This article proposes a robust technique for needle detection and tracking using three-dimensional ultrasound (3D US). It is difficult for radiologists to detect and follow the position of micro tools, such as biopsy needles, that are inserted in human tissues under 3D US guidance. To overcome this difficulty, we propose a method that automatically reduces the processed volume to a limited region of interest (ROI), increasing at the same time the calculation speed and the robustness of the proposed technique. First, a line filter method that enhances the contrast of the needle against the background is used to facilitate the initialization of ROI using the tubularness information of the complete US volume. Then, the random sample consensus (RANSAC) and Kalman filter (RK) algorithm is used in the ROI to detect and track the precise position of the needle. A series of numerical inhomogeneous phantoms with a needle simulated from real 3D US volumes are used to evaluate our method. The results show that the proposed method is much more robust than the RANSAC algorithm when detecting the needle, regardless of whether or not the insertion axis corresponds to an acquisition plane in the 3D US volume. The possibility of failure is also discussed in this article.

Tibial nerve excursion during lumbar spine and hip flexion measured with diagnostic ultrasound

Ultrasound imaging provides a method for non-invasive in vivo measurement of nerve motion resulting from joint movement. This study measured the proximal excursion of the tibial branch of the sciatic nerve at the popliteal fossa during forward bending in healthy subjects. Long-axis image sequences of the nerve were analysed using frame-by-frame cross-correlation software that calculated the longitudinal and axial movement of the nerve. Proximal excursion was calculated from the hypotenuse of these values. The mean proximal excursion recorded was 12.2 mm (SD 2.2 mm, n = 24). The reliability of three repeat measurements was found to be excellent (ICC 0.97, 95% CI 0.93-0.99; SEM 0.7 mm, n = 21). The protocol described provides a reliable method for analysing tibial nerve movement that could prove useful in future clinical studies.

Ultrasound echoes as biometric navigators

We demonstrate a new method of using ultrasound data to achieve prospective motion compensation in MRI, especially for respiratory motion during interventional MRI procedures in moving organs such as the liver. The method relies on fingerprint-like biometrically distinct ultrasound echo patterns produced by different locations in tissue, which are collated with geometrical information from MRI during a training stage to form a mapping table that relates ultrasound measurements to positions. During prospective correction, the system makes frequent ultrasound measurements and uses the map to determine the corresponding position. Results in motorized linear motion phantoms and freely breathing animals indicate that the system performs well. Apparent motion is reduced by up to 97.8%, and motion artifacts are reduced or eliminated in two-dimensional spoiled gradient-echo images. The motion compensation is sufficient to permit MRI thermometry of focused ultrasound heating during respiratory-like motion, with results similar to those obtained in the absence of motion. This new technique may have applications for MRI thermometry and other dynamic imaging in the abdomen during free breathing.