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

O’Shea, Tuathan; Garcia, Leo; Rosser, K E; Harris, Emma; Evans, Philip; Bamber, Jeffrey C.

doi:10.1088/0031-9155/59/7/1701

Cited by 19 publications

(16 citation statements)

References 43 publications

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“…[3]- [5], in-vivo validation of real-time target localization remains challenging due to the difficulty to obtain a reliable ground truth. So far, this has either been restricted by the inter-and intra-observer variability of manual annotations, which are difficult to obtain in ultrasound volumes [6], or been limited to static scenarios where the setup accuracy of ultrasound is compared to another target localization modality [5,7].…”

Section: Introductionmentioning

confidence: 99%

Simultaneous acquisition of 4D ultrasound and wireless electromagnetic tracking for in-vivo accuracy validation

Ipsen

Bruder

Worm

et al. 2017

Current Directions in Biomedical Engineering

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Ultrasound is being increasingly investigated for real-time target localization in image-guided interventions. Yet, in-vivo validation remains challenging due to the difficulty to obtain a reliable ground truth. For this purpose, real-time volumetric (4D) ultrasound imaging was performed simultaneously with electromagnetic localization of three wireless transponders implanted in the liver of a radiotherapy patient. 4D ultrasound and electromagnetic tracking were acquired at framerates of 12Hz and 8Hz, respectively, during free breathing over 8 min following treatment. The electromagnetic antenna was placed directly above and the ultrasound probe on the right side of the patient to visualize the liver transponders. It was possible to record 25.7 s of overlapping ultrasound and electromagnetic position data of one transponder. Good spatial alignment with 0.6 mm 3D root-mean-square error between both traces was achieved using a rigid landmark transform. However, data acquisition was impaired since the electromagnetic tracking highly influenced the ultrasound equipment and vice versa. High intensity noise streaks appeared in the ultrasound scan lines irrespective of the chosen frequency (1.7-3.3 MHz, 2/4 MHz harmonic). To allow for target visualization and tracking in the ultrasound volumes despite the artefacts, an online filter was designed where corrupted pixels in the newest ultrasound frame were replaced with non-corrupted pixels from preceding frames. Aside from these artefacts, the recorded electromagnetic tracking data was fragmented and only the transponder closest to the antenna could be detected over a limited period of six consecutive breathing cycles. This problem was most likely caused by interference from the metal holder of the ultrasound probe and was solved in a subsequent experiment using a 3D-printed non-metal probe fixation. Real-time wireless electromagnetic tracking was compared with 4D ultrasound imaging in-vivo for the first time. For stable tracking, large metal components need to be avoided during data acquisition and ultrasound filtering is required.

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Section: Introductionmentioning

confidence: 99%

Simultaneous acquisition of 4D ultrasound and wireless electromagnetic tracking for in-vivo accuracy validation

Ipsen

Bruder

Worm

et al. 2017

Current Directions in Biomedical Engineering

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“…Previous work demonstrates the feasibility of real-time volumetric monitoring of intrafraction organ motion using an intrinsic property of US images known as speckle. [9][10][11][12] In addition, the radiation therapy LINAC does not affect speckle tracking algorithms, 13 while commercially-available optical tracking systems may be used to relate speckle tracking coordinates to the treatment room coordinate system. 14,15 For subtle probe adjustments that may be required during treatment, a haptic teleoperated robotic system was introduced by Schlosser et al 16 with minimal treatment plan modifications required to accommodate the robot and US probe.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2014

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Abstract. 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.

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“…Both the training and testing data involved 64 2D+t sequences; herein, the training size is 25, while the testing size is 39. The data had varying spatial (0.27-0.77 mm) and temporal resolution (11)(12)(13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30). The training data were annotated by CLUST as ground truth (center of blood vessels) of fiducial features throughout the acquisition sequence.…”

Section: A Liver Ultrasound Data and Attention-aware Video Generationmentioning

confidence: 99%

“…11 Up to this point, majority approaches of object tracking involve a search over multiple window candidates based on a similarity measure, such as template matching. O'Shea et al 12 applied 3D cross-correlation block matching to track speckle in the ultrasound image and achieved high tracking accuracy at a cost of computational speed. Shepard et al 13 utilized a similarity-based block matching algorithm with incorporation of training methods and multiple simultaneous templates.…”

Section: Introductionmentioning

confidence: 99%

Attention‐aware fully convolutional neural network with convolutional long short‐term memory network for ultrasound‐based motion tracking

Huang

Lü

et al. 2019

Medical Physics

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Purpose One of the promising options for motion management in radiation therapy (RT) is the use of LINAC‐compatible robotic‐arm‐mounted ultrasound imaging system due to its high soft tissue contrast, real‐time capability, absence of ionizing radiation, and low cost. The purpose of this work is to develop a novel deep learning‐based real‐time motion tracking strategy for ultrasound image‐guided RT. Methods The proposed tracker combined the attention‐aware fully convolutional neural network (FCNN) and the convolutional long short‐term memory network (CLSTM) that is end‐to‐end trainable. The glimpse sensor module was built inside the attention‐aware FCNN to discard majority of background by focusing on a region containing the object of interest. FCNN extracted discriminating spatial features of glimpse to facilitate temporal modeling for CLSTM. The saliency mask computed from CLSTM refined the features particular to the tracked landmarks. Moreover, the multitask loss strategy including bounding box loss, localization loss, saliency loss, and adaptive loss weighting term was utilized to facilitate training convergence and avoid over/underfitting. The tracker was tested on the databases provided by MICCAI 2015 challenges, and the ground truth data were obtained with the help of brute force‐based template matching technology. Results The mean tracking error of 0.97 ± 0.52 mm and maximum tracking error of 1.94 mm were observed for 85 point landmarks across 39 ultrasound cases compared to the ground truth annotations. The tracking speed per frame per landmark with the GPU implementation ranged from 66 and 101 frames per second, which largely exceeded the ultrasound imaging rate. Conclusion The results demonstrated the robustness and accuracy of the proposed deep learning‐based motion estimation, despite the existence of some known shortcomings of ultrasound imaging such as speckle noise. The tracking speed of the system was found to be remarkable, sufficiently fast for real‐time applications in RT environment. The approach provides a valuable tool to guide RT treatment with beam gating or multileaf collimator (MLC) tracking in real time.

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

Cited by 19 publications

References 43 publications

Simultaneous acquisition of 4D ultrasound and wireless electromagnetic tracking for in-vivo accuracy validation

Simultaneous acquisition of 4D ultrasound and wireless electromagnetic tracking for in-vivo accuracy validation

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

Attention‐aware fully convolutional neural network with convolutional long short‐term memory network for ultrasound‐based motion tracking

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