System integration and preliminary in-vivo experiments of a robot for ultrasound guidance and monitoring during radiotherapy

Şen, H. Tutkun; Bell, Muyinatu A. Lediju; Zhang, Yin; Ding, Kai; Wong, John; Iordachita, Iulian; Kazanzides, Peter

doi:10.1109/icar.2015.7251433

Cited by 16 publications

(10 citation statements)

References 15 publications

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“…To address the first concern, the robot can be programmed to enable similar maneuverability to a free-hand approach with cooperative control, as described in our previous publications [36], [42]. With cooperative control, the robot and operator share control of the ultrasound probe via a force sensor that determines the direction of external forces applied (representative of the direction that the operator intends to move the probe).…”

Section: Discussionmentioning

confidence: 99%

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

Bell

Kumar

Kuo

et al. 2016

IEEE Trans. Biomed. Eng.

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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.

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Section: Discussionmentioning

confidence: 99%

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

Bell

Kumar

Kuo

et al. 2016

IEEE Trans. Biomed. Eng.

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“…The robot software contains an interface to the optical tracking system (Polaris, Northern Digital Inc., Waterloo, ON, Canada). In our clinical environment, the interface to the ceiling-mounted tracking system is provided by a research version of the Clarity System, as described for the in vivo canine experiments reported in Sen et al (2015). For the phantom experiments reported here, we use a direct connection to a tracking system mounted on a tripod.…”

Section: Robot Systemmentioning

confidence: 99%

“…The workflow is separated into a planning day, where the planning images of the patient are acquired, and multiple (fractionated) treatment days, where the radiation therapy is delivered. A more detailed discussion of this workflow can be found in Bell et al (2014) and Sen et al (2015). In this section, we focus on the use of cooperative control within this workflow.…”

Section: Cooperative Control In the Radiotherapy Workflowmentioning

confidence: 99%

Cooperative Control with Ultrasound Guidance for Radiation Therapy

et al. 2016

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Radiation therapy typically begins with the acquisition of a CT scan of the patient for planning, followed by multiple days where radiation is delivered according to the plan. This requires that the patient be reproducibly positioned (set up) on the radiation therapy device (linear accelerator) such that the radiation beams pass through the target. Modern linear accelerators provide cone-beam computed tomography (CBCT) imaging, but this does not provide sufficient contrast to discriminate many abdominal soft-tissue targets, and therefore patient setup is often done by aligning bony anatomy or implanted fiducials. Ultrasound (US) can be used to both assist with patient setup and to provide real-time monitoring of soft-tissue targets. However, one challenge is that the ultrasound probe contact pressure can deform the target area and cause discrepancies with the treatment plan. Another challenge is that radiation therapists typically do not have ultrasound experience and therefore cannot easily find the target in the US image. We propose cooperative control strategies to address both the challenges. First, we use cooperative control with virtual fixtures (VFs) to enable acquisition of a planning CT that includes the soft-tissue deformation. Then, for the patient setup during the treatment sessions, we propose to use real-time US image feedback to dynamically update the VFs; this co-manipulation strategy provides haptic cues that guide the therapist to correctly place the US probe. A phantom study is performed to demonstrate that the co-manipulation strategy enables inexperienced operators to quickly and accurately place the probe on a phantom to reproduce a desired reference image. This is a necessary step for patient setup and, by reproducing the reference image, creates soft-tissue deformations that are consistent with the treatment plan, thereby enabling real-time monitoring during treatment delivery.

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“…At this point, image based tracking methods can be used to track the needle tip. A robot can guide the US probe to collect images during operation [1]. The robot assisted US probe on the patient can produce tissue deformation, which might cause the imaging plane to shift, and could result in failure to track the needle tip.…”

Section: Introductionmentioning

confidence: 99%

Visual tracking of biopsy needles in 2D ultrasound images

Kaya

Senel

Ahmad

et al. 2016

2016 IEEE International Conference on Robotics and Automation (ICRA)

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Due to copyright restrictions, the access to the full text of this article is only available via subscription.Ultrasound (US) is one the most commonly used medical imaging techniques in percutaneous needle procedures. However, US images are inherently noisy and contain excessive number of artifacts. Hence, it is not easy to track the needle tip in the US images during the needle insertions. At this point, image based visual tracking techniques can be used for needle tip tracking. This paper presents a method for visual tracking of biopsy needles in 2D US images using sum of squared differences and sum of conditional variances. Second order Gauss-Newton optimization is used to decrease processing time and make the tracking more robust. The needle template images used in the method are updated with a strategy to prevent needle loss and detection failures during tracking. The paper also explains how to identify needle losses during tracking and how to recover the needle position without using a needle localization algorithm. We demonstrate the precision of the visual needle tip tracking method with experiments under challenging tracking conditions.TÜBİTA

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System integration and preliminary in-vivo experiments of a robot for ultrasound guidance and monitoring during radiotherapy

Cited by 16 publications

References 15 publications

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

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

Cooperative Control with Ultrasound Guidance for Radiation Therapy

Visual tracking of biopsy needles in 2D ultrasound images

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