Troy K. Adebar

3-D ultrasound-guided robotic needle steering in biological tissue.

Robotic needle steering systems have the potential to greatly improve medical interventions, but they require new methods for medical image guidance. Three-dimensional (3-D) ultrasound is a widely available, low-cost imaging modality that may be used to provide real-time feedback to needle steering robots. Unfortunately, the poor visibility of steerable needles in standard grayscale ultrasound makes automatic segmentation of the needles impractical. A new imaging approach is proposed, in which high-frequency vibration of a steerable needle makes it visible in ultrasound Doppler images. Experiments demonstrate that segmentation from this Doppler data is accurate to within 1-2 mm. An image-guided control algorithm that incorporates the segmentation data as feedback is also described. In experimental tests in ex vivo bovine liver tissue, a robotic needle steering system implementing this control scheme was able to consistently steer a needle tip to a simulated target with an average error of 1.57 mm. Implementation of 3-D ultrasound-guided needle steering in biological tissue represents a significant step toward the clinical application of robotic needle steering.

3D ultrasound to stereoscopic camera registration through an air-tissue boundary

A novel registration method between 3D ultrasound and stereoscopic cameras is proposed based on tracking a registration tool featuring both ultrasound fiducials and optical markers. The registration tool is pressed against an air-tissue boundary where it can be seen both in ultrasound and in the camera view. By localizing the fiducials in the ultrasound volume, knowing the registration tool geometry, and tracking the tool with the cameras, a registration is found. This method eliminates the need for external tracking, requires minimal setup, and may be suitable for a range of minimally invasive surgeries. A study of the appearance of ultrasound fiducials on an air-tissue boundary is presented, and an initial assessment of the ability to localize the fiducials in ultrasound with sub-millimeter accuracy is provided. The overall accuracy of registration (1.69 +/- 0.60 mm) is a noticeable improvement over other reported methods and warrants patient studies.

A robotic system for intra-operative trans-rectal ultrasound and ultrasound elastography in radical prostatectomy

A new robotic system for trans-rectal ultrasound (TRUS) imaging during robot-assisted laparoscopic radical prostatectomy is described. The system consists of three main parts: a robotic probe manipulator (robot), an ultrasound machine with a biplane TRUS probe, and control and image processing software. A review of prior use of TRUS during prostatectomy is provided in order to demonstrate the potential benefits of such intra-operative imaging. The ability of the system to capture two-dimensional and three-dimensional B-mode and elastography data is demonstrated using a prostate phantom. A registration method that can be used for instrument tracking in RALRP is described and tested. Initial patient images captured using the system are presented.

Methods for Improving the Curvature of Steerable Needles in Biological Tissue

Objective: Robotic needle steering systems have the potential to improve percutaneous interventions such as radiofrequency ablation of liver tumors, but steering techniques described to date have not achieved sufficiently small radius of curvature in biological tissue to be relevant to this application. In this study, the impact of tip geometry on steerable needle curvature was examined. Methods: Finite-element simulations and experiments with bent-tip needles in ex vivo liver tissue were performed. Motivated by the results of this analysis, a new articulated-tip steerable needle was designed, in which a distal section is actively switched by a robotic system between a straight tip (resulting in a straight path) and a bent tip (resulting in a curved path). Results: Selection of tip length and angle can greatly improve curvature, with radius of curvature below 5 cm in liver tissue possible through judicious selection of these parameters. An articulated-tip mechanism allows the tip length and angle to be increased, while the straight configuration allows the needle tip to still pass through an introducer sheath and rotate inside the body. Conclusion: Validation testing in liver tissue shows that the new articulated-tip steerable needle achieves smaller radius of curvature compared to bent-tip needles described in previous work. Significance: Steerable needles with optimized tip parameters, which can generate tight curves in liver tissue, increase the clinical relevance of needle steering to percutaneous interventions.

3D segmentation of curved needles using doppler ultrasound and vibration

A method for segmenting the 3D shape of curved needles in solid tissue is described. An actuator attached to the needle outside the tissue vibrates at frequencies between 600 Hz and 6500 Hz, while 3D power Doppler ultrasound imaging is applied to detect the resulting motion of the needle shaft and surrounding tissue. The cross section of the vibrating needle is detected across the series of 2D images produced by a mechanical 3D ultrasound transducer, and the needle shape is reconstructed by fitting a 3D curve to the resulting points. The sensitivity of segmentation accuracy to tissue composition, vibration frequency, and Doppler pulse repetition frequency (PRF) was examined. Comparison with manual segmentation demonstrates that this method results in an average error of 1.09 mm in ex vivo tissue. This segmentation method may be useful in the future for providing feedback on curved needle shape for control of robotic needle steering systems.

Automatic Localization of the da Vinci Surgical Instrument Tips in 3-D Transrectal Ultrasound

Robot-assisted laparoscopic radical prostatectomy (RALRP) using the da Vinci surgical system is the current state-of-the-art treatment option for clinically confined prostate cancer. Given the limited field of view of the surgical site in RALRP, several groups have proposed the integration of transrectal ultrasound (TRUS) imaging in the surgical workflow to assist with accurate resection of the prostate and the sparing of the neurovascular bundles (NVBs). We previously introduced a robotic TRUS manipulator and a method for automatically tracking da Vinci surgical instruments with the TRUS imaging plane, in order to facilitate the integration of intraoperative TRUS in RALRP. Rapid and automatic registration of the kinematic frames of the da Vinci surgical system and the robotic TRUS probe manipulator is a critical component of the instrument tracking system. In this paper, we propose a fully automatic registration technique based on automatic 3-D TRUS localization of robot instrument tips pressed against the air-tissue boundary anterior to the prostate. The detection approach uses a multiscale filtering technique to identify and localize surgical instrument tips in the TRUS volume, and could also be used to detect other surface fiducials in 3-D ultrasound. Experiments have been performed using a tissue phantom and two ex vivo tissue samples to show the feasibility of the proposed methods. Also, an initial in vivo evaluation of the system has been carried out on a live anaesthetized dog with a da Vinci Si surgical system and a target registration error (defined as the root mean square distance of corresponding points after registration) of 2.68 mm has been achieved. Results show this methods accuracy and consistency for automatic registration of TRUS images to the da Vinci surgical system.

Real-Time 3D Curved Needle Segmentation Using Combined B-Mode and Power Doppler Ultrasound

This paper presents a real-time segmentation method for curved needles in biological tissue based on analysis of B-mode and power Doppler images from a tracked 2D ultrasound transducer. Mechanical vibration induced by an external voice coil results in a Doppler response along the needle shaft, which is centered around the needle section in the ultrasound image. First, B-mode image analysis is performed within regions of interest indicated by the Doppler response to create a segmentation of the needle section in the ultrasound image. Next, each needle section is decomposed into a sequence of points and transformed into a global coordinate system using the tracked transducer pose. Finally, the 3D shape is reconstructed from these points. The results of this method differ from manual segmentation by 0.71 ± 0.55 mm in needle tip location and 0.38 ± 0.27 mm along the needle shaft. This method is also fast, taking 5-10 ms to run on a standard PC, and is particularly advantageous in robotic needle steering, which involves thin, curved needles with poor echogenicity.

Recursive estimation of needle pose for control of 3D-ultrasound-guided robotic needle steering

Robotic systems can improve percutaneous interventions by steering flexible needles along nonlinear trajectories. These systems require medical image feedback for accurate closed-loop control. Three-dimensional (3D) ultrasound can provide real-time measurements of needle pose within tissue; however, the ultrasound produces relatively large amounts of measurement noise. A recursive estimation approach is described for accurately estimating the six-degree-of-freedom pose of a steerable needle tip, by applying an unscented Kalman filter (UKF) to 3D ultrasound segmentation results. The UKF is formulated based on a kinematic process model of needle steering, as well as experimental quantification of the statistical variability of steering and imaging needles in biological tissue. Validation testing shows that the UKF method makes accurate closed-loop robotic control of the needle tip possible in biological tissue. Compared to direct use of noisy ultrasound data for control feedback, the UKF reduced average positioning error by 9.58 mm (81%) when steering towards a simulated target. This new estimation scheme will contribute towards the future evaluation of needle steering robots in real-world clinical applications.

Automatic detection and localization of da vinci tool tips in 3d ultrasound

Radical prostatectomy (RP) is viewed by many as the gold standard treatment for clinically localized prostate cancer. State of the art radical prostatectomy involves the da Vinci surgical system, a laparoscopic robot which provides the surgeon with excellent 3D visualization of the surgical site and improved dexterity over standard laparoscopic instruments. Given the limited field of view of the surgical site in Robot-Assisted Laparoscopic Radical Prostatectomy (RALRP), several groups have proposed the integration of Transrectal Ultrasound (TRUS) imaging in the surgical work flow to assist with the resection of prostate and sparing the Neuro-Vascular Bundle (NVB). Rapid and automatic registration of TRUS imaging coordinates to the da Vinci tools or camera is a critical component of this integration. We propose a fully automatic registration technique based on accurate and automatic localization of robot tool tips pressed against the air-tissue boundary of the prostate, in 3D TRUS. The detection approach uses a multi-scale filtering technique to uniquely identify and localize the tool tip in the ultrasound volume and could also be used to detect other surface fiducials in 3D ultrasound. Feasibility experiments using a phantom and two ex vivo tissue samples yield promising results with target registration error (defined as the root mean square distance of corresponding points after registration) of (

Remote electromagnetic vibration of steerable needles for imaging in power Doppler ultrasound

1.80\ mm