H. Tutkun Sen

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

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.

A cooperatively controlled robot for ultrasound monitoring of radiation therapy

Image-guided radiation therapy (IGRT) involves two main procedures, performed in different rooms on different days: (1) treatment planning in the simulator room on the first day, and (2) radiotherapy in the linear accelerator room over multiple subsequent days. Both the simulator and the linear accelerator include CT imaging capabilities, which enables both treatment planning and reproducible patient setup, but does not provide good soft tissue contrast or allow monitoring of the target during treatment. We propose a cooperatively-controlled robot to reproducibly position an ultrasound (US) probe on the patient during simulation and treatment, thereby improving soft tissue visualization and allowing real-time monitoring of the target. A key goal of the robotic system is to produce consistent tissue deformations for both CT and US imaging, which simplifies registration of these two modalities. This paper presents the robotic system design and describes a novel control algorithm that employs virtual springs to implement guidance virtual fixtures during “hands on” cooperative control.

Enabling technologies for natural orifice transluminal endoscopic surgery (N.O.T.E.S) using robotically guided elasticity imaging

Natural orifice transluminal endoscopic surgery (N.O.T.E.S) is a minimally invasive surgical technique that could benefit greatly from additional methods for intraoperative detection of tissue malignancies (using elastography) along with more precise control of surgical tools. Ultrasound elastography has proven itself as an invaluable imaging modality. However, elasticity images typically suffer from low contrast when imaging organs from the surface of the body. In addition, the palpation motions needed to generate elastography images useful for identifying clinically significant changes in tissue properties are difficult to produce because they require precise axial displacements along the imaging plane. Improvements in elasticity imaging necessitate an approach that simultaneously removes the need for imaging from the body surface while providing more precise palpation motions. As a first step toward performing N.O.T.E.S in-vivo, we integrated a phased ultrasonic micro-array with a flexible snake-like robot. The integrated system is used to create elastography images of a spherical isoechoic lesion (approximately 5mm in cross-section) in a tissue-mimicking phantom. Images are obtained by performing robotic palpation of the phantom at the location of the lesion.

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 real-time 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.

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.

Force-controlled ultrasound robot for consistent tissue pre-loading: Implications for acoustic radiation force elasticity imaging

Acoustic radiation force (ARF)-based measurements of tissue elasticity require transmission of an acoustic pulse and ultrasound image-based tracking of the resulting tissue displacements. This technique provides diagnostic information about various disease states of tissue. One limitation, however, is the dependency on applied probe pressure, which is difficult to control manually and prohibits standardization of quantitative measurements. To overcome this limitation, we introduce a custom-built robot that controls probe contact forces. The robot was evaluated in an in vivo canine prostate and ex vivo bovine liver. Markers implanted in the prostate were visualized with 3D probe contact forces (i.e. tissue pre-loading) that ranged 10-11 N. The resulting displacement of the markers were evaluated to estimate the variability in pre-loading strains that could exist prior to making an ARF-based elasticity measurement. One standard deviation of corresponding strains ranged 0-2%. In the ex vivo liver, differences in speckle-tracked tissue displacements were observed when the probe sustained tissue contact as it returned to its initial position, indicating that there is a potential benefit in losing tissue contact prior to taking measurements that will be used for standardization (e.g. to avoid differences in pre-loading and corresponding tissue elasticity). Results are promising for the introduction of robotic systems to control the applied probe pressure for ARF-based measurements of tissue elasticity.

Particle filtering to improve the dynamic accuracy of electromagnetic tracking

Tracking systems play a crucial role in many computer-assisted interventions by providing precise tool position and orientation with respect to the patient anatomy. In this study, we focus on a Particle Filtering (PF) approach to enhance the dynamic tracking performance of an electromagnetic tracking (EMT) system, even when the transmit coils are driven sequentially and/or the receive coils are not sampled simultaneously (indeed, it is applicable to any EMT system). The PF is applied to a custom EMT that consists of an array of transmitting coils and one (or more) receiving coils. The dynamic tracking accuracy is tested using a motorized linear stage to precisely move the receiving coil at different velocities. The results indicate that the PF provides an accurate estimate of the 5 degree of freedom (DOF) position and orientation of the receiving coil. Furthermore, it is shown that the dynamic tracking error is independent of the velocity for the range of velocities tested.

SU‐E‐U‐13: Repeatability of Robotic Placement of Ultrasound Probes for An Integrated US‐CT Approach to Image‐Guided Radiotherapy

Purpose: Ultrasound (US) has potential to provide real‐time monitoring of radiotherapy, but the tissue deformations and CT artifacts caused by US probes limit clinical utility. This work investigates the repeatability of robot‐assisted placement of geometically‐identical imaging and model probes. The CT‐compatible model is proposed for use during treatment planning. Methods: An ex vivo bovine liver was fixed in gelatin. Six 2mm‐diameter spherical metallic fiducials were embedded in the liver at depths 1– 2cm and 4–5cm. Volumetric data were acquired with a Philips CT scanner and Elekta Clarity® ultrasound system. Probe placement was controlled with a robot consisting of a passive arm, three translation stages, and a sensor to monitor probe‐tissue contact forces. Fiducial positions were measured in US images acquired after placement of the imaging probe, as well as in CT images acquired before and after placement of both probes. Results: The mean absolute difference between fiducial displacements after six repeated probe placements was 0.4±0.4 mm in US images and 0.3±0.2 mm in CT images acquired with the model probe. Maximum displacements generally occurred in the anterior‐posterior (AP) direction (i.e. normal to the probe), where the imaging and model probes displaced the three shallow fiducials by 5.0±1.7mm and 3.7±1.6mm, respectively. The AP displacement of the three deeper fiducials was 1.0±0.7mm with the model probe. The mean contact forces of the imaging and model probes were 1.3±0.13N and 0.3±0.01N, respectively, for the shallow fiducials, and 1.1±0.2N and 0.1±0.02N, respectively, for the deeper fiducials. Conclusions: Robot position, fiducial displacements, and contact forces were sufficiently repeatable with either probe. Displacement and force discrepancies between probes are likely due to weight and alignment differences. Solutions to reduce the discrepancies are under investigation. Yet, with <2mm mean difference between probes, this work is promising as it demonstrates the feasibility of a potentially revolutionary approach to IGRT. This work is supported in part by NCI CA R01‐161613.

Bayesian filtering to improve the dynamic accuracy of electromagnetic tracking

Tracking systems are essential components for many computer assisted interventions because they enable the doctor to visualize anatomical information, derived from preoperative or intraoperative images, registered with respect to the actual patient anatomy. This paper presents two applications of Bayesian filters: Particle Filter (PF) and Extended Kalman Filter (EKF) to obtain accurate dynamic tracking performance from an electromagnetic tracking (EMT) system, even if the EMT cannot provide the full measurement state at each sampling interval (for example, when transmit coils are driven sequentially and/or receive coils are not sampled simultaneously). Experiments are performed with a custom EMT system, consisting of a transmitter coil array and one or more receiving coils, to demonstrate that the proposed method provides good dynamic tracking accuracy at different velocities.

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

Abstract 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.