Aim: Precise targeting is essential for adequate treatment of lesions during image-guided therapy. The aim of this study was to compare the performance of two emerging image-guided targeting technologies in a phantom model. Materials and Methods: A computer-assisted navigation system and AcuBot were tested using three operators: an interventional radiologist and two endourologists. Fiducials were placed in an anatomic gelatin phantom and targeted by both systems. The images were reconstructed and analyzed using a specialized software package (Amira; Visage Imaging, Carlsbad, CA). Accuracy was assessed by measuring proximity of the tip of the needle to the fiducial on computed-tomography-guided imaging. Accuracy and time to target were quantified and compared. Results: The mean distance from the desired target for AcuBot was 1.2 mm (range: 0.39-2.82). The mean distance from the desired target for the navigation system was 5.8 mm (range: 1.8-11.9). The AcuBot was significantly more accurate than the navigation system ( p < 0.0001). The mean time from target acquisition to needle placement was 37 seconds (range: 15-75) for the AcuBot and 108 seconds (range: 45-315) for the navigation system ( p ¼ 0.001). Conclusion: Emerging technologies hold promise for increased accuracy during percutaneous targeted procedures. Both the AcuBot and the computer-assisted navigation system were accurate and efficient in a phantom targeting model. AcuBot was significantly more accurate, faster, and less user dependent than the navigation system. Further studies in animal and clinical studies are warranted to further advance this promising technology.
INTRODUCTION-The preservation of the neurovascular bundle (NVB) during radical prostatectomy improves the postoperative recovery of sexual potency. The accompanying blood vessels in the NVB can serve as a macroscopic landmark to localize the microscopic cavernous nerves in the NVB. We examined the feasibility of image-guided navigation using transrectal ultrasound (TRUS) to visualize NVB during robot assisted laparoscopic radical prostatectomy (RALP).
Animal models are widely used to explore the mechanisms underlying sensorimotor control and learning. However, current experimental paradigms allow only limited control over task difficulty and cannot provide detailed information on forelimb kinematics and dynamics. Here we propose a novel robotic device for use in motor learning investigations with rats. The compact, highly transparent, three degree-of-freedom manipulandum is capable of rendering nominal forces of 2 N to guide or perturb rat forelimb movements, while providing objective and quantitative assessments of endpoint motor performance in a 50×30 mm(2) planar workspace. Preliminary experiments with six healthy rats show that the animals can be familiarized with the experimental setup and are able to grasp and manipulate the end-effector of the robot. Further, dynamic perturbations and guiding force fields (i.e., haptic tunnels) rendered by the device had significant influence on rat motor behavior (ANOVA, ). This approach opens up new research avenues for future characterizations of motor learning stages, both in healthy and in stroke models.
Our hands and fingers are involved in almost all activities of daily living and, as such, have a disproportionately large neural representation. Functional magnetic resonance imaging investigations into the neural control of the hand have revealed great advances, but the harsh MRI environment has proven to be a challenge to devices capable of delivering a large variety of stimuli necessary for well-controlled studies. This paper presents a fMRI-compatible haptic interface to investigate the neural mechanisms underlying precision grasp control. The interface, located at the scanner bore, is controlled remotely through a shielded electromagnetic actuation system positioned at the end of the scanner bed and then through a high stiffness, low inertia cable transmission. We present the system design, taking into account requirements defined by the biomechanics and dynamics of the human hand, as well as the fMRI environment. Performance evaluation revealed a structural stiffness of 3.3 N/mm, renderable forces up to 94 N, and a position control bandwidth of at least 19 Hz. MRI-compatibility tests showed no degradation in the operation of the haptic interface or the image quality. A preliminary fMRI experiment during a pilot study validated the usability of the haptic interface, illustrating the possibilities offered by this device.
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