Design and evaluation of a computed tomography (CT)-compatible needle insertion device using an electromagnetic tracking system and CT images

Purpose Percutaneous needle insertion procedures are commonly used for diagnostic and therapeutic purposes. Although current technology allows accurate localization of lesions, they cannot yet be precisely targeted. Lung cancer is the most common cause of cancer-related death, and early detection reduces the mortality rate. Therefore, suspicious lesions are tested for diagnosis by performing needle biopsy. Methods In this paper, we have presented a novel computed tomography (CT)-compatible needle insertion device (NID). The NID is used to steer a flexible needle (ϕ0.55mm ϕ0.55mm) with a bevel at the tip in biological tissue. CT images and an electromagnetic (EM) tracking system are used in two separate scenarios to track the needle tip in three-dimensional space during the procedure. Our system uses a control algorithm to steer the needle through a combination of insertion and minimal number of rotations. Results Noise analysis of CT images has demonstrated the compatibility of the device. The results for three experimental cases (case 1: open-loop control, case 2: closed-loop control using EM tracking system and case 3: closed-loop control using CT images) are presented. Each experimental case is performed five times, and average targeting errors are 2.86±1.14 2.86±1.14, 1.11±0.14 1.11±0.14 and 1.94 0.63mm 1.94±0.63mm for case 1, case 2 and case 3, respectively. Conclusions The achieved results show that our device is CT-compatible and it is able to steer a bevel-tipped needle toward a target. We are able to use intermittent CT images and EM tracking data to control the needle path in a closed-loop manner. These results are promising and suggest that it is possible to accurately target the lesions in real clinical procedures in the future

3D motion tracking of pulmonary lesions using CT fluoroscopy images for robotically assisted lung biopsy

ABSTRACT We are developing a prototype system for robotically assisted lung biopsy. For directing the robot in biopsy needle placement, we propose a non-invasive algorithm to track the 3D position of the target lesion using 2D CT fluoroscopy image sequences. A small region of the CT fluoroscopy image is registered to a corresponding region in a pre-operative CT volume to infer the position of the target lesion with respect to the imaging plane. The registration is implemented in a coarse to fine fashion. The local deformation between the two regions is modeled by an affine transformation. The sum-of-squared-differences (SSD) between the two regions is minimized using the Levenberg-Marquardt method. Multiresolution and multi-start strategies are used to avoid local minima. As a result, multiple candidate transformations between the two regions are obtained, from which the true transformation is selected by similarity voting. The true transformation of each frame of the CT fluoroscopy image is then incorporated into a Kalman filter to predict the lesion's position for the next frame. Tests were completed to evaluate the performance of the algorithm using a respiratory motion simulator and a swine animal study

On the Application of Mechanical Vibration in Robotics-Assisted Soft Tissue Intervention

Mechanical vibration as a way of transmitting energy has been an interesting subject to study. While cyclic oscillation is usually associated with fatigue effect, and hence a detrimental factor in failure of structures and machineries, by controlled transmission of vibration, energy can be transferred from the source to the target. In this thesis, the application of such mechanical vibration in a few surgical procedures is demonstrated. Three challenges associated with lung cancer diagnosis and treatment are chosen for this purpose, namely, Motion Compensation, tumor targeting in lung Needle Insertion and Soft Tissue Dissection: A robotic solution is proposed for compensating for the undesirable oscillatory motion of soft tissue (caused by heart beat and respiration) during needle insertion in the lung. An impedance control strategy based on a mechanical vibratory system is implemented to minimize the tissue deformation during needle insertion. A prototype was built to evaluate the proposed approach using: 1) two Mitsubishi PA10-7C robots, one for manipulating the macro part and the other for mimicking the tissue motion, 2) one motorized linear stage to handle the micro part, and 3) a Phantom Omni haptic device for remote manipulation. Experimental results are given to demonstrate the performance of the motion compensation system. A vibration-assisted needle insertion technique has been proposed in order to reduce needle–tissue friction. The LuGre friction model is employed as a basis for the study and the model is extended and analyzed to include the impact of high-frequency vibration on translational friction. Experiments are conducted to evaluate the role of insertion speed as well as vibration frequency on frictional effects. In the experiments conducted, an 18 GA brachytherapy needle was vibrated and inserted into an ex-vivo soft tissue sample using a pair of amplified piezoelectric actuators. Analysis demonstrates that the translational friction can be reduced by introducing a vibratory low-amplitude motion onto a regular insertion profile, which is usually performed at a constant rate. A robotics-assisted articulating ultrasonic surgical scalpel for minimally invasive soft tissue cutting and coagulation is designed and developed. For this purpose, the optimal design of a Langevin transducer with stepped horn profile is presented for internal-body applications. The modeling, optimization and design of the ultrasonic scalpel are performed through equivalent circuit theory and verified by finite element analysis. Moreover, a novel surgical wrist, compatible with the da Vinci® surgical system, with decoupled two degrees-of-freedom (DOFs) is developed that eliminates the strain of pulling cables and electrical wires. The developed instrument is then driven using the dVRK (da Vinci® research kit) and the Classic da Vinci® surgical system