Hybrid control algorithm for flexible needle steering: Demonstration in phantom and human cadaver.

Needles are commonly used in the clinic for percutaneous procedures. The outcome of such procedures heavily depends on accurate placement of the needle. There are two main challenges to achieve high accuracy: First, aligning the needle with the targeted lesion, and second, compensating for the deflection of the needle in the tissue. In order to address these challenges, scientists have developed several robotic setups for needle steering. However, the subject is still under research and reliable implementations which can be used in clinical practice are not yet available. In this paper, we have taken some steps in order to bring needle steering closer to practice. A new hybrid control algorithm is developed, which enables us to control a flexible needle by combing base-manipulation and beveled-tip steering methods. A pre-operative path planner is developed which considers the clinical requirements. The proposed method is tested in the lung of a fresh-frozen human cadaver. The work-flow of the experiments are similar to the current clinical practice. Three experimental cases are used to evaluate the proposed steering algorithm. Experimental Case I shows that using the proposed steering algorithm controllability of the needle is increased. In Case II and Case III, the needle is steered in a gelatin phantom and a human cadaver, respectively. The targeting accuracy of 1.35±0.49mm in gelatin phantom and 1.97±0.89mm in cadave is achieved. A feasibility study is performed, in which a fine needle aspiration (FNA) needle is steered in the lungs of a human cadaver under computed tomography guidance. The targeting error for the feasibility study is 2.89±0.22mm. The results suggest that such a robotic system can be beneficial for clinical use and the patient receives less x-ray radiation.

Computed tomography (CT)-compatible remote center of motion needle steering robot: Fusing CT images and electromagnetic sensor data.

Lung cancer is the most common cause of cancer-related death, and early detection can reduce the mortality rate. Patients with lung nodules greater than 10 mm usually undergo a computed tomography (CT)-guided biopsy. However, aligning the needle with the target is difficult and the needle tends to deflect from a straight path. In this work, we present a CT-compatible robotic system, which can both position the needle at the puncture point and also insert and rotate the needle. The robot has a remote-center-of-motion arm which is achieved through a parallel mechanism. A new needle steering scheme is also developed where CT images are fused with electromagnetic (EM) sensor data using an unscented Kalman filter. The data fusion allows us to steer the needle using the real-time EM tracker data. The robot design and the steering scheme are validated using three experimental cases. Experimental Case I and II evaluate the accuracy and CT-compatibility of the robot arm, respectively. In experimental Case III, the needle is steered towards 5 real targets embedded in an anthropomorphic gelatin phantom of the thorax. The mean targeting error for the 5 experiments is 1.78 ± 0.70 mm. The proposed robotic system is shown to be CT-compatible with low targeting error. Small nodule size and large needle diameter are two risk factors that can lead to complications in lung biopsy. Our results suggest that nodules larger than 5 mm in diameter can be targeted using our method which may result in lower complication rate.

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 (φ0.55 mm) 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, 1.11 ± 0.14 and 1.94 ± 0.63 mm 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.

Ultrasound-guided three-dimensional needle steering in biological tissue with curved surfaces.

In this paper, we present a system capable of automatically steering a bevel-tipped flexible needle under ultrasound guidance toward a physical target while avoiding a physical obstacle embedded in gelatin phantoms and biological tissue with curved surfaces. An ultrasound pre-operative scan is performed for three-dimensional (3D) target localization and shape reconstruction. A controller based on implicit force control is developed to align the transducer with curved surfaces to assure the maximum contact area, and thus obtain an image of sufficient quality. We experimentally investigate the effect of needle insertion system parameters such as insertion speed, needle diameter and bevel angle on target motion to adjust the parameters that minimize the target motion during insertion. A fast sampling-based path planner is used to compute and periodically update a feasible path to the target that avoids obstacles. We present experimental results for target reconstruction and needle insertion procedures in gelatin-based phantoms and biological tissue. Mean targeting errors of 1.46±0.37 mm, 1.29±0.29 mm and 1.82±0.58 mm are obtained for phantoms with inclined, curved and combined (inclined and curved) surfaces, respectively, for insertion distance of 86-103 mm. The achieved targeting errors suggest that our approach is sufficient for targeting lesions of 3mm radius that can be detected using clinical ultrasound imaging systems.