Flexible needle steering for computed tomography-guided interventions

In the last few decades, the surgical tools and procedures have developed significantly. Invasive surgeries are avoided as much as possible and minimally-invasive or non-invasive procedures are preferred. Needles are among the common tools which are used in clinical procedures, such as brachytherapy, microwave and radio frequency ablations and biopsies. Needle insertions usually require alignment of the needle with a lesion or a tumor, which is a challenging task even for experienced clinicians. Furthermore, the needles tend to deflect while being inserted into the tissue, since the clinical needles usually have an asymmetric tip, and the cutting force deflects the needle in a certain direction. In this thesis, a robotic system is developed which is used to steer a flexible needle within the tissue. The robot is designed for the procedure on the lung and liver, which are commonly performed under CT guidance. A review of the available solutions in the market and in the literature is discussed and the design and evaluation of the proposed CT-compatible needle steering robot is presented. Functional tests prove the design concept, and experiments in biological tissue and human cadaver validate the steering concept. A data fusion scheme based on unscented Kalman filter is developed in order to combine the tracking information from multiple devices. Finally, a motion compensation algorithm is presented which can be used to compensate patients voluntary or non-voluntary motions (such as breathing) while the needle is being inserted into the body

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

Three-dimensional needle steering towards a localized target in a prostate phantom

Prostate biopsy and brachytherapy are commonly used for surgical interventions. In this paper, we present a three-dimensional (3D) pre-operative target localization algorithm and a real-time closed-loop control algorithm to robotically steer flexible needles with an asymmetric tip towards a real target in a prostate phantom. The phantom is composed of different tissues including rectal wall, bladder and prostate. The elasticities of these tissues are obtained using an ultrasound-based (acoustic radiation force impulse imaging) technique, and their geometry are obtained using magnetic resonance images. Six experimental cases are performed to evaluate the steering system while inserting the needle into a prostate phantom with different skin thicknesses, insertion angles and surface inclinations. The experimental results show that the target is reached by the needle in all trials. The mean targeting errors between the needle tip and the center of the target embedded in phantoms with 0 mm, 1.5 mm and 2.5 mm skin thicknesses are 1.12 mm, 0.93 mm and 0.49 mm, respectively. The variation of the insertion angle does not have an appreciable affect on the targeting accuracy. The mean targeting error during insertion into a phantom with an inclined surface is 0.85 mm. The results demonstrate the capability of proposed system to robotically steer needles towards a target for interventions in the prostate

Robotic visual servoing of moving targets

We present a new image-based visual servoing scheme for tracking moving targets. This is achieved with a twofold approach. First, we devise a straightforward adaptation of a previously proposed depth observer to account for the fact that the target is not stationary. Second, we estimate the disturbance on the visual feature dynamics due to the target motion, and we add a related compensation term to the visual controller. In particular, the target velocity components parallel to the image plane are reconstructed using a disturbance observer, whereas the orthogonal component is retrieved from the measurement of the Focus Of Expansion. Comparative experiments show that the proposed method can improve over classical visual servoing schemes by 50% or more

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

Flexible Needle Steering in Moving Biological Tissue with Motion Compensation using Ultrasound and Force Feedback

International audienceNeedle insertion procedures under ultrasound guidance are commonly used for diagnosis and therapy. It is often critical to accurately reach a targeted region, and this can be difficult to achieve due to intra-operative tissue motion. In this paper, we present a method to steer a beveled-tip flexible needle towards a target embedded in moving tissue. Needle steering is performed using a needle insertion device attached to a robot arm. Closed-loop 3D steering of the needle is achieved using tracking of an artificial target in 2D ultrasound images and tracking of the needle tip position and orientation with an electromagnetic tracker. Tissue motion compensation is performed using force feedback to reduce targeting error and forces applied to the tissue. The method uses a mechanics-based interaction model that is updated online. A novel control law using task functions is proposed to fuse motion compensation, steering via base manipulation and tip-based steering. Validation of the tracking and steering algorithms are performed in gelatin phantom and bovine liver. Tissue motion up to 15mm is applied and average targeting error is 1.2±0.8mm and 2.5±0.7mm in gelatin and liver, respectively, which is sufficiently accurate for commonly performed needle insertion procedures