Review of robotic systems for thoracoabdominal puncture interventional surgery

Cancer, with high morbidity and high mortality, is one of the major burdens threatening human health globally. Intervention procedures via percutaneous puncture have been widely used by physicians due to its minimally invasive surgical approach. However, traditional manual puncture intervention depends on personal experience and faces challenges in terms of precisely puncture, learning-curve, safety and efficacy. The development of puncture interventional surgery robotic (PISR) systems could alleviate the aforementioned problems to a certain extent. This paper attempts to review the current status and prospective of PISR systems for thoracic and abdominal application. In this review, the key technologies related to the robotics, including spatial registration, positioning navigation, puncture guidance feedback, respiratory motion compensation, and motion control, are discussed in detail.

A Survey of Needle Steering Approaches in Minimally Invasive Surgery

In virtue of a curved insertion path inside tissues, needle steering techniques have revealed the potential with the assistance of medical robots and images. The superiority of this technique has been preliminarily verified with several maneuvers: target realignment, obstacle circumvention, and multi-target access. However, the momentum of needle steering approaches in the past decade leads to an open question-"How to choose an applicable needle steering approach for a specific clinical application?" This survey discusses this question in terms of design choices and clinical considerations, respectively. In view of design choices, this survey proposes a hierarchical taxonomy of current needle steering approaches. Needle steering approaches of different manipulations and designs are classified to systematically review the design choices and their influences on clinical treatments. In view of clinical consideration, this survey discusses the steerability and acceptability of the current needle steering approaches. On this basis, the pros and cons of the current needle steering approaches are weighed and their suitable applications are summarized. At last, this survey concluded with an outlook of the needle steering techniques, including the potential clinical applications and future developments in mechanical design.

A review on tissue-needle interaction and path planning models for bevel tip type flexible needle minimal intervention

A flexible needle has emerged as a crucial clinical technique in contemporary medical practices, particularly for minimally invasive interventions. Its applicability spans diverse surgical domains such as brachytherapy, cardiovascular surgery, neurosurgery and others. Notably, flexible needles find utility in biopsies requiring deep skin penetration to access infected areas. Despite its minimally invasive advantages, the precise guidance of the needle to its intended target, while avoiding damage to bones, blood vessels, organs and tissues, remains a significant challenge for researchers. Consequently, extensive research has been dedicated to enhancing the steering and accuracy of flexible needles. Here, we aim to elucidate the recent advancements, trends and perspectives in flexible needle steering models and path planning over the last 15 years. The discussed models encompass various types, including symmetric-tip needles, curved-tip needles, tendon-actuated needles, programmable needles and the innovative fracture-directed waterjet needles. Moreover, the paper offers a comprehensive analysis, comparing the trajectories followed by these needle models to attain the desired target with minimal tissue damage. By delving into these aspects, the paper contributes to a deeper understanding of the current landscape of flexible needle technology and guides future research directions in this dynamic field.

Towards a Procedure-Optimised Steerable Catheter for Deep-Seated Neurosurgery

In recent years, steerable needles have attracted significant interest in relation to minimally invasive surgery (MIS). Specifically, the flexible, programmable bevel-tip needle (PBN) concept was successfully demonstrated in vivo in an evaluation of the feasibility of convection-enhanced delivery (CED) for chemotherapeutics within the ovine model with a 2.5 mm PBN prototype. However, further size reductions are necessary for other diagnostic and therapeutic procedures and drug delivery operations involving deep-seated tissue structures. Since PBNs have a complex cross-section geometry, standard production methods, such as extrusion, fail, as the outer diameter is reduced further. This paper presents our first attempt to demonstrate a new manufacturing method for PBNs that employs thermal drawing technology. Experimental characterisation tests were performed for the 2.5 mm PBN and the new 1.3 mm thermally drawn (TD) PBN prototype described here. The results show that thermal drawing presents a significant advantage in miniaturising complex needle structures. However, the steering behaviour was affected due to the choice of material in this first attempt, a limitation which will be addressed in future work.

Optical Fiber -Based Needle Shape Sensing: Three-channel Single Core vs. Multicore Approaches

Bevel-tip needles are commonly utilized in percutaneous medical interventions where a curved insertion trajectory is required. To avoid deviation from the intended trajectory, needle shape sensing and tip localization is crucial in providing the operator with feedback. There is an abundance of previous work that investigate the medical application of fiber Bragg grating (FBG) sensors, but most works select only one specific type of fiber among the many available sensor options to integrate into their hardware designs. In this work, we compare two different types of FBG sensors under identical conditions and application, namely, acting as the sensor for needle insertion shape reconstruction. We built a three-channel single core needle and a seven-channel multicore fiber (MCF) needle and discuss the pros and cons of both constructions for shape sensing experiments into constant curvature jigs. The overall needle tip error is 1.23 mm for the single core needle and 2.08 mm for the multicore needle.

In Situ Flexible Needle Adjustment Towards MRI-Guided Spinal Injections Based on Finite Element Simulation

This paper investigates the possibility of robotically performing in situ needle manipulations to correct the needle tip position in the setting of robot-assisted, MRI-guided spinal injections, where real time MRI images cannot be effectively used to guide the needle. Open-loop control of the needle tip is derived from finite element simulation, and the proposed method is tested with ex vivo animal muscle tissues and validated by cone beam computed tomography. Preliminary results have shown promise of performing needle tip correction in situ to improve needle insertion accuracy when real-time feedback is not readily available.

Flexible Needle Bending Model for Spinal Injection Procedures

An in situ needle manipulation technique used by physicians when performing spinal injections is modeled to study its effect on needle shape and needle tip position. A mechanics-based model is proposed and solved using finite element method. A test setup is presented to mimic the needle manipulation motion. Tissue phantoms made from plastisol as well as porcine skeletal muscle samples are used to evaluate the model accuracy against medical images. The effect of different compression models as well as model parameters on model accuracy is studied, and the effect of needle-tissue interaction on the needle remote center of motion is examined. With the correct combination of compression model and model parameters, the model simulation is able to predict needle tip position within submillimeter accuracy.

Review of research on path planning and control methods of flexible steerable needle puncture robot

In the field of minimally invasive interventional therapy, the related research on the soft tissue puncture robot and its technology based on the flexible steerable needle as a research hot topic at present, and it has been developed rapidly in the past ten years. In order to better understand the development status of the flexible steerable needle puncture (FSNP) robot and provide reference for its design and improvement in subsequent research, it is necessary to introduce in two aspects of FSNP robot: the puncture path planning and the control methods. First, this article introduced the concept of the FSNP technology, and the necessity of the application of FSNP soft tissue robot in minimally invasive interventional surgery. Second, this article mainly introduced the principle of FSNP, the path planning of FSNP, the navigation and positioning control of the needle tip of the flexible steerable needle, the control method of FSNP system, and the controllable flexible needle. Finally, combined with the above analysis and introduction, it was pointed out that FSNP soft tissue robot and its related technology would be an important development direction in the field of minimally invasive interventional therapy in the future, and the current existing problems were pointed out. Meanwhile, the development trend of FSNP robot control technology was summarized and prospected.

Lie-Group Theoretic Approach to Shape-Sensing Using FBG-Sensorized Needles Including Double-Layer Tissue and S-Shape Insertions

Flexible bevel-tipped needles are often used for needle insertion in minimally-invasive surgical techniques due to their ability to be steered in cluttered environments. Shapesensing enables physicians to determine the location of needles intra-operatively without requiring radiation of the patient, enabling accurate needle placement. In this paper, we validate a theoretical method for flexible needle shape-sensing that allows for complex curvatures, extending upon a previous sensor-based model. This model combines curvature measurements from fiber Bragg grating (FBG) sensors and the mechanics of an inextensible elastic rod to determine and predict the 3D needle shape during insertion. We evaluate the model's shape sensing capabilities in C- and S-shape insertions in single-layer isotropic tissue, and C-shape insertions in two-layer isotropic tissue. Experiments on a four-active area, FBG-sensorized needle were performed in varying tissue stiffnesses and insertion scenarios under stereo vision to provide the 3D ground truth needle shape. The results validate a viable 3D needle shape-sensing model accounting for complex curvatures in flexible needles with mean needle shape sensing root-mean-square errors of 0.160 ± 0.055 mm over 650 needle insertions.

Modular robotic platform for precision neurosurgery with a bio-inspired needle: System overview and first in-vivo deployment

Over the past 10 years, minimally invasive surgery (MIS) has shown significant benefits compared to conventional surgical techniques, with reduced trauma, shorter hospital stays, and shorter patient recovery times. In neurosurgical MIS procedures, inserting a straight tool (e.g. catheter) is common practice in applications ranging from biopsy and laser ablation, to drug delivery and fluid evacuation. How to handle tissue deformation, target migration and access to deep-seated anatomical structures remain an open challenge, affecting both the preoperative planning phase and eventual surgical intervention. Here, we present the first neurosurgical platform in the literature, able to deliver an implantable steerable needle for a range of diagnostic and therapeutic applications, with a short-term focus on localised drug delivery. This work presents the system's architecture and first in vivo deployment with an optimised surgical workflow designed for pre-clinical trials with the ovine model, which demonstrate appropriate function and safe implantation.

Data-Driven Modelling and Control for Robot Needle Insertion in Deep Anterior Lamellar Keratoplasty

Deep anterior lamellar keratoplasty (DALK) is a technique for cornea transplantation which is associated with reduced patient morbidity. DALK has been explored as a potential application of robot microsurgery because the small scales, fine control requirements, and difficulty of visualization make it very challenging for human surgeons to perform. We address the problem of modelling the small scale interactions between the surgical tool and the cornea tissue to improve the accuracy of needle insertion, since accurate placement within 5% of target depth has been associated with more reliable clinical outcomes. We develop a data-driven autoregressive dynamic model of the tool-tissue interaction and a model predictive controller to guide robot needle insertion. In an ex vivo model, our controller significantly improves the accuracy of needle positioning by more than 40% compared to prior methods.

Preoperative Motion Planner for Steerable Needles Using Cost Map Based on Repulsive Field and Empirical Model of Needle Deflection

Needle insertion is a common procedure in percutaneous puncture. A motion planner for a steerable needle that considers the risk level of the path in anatomical environment and the actual deflection of clinical needle is necessary. A novel preoperative motion planner for a steerable needle controlled by robot is proposed. Our method utilizes sampling-based planner to compute candidate path in the reachable region, the path solutions are optimized by calculating the cost of a path based on a cost map. The cost-map, which is built based on repulsive field theory from CT image, encodes the information of the obstacle locations and the criticality of the anatomical environment. The empirical formula that can predict needle trajectory is obtained by insertion experiments. Experiments shown that positioning error in gelatin phantom under the guidance of our planner is less than 1.1mm. Comparing with the straight-line insertion method, the positioning error was reduced by 80%. The results indicate that the motion planner has the potential to provide effective guidance for robot-assisted puncture surgery while enhancing the position precision and patient safety.

Coordinated control of a 3DOF cartesian robot and a shape memory alloy-actuated flexible needle for surgical interventions: a non-model-based control method

Success of any needle-based medical procedures depends on accurate placement of the needle at the target location. However, accurate targeting and control of flexible self-actuating (active) needle are challenging. We have developed a shape memory alloy-actuated flexible needle steered by a 3D Cartesian robot and performed a comparative study of four, non-model-based, coordinated control methodologies for the combined robot steering and flexible-needle insertion process for surgical interventions. Investigated four controllers are: proportional–integral–derivative (PID), PID with the cubic of positional error term (PID-P3), static PID sliding mode controller, and robust adaptive PID sliding mode controller (RAPID-SMC). Relative efficacies of these controllers are demonstrated by performing experiements using a tissue-mimicking soft material phantom. Results from experiments have reavealed that RAPID-SMC is superior to other three controllers.

Towards Safe In Situ Needle Manipulation for Robot Assisted Lumbar Injection in Interventional MRI

Lumbar injection is an image-guided procedure performed manually for diagnosis and treatment of lower back pain and leg pain. Previously, we have developed and verified an MR-Conditional robotic solution to assisting the needle insertion process. Drawing on our clinical experiences, a virtual remote center of motion (RCM) constraint is implemented to enable our robot to mimic a clinician's hand motion to adjust the needle tip position in situ. Force and image data are collected to study the needle behavior in gel phantoms during this motion, and a mechanics-based needle-tissue interaction model is proposed and evaluated to further examine the underlying physics. This work extends the commonly-adopted notion of an RCM for flexible needles, and introduces new motion parameters to describe the needle behavior. The model parameters can be tuned to match the experimental result to sub-millimeter accuracy, and this proposed needle manipulation method presents a safer alternative to laterally translating the needle during in situ needle adjustments.

Control of a flexible bevel-tipped needle using super-twisting controller based sliding mode observer

This article presents the implementation of super twisting controller based on higher-order sliding mode observer during needle maneuverability in minimal invasive surgery. To ensure chattering free and stable maneuverability of the needle in spite of external disturbances, a robust control strategy is necessary. Technically, it is cumbersome to develop the structure of super twisting controller with a third-order sliding mode observer leading to discontinuous control law. Henceforth, we propose the higher order (n+1) sliding mode observer with continuous control law. Our study involves the kinematic model of the bevel-tipped flexible needle to inculcate an accurate target reaching regulation of the needling system. Both simulation and experimental results with various bevel angles are presented to verify the proposed needle steering control methodology in biological tissue environment.

Biologically Inspired Surgical Needle Steering: Technology and Application of the Programmable Bevel-Tip Needle

Percutaneous interventions via minimally invasive surgical systems can provide patients with better outcomes and faster recovery times than open surgeries. Accurate needle insertions are vital for successful procedures, and actively steered needles can increase system precision. Here, we describe how biology inspired the design of a novel Programmable Bevel-Tip Needle (PBN), mimicking the mechanics and control methods of certain insects ovipositors. Following an overview of our unique research and development journey, this paper explores our latest, biomimetic control of PBNs and its application to neurosurgery, which we validate within a simulated environment. Three modalities are presented, namely a Direct Push Controller, a Cyclic Actuation Controller, and a newly developed Hybrid Controller, which have been integrated into a surgical visual interface. The results of open loop, expert human-in-the-loop and a non-expert user study show that the Hybrid Controller is the best choice when considering system performance and the ability to lesson strain on the surrounding tissue which we hypothesis will result in less damage along the insertion tract. Over representative trajectories for neurosurgery using a Hybrid Controller, an expert user could reach a target along a 3D path with an accuracy of 0.70±0.69 mm, and non-expert users 0.97±0.72 mm, both clinically viable results and equivalent or better than the state-of-the-art actively steered needles over 3D paths. This paper showcases a successful example of a biologically inspired, actively steered needle, which has been integrated within a clinical interface and designed for seamless integration into the neurosurgical workflow.

Medical Imaging of Microrobots: Toward In Vivo Applications

Medical microrobots (MRs) have been demonstrated for a variety of non-invasive biomedical applications, such as tissue engineering, drug delivery, and assisted fertilization, among others. However, most of these demonstrations have been carried out in in vitro settings and under optical microscopy, being significantly different from the clinical practice. Thus, medical imaging techniques are required for localizing and tracking such tiny therapeutic machines when used in medical-relevant applications. This review aims at analyzing the state of the art of microrobots imaging by critically discussing the potentialities and limitations of the techniques employed in this field. Moreover, the physics and the working principle behind each analyzed imaging strategy, the spatiotemporal resolution, and the penetration depth are thoroughly discussed. The paper deals with the suitability of each imaging technique for tracking single or swarms of MRs and discusses the scenarios where contrast or imaging agent's inclusion is required, either to absorb, emit, or reflect a determined physical signal detected by an external system. Finally, the review highlights the existing challenges and perspective solutions which could be promising for future in vivo applications.

Real-Time Impedance Detection of Intra-Articular Space in a Porcine Model Using a Monopolar Injection Needle

Rheumatoid arthritis and osteoarthritis can be treated through specific drug injection into the intra-articular space. Several failures during drug injection attempts with conventional fluoroscopy and ultrasonography in a small area of the intra-articular space have been reported. In this work we present an innovative impedance measurement-based method/algorithm for needle tip positioning to enhance image-guided intra-articular vaccination treatment. A novel algorithm for detecting the intra-articular space in the elbow and knee joints of a live porcine model is reported. An impedance measurement system was developed for biological tissue measurement. The electrical impedance in the intra-articular space was monitored and the needle tip was examined by ultrasonography. The contrast dye was vaccinated and checked using fluoroscopy to confirm that the dye was properly inoculated in the cavity. The electrical impedance was estimated for various needle inclusion profundity levels in saline solution, which were broadly used to evaluate the proposed device for in vivo examinations. Good efficiency was observed in the impedance-based measurements using a monopolar injection needle for intra-articular therapy. To enhance the needle tip positioning for intra-articular therapy, the intended impedance measurement device with a monopolar injection needle can be used as a complement to existing modalities.

Bevel angle study of flexible hollow needle insertion into biological mimetic soft-gel: Simulation and experimental validation

BACKGROUND

A thorough understanding of cutting-edge geometry and cutting forces of hollow biopsy needles are required to optimise needle tip design to improve fine needle aspiration procedures.

OBJECTIVES

To incorporate the dynamics of needle motion in a model for flexible hollow bevel tipped needle insertion into a biological mimetic soft-gel using parameters obtained from experimental work. Additionally, the models will be verified against corresponding needle insertion experiments.

METHODS

To verify simulation results, needle deflection and insertion forces were compared with corresponding experimental results acquired with an in-house developed needle insertion mechanical system. Additionally, contact stress distribution on needles from agar gel for various time scales were also studied.

RESULTS

For the 15°, 30°, 45°, 60° bevel angle needles, and 90° blunt needle, the percentage error in needle deflection of each needle compared to experiments, were 7.3%, 9.9%, 8.6%, 7.8%, and 9.7% respectively. Varying the bevel angle at the needle tip demonstrates that the needle with a lower bevel angle produces the largest deflection, although the insertion force does not vary too much among the tested bevel angles.

CONCLUSION

This experimentally verified computer-based simulation model could be used as an alternative tool for better understanding the needle-tissue interaction to optimise needle tip design towards improved biopsy efficiency.

Optical Coherence Tomography-Guided Robotic Ophthalmic Microsurgery via Reinforcement Learning from Demonstration

Ophthalmic microsurgery is technically difficult because the scale of required surgical tool manipulations challenge the limits of the surgeon's visual acuity, sensory perception, and physical dexterity. Intraoperative optical coherence tomography (OCT) imaging with micrometer-scale resolution is increasingly being used to monitor and provide enhanced real-time visualization of ophthalmic surgical maneuvers, but surgeons still face physical limitations when manipulating instruments inside the eye. Autonomously controlled robots are one avenue for overcoming these physical limitations. We demonstrate the feasibility of using learning from demonstration and reinforcement learning with an industrial robot to perform OCT-guided corneal needle insertions in an ex vivo model of deep anterior lamellar keratoplasty (DALK) surgery. Our reinforcement learning agent trained on ex vivo human corneas, then outperformed surgical fellows in reaching a target needle insertion depth in mock corneal surgery trials. This work shows the combination of learning from demonstration and reinforcement learning is a viable option for performing OCT guided robotic ophthalmic surgery.

Robotically Steered Needles: A Survey of Neurosurgical Applications and Technical Innovations

This paper surveys both the clinical applications and main technical innovations related to steered needles, with an emphasis on neurosurgery. Technical innovations generally center on curvilinear robots that can adopt a complex path that circumvents critical structures and eloquent brain tissue. These advances include several needle-steering approaches, which consist of tip-based, lengthwise, base motion-driven, and tissue-centered steering strategies. This paper also describes foundational mathematical models for steering, where potential fields, nonholonomic bicycle-like models, spring models, and stochastic approaches are cited. In addition, practical path planning systems are also addressed, where we cite uncertainty modeling in path planning, intraoperative soft tissue shift estimation through imaging scans acquired during the procedure, and simulation-based prediction. Neurosurgical scenarios tend to emphasize straight needles so far, and span deep-brain stimulation (DBS), stereoelectroencephalography (SEEG), intracerebral drug delivery (IDD), stereotactic brain biopsy (SBB), stereotactic needle aspiration for hematoma, cysts and abscesses, and brachytherapy as well as thermal ablation of brain tumors and seizure-generating regions. We emphasize therapeutic considerations and complications that have been documented in conjunction with these applications.

Study on the Low Velocity Stability of a Prostate Seed Implantation Robot’s Rotatory Joint

Prostate cancer has one of the highest incidences of male malignant tumors worldwide. Its treatment involves the robotic implantation of radioactive seeds in the perineum, a safe and effective procedure for early, low-risk prostate cancer. In order to ensure precise positioning, the seed implantation needle is set at low terminal velocity. In this paper, the motion output position instability caused by the friction torque of the robot’s motor and rotating joint during low velocity motion was analyzed and studied. This paper also presents a compensation control method based on the LuGre friction model, which offers piecewise parameter identification with GA-PSO. First, based on an analysis of its structure and working principle, the friction torque model of the robotic system and the torque model of the driving motor are established, and the influence of friction torque on motion stability analyzed. Then, based on experimental data of the relationship between velocity and friction torque for no-friction compensation, the velocity point of the minimum torque of the rotating joint and the critical Stribeck velocity point were used for segmental parameter identification; cubic spline interpolation was used for segmental fitting. Furthermore, on the basis of the LuGre model identification method, parameter identification of the genetic algorithm-particle swarm optimization, and compensation control of the LuGre friction model, a control method is analysed and set forth. Malab2017a/Simulink simulation software was used to simulate and analyze the control method, and verify its feasibility. Finally, the cantilever prostate seed implantation robot system was tested to verify the effectiveness of the segmented identification method and the compensation control strategy. The results reveal that motion output position stability at low velocity meets the requirements of the cantilever prostate seed implantation robot, thus providing a vital reference for further research.

Steerable Microinvasive Probes for Localized Drug Delivery to Deep Tissue

Enhanced understanding of neuropathologies has created a need for more advanced tools. Current neural implants result in extensive glial scarring and are not able to highly localize drug delivery due to their size. Smaller implants reduce surgical trauma and improve spatial resolution, but such a reduction requires improvements in device design to enable accurate and chronic implantation in subcortical structures. Flexible needle steering techniques offer improved control over implant placement, but often require complex closed-loop control for accurate implantation. This study reports the development of steerable microinvasive neural implants (S-MINIs) constructed from borosilicate capillaries (OD = 60 µm, ID = 20 µm) that do not require closed-loop guidance or guide tubes. S-MINIs reduce glial scarring 3.5-fold compared to prior implants. Bevel steered needles are utilized for open-loop targeting of deep-brain structures. This study demonstrates a sinusoidal relationship between implant bevel angle and the trajectory radius of curvature both in vitro and ex vivo. This relationship allows for bevel-tipped capillaries to be steered to a target with an average error of 0.23 mm ± 0.19 without closed-loop control. Polished microcapillaries present a new microinvasive tool for chronic, predictable targeting of pathophysiological structures without the need for closed-loop feedback and complex imaging.

Steerable catheters for minimally invasive surgery: a review and future directions

The steerable catheter refers to the catheter that is manipulated by a mechanism which may be driven by operators or by actuators. The steerable catheter for minimally invasive surgery has rapidly become a rich and diverse area of research. Many important achievements in design, application and analysis of the steerable catheter have been made in the past decade. This paper aims to provide an overview of the state of arts of steerable catheters. Steerable catheters are classified into four main groups based on the actuation principle: (1) tendon driven catheters, (2) magnetic navigation catheters, (3) soft material driven catheters (shape memory effect catheters, steerable needles, concentric tubes, conducting polymer driven catheters and hydraulic pressure driven catheters), and (4) hybrid actuation catheters. The advantages and limitations of each of them are commented and discussed in this paper. The future directions of research are summarized.

Simulation of biopsy bevel-tipped needle insertion into soft-gel

Planning and practice of surgical procedures can be improved through the use of modelling. This study provides an insight into the biopsy needle (i.e. hollow cannula) and needle-tissue interactions using a modelling approach, thus enabling the optimization of needle-tip designs not only for training but also for the planning of surgical procedures. Simulations of needle insertion into agar gel were performed using a Coupled Eulerian-Lagrangian (CEL) based finite element (FE) analysis, adapted for large deformation and tissue fracture. The experimental work covers needle insertion into 3% agar gel using a needle with a beveled tip of various angles, to assess the validity of the simulation. The simulated needle deflection and insertion force for two needles (i.e. Needle 1 with 18° bevel angle and Needle 2 with 27° bevel angle) were compared with corresponding experimental results. The contact stress (i.e. contact pressure) on the needles from the agar gel during the insertion of the needles were also studied. Observations indicate that varying the needle bevel angle from 27° to 18° results in a decrease of the peak force (i.e. puncture force) and an increase in needle deflection. Quantitatively, the percentage errors between the experimental data and the FE model for the total insertion force along the z-direction (i.e. Z Force) for Needle 1 and 2 were 4% and 4.8% (p > 0.05), respectively. Similarly, needle deflection percentage errors along the x-z plane were 5.7% and 10% respectively. Therefore, the forces and needle deflection values predicted by the simulation are a close approximation of the experimental model, validating the Coupled Eulerian-Lagrangian based FE model. Thus, providing an experimentally validated model for biopsy and cytology needle design in silico that has the potential to replace the current build and break approach of needle design used by manufacturers.

A simple insertion technique to reduce the bending of thinbevel-point needles

Objective: Needle insertion is a common component of most diagnostic and therapeutic interventions. Needles with asymmetrically sharpened points such as the bevel point are ubiquitous. Their insertion path is typically curved due to the rudder effect at the point. However, the common planned path is straight, leading to targeting errors. We present a simple technique that may substantially reduce these errors. The method was inspired by practical experience, conceived mathematically, and refined experimentally. Methods: Targeting errors are reduced by flipping the bevel on the opposite side (rotating the needle 180° about its axis), at a certain depth during insertion. The ratio of the flip depth to the full depth of insertion is defined as the flip depth ratio (FDR). Based on a model, FDR is constant 0.3. Results: Experimentally, the ratio depends on the needle diameter, 0.35 for 20Ga and 0.45 for 18Ga needles. Thinner needles should be flipped a little shallower, but never less than 0.3. Conclusion: Practically, a physician may expect to reduce ∼80% of needle deflection errors by simply flipping the needle. The technique may be used by hand or with guidance devices.

The Adaptive Hermite Fractal Tree (AHFT): a novel surgical 3D path planning approach with curvature and heading constraints

PURPOSE

In the context of minimally invasive neurosurgery, steerable needles such as the one developed within the Horizon2020-funded EDEN2020 project (Frasson et al. in Proc Inst Mech Eng Part H J Eng Med 224(6):775-88, 2010. https://doi.org/10.1243/09544119JEIM663 ; Secoli and y Baena in IEEE international conference on robotics and automation, 2013) aspire to address the clinical challenge of better treatment for cancer patients. The direct, precise infusion of drugs in the proximity of a tumor has been shown to enhance its effectiveness and diffusion in the surrounding tissue (Vogelbaum and Aghi in Neuro-Oncology 17(suppl 2):ii3-ii8, 2015. https://doi.org/10.1093/neuonc/nou354 ). However, planning for an appropriate insertion trajectory for needles such as the one proposed by EDEN2020 is challenging due to factors like kinematic constraints, the presence of complex anatomical structures such as brain vessels, and constraints on the required start and target poses.

METHODS

We propose a new parallelizable three-dimensional (3D) path planning approach called Adaptive Hermite Fractal Tree (AHFT), which is able to generate 3D obstacle-free trajectories that satisfy curvature constraints given a specified start and target pose. The AHFT combines the Adaptive Fractal Tree algorithm's efficiency (Liu et al. in IEEE Robot Autom Lett 1(2):601-608, 2016. https://doi.org/10.1109/LRA.2016.2528292 ) with optimized geometric Hermite (Yong and Cheng in Comput Aided Geom Des 21(3):281-301, 2004. https://doi.org/10.1016/j.cagd.2003.08.003 ) curves, which are able to handle heading constraints.

RESULTS

Simulated results demonstrate the robustness of the AHFT to perturbations of the target position and target heading. Additionally, a simulated preoperative environment, where the surgeon is able to select a desired entry pose on the patient's skull, confirms the ability of the method to generate multiple feasible trajectories for a patient-specific case.

CONCLUSIONS

The AHFT method can be adopted in any field of application where a 3D path planner with kinematic and heading constraints on both start and end poses is required.

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.

Automatic Robotic Steering of Flexible Needles from 3D Ultrasound Images in Phantoms and Ex Vivo Biological Tissue

Robotic control of needle bending aims at increasing the precision of percutaneous procedures. Ultrasound feedback is preferable for its clinical ease of use, cost and compactness but raises needle detection issues. In this paper, we propose a complete system dedicated to robotized guidance of a flexible needle under 3D ultrasound imaging. This system includes a medical robot dedicated to transperineal needle positioning and insertion, a rapid path planning for needle steering using bevel-tip needle natural curvature in tissue, and an ultrasound-based automatic needle detection algorithm. Since ultrasound-based automatic needle steering is often made difficult by the needle localization in biological tissue, we quantify the benefit of using flexible echogenic needles for robotized guidance under 3D ultrasound. The "echogenic" term refers to the etching of microstructures on the needle shaft. We prove that these structures improve needle visibility and detection robustness in ultrasound images. We finally present promising results when reaching targets using needle steering. The experiments were conducted with various needles in different media (synthetic phantoms and ex vivo biological tissue). For instance, with nitinol needles the mean accuracy is 1.2 mm (respectively 3.8 mm) in phantoms (resp. biological tissue).

Evaluation of a CT-Guided Robotic System for Precise Percutaneous Needle Insertion

PURPOSE

To assess overall targeting accuracy for CT-guided needle insertion using prototype robotic system for common target sites.

MATERIALS AND METHODS

Using CT guidance, metallic (2 × 1 mm) targets were embedded in retroperitoneum (n = 8), kidneys (n = 8), and liver (n = 14) of 8 Yorkshire pigs (55-65 kg). Bronchial bifurcations were targeted in the lung (n = 13). CT datasets were obtained for planning and controlled needle placement of commercially available 17- to 19-gauge needles (length 15-20 cm) using a small, patient-mounted, CT-guided robotic system with 5° of motion. Mean distance to target was 92.9 mm ± 19.7 (range, 64-146 mm). Planning included selection of target, skin entry point, and 4.6 ± 1.3 predetermined checkpoints (range, 2-9) where additional CT imaging was performed to permit stepwise correction of needle trajectory path as needed. Scanning and needle advancement were coordinated with breath motion using respiratory gating. Accuracy was assessed as distance from needle tip to predefined target.

RESULTS

Of 45 needle insertions performed, 2 were unsuccessful owing to technical issues. Accuracy of targeting was 1.2-1.4 mm ± 0.6 for kidney, retroperitoneum, and lung (P = .51), with 2.9 mm ± 1.9 accuracy for liver (P = .0003). This was achieved in 39 cases (91%) using a single insertion. Intraprocedural target movement was detected (3.5 mm ± 2.1 in retroperitoneum and 6.4 mm ± 3.9 in liver); the system compensated for 52.9% ± 30.3 of this movement. One pneumothorax was the only complication (8%).

CONCLUSIONS

Accurate needle insertion (< 3 mm error) can be achieved in common target sites when using a CT-guided robotic system. Stepwise checks with corrective angulation can potentially overcome issues of target movement during a procedure from organ deformity and other causes.

Reduced-Dose Imageless Needle and Patient Tracking in Interventional CT Procedures

This paper describes a new method for imageless needle and patient tracking in interventional CT procedures based on fractional CT scanning. Our method accurately locates a needle with a spherical marker attached to it at a known distance from the tip with respect to the patient in the CT scanner coordinate frame with online sparse scan sampling and without reconstructing the CT image. The key principle of our method is to detect the needle and attached spherical marker in projection (sinogram) space based on the strongly attenuated X-ray signal due to the metallic composition of the needle and the needle's thin cylindrical geometry, and based on the marker's spherical geometry. A transformation from projection space to physical space uniquely determines the location and orientation of the needle and the needle tip position. Our method works directly in projection space and simultaneously performs patient registration and needle localization for every fractional CT scanning acquisition using the same sparse set of views. We performed registration and needle tip localization in five abdomen phantom scans using a rigid needle, and obtained a voxel-size tip localization error. Our experimental results indicate a voxel-sized deviation of the localization from a comparable method in 3-D image space, with the benefit of allowing X-ray dose reduction via fractional scanning at each localization. This benefit enables more frequent tip localizations during needle insertion for a similar total dose, or a reduced total dose for the same frequency of tip localization.

Active Localization and Tracking of Needle and Target in Robotic Image-Guided Intervention Systems

This paper describes a framework of algorithms for the active localization and tracking of flexible needles and targets during image-guided percutaneous interventions. The needle and target configurations are tracked by Bayesian filters employing models of the needle and target motions and measurements of the current system state obtained from an intra-operative imaging system which is controlled by an entropy-minimizing active localization algorithm. Versions of the system were built using particle and unscented Kalman filters and their performance was measured using both simulations and hardware experiments with real magnetic resonance imaging data of needle insertions into gel phantoms. Performance of the localization algorithms is given in terms of accuracy of the predictions and computational efficiency is discussed.

Needle-like instruments for steering through solid organs: A review of the scientific and patent literature

High accuracy and precision in reaching target locations inside the human body is necessary for the success of percutaneous procedures, such as tissue sample removal (biopsy), brachytherapy, and localized drug delivery. Flexible steerable needles may allow the surgeon to reach targets deep inside solid organs while avoiding sensitive structures (e.g. blood vessels). This article provides a systematic classification of possible mechanical solutions for three-dimensional steering through solid organs. A scientific and patent literature search of steerable instrument designs was conducted using Scopus and Web of Science Derwent Innovations Index patent database, respectively. First, we distinguished between mechanisms in which deflection is induced by the pre-defined shape of the instrument versus mechanisms in which an actuator changes the deflection angle of the instrument on demand. Second, we distinguished between mechanisms deflecting in one versus two planes. The combination of deflection method and number of deflection planes led to eight logically derived mechanical solutions for three-dimensional steering, of which one was dismissed because it was considered meaningless. Next, we classified the instrument designs retrieved from the scientific and patent literature into the identified solutions. We found papers and patents describing instrument designs for six of the seven solutions. We did not find papers or patents describing instruments that steer in one-plane on-demand via an actuator and in a perpendicular plane with a pre-defined deflection angle via a bevel tip or a pre-curved configuration.

A Concentric Tube Continuum Robot with Piezoelectric Actuation for MRI-Guided Closed-Loop Targeting

This paper presents the design, modeling and experimental evaluation of a magnetic resonance imaging (MRI)-compatible concentric tube continuum robotic system. This system enables MRI-guided deployment of a precurved and steerable concentric tube continuum mechanism, and is suitable for clinical applications where a curved trajectory is needed. This compact 6 degree-of-freedom (DOF) robotic system is piezoelectrically-actuated, and allows simultaneous robot motion and imaging with no visually observable image artifact. The targeting accuracy is evaluated with optical tracking system and gelatin phantom under live MRI-guidance with Root Mean Square (RMS) errors of 1.94 and 2.17 mm respectively. Furthermore, we demonstrate that the robot has kinematic redundancy to reach the same target through different paths. This was evaluated in both free space and MRI-guided gelatin phantom trails, with RMS errors of 0.48 and 0.59 mm respectively. As the first of its kind, MRI-guided targeted concentric tube needle placements with ex vivo porcine liver are demonstrated with 4.64 mm RMS error through closed-loop control of the piezoelectrically-actuated robot.

Manually controlled steerable needle for MRI-guided percutaneous interventions

This study aims to develop and evaluate a manually controlled steerable needle that is compatible with and visible on MRI to facilitate full intra-procedural control and accurate navigation in percutaneous interventions. The steerable needle has a working channel that provides a lumen to a cutting stylet or a therapeutic instrument. A steering mechanism based on cable-operated compliant elements is integrated in the working channel. The needle can be steered by adjusting the orientation of the needle tip through manipulation of the handle. The steering mechanism is evaluated by recording needle deflection at constant steering angles. A steering angle of 20.3° results in a deflection of 9.1–13.3 mm in gelatin and 4.6–18.9 mm in porcine liver tissue at an insertion depth of 60 mm. Additionally, the possibility to control the needle path under MRI guidance is evaluated in a gelatin phantom. The needle can be steered to targets at different locations while starting from the same initial position and orientation under MRI guidance with generally available sequences. The steerable needle offers flexibility to the physician in control and choice of the needle path when navigating the needle toward the target position, which allows for optimization of individual treatment and may increase target accuracy.