In Vivo Feasibility Study: Evaluating Autonomous Data-Driven Robotic Needle Trajectory Correction in MRI-Guided Transperineal Procedures

This study addresses the targeting challenges in MRI-guided transperineal needle placement for prostate cancer (PCa) diagnosis and treatment, a procedure where accuracy is crucial for effective outcomes. We introduce a parameter-agnostic trajectory correction approach incorporating a data-driven closed-loop strategy by radial displacement and an FBG-based shape sensing to enable autonomous needle steering. In an animal study designed to emulate clinical complexity and assess MRI compatibility through a PCa mock biopsy procedure, our approach demonstrated a significant improvement in targeting accuracy (p<0.05), with mean target error of only 2.2 ± 1.9 mm on first insertion attempts, without needle reinsertions. To the best of our knowledge, this work represents the first in vivo evaluation of robotic needle steering with FBG-sensor feedback, marking a significant step towards its clinical translation.

A method for predicting needle insertion deflection in soft tissue based on cutting force identification

The deflection modeling during the insertion of bevel-tipped flexible needles into soft tissues is crucial for robot-assisted flexible needle insertion into specific target locations within the human body during percutaneous biopsy surgery. This paper proposes a mechanical model based on cutting force identification to predict the deflection of flexible needles in soft tissues. Unlike other models, this method does not require measuring Young's modulus (E ) and Poisson's ratio (ν ) of tissues, which require complex hardware to obtain. In the model, the needle puncture process is discretized into a series of uniform-depth puncture steps. The needle is simplified as a cantilever beam supported by a series of virtual springs, and the influence of tissue stiffness on needle deformation is represented by the spring stiffness coefficient of the virtual spring. By theoretical modeling and experimental parameter identification of cutting force, the spring stiffness coefficients are obtained, thereby modeling the deflection of the needle. To verify the accuracy of the proposed model, the predicted model results were compared with the deflection of the puncture experiment in polyvinyl alcohol (PVA) gel samples, and the average maximum error range predicted by the model was between 0.606 ± 0.167 mm and 1.005 ± 0.174 mm, which showed that the model can successfully predict the deflection of the needle. This work will contribute to the design of automatic control strategies for needles.

Simulation-based Flexible Needle Control with Single-core FBG Feedback for Spinal Injections

Objective

We present a general framework of simultaneous needle shape reconstruction and control input generation for robot-assisted spinal injection procedures, without continuous imaging feedback.

Methods

System input-output mapping is generated with a real-time needle-tissue interaction simulation, and single-core FBG sensor readings are used as local needle shape feedback within the same simulation framework. FBG wavelength shifts due to temperature variation is removed by exploiting redundancy in fiber arrangement.

Results

Targeting experiments performed on both plastisol lumbar phantoms as well as an ex vivo porcine lumbar section achieved in-plane tip errors of 0.6 ± 0.3 mm and 1.6 ± 0.9 mm , and total tip errors of 0.9 ± 0.7 mm and 2.1 ± 0.8 mm for the two testing environments.

Significance

Our clinically inspired control strategy and workflow is self-contained and not dependent on the modality of imaging guidance. The generalizability of the proposed approach can be applied to other needle-based interventions where medical imaging cannot be reliably utilized as part of a closed-loop control system for needle guidance.

Shape Manipulation of Bevel-Tip Needles for Prostate Biopsy Procedures: A Comparison of Two Resolved-Rate Controllers

Prostate cancer diagnosis continues to encounter challenges, often due to imprecise needle placement in standard biopsies. Several control strategies have been developed to compensate for needle tip prediction inaccuracies, however none were compared against each other, and it is unclear whether any of them can be safely and universally applied in clinical settings. This paper compares the performance of two resolved-rate controllers, derived from a mechanics-based and a data-driven approach, for bevel-tip needle control using needle shape manipulation through a template. We demonstrate for a simulated 12-core biopsy procedure under model parameter uncertainty that the mechanics-based controller can better reach desired targets when only the final goal configuration is presented even with uncertainty on model parameters estimation, and that providing a feasible needle path is crucial in ensuring safe surgical outcomes when either controller is used for needle shape manipulation.

Bevel-Tip Needle Deflection Modeling, Simulation, and Validation in Multi-Layer Tissues

Percutaneous needle insertions are commonly performed for diagnostic and therapeutic purposes as an effective alternative to more invasive surgical procedures. However, the outcome of needle-based approaches relies heavily on the accuracy of needle placement, which remains a challenge even with robot assistance and medical imaging guidance due to needle deflection caused by contact with soft tissues. In this paper, we present a novel mechanics-based 2D bevel-tip needle model that can account for the effect of nonlinear strain-dependent behavior of biological soft tissues under compression. Real-time finite element simulation allows multiple control inputs along the length of the needle with full three-degree-of-freedom (DOF) planar needle motions. Cross-validation studies using custom-designed multi-layer tissue phantoms as well as heterogeneous chicken breast tissues result in less than 1mm in-plane errors for insertions reaching depths of up to 61 mm, demonstrating the validity and generalizability of the proposed method.

Data-driven adaptive needle insertion assist for transperineal prostate interventions

Objective.Clinical outcomes of transperineal prostate interventions, such as biopsy, thermal ablations, and brachytherapy, depend on accurate needle placement for effectiveness. However, the accurate placement of a long needle, typically 150-200 mm in length, is challenging due to needle deviation induced by needle-tissue interaction. While several approaches for needle trajectory correction have been studied, many of them do not translate well to practical applications due to the use of specialized needles not yet approved for clinical use, or to relying on needle-tissue models that need to be tailored to individual patients.Approach.In this paper, we present a robot-assisted collaborative needle insertion method that only requires an actuated passive needle guide and a conventional needle. The method is designed to assist a physician inserting a needle manually through a needle guide. If the needle is deviated from the intended path, actuators shifts the needle radially in order to steer the needle trajectory and compensate for needle deviation adaptively. The needle guide is controlled by a new data-driven algorithm which does not requirea prioriinformation about needle or tissue properties. The method was evaluated in experiments with bothin vitroandex vivophantoms.Main results.The experiments inex vivotissue reported a mean final placement error of 0.36 mm with a reduction of 96.25% of placement error when compared to insertions without the use of assistive correction.Significance.Presented results show that the proposed closed-loop formulation can be successfully used to correct needle deflection during collaborative manual insertion with potential to be easily translated into clinical application.

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 Steering with Tethered and Untethered Actuation: Current States, Targeting Errors, Challenges and Opportunities

Accurate needle targeting is critical for many clinical procedures, such as transcutaneous biopsy or radiofrequency ablation of tumors. However, targeting errors may arise, limiting the widespread adoption of these procedures. Advances in flexible needle (FN) steering are emerging to mitigate these errors. This review summarizes the state-of-the-art developments of FNs and addresses possible targeting errors that can be overcome with steering actuation techniques. FN steering techniques can be classified as passive and active. Passive steering directly results from the needle-tissue interaction forces, whereas active steering requires additional forces to be applied at the needle tip, which enhances needle steerability. Therefore, the corresponding targeting errors of most passive FNs and active FNs are between 1 and 2 mm, and less than 1 mm, respectively. However, the diameters of active FNs range from 1.42 to 12 mm, which is larger than the passive steering needle varying from 0.5 to 1.4 mm. Therefore, the development of active FNs is an area of active research. These active FNs can be steered using tethered internal direct actuation or untethered external actuation. Examples of tethered internal direct actuation include tendon-driven, longitudinal segment transmission and concentric tube transmission. Tendon-driven FNs have various structures, and longitudinal segment transmission needles could be adapted to reduce tissue damage. Additionally, concentric tube needles have immediate advantages and clinical applications in natural orifice surgery. Magnetic actuation enables active FN steering with untethered external actuation and facilitates miniaturization. The challenges faced in the fabrication, sensing, and actuation methods of FN are analyzed. Finally, bio-inspired FNs may offer solutions to address the challenges faced in FN active steering mechanisms.

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.

Planning of Medical Flexible Needle Motion in Effective Area of Clinical Puncture

Lung cancer is the leading cause of cancer deaths worldwide. Although several lung cancer diagnostic methods are available for lung nodule biopsy, there are limitations in terms of accuracy, safety, and invasiveness. Transbronchial needle aspiration (TBNA) is a common method for diagnosing and treating lung cancer that involves a robot-assisted medical flexible needle moving along a curved three-dimensional trajectory, avoiding anatomical barriers to achieve clinically meaningful goals in humans. Inspired by the puncture angle between the needle tip and the vessel in venipuncture, we suggest that different orientations of the medical flexible needle puncture path affect the cost of the puncture trajectory and propose an effective puncture region based on the optimal puncture direction, which is a strategy based on imposing geometric constraints on the search space of the puncture direction, and based on this, we focused on the improved implementation of RCS*. Planning within the TBNA-based lung environment was performed using the rapidly exploring random tree (RRT), resolution-complete search (RCS), and RCS* (a resolution-optimal version of RCS) within an effective puncture region. The experimental results show that the optimal puncture direction corresponding to the lowest cost puncture trajectory is consistent among the three algorithms and RCS* is more efficient for planning. The experiments verified the feasibility and practicality of our proposed minimum puncture angle and puncture effective region and facilitated the study of the puncture direction of flexible needle puncture.

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.

Review on generic methods for mechanical modeling, simulation and control of soft robots

In this review paper, we are interested in the models and algorithms that allow generic simulation and control of a soft robot. First, we start with a quick overview of modeling approaches for soft robots and available methods for calculating the mechanical compliance, and in particular numerical methods, like real-time Finite Element Method (FEM). We also show how these models can be updated based on sensor data. Then, we are interested in the problem of inverse kinematics, under constraints, with generic solutions without assumption on the robot shape, the type, the placement or the redundancy of the actuators, the material behavior… We are also interested by the use of these models and algorithms in case of contact with the environment. Moreover, we refer to dynamic control algorithms based on mechanical models, allowing for robust control of the positioning of the robot. For each of these aspects, this paper gives a quick overview of the existing methods and a focus on the use of FEM. Finally, we discuss the implementation and our contribution in the field for an open soft robotics research.

A computational multilayer model to simulate hollow needle insertion into biological porcine liver tissue

Modelling of needle insertion in soft tissue has developed significant interest in recent years due to its application in robot-assisted minimally invasive surgeries such as biopsies and brachytherapy. However, this type of surgery requires real-time feedback and processing which complex computational models may not be able to provide. In contrast to the existing mechanics-based kinetic models, a simple multilayer tissue model using a Coupled Eulerian Lagrangian based Finite Element method has been developed using the dynamic principle. The model simulates the needle motion for flexible hollow bevel-angled needle (15° and 30°, 22 Gauge) insertion into porcine liver tissue, which includes material parameters obtained from unconfined compression testing of porcine liver tissue. To validate simulation results, needle insertion force and cutting force within porcine liver tissue were compared with corresponding experimental results obtained from a custom-built needle insertion system. For the 15° and 30° bevel-angle needles, the percentage error for cutting force (mean) of each needle compared to computational model, were 18.7% and 11.9% respectively. Varying the needle bevel angle from 30° to 15° results in an increase of the cutting force, but insertion force does not vary among the tested bevel angles. The validation of this computationally efficient multilayer Finite Element model can help engineers to better understand the biomechanical behaviour of medical needle inside soft biological tissue. Ultimately, this multilayer approach can help advance state-of-art clinical applications such as robot-assisted surgery that requires real-time feedback and processing. STATEMENT OF SIGNIFICANCE: The significance of the work is in confirming the effectiveness of multilayer material based finite element (FE) method to model biopsy needle insertion into soft biological porcine liver tissue. A multilayer Coupled Eulerian Lagrangian (CEL) based FE modelling technique allowed testing of heterogeneous, non-linear viscoelastic porcine liver tissue in a system, so direct comparison of needle tissue interaction forces on the intrinsic material (tissue) behaviour could be made. To the best of the authors' knowledge, the present research investigates for the first time modelling of a three dimensional (3D) hollow needle insertion using a multilayer stiffness model of biological tissue using FE based CEL method and presents a comparison of simulation results with experimental data.

Investigation on puncture mechanical performance of tracheal tissue

This paper investigated the mechanical behavior of the contact between the oblique tip puncture needle and the tracheal tissue during pathological examination for the diagnosis of respiratory diseases. By analyzing the force of the oblique tip puncture needle, this paper established a theoretical model of the contact mechanics between the needle and the tracheal tissue. With the material characteristics, needle diameter and puncture angle of trachea tissue as the loading conditions, the biomechanical simulation of piercing process was carried out by using the finite element simulation method, and realistic puncture experiments on isolated porcine tracheal tissue were performed by electronic universal testing machine. The results showed that the puncture needle was mainly subjected to the combined effect of cutting force, clamping force and frictional force on the needle shaft. When the needle diameter was 22G, penetrating the tracheal tissue vertically, the force on the needle was minimal. Meanwhile, it was found that the error between the experimental and theoretical values of the puncture force did not exceed 10%, thus verifying the feasibility of the hypothetical model of the puncture force in the tracheal tissue rupture stage. It provided a theoretical basis for the intervention of surgical instruments and reduced surgical risks.

Mathematical modeling and computer simulation of needle insertion into soft tissue

In this study we present a kinematic approach for modeling needle insertion into soft tissues. The kinematic approach allows the presentation of the problem as Dirichlet-type (i.e. driven by enforced motion of boundaries) and therefore weakly sensitive to unknown properties of the tissues and needle-tissue interaction. The parameters used in the kinematic approach are straightforward to determine from images. Our method uses Meshless Total Lagrangian Explicit Dynamics (MTLED) method to compute soft tissue deformations. The proposed scheme was validated against experiments of needle insertion into silicone gel samples. We also present a simulation of needle insertion into the brain demonstrating the method's insensitivity to assumed mechanical properties of tissue.

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.