Needle insertions modeling: Identifiability and limitations

Real-time haptic characterisation of Hunt-Crossley model based on radial basis function neural network for contact environment

Dynamic soft tissue characterisation is an important element in robotic minimally invasive surgery. This paper presents a novel method by combining neural network with recursive least square (RLS) estimation for dynamic soft tissue characterisation based on the nonlinear Hunt-Crossley (HC) model. It develops a radial basis function neural network (RBFNN) to compensate for the error caused by natural logarithmic factorisation (NLF) of the HC model for dynamic RLS estimation of soft tissue properties. The RBFNN weights are estimated according to the maximum likelihood principle to evaluate the probability distribution of the neural network modelling residual. Further, by using the linearisation error modelled by RBFNN to compensate for the linearised HC model, an RBFNN-based RLS algorithm is developed for dynamic soft tissue characterisation. Simulation and experimental results demonstrate that the proposed method can effectively model the natural logarithmic linearisation error, leading to improved accuracy for RLS estimation of the HC model parameters.

Multimodal Haptic Simulation for Ventriculostomy Training. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023;2023:1-4. [PMID: 38083370 DOI: 10.1109/embc40787.2023.10340701] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Freehand ventriculostomy is a frequent surgical procedure and is among the first ones that junior neurosurgery residents learn. Although training simulators exist, none has been adopted in the clinical routine to train junior residents. This paper focuses on a novel multimodal haptic training simulator that will lift the limitations of current simulators. We thus propose an architecture that integrates (1) visual feedback through augmented MRIs, and (2) a physical mock-up of the patient's skull to (3) active haptic feedback.

Biomechanical analysis of practitioner's gesture for peripheral venous catheter insertion

Peripheral venous catheter insertion (PVCI) is one of the most common procedures performed by healthcare professionals but remains technically difficult. To develop new medical simulators with better representativeness of the human forearm, an experimental study was performed to collect data related to the puncturing of human skin and a vein in the antebrachial area. A total of 31 volunteers participated in this study. Force sensors and digital image correlation were used to measure the force during the palpation and puncturing of the vein and to retrieve the kinematics of the practitioner's gesture. The in vivo skin rupture load, vein rupture load, and friction loads for skin only and for both the skin and vein were (mean ± standard deviation) 0.85 ± 0.34 N, 1.25 ± 0.37 N, -0.49 ± 0.19 N, and -0.51 ± 0.16 N, respectively. The results of this study can be used to develop realistic skin and vein substitutes and mechanically assess them by reproducing the practitioner's gesture in a controlled fashion.

Force modeling to develop a novel method for fabrication of hollow channels inside a gel structure

Fabrication of hollow channels with user-defined dimensions and patterns inside viscoelastic, gel-type materials is required for several applications, especially in biomedical engineering domain. These include objectives of obtaining vascularized tissues and enclosed or subsurface microfluidic devices. However, presently there is no suitable manufacturing technology that can create such channels and networks in a gel structure. The advent of three-dimensional bioprinting has opened new possibilities for fabricating structures with complex geometries. However, application of this technique to fabricate internal hollow channels in viscoelastic material has not been yet explored to a great extent. In this article, we present the theoretical modeling/background of a proposed manufacturing paradigm through which hollow channels can be conveniently fabricated inside a gel structure. We propose that a tip connected to a robotic arm can be moved in X-, Y-, and Z-axis as per the desired design. The tip can be moved by a magnet or mechanical force. If the tip is further trailed with porous tube and moved inside the viscoelastic material, corresponding internal channels can be fabricated. To achieve this, however, force modeling to understand the forces that will be required to move the tip inside viscoelastic material should be known and understood. Therefore, in our first attempt, we developed the computational force modeling of the tip movement inside gels with different viscoelastic properties to create the channels.

Guidelines for designing a realistic peripheral venous catheter insertion simulator: A literature review

A literature review was conducted to develop more realistic medical simulators that better prepare aspiring health professionals to perform a medical procedure in vivo. Thus, this review proposes an approach that might assist researchers design improved medical simulators, particularly new materials that would enhance the sensation of touch for skin substitutes. By targeting the current needs in the field of simulation learning, we concluded that peripheral venous catheter insertion simulators lack realistic haptic feedback. Enhanced peripheral venous catheter insertion simulators will accelerate the mastery of the medical procedure, thus decreasing the number of failures in patients and costs related to this procedure.

Haptic Feedback in Needle Insertion Modeling and Simulation

Needle insertion is the most basic skill in medical care, and training has to be imparted not only for physicians but also for nurses and paramedics. In most needle insertion procedures, haptic feedback from the needle is the main stimulus in which novices need training. For better patient safety, the classical methods of training the haptic skills have to be replaced with simulators based on new robotic and graphics technologies. This paper reviews the current advances in needle insertion modeling, classified into three sections: needle insertion models, tissue deformation models, and needle-tissue interaction models. Although understated in the literature, the classical and dynamic friction models, which are critical for needle insertion modeling, are also discussed. The experimental setup or the needle simulators that have been developed to validate the models are described. The need of psychophysics for needle simulators and psychophysical parameter analysis of human perception in needle insertion are discussed, which are completely ignored in the literature.

Methods for Improving the Curvature of Steerable Needles in Biological Tissue

OBJECTIVE

Robotic needle steering systems have the potential to improve percutaneous interventions such as radiofrequency ablation of liver tumors, but steering techniques described to date have not achieved sufficiently small radius of curvature in biological tissue to be relevant to this application. In this study, the impact of tip geometry on steerable needle curvature was examined.

METHODS

Finite-element simulations and experiments with bent-tip needles in ex vivo liver tissue were performed. Motivated by the results of this analysis, a new articulated-tip steerable needle was designed, in which a distal section is actively switched by a robotic system between a straight tip (resulting in a straight path) and a bent tip (resulting in a curved path).

RESULTS

Selection of tip length and angle can greatly improve curvature, with radius of curvature below 5 cm in liver tissue possible through judicious selection of these parameters. An articulated-tip mechanism allows the tip length and angle to be increased, while the straight configuration allows the needle tip to still pass through an introducer sheath and rotate inside the body.

CONCLUSION

Validation testing in liver tissue shows that the new articulated-tip steerable needle achieves smaller radius of curvature compared to bent-tip needles described in previous work.

SIGNIFICANCE

Steerable needles with optimized tip parameters, which can generate tight curves in liver tissue, increase the clinical relevance of needle steering to percutaneous interventions.

Multiscale layered biomechanical model of the pacinian corpuscle

This paper describes a multiscale analytical model of the lamellar structure and the biomechanical response of the Pacinian Corpuscle (PC). In order to analyze the contribution of the PC lamellar structure for detecting high-frequency vibrotactile (VT) stimuli covering 10 Hz to a few kHz, the model response is studied against trapezoidal and sinusoidal stimuli. The model identifies a few generalizable features of the lamellar structure which makes it scalable for different sizes of PC with different number of lamellae. The model describes the mechanical signal conditioning of the lamellar structure in terms of a recursive transfer-function, termed as the Compression-Transmittance-Transfer-Function (CTTF). The analytical results show that with the increase of the PC layer index above 15, the PC inner core (IC) relaxes within 1 ms against step compression of the outermost layer. This model also considers the mass of each PC layer to investigate its effect on the biomechanical response of the lamellar structure. The interlamellar spacing and its biomechanical properties along with the model response are validated with experimental data in the literature. The proposed model can be used for simulating a network of PCs considering their diversity for analyzing the high-frequency VT sensitivity of the human skin.

Needle Insertion Force Modeling using Genetic Programming Polynomial Higher Order Neural Network

Precise insertion of a medical needle as an end-effecter of a robotic or computer-aided system into biological tissue is an important issue and should be considered in different operations, such as brain biopsy, prostate brachytherapy, and percutaneous therapies. Proper understanding of the whole procedure leads to a better performance by an operator or system. In this chapter, the authors use a 0.98 mm diameter needle with a real-time recording of force, displacement, and velocity of needle through biological tissue during in-vitro insertions. Using constant velocity experiments from 5 mm/min up to 300 mm/min, the data set for the force-displacement graph of insertion was gathered. Tissue deformation with a small puncture and a constant velocity penetration are the two first phases in the needle insertion process. Direct effects of different parameters and their correlations during the process is being modeled using a polynomial neural network. The authors develop different networks in 2nd and 3rd order to model the two first phases of insertion separately. Modeling accuracies were 98% and 86% in phase 1 and 2, respectively.

Combining ultrasound-based elasticity estimation and FE models to predict 3D target displacement

During minimally invasive surgical procedures (e.g., needle insertion during interventional radiological procedures), needle-tissue interactions and physiological processes cause tissue deformation. Target displacement is caused by soft-tissue deformation, which results in misplacement of the surgical tool (needle). This study presents a technique to predict target displacement in three-dimensions (3D) by combining soft-tissue elasticity estimation using an ultrasound-based acoustic radiation force impulse (ARFI) technique and finite element (FE) models. Three different phantoms with targets are manufactured, and subjected to varying loading and boundary conditions. Ultrasound images are acquired using a 3D probe during loading and unloading of each phantom, and subsequently target displacement is calculated. 3D FE models of the phantoms are developed, and they are used to predict target displacement. The maximum absolute error in target displacement between the experiments and FE analyses is found to be 1.39mm. This error is less than the smallest tumor diameter (2.0-3.0mm) which can be detected in breast tissue. This study shows that the combination of soft-tissue elasticity estimation using the ARFI technique and 3D FE models can accurately predict target displacement, and could be used to develop patient-specific plans for surgical interventions.

Coaxial needle insertion assistant with enhanced force feedback

Many medical procedures involving needle insertion into soft tissues, such as anesthesia, biopsy, brachytherapy, and placement of electrodes, are performed without image guidance. In such procedures, haptic detection of changing tissue properties at different depths during needle insertion is important for needle localization and detection of subsurface structures. However, changes in tissue mechanical properties deep inside the tissue are difficult for human operators to sense, because the relatively large friction force between the needle shaft and the surrounding tissue masks the smaller tip forces. A novel robotic coaxial needle insertion assistant, which enhances operator force perception, is presented. This one-degree-of-freedom cable-driven robot provides to the operator a scaled version of the force applied by the needle tip to the tissue, using a novel design and sensors that separate the needle tip force from the shaft friction force. The ability of human operators to use the robot to detect membranes embedded in artificial soft tissue was tested under the conditions of 1) tip force and shaft force feedback, and 2) tip force only feedback. The ratio of successful to unsuccessful membrane detections was significantly higher (up to 50%) when only the needle tip force was provided to the user.

Target motion predictions for pre-operative planning during needle-based interventions

During biopsies, breast tissue is subjected to displacement upon needle indentation, puncture, and penetration. Thus, accurate needle placement requires pre-operative predictions of the target motions. In this paper, we used ultrasound elastography measurements to non-invasively predict elastic properties of breast tissue phantoms. These properties were used in finite element (FE) models of indentation of breast soft tissue phantoms. To validate the model predictions of target motion, experimental measurements were carried out. Breast tissue phantoms with cubic and hemispherical geometries were manufactured and included materials with different elastic properties to represent skin, adipose tissue, and lesions. Ultrasound was used to track the displacement of the target (i.e., the simulated lesion) during indentation. The FE model predictions were compared with ultrasound measurements for cases with different boundary conditions and phantom geometry. Maximum errors between measured and predicted target motions were 12% and 3% for the fully supported and partially supported cubic phantoms at 6.0 mm indentation, respectively. Further, FE-based parameter sensitivity analysis indicated that increasing skin elastic modulus and reducing the target depth location increased the target motion. Our results indicate that with a priori knowledge about the geometry, boundary conditions, and linear elastic properties, indentation of breast tissue phantoms can be accurately predicted with FE models. FE models for pre-operative planning in combination with robotic needle insertions, could play a key role in improving lesion targeting for breast biopsies.

Mechanics of Flexible Needles Robotically Steered through Soft Tissue

The tip asymmetry of a bevel-tip needle results in the needle naturally bending when it is inserted into soft tissue. This enables robotic needle steering, which can be used in medical procedures to reach subsurface targets inaccessible by straight-line trajectories. However, accurate path planning and control of needle steering requires models of needle-tissue interaction. Previous kinematic models required empirical observations of each needle and tissue combination in order to fit model parameters. This study describes a mechanics-based model of robotic needle steering, which can be used to predict needle behavior and optimize system design based on fundamental mechanical and geometrical properties of the needle and tissue. We first present an analytical model for the loads developed at the tip, based on the geometry of the bevel edge and material properties of soft-tissue simulants (gels). We then present a mechanics-based model that calculates the deflection of a bevel-tipped needle inserted through a soft elastic medium. The model design is guided by microscopic observations of needle-gel interactions. The energy-based formulation incorporates tissue-specific parameters, and the geometry and material properties of the needle. Simulation results follow similar trends (deflection and radius of curvature) to those observed in experimental studies of robotic needle insertion.

Characterization of Plastic Hypodermic Needles

A significant potential for plastic hypodermic needles exists as an alternative to current steel needles. This paper presents the design and testing of one type of plastic hypodermic needle. The buckling and penetration characteristics of the needles were modeled and analyzed analytically and by finite element analyses. Experimental penetration tests using plastic and steel control hypodermic needles with skin mimics, specifically polyurethane film and pig skin, were performed to determine penetration and friction forces. Lubricated plastic needles achieved successful penetrations in 25–75% of the tests in both polyurethane film and pig skin with penetration forces ranging from 7 N to 10 N. Penetration tests into butyl rubber stoppers also were conducted with lubricated plastic needles penetrating in 75% of the tests with an average penetration force of 8.3 N. Various lubricants, including silicone oil and a medical grade silicone dispersion, were also studied. In addition, the needles underwent successful perpendicular bending tests and cannula stiffness tests. Finally, fluid flow tests determined fluid flow rates through the needles. Experimental results were compared with each other and to finite element analyses and are discussed.

Dual-channel Haptic Synthesis of Viscoelastic Tissue Properties using Programmable Eddy Current Brakes

We describe a novel method for haptic synthesis of viscoelastic responses which employs a dual-channel haptic interface. It has motors that generate torque independently of velocity and brakes that generate viscous torque independently of position. In this way, twice as many states are directly accessible, which reduces reliance on observation and feedback. Torque-generating actuators, e.g. DC motors, are well known. For the viscous actuators, we use eddy current brakes as programmable, linear, non-contact, physical dampers. By decomposing a mechanical impedance to be realized into viscous and elastic components, we can dedicate each actuator to that component it is ideally suited to synthesize, dampers for the viscous component, and motors for the elastic component. The decomposition is in general not unique so it is possible to select the option that takes the best advantage of the hardware. Experimental results show that this technique can render a variety of viscoelastic models without the artifacts that can occur when synthesizing viscous components on conventional haptic interfaces. The synthesized mechanical impedances have guaranteed passivity, and can have arbitrarily high or low viscous and elastic components.

Characterization of pre-curved needles for steering in tissue

Needles with tip asymmetry deflect upon insertion into soft tissue, an effect that can be used to steer needles within the body. This paper presents a phenomenological characterization of the steering behavior of pre-curved needles, which have tip asymmetry due to curvature of the needle near the tip. We describe needle construction methods and a needle shaft triangulation algorithm to compute the shape of the needle based on images. Experimental results show that pre-curved needles possess greater dexterity than bevel-tipped needles and achieve radii of curvature similar to pre-bent needles. For long pre-curve arc lengths, the radius of curvature of the needle was found to approach the radius of curvature of the pre-curve. Pre-curved needles were found to display behaviors not seen with bevel-tipped needles, such as the insertion velocity influencing the path of the tip within the tissue and the ability to plastically deform the needle during steering.