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Interventional radiologists mainly rely on visual feedback via imaging modalities to steer a needle toward a tumor during biopsy and ablation procedures. In the case of CT-guided procedures, there is a risk of exposure to hazardous X-ray-based ionizing radiation. Therefore, CT scans are usually not used continuously, which increases the chances of a misplacement of the needle and the need for reinsertion, leading to more tissue trauma. Interventionalists also encounter haptic feedback via needle-tissue interaction forces while steering a needle. These forces are useful but insufficient to clearly perceive and identify deep-tissue structures such as tumors. The objective of this paper was to investigate the effect of enhanced force feedback for sensing interaction forces and guiding the needle when applied individually and simultaneously during a virtual CT-guided needle insertion task. We also compared the enhanced haptic feedback to enhanced visual feedback. We hypothesized that enhancing the haptic feedback limits the time needed to reach the target accurately and reduces the number of CT scans, as the interventionalist depends more on real-time enhanced haptic feedback. To test the hypothesis, a simulation environment was developed to virtually steer a needle in five degrees of freedom (DoF) to reach a tumor target embedded in a liver model. Twelve participants performed in the experiment with different feedback conditions where we measured their performance in terms of the following: targeting accuracy, trajectory tracking, number of CT scans required, and the time needed to finish the task. The results suggest that the combination of enhanced haptic feedback for guidance and sensing needle-tissue interaction forces significantly reduce the number of scans and the duration required to finish the task by 32.1% and 46.9%, respectively, when compared to nonenhanced haptic feedback. The other feedback modalities significantly reduced the duration to finish the task by around 30% compared to nonenhanced haptic feedback.

Purpose: Accurate needle placement is crucial for successful tumor treatment using the irreversible electroporation (IRE) method. Multiple needles are inserted around the tumor, ideally in parallel, to achieve uniform electric field distribution. This paper presents a robot utilizing a grid system to enable multiple needles insertion while maintaining parallelism between them., Methods: The robotic system has two degrees of freedom, which allow for the adjustment of the grid system to accommodate targeting lesions in various positions. The robot's performance was evaluated by testing its accuracy across various configurations and target depth locations, as well as its ability to maintain the needle parallelism., Results: The robot has dimensions of ϕ 134 mm and a height of 46 mm, with a total weight of 295 g. The system accuracy test showed that the robot can precisely target points across different target depths and needle orientations, with an average error of 2.71 ± 0.68 mm. Moreover, multiple insertions at different grid locations reveal needle orientation deviations typically below 1 ∘ ., Conclusion: This study presented the design and validation of a robotic grid system. The robot is capable of maintaining insertion accuracy and needle parallelism during multiple needle insertions at various robot configurations. The robot showed promising results with limited needle deviation, making it suitable for IRE procedures., (© 2024. The Author(s).)

Purpose: This work presents the implementation of an RGB-D camera as a surrogate signal for liver respiratory-induced motion estimation. This study aims to validate the feasibility of RGB-D cameras as a surrogate in a human subject experiment and to compare the performance of different correspondence models., Methods: The proposed approach uses an RGB-D camera to compute an abdominal surface reconstruction and estimate the liver respiratory-induced motion. Two sets of validation experiments were conducted, first, using a robotic liver phantom and, secondly, performing a clinical study with human subjects. In the clinical study, three correspondence models were created changing the conditions of the learning-based model., Results: The motion model for the robotic liver phantom displayed an error below 3 mm with a coefficient of determination above 90% for the different directions of motion. The clinical study presented errors of 4.5, 2.5, and 2.9 mm for the three different motion models with a coefficient of determination above 80% for all three cases., Conclusion: RGB-D cameras are a promising method to accurately estimate the liver respiratory-induced motion. The internal motion can be estimated in a non-contact, noninvasive and flexible approach. Additionally, three training conditions for the correspondence model are studied to potentially mitigate intra- and inter-fraction motion., (© 2024. The Author(s).)

Background: Liver medical procedures are considered one of the most challenging because of the liver's complex geometry, heterogeneity, mechanical properties, and movement due to respiration. Haptic features integrated into needle insertion systems and other medical devices could support physicians but are uncommon. Additional training time and safety concerns make it difficult to implement in robot-assisted surgery. The main challenges of any haptic device in a teleoperated system are the stability and transparency levels required to develop a safe and efficient system that suits the physician's needs., Purpose: The objective of the review article is to investigate whether haptic-based teleoperation potentially improves the efficiency and safety of liver needle insertion procedures compared with insertion without haptic feedback. In addition, it looks into haptic technology that can be integrated into simulators to train novice physicians in liver procedures., Methods: This review presents the physician's needs during liver interventions and the consequent requirements of haptic features to help the physician. This paper provides an overview of the different aspects of a teleoperation system in various applications, especially in the medical field. It finally presents the state-of-the-art haptic technology in robot-assisted procedures for the liver. This includes 3D virtual models of the liver and force measurement techniques used in haptic rendering to estimate the real-time position of the surgical instrument relative to the liver., Results: Haptic feedback technology can be used to navigate the surgical tool through the desired trajectory to reach the target accurately and avoid critical regions. It also helps distinguish between various textures of liver tissue., Conclusion: Haptic feedback can complement the physician's experience to compensate for the lack of real-time imaging during Computed Tomography guided (CT-guided) liver procedures. Consequently, it helps the physician mitigate the destruction of healthy tissues and takes less time to reach the target., (© 2023 The Authors. The International Journal of Medical Robotics and Computer Assisted Surgery published by John Wiley & Sons Ltd.)

Irreversible electroporation (IRE) has emerged as an appealing non-ionizing, non-thermal ablation therapy, independent of antineoplastic drugs. Limited but successful outcomes in IRE conducted in vivo, in small focal hepatocellular carcinomas (HCC), have been reported. Nonetheless, the electric parameters of IRE are usually delivered in an unplanned manner. This work investigates the integration of computational modeling to hydrogels mimicking the HCC microenvironment, as a powerful framework to: circumvent ethical concerns of in vivo experimentation; safely tune the electric parameters reaching the IRE electric field threshold; and propel the translation of IRE as a routine clinical alternative to the treatment of HCC. Therefore, a parametric study served to evaluate the effects of the pulse amplitude, the number of pulses and electrodes, the treatment time, the hydrogel-tumor size, and the cell type. The ablation extent was surveyed by confocal microscopy and magnetic resonance imaging (MRI) in cylindrical and realistic tumor-shaped hydrogels, respectively. A large ablation (70%-100%) was verified in all constructs., Competing Interests: The authors declare no conflicts of interest., (© 2023 The Authors. Bioengineering & Translational Medicine published by Wiley Periodicals LLC on behalf of American Institute of Chemical Engineers.)

Fiber reinforced soft pneumatic actuators are hard to control due to their non-linear behavior and non-uniformity introduced by the fabrication process. Model-based controllers generally have difficulty compensating non-uniform and non-linear material behaviors, whereas model-free approaches are harder to interpret and tune intuitively. In this study, we present the design, fabrication, characterization, and control of a fiber reinforced soft pneumatic module with an outer diameter size of 12 mm. Specifically, we utilized the characterization data to adaptively control the soft pneumatic actuator. From the measured characterization data, we fitted mapping functions between the actuator input pressures and the actuator space angles. These maps were used to construct the feedforward control signal and tune the feedback controller adaptively depending on the actuator bending configuration. The performance of the proposed control approach is experimentally validated by comparing the measured 2D tip orientation against the reference trajectory. The adaptive controller was able to successfully follow the prescribed trajectory with a mean absolute error of 0.68° for the magnitude of the bending angle and 3.5° for the bending phase around the axial direction. The data-driven control method introduced in this paper may offer a solution to intuitively tune and control soft pneumatic actuators, compensating for their non-uniform and non-linear behavior., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Mak, Naghibi, Lin and Abayazid.)

Purpose: In recent years, irreversible electroporation (IRE) has been developed to specifically destroy undesirable tissues as an alternative to surgical resection. In this treatment, placing multiple electrodes in parallel is required to create a uniform electric field distribution. The process of maintaining parallel electrodes is challenging, and the effect of the electrodes' orientation accuracy has not been investigated quantitatively. This study investigates the impact of the electrode orientation along with various electrode and pulse parameters on the outcomes of IRE., Methods: The electrode configurations that were considered were parallel, forward, and sideward orientation. A numerical model was developed to study the effect of electrode orientation on the electric field distribution, which was validated experimentally on potato tubers as it has similar properties to biological tissue. In addition, a conductivity test was performed to evaluate the conductivity and electroporation threshold of the potatoes., Results: The developed numerical model was validated by comparing the electroporated volumes between potatoes from the experiment and simulation, which achieved a mean dice score of [Formula: see text]. The potato has an electrical conductivity of 0.044-0.454 S/m with an electroporation threshold of 375 V/cm. ANOVA test showed that the difference in the electroporated regions obtained between a parallel orientation and a 5[Formula: see text] forward and sideward orientation was not significant., Conclusion: This study showed that the developed numerical models were validated and able to predict the outcome of IRE on potatoes. In addition, a 5[Formula: see text] tolerance on the electrode orientation can be defined to obtain a similar response to the parallel orientation., (© 2022. The Author(s).)

Soft pneumatic endoscopes developed for Minimally Invasive Surgeries (MIS) are designed upright which means that the starting positions straight. As the internal chambers are pressurized the endoscopic module starts bending. The relation between the pneumatic pressure and bending is nonlinear as the air needs first to fill the chamber before bending, and additionally frictional interaction to the sheath adds more to this start-up transient behaviour. This highly nonlinear behaviour severely limits the actuator sensitivity, accuracy, and repeatability near the endoscope's center of operating range. This paper introduces a novel pre-bent MR-compatible soft-surgical pneumatic endoscope design aimed to improve the bending performance of soft endoscopes by shifting the start-up transient out of the operating range. The pre-bent design of 12 mm diameter consists of an actuation and stiffening chamber, inextensible shell reinforcement with a backbone and rings, and external sheathing. The design parameters that include cross-sectional area, number of rings and backbone width are determined using Finite Element (FE) analysis. The motion profile of the fabricated endoscope, determined via experimentation, shows a successful shift of the start-up transient while the jamming structure increases the stiffness of the endoscope but limits the bending range. Further design developments of the endoscope are required for clinical application.

Purpose: Irreversible electroporation (IRE) is an emerging technique that has drawn attention in the field of cancer treatment. IRE uses non-thermal electric pulses to induce death of cancerous cells. However, recent studies have shown that the application of this technique may result in heating of the tissue. There is still room for improving its efficiency and defining better treatment protocols. This study investigates the optimal IRE protocols that avoiding the thermal damage during the IRE treatment., Methods: Electrode and pulse parameter are investigated. Finite element models are created to evaluate the ablation area and the temperature changes in the tissue. The model is validated experimentally in bovine liver tissue, while the parameters were optimized using response surface method (RSM)., Results: From analysis of variance, the parameter of electrode distance and input voltage has significant effect to the temperature rise in the IRE treatment of bovine liver (P = 0.020 and P = 0.003 respectively). Meanwhile, only the input voltage significantly affects the ablation area (P < 0.001). The optimal result from RSM showed that for maximum ablation area 250.82mm 2 with no thermal damage, the IRE protocol consisted of an active electrode length of 10 mm, a distance between electrodes of 10 mm, and the delivery of 50 pulses of 41.21 µs and 3000 V., Conclusions: The approach presented in this study allows the optimization of the IRE protocols. An optimal IRE protocol that maximizes the ablation area was successfully calculated which can be applied with no risk of thermal damage to the tissue., (© 2021. The Author(s).)

Purpose: We investigated the parameter configuration in the automatic liver and tumor segmentation using a convolutional neural network based on 2.5D model. The implementation of 2.5D model shows promising results since it allows the network to have a deeper and wider network architecture while still accommodates the 3D information. However, there has been no detailed investigation of the parameter configurations on this type of network model., Methods: Some parameters, such as the number of stacked layers, image contrast, and the number of network layers, were studied and implemented on neural networks based on 2.5D model. Networks are trained and tested by utilizing the dataset from liver and tumor segmentation challenge (LiTS). The network performance was further evaluated by comparing the network segmentation with manual segmentation from nine technical physicians and an experienced radiologist., Results: Slice arrangement testing shows that multiple stacked layers have better performance than a single-layer network. However, the dice scores start decreasing when the number of stacked layers is more than three layers. Adding higher number of layers would cause overfitting on the training set. In contrast enhancement test, implementing contrast enhancement method did not show a statistically significant different to the network performance. While in the network layer test, adding more layers to the network architecture does not always correspond to the increasing dice score result of the network., Conclusions: This paper compares the performance of the network based on 2.5D model using different parameter configurations. The result obtained shows the effect of each parameter and allow the selection of the best configuration in order to improve the network performance in the application of automatic liver and tumor segmentation.

Background: Soft materials, with their compliant properties, enable conformity and safe interaction with human body. With the advance in actuation and sensing of soft materials, new paradigm in robotics called "soft robotics" emerges. Soft robotics has become a new approach in designing medical devices such as wearable robotic gloves and exoskeleton. However, application of soft robotics in surgical instrument inside human body is still in its infancy., Aims: In this paper, current application and design of soft robots specifically applied for endoscopy are reviewed., Materials & Methods: Different aspects in the implementation of soft robotics in endoscope design were reviewed. The key studies about MIS and NOTES were reviewed to establish the clinical background and extract the limitations of current endoscopic device in the last decade., Results and Discussion: In this review study, the implementation of soft robotics concepts in endoscopic application, with highlights on different features of several soft endoscopes, were evaluated. The progress in different aspects of soft robotics endoscope, current state, and future perspectives were also discussed., Conclusion: Based on the survey on the structural specification, actuation, sensing, and stiffening the future soft surgical endoscopes are recommended to fulfil the following specifications: safe especially from pressure leakage, fully biocompatible materials, MR-compatible, capable for large bending in at least two antagonistic directions, modularity, adjustable stiffness., (© 2019 The Authors. The International Journal of Medical Robotics and Computer Assisted Surgery Published by John Wiley & Sons Ltd.)

Background: Respiratory-induced motion (RIM) causes uncertainties in localizing hepatic lesions, which could lead to inaccurate targeting during interventions. One approach to mitigate the problem is respiratory motion estimation (RME), in which the liver motion is estimated by measuring external signals called surrogates., Methods: A learning-based approach has been developed and validated to estimate the RIM of hepatic lesions. External markers placed on the human's abdomen were chosen as surrogates. Accordingly, appropriate motion models (multivariate, Ridge and Lasso regression models) were designed to correlate the liver motion with the abdominal motion, and trained to estimate the superior-inferior (SI) motion of the liver. Three subjects volunteered for 6 sessions of such that liver images acquired by magnetic resonance imaging (MRI) were recorded alongside camera-tracked external markers., Results and Conclusions: The proposed machine learning approach was validated in MRI on human subjects and the results show that the approach could estimate the respiratory-induced SI motion of the liver with a mean absolute error (MAE) accuracy below 2 mm., (© 2018 The Authors. The International Journal of Medical Robotics and Computer Assisted Surgery Published by John Wiley & Sons Ltd.)

Purpose: To develop and evaluate an approach to estimate the respiratory-induced motion of lesions in the chest and abdomen., Materials and Methods: The proposed approach uses the motion of an initial reference needle inserted into a moving organ to estimate the lesion (target) displacement that is caused by respiration. The needles position is measured using an inertial measurement unit (IMU) sensor externally attached to the hub of an initially placed reference needle. Data obtained from the IMU sensor and the target motion are used to train a learning-based approach to estimate the position of the moving target. An experimental platform was designed to mimic respiratory motion of the liver. Liver motion profiles of human subjects provided inputs to the experimental platform. Variables including the insertion angle, target depth, target motion velocity and target proximity to the reference needle were evaluated by measuring the error of the estimated target position and processing time., Results: The mean error of estimation of the target position ranged between 0.86 and 1.29 mm. The processing maximum training and testing time was 5 ms which is suitable for real-time target motion estimation using the needle position sensor., Conclusion: The external motion of an initially placed reference needle inserted into a moving organ can be used as a surrogate, measurable and accessible signal to estimate in real-time the position of a moving target caused by respiration; this technique could then be used to guide the placement of subsequently inserted needles directly into the target.

Background: Ultrasound is an effective tool for breast cancer diagnosis. However, its relatively low image quality makes small lesion analysis challenging. This promotes the development of tools to help clinicians in the diagnosis., Methods: We propose a method for segmentation and three-dimensional (3D) reconstruction of lesions from ultrasound images acquired using the automated breast volume scanner (ABVS). Segmentation and reconstruction algorithms are applied to obtain the lesion's 3D geometry. A total of 140 artificial lesions with different sizes and shapes are reconstructed in gelatin-based phantoms and biological tissue. Dice similarity coefficient (DSC) is used to evaluate the reconstructed shapes. The algorithm is tested using a human breast phantom and clinical data from six patients., Results: DSC values are 0.86 ± 0.06 and 0.86 ± 0.05 for gelatin-based phantoms and biological tissue, respectively. The results are validated by a specialized clinician., Conclusions: Evaluation metrics show that the algorithm accurately segments and reconstructs various lesions. Copyright © 2016 John Wiley & Sons, Ltd., (Copyright © 2016 John Wiley & Sons, Ltd.)

Background: A teleoperation system for bevel-tipped flexible needle steering has been evaluated. Robotic systems have been exploited as the main tool to achieve high accuracy and reliability. However, for reasons of safety and acceptance by the surgical community, keeping the physician tightly in the loop is preferable., Methods: The system uses ultrasound imaging, path planning, and control to compute the desired needle orientation during the insertion and intuitively passes this information to the operator, who teleoperates the motion of the needle's tip. Navigation cues about the computed orientation are provided through haptic and visual feedback to the operator to steer the needle., Results: The targeting accuracy of several co-manipulation strategies were studied in four sets of experiments involving human subjects with clinical backgrounds., Conclusions: Experimental results show that receiving feedback regarding the desired needle orientation improves the targeting accuracy by a factor of 9 with respect to manual insertions. Copyright © 2015 John Wiley & Sons, Ltd., (Copyright © 2015 John Wiley & Sons, Ltd.)

In order to handle complex tasks in hard-to-reach environments, small-scale robots have to possess suitable dexterous and untethered control capabilities. The fabrication and manipulation of soft, small-scale grippers complying to these requirements is now made possible by advances in material science and robotics. In this paper, we use soft, small-scale grippers to demonstrate pick-and-place tasks. The precise remote control is obtained by altering both the magnetic field gradient and the temperature in the workspace. This allows us to regulate the position and grasping configuration of the soft thermally-responsive hydrogel-nanoparticle composite magnetic grippers. The magnetic closed-loop control achieves precise localization with an average region-of-convergence of the gripper of 0.12±0.05 mm. The micro-sized payload can be placed with a positioning error of 0.57±0.33 mm. The soft grippers move with an average velocity of 0.72±0.13 mm/s without a micro-sized payload, and at 1.09±0.07 mm/s with a micro-sized payload.

In this paper, we present a system capable of automatically steering a bevel-tipped flexible needle under ultrasound guidance toward a physical target while avoiding a physical obstacle embedded in gelatin phantoms and biological tissue with curved surfaces. An ultrasound pre-operative scan is performed for three-dimensional (3D) target localization and shape reconstruction. A controller based on implicit force control is developed to align the transducer with curved surfaces to assure the maximum contact area, and thus obtain an image of sufficient quality. We experimentally investigate the effect of needle insertion system parameters such as insertion speed, needle diameter and bevel angle on target motion to adjust the parameters that minimize the target motion during insertion. A fast sampling-based path planner is used to compute and periodically update a feasible path to the target that avoids obstacles. We present experimental results for target reconstruction and needle insertion procedures in gelatin-based phantoms and biological tissue. Mean targeting errors of 1.46±0.37 mm, 1.29±0.29 mm and 1.82±0.58 mm are obtained for phantoms with inclined, curved and combined (inclined and curved) surfaces, respectively, for insertion distance of 86-103 mm. The achieved targeting errors suggest that our approach is sufficient for targeting lesions of 3mm radius that can be detected using clinical ultrasound imaging systems., (Copyright © 2014 IPEM. Published by Elsevier Ltd. All rights reserved.)

Purpose: In this paper, we present a system capable of automatically steering bevel tip flexible needles under ultrasound guidance toward stationary and moving targets in gelatin phantoms and biological tissue while avoiding stationary and moving obstacles. We use three-dimensional (3D) ultrasound to track the needle tip during the procedure., Methods: Our system uses a fast sampling-based path planner to compute and periodically update a feasible path to the target that avoids obstacles. We then use a novel control algorithm to steer the needle along the path in a manner that reduces the number of needle rotations, thus reducing tissue damage. We present experimental results for needle insertion procedures for both stationary and moving targets and obstacles for up to 90 mm of needle insertion., Results: We obtained a mean targeting error of [Formula: see text] and [Formula: see text] mm in gelatin-based phantom and biological tissue, respectively., Conclusions: The achieved submillimeter accuracy suggests that our approach is sufficient to target the smallest lesions ([Formula: see text] 2 mm) that can be detected using state-of-the-art ultrasound imaging systems.

Needle insertion in soft-tissue is a minimally invasive surgical procedure that demands high accuracy. In this respect, robotic systems with autonomous control algorithms have been exploited as the main tool to achieve high accuracy and reliability. However, for reasons of safety and responsibility, autonomous robotic control is often not desirable. Therefore, it is necessary to focus also on techniques enabling clinicians to directly control the motion of the surgical tools. In this work, we address that challenge and present a novel teleoperated robotic system able to steer flexible needles. The proposed system tracks the position of the needle using an ultrasound imaging system and computes needle's ideal position and orientation to reach a given target. The master haptic interface then provides the clinician with mixed kinesthetic-vibratory navigation cues to guide the needle toward the computed ideal position and orientation. Twenty participants carried out an experiment of teleoperated needle insertion into a soft-tissue phantom, considering four different experimental conditions. Participants were provided with either mixed kinesthetic-vibratory feedback or mixed kinesthetic-visual feedback. Moreover, we considered two different ways of computing ideal position and orientation of the needle: with or without set-points. Vibratory feedback was found more effective than visual feedback in conveying navigation cues, with a mean targeting error of 0.72 mm when using set-points, and of 1.10 mm without set-points.

Needle insertion is commonly performed in minimally invasive medical procedures such as biopsy and radiation cancer treatment. During such procedures, accurate needle tip placement is critical for correct diagnosis or successful treatment. Accurate placement of the needle tip inside tissue is challenging, especially when the target moves and anatomical obstacles must be avoided. We develop a needle steering system capable of autonomously and accurately guiding a steerable needle using two-dimensional (2D) ultrasound images. The needle is steered to a moving target while avoiding moving obstacles in a three-dimensional (3D) non-static environment. Using a 2D ultrasound imaging device, our system accurately tracks the needle tip motion in 3D space in order to estimate the tip pose. The needle tip pose is used by a rapidly exploring random tree-based motion planner to compute a feasible needle path to the target. The motion planner is sufficiently fast such that replanning can be performed repeatedly in a closed-loop manner. This enables the system to correct for perturbations in needle motion, and movement in obstacle and target locations. Our needle steering experiments in a soft-tissue phantom achieves maximum targeting errors of 0.86 ± 0.35 mm (without obstacles) and 2.16 ± 0.88 mm (with a moving obstacle).

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.