41 research outputs found

    Context-aware learning for robot-assisted endovascular catheterization

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    Endovascular intervention has become a mainstream treatment of cardiovascular diseases. However, multiple challenges remain such as unwanted radiation exposures, limited two-dimensional image guidance, insufficient force perception and haptic cues. Fast evolving robot-assisted platforms improve the stability and accuracy of instrument manipulation. The master-slave system also removes radiation to the operator. However, the integration of robotic systems into the current surgical workflow is still debatable since repetitive, easy tasks have little value to be executed by the robotic teleoperation. Current systems offer very low autonomy, potential autonomous features could bring more benefits such as reduced cognitive workloads and human error, safer and more consistent instrument manipulation, ability to incorporate various medical imaging and sensing modalities. This research proposes frameworks for automated catheterisation with different machine learning-based algorithms, includes Learning-from-Demonstration, Reinforcement Learning, and Imitation Learning. Those frameworks focused on integrating context for tasks in the process of skill learning, hence achieving better adaptation to different situations and safer tool-tissue interactions. Furthermore, the autonomous feature was applied to next-generation, MR-safe robotic catheterisation platform. The results provide important insights into improving catheter navigation in the form of autonomous task planning, self-optimization with clinical relevant factors, and motivate the design of intelligent, intuitive, and collaborative robots under non-ionizing image modalities.Open Acces

    Image-Based Force Estimation and Haptic Rendering For Robot-Assisted Cardiovascular Intervention

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    Clinical studies have indicated that the loss of haptic perception is the prime limitation of robot-assisted cardiovascular intervention technology, hindering its global adoption. It causes compromised situational awareness for the surgeon during the intervention and may lead to health risks for the patients. This doctoral research was aimed at developing technology for addressing the limitation of the robot-assisted intervention technology in the provision of haptic feedback. The literature review showed that sensor-free force estimation (haptic cue) on endovascular devices, intuitive surgeon interface design, and haptic rendering within the surgeon interface were the major knowledge gaps. For sensor-free force estimation, first, an image-based force estimation methods based on inverse finite-element methods (iFEM) was developed and validated. Next, to address the limitation of the iFEM method in real-time performance, an inverse Cosserat rod model (iCORD) with a computationally efficient solution for endovascular devices was developed and validated. Afterward, the iCORD was adopted for analytical tip force estimation on steerable catheters. The experimental studies confirmed the accuracy and real-time performance of the iCORD for sensor-free force estimation. Afterward, a wearable drift-free rotation measurement device (MiCarp) was developed to facilitate the design of an intuitive surgeon interface by decoupling the rotation measurement from the insertion measurement. The validation studies showed that MiCarp had a superior performance for spatial rotation measurement compared to other modalities. In the end, a novel haptic feedback system based on smart magnetoelastic elastomers was developed, analytically modeled, and experimentally validated. The proposed haptics-enabled surgeon module had an unbounded workspace for interventional tasks and provided an intuitive interface. Experimental validation, at component and system levels, confirmed the usability of the proposed methods for robot-assisted intervention systems

    Pressure drop and recovery in cases of cardiovascular disease: a computational study

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    The presence of disease in the cardiovascular system results in changes in flow and pressure patterns. Increased resistance to the flow observed in cases of aortic valve and coronary artery disease can have as a consequence abnormally high pressure gradients, which may lead to overexertion of the heart muscle, limited tissue perfusion and tissue damage. In the past, computational fluid dynamics (CFD) methods have been used coupled with medical imaging data to study haemodynamics, and it has been shown that CFD has great potential as a way to study patient-specific cases of cardiovascular disease in vivo, non-invasively, in great detail and at low cost. CFD can be particularly useful in evaluating the effectiveness of new diagnostic and treatment techniques, especially at early ‘concept’ stages. The main aim of this thesis is to use CFD to investigate the relationship between pressure and flow in cases of disease in the coronary arteries and the aortic valve, with the purpose of helping improve diagnosis and treatment, respectively. A transitional flow CFD model is used to investigate the phenomenon of pressure recovery in idealised models of aortic valve stenosis. Energy lost as turbulence in the wake of a diseased valve hinders pressure recovery, which occurs naturally when no energy losses are observed. A “concept” study testing the potential of a device that could maximise pressure recovery to reduce the pressure load on the heart muscle was conducted. The results indicate that, under certain conditions, such a device could prove useful. Fully patient-specific CFD studies of the coronary arteries are fewer than studies in larger vessels, mostly due to past limitations in the imaging and velocity data quality. A new method to reconstruct coronary anatomy from optical coherence tomography (OCT) data is presented in the thesis. The resulting models were combined with invasively acquired pressure and flow velocity data in transient CFD simulations, in order to test the ability of CFD to match the invasively measured pressure drop. A positive correlation and no bias were found between the calculated and measured results. The use of lower resolution reconstruction methods resulted in no correlation between the calculated and measured results, highlighting the importance of anatomical accuracy in the effectiveness of the CFD model. However, it was considered imperative that the limitations of CFD in predicting pressure gradients be further explored. It was found that the CFD-derived pressure drop is sensitive to changes in the volumetric flow rate, while bench-top experiments showed that the estimation of volumetric flow rate from invasively measured velocity data is subject to errors and uncertainties that may have a random effect on the CFD pressure result. This study demonstrated that the relationship between geometry, pressure and flow can be used to evaluate new diagnostic and treatment methods. In the case of aortic stenosis, further experimental work is required to turn the concept of a pressure recovery device into a potential clinical tool. In the coronary study it was shown that, though CFD has great power as a study tool, its limitations, especially those pertaining to the volumetric flow rate boundary condition, must be further studied and become fully understood before CFD can be reliably used to aid diagnosis in clinical practice.Open Acces

    Design, Development and Force Control of a Tendon-driven Steerable Catheter with a Learning-based Approach

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    In this research, a learning-based force control schema for tendon-driven steerable catheters with the application in robot-assisted tissue ablation procedures was proposed and validated. To this end, initially a displacement-based model for estimating the contact force between the catheter and tissue was developed. Afterward, a tendon-driven catheter was designed and developed. Next, a software-hardware-integrated robotic system for controlling and monitoring the pose of the catheter was designed and developed. Also, a force control schema was developed based on the developed contact force model as a priori knowledge. Furthermore, the position control of the tip of the catheter was performed using a learning-based inverse kinematic approach. By combining the position control and the contact model, the force control schema was developed and validated. Validation studies were performed on phantom tissue as well as excised porcine tissue. Results of the validation studies showed that the proposed displacement-based model was 91.5% accurate in contact force prediction. Also, the system was capable of following a set of desired trajectories with an average root-mean-square error of less than 5%. Further validation studies revealed that the system could fairly generate desired static and dynamic force profiles on the phantom tissue. In summary, the proposed force control system did not necessitate the utilization of force sensors and could fairly contribute in automatizing the ablation task for robotic tissue ablation procedures

    Modeling and Force Estimation of Cardiac Catheters for Haptics-enabled Tele-intervention

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    Robot-assisted cardiovascular intervention (RCI) systems have shown success in reducing the x-ray exposure to surgeons and patients during cardiovascular interventional procedures. RCI systems typically are teleoperated systems with leader-follower architecture. With such system architecture, the surgeon is placed out of the x-ray exposure zone and uses a console to control the robot remotely. Despite its success in reducing x-ray exposure, clinicians have identified the lack of force feedback as to its main technological limitation that can lead to vascular perforation of the patient’s vessels and even their death. The objective of this thesis was to develop, verify, and validate mechatronics technology for real-time accurate and robust haptic feedback rendering for RCI systems. To attain the thesis objective, first, a thorough review of the state-of-the-art clinical requirements, modeling approaches and methods, and current knowledge gaps for the provision of force feedback for RCI systems was performed. Afterward, a real-time tip force estimation method based on image-based shape-sensing and learning-from-simulation was developed and validated. The learning-based model was fairly accurate but required a large database for training which was computationally expensive. Next, a new mechanistic model, i.e., finite arc method (FAM) for soft robots was proposed, formulated, solved, and validated that allowed for fast and accurate modeling of catheter deformation. With FAM, the required training database for the proposed learning-from-simulation method would be generated with high speed and accuracy. In the end, to robustly relay the estimated forces from real-time imaging from the follower robot to the leader haptic device, a novel impedance-based force feedback rendering modality was proposed and implemented on a representative teleoperated RCI system for experimental validation. The proposed method was compared with the classical direct force reflection method and showed enhanced stability, robustness, and accuracy in the presence of communication disruption. The results of this thesis showed that the performance of the proposed integrated force feedback rendering system was in fair compliance with the clinical requirements and had superior robustness compared to the classical direct force reflection method

    Design, Modeling and Control of Micro-scale and Meso-scale Tendon-Driven Surgical Robots

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    Manual manipulation of passive surgical tools is time consuming with uncertain results in cases of navigating tortuous anatomy, avoiding critical anatomical landmarks, and reaching targets not located in the linear range of these tools. For example, in many cardiovascular procedures, manual navigation of a micro-scale passive guidewire results in increased procedure times and radiation exposure. This thesis introduces the design of two steerable guidewires: 1) A two degree-of-freedom (2-DoF) robotic guidewire with orthogonally oriented joints to access points in a three dimensional workspace, and 2) a micro-scale coaxially aligned steerable (COAST) guidewire robot that demonstrates variable and independently controlled bending length and curvature of the distal end. The 2-DoF guidewire features two micromachined joints from a tube of superelastic nitinol of outer diameter 0.78 mm. Each joint is actuated with two nitinol tendons. The joints that are used in this robot are called bidirectional asymmetric notch (BAN) joints, and the advantages of these joints are explored and analyzed. The design of the COAST robotic guidewire involves three coaxially aligned tubes with a single tendon running centrally through the length of the robot. The outer tubes are made from micromachined nitinol allowing for tendon-driven bending of the robot at variable bending curvatures, while an inner stainless steel tube controls the bending length of the robot. By varying the lengths of the tubes as well as the tendon, and by insertion and retraction of the entire assembly, various joint lengths and curvatures may be achieved. Kinematic and static models, a compact actuation system, and a controller for this robot are presented. The capability of the robot to accurately navigate through phantom anatomical bifurcations and tortuous angles is also demonstrated in three dimensional phantom vasculature. At the meso-scale, manual navigation of passive pediatric neuroendoscopes for endoscopic third ventriculostomy may not reach target locations in the patient's ventricle. This work introduces the design, analysis and control of a meso-scale two degree-of-freedom robotic bipolar electrocautery tool that increases the workspace of the neurosurgeon. A static model is proposed for the robot joints that avoids problems arising from pure kinematic control. Using this model, a control system is developed that comprises of a disturbance observer to provide precise force control and compensate for joint hysteresis. A handheld controller is developed and demonstrated in this thesis. To allow the clinician to estimate the shape of the steerable tools within the anatomy for both micro-scale and meso-scale tools, a miniature tendon force sensor and a high deflection shape sensor are proposed and demonstrated. The force sensor features a compact design consisting of a single LED, dual-phototransistor, and a dual-screen arrangement to increase the linear range of sensor output and compensate for external disturbances, thereby allowing force measurement of up to 21 N with 99.58 % accuracy. The shape sensor uses fiber Bragg grating based optical cable mounted on a micromachined tube and is capable of measuring curvatures as high as 145 /m. These sensors were incorporated and tested in the guidewire and the neuroendoscope tool robots and can provide robust feedback for closed-loop control of these devices in the future.Ph.D

    INTEGRATED DESIGN APPROACH FOR CORONARY STENTS USING FLEXINOL SHAPE MEMORY ALLOY

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    This research seeks to develop and verify a model for control of the shape memory alloy (SMA) Flexinol and apply such findings to practical application of the material as a platform for bare metal stenting technologies. Utilizing experimental data and material properties, a mathematical model of the thermoelectric contraction behavior of Flexinol wire samples was developed. This model accounted for variable resistance due to the shape memory effect of the Flexinol wire as it experiences a crystalline phase change. It also accounted for the change in the cross-sectional area of the wire as the wire experienced thermal expansion and contraction. The resulting constitutive equations were verified via experimentation. This thesis further expanded upon these models and presented the practical application of the SMA Flexinol as a platform for coronary artery stenting technologies. The research presented includes computer-aided design (CAD) modeling and finite element analysis (FEA) simulation of the stress loads when working conditions are applied, which revealed the response behavior of the proposed stent design. With the FEA verification that the Flexinol stent design will be able to sustain normal working conditions once implanted into the human body, it was demonstrated that the proposed low stress design has the potential to reduce the rate of stent failure and restenosis in comparison to typical technologies available on the market

    Coronary atherosclerosis:biomechanics and imaging

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    Coronary atherosclerosis:biomechanics and imaging

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    Guidewire-mounted thermal sensors to assess coronary hemodynamics

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    The vessels of the coronary circulation are prone to arteriosclerotic disease, which can lead to the development of obstructions to blood flow. The conventional way to diagnose the severity of this type of disease is by coronary angiography. This method, however, only provides insight into the morphology of the coronary vessels, whereas for an accurate diagnosis a measure for the actual flow impediment is needed. To perform these measurements, sensor-tipped guidewires have been developed to measure intra-coronary pressure and blood flow velocity. Diagnosis of coronary disease based on the time-average of these measurements have been shown to improve the clinical outcome of treatment significantly. However, since the coronary vessels are embedded in the (contracting) cardiac muscle, the interpretation of these indices is complicated and can be improved by simultaneously assessing the dynamics of coronary pressure and flow. The research described in this thesis therefore focusses on the one hand on developing devices for the simultaneous assessment of coronary pressure and flow dynamics and on the other hand on modeling the heart and coronary vessels to support the interpretation of these dynamic measurements. In the development of a device which can measure both coronary pressure and flow, two different strategies have been chosen. In the first strategy, a method has been developed to operate an already clinically used pressure sensor-tipped guidewire (pressure wire) as a thermal anemometer to also measure flow. In an in-vitro model it has been demonstrated that the power required to electrically heat the sensor is a measure for the shear rate at the sensor surface and that the method can be used to assess coronary flow reserve (CFR). By slightly adapting the method and combining it with a continuous thermodilution method, it has also been shown that the dynamics of both pressure and volumetric flow can be measured simultaneously in physiological representative in-vitro and ex-vivo experiments. The main drawbacks of this thermal method with a pressure wire are the relatively high sensor temperature required and the inability to detect flow reversal. In the second strategy, a new flow sensor, embedded in a flexible polyimide chip, has been specially designed to be mounted on a guidewire. The flow sensing element consists of a heater, operated at constant power, and thermocouples measuring the temperature difference up- and downstream from the heater. To gain insight into the working principle and the importance of the different design parameters, an analytical model has been developed. Experiments where upscaled sensors have been subjected to steady and pulsatile flow, indicate that the model is able to reproduce the experimental results fairly well but that the sensitivity to shear rate is rather limited in the physiological range. This sensitivity to shear rate can possibly be improved by operating the heater at constant temperature, which has been investigated with invitro experiments with upscaled sensors and a finite element analysis of the real, small size sensor. These studies have demonstrated that constant temperature operation of the heater is beneficial over constant power operation and that the dynamics of physiological coronary shear rate, including retrograde flow, can be assessed at an overheat temperature of only 5 K. From these characterization studies a new design of the sensor has been proposed, which is currently being manufactured to be tested in both in-vitro and ex-vivo experiments. To support the interpretation of the dynamic pressure and flow measurements, a numerical model of the heart and coronary circulation has been developed. The model is based on the coupling of four interacting parts: A model for the left ventricle which is based on the mechanics of a single myofiber, a 1D wave propagation model for the large epicardial coronary arteries, a stenosis element, and a Windkessel representation of the coronary micro-vessels. Comparison of the results obtained with the model with experimental observations described in literature has shown that the model is able to simulate the effect of different types of disease on coronary hemodynamics. After further validation, the model can be used as a tool to study the effect of combinations of epicardial and/or microcirculatory disease on pressure- and flow-based indices. To model the relation between the pressure and flow waves in the coronary arteries correctly, as well as to assist in the decision-making regarding the mechanical treatment of coronary stenoses, the mechanical behaviour of the coronary arterial wall is required. Therefore, a mixed numerical-experimental method has been employed to fit a micro-structurally based constitutive model to in-situ extensioninflation experiments on porcine coronary arteries. It has been demonstrated that the model can accurately describe the experimental data and, additionally, it has been found that the most influential parameter, describing the collagen fiber orientation, can be considered constant at physiological loading. In further research, this can be used to tackle over-parameterization issues inherent to fitting similar constitutive models to data obtained in a clinical setting. In this thesis, a computational model of the coronary circulation is presented and methods for simultaneous pressure and flow assessment are introduced. By operating an already clinically used pressure wire as a thermal anemometer, a methodology was developed which is close to clinical application, while a new sensor was designed to be more accurate in different flow conditions
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