Modeling and Control of Steerable Ablation Catheters

Catheters are long, flexible tubes that are extensively used in vascular and cardiac interventions, e.g., cardiac ablation, coronary angiography and mitral valve annuloplasty. Catheter-based cardiac ablation is a well-accepted treatment for atrial fibrillation, a common type of cardiac arrhythmia. During this procedure, a steerable ablation catheter is guided through the vasculature to the left atrium to correct the signal pathways inside the heart and restore normal heart rhythm. The outcome of the ablation procedure depends mainly on the correct positioning of the catheter tip at the target location inside the heart and also on maintaining a consistent contact between the catheter tip and cardiac tissue. In the presence of cardiac and respiratory motions, achieving these goals during the ablation procedure is very challenging without proper 3D visualization, dexterous control of the flexible catheter and an estimate of the catheter tip/tissue contact force. This research project provides the required basis for developing a robotics-assisted catheter manipulation system with contact force control for use in cardiac ablation procedures. The behavior of the catheter is studied in free space as well in contact with the environment to develop mathematical models of the catheter tip that are well suited for developing control systems. The validity of the proposed modeling approaches and the performance of the suggested control techniques are evaluated experimentally. As the first step, the static force-deflection relationship for ablation catheters is described with a large-deflection beam model and an optimized pseudo-rigid-body 3R model. The proposed static model is then used in developing a control system for controlling the contact force when the catheter tip is interacting with a static environment. Our studies also showed that it is possible to estimate the tip/tissue contact force by analyzing the shape of the catheter without installing a force sensor on the catheter. During cardiac ablation, the catheter tip is in contact with a relatively fast moving environment (cardiac tissue). Robotic manipulation of the catheter has the potential to improve the quality of contact between the catheter tip and cardiac tissue. To this end, the frequency response of the catheter is investigated and a control technique is proposed to compensate for the cardiac motion and to maintain a constant tip/tissue contact force. Our study on developing a motion compensated robotics-assisted catheter manipulation system suggests that redesigning the actuation mechanism of current ablation catheters would provide a major improvement in using these catheters in robotics-assisted cardiac ablation procedures

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

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

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

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

Robotic Catheters for Beating Heart Surgery

Compliant and flexible cardiac catheters provide direct access to the inside of the heart via the vascular system without requiring clinicians to stop the heart or open the chest. However, the fast motion of the intracardiac structures makes it difficult to modify and repair the cardiac tissue in a controlled and safe manner. In addition, rigid robotic tools for beating heart surgery require the chest to be opened and the heart exposed, making the procedures highly invasive. The novel robotic catheter system presented here enables minimally invasive repair on the fast-moving structures inside the heart, like the mitral valve annulus, without the invasiveness or risks of stopped heart procedures. In this thesis, I investigate the development of 3D ultrasound-guided robotic catheters for beating heart surgery. First, the force and stiffness values of tissue structures in the left atrium are measured to develop design requirements for the system. This research shows that a catheter will experience contractile forces of 0.5 – 1.0 N and a mean tissue structure stiffness of approximately 0.1 N/mm while interacting with the mitral valve annulus. Next, this thesis presents the catheter system design, including force sensing, tissue resection, and ablation end effectors. In order to operate inside the beating heart, position and force control systems were developed to compensate for the catheter performance limitations of friction and deadzone backlash and evaluated with ex vivo and in vivo experiments. Through the addition of friction and deadzone compensation terms, the system is able to achieve position tracking with less than 1 mm RMS error and force tracking with 0.08 N RMS error under ultrasound image guidance. Finally, this thesis examines how the robotic catheter system enhances beating heart clinical procedures. Specifically, this system improves resection quality while reducing the forces experienced by the tissue by almost 80% and improves ablation performance by reducing contact resistance variations by 97% while applying a constant force on the moving tissue.Engineering and Applied Science

A Survey on the Current Status and Future Challenges Towards Objective Skills Assessment in Endovascular Surgery

Minimally-invasive endovascular interventions have evolved rapidly over the past decade, facilitated by breakthroughs in medical imaging and sensing, instrumentation and most recently robotics. Catheter based operations are potentially safer and applicable to a wider patient population due to the reduced comorbidity. As a result endovascular surgery has become the preferred treatment option for conditions previously treated with open surgery and as such the number of patients undergoing endovascular interventions is increasing every year. This fact coupled with a proclivity for reduced working hours, results in a requirement for efficient training and assessment of new surgeons, that deviates from the “see one, do one, teach one” model introduced by William Halsted, so that trainees obtain operational expertise in a shorter period. Developing more objective assessment tools based on quantitative metrics is now a recognised need in interventional training and this manuscript reports the current literature for endovascular skills assessment and the associated emerging technologies. A systematic search was performed on PubMed (MEDLINE), Google Scholar, IEEXplore and known journals using the keywords, “endovascular surgery”, “surgical skills”, “endovascular skills”, “surgical training endovascular” and “catheter skills”. Focusing explicitly on endovascular surgical skills, we group related works into three categories based on the metrics used; structured scales and checklists, simulation-based and motion-based metrics. This review highlights the key findings in each category and also provides suggestions for new research opportunities towards fully objective and automated surgical assessment solutions

Shape Memory Alloy Actuators and Sensors for Applications in Minimally Invasive Interventions

Reduced access size in minimally invasive surgery and therapy (MIST) poses several restriction on the design of the dexterous robotic instruments. The instruments should be developed that are slender enough to pass through the small sized incisions and able to effectively operate in a compact workspace. Most existing robotic instruments are operated by big actuators, located outside the patient’s body, that transfer forces to the end effector via cables or magnetically controlled actuation mechanism. These instruments are certainly far from optimal in terms of their cost and the space they require in operating room. The lack of adequate sensing technologies make it very challenging to measure bending of the flexible instruments, and to measure tool-tissue contact forces of the both flexible and rigid instruments during MIST. Therefore, it requires the development of the cost effective miniature actuators and strain/force sensors. Having several unique features such as bio-compatibility, low cost, light weight, large actuation forces and electrical resistivity variations, the shape memory alloys (SMAs) show promising applications both as the actuators and strain sensors in MIST. However, highly nonlinear hysteretic behavior of the SMAs hinders their use as actuators. To overcome this problem, an adaptive artificial neural network (ANN) based Preisach model and a model predictive controller have been developed in this thesis to precisely control the output of the SMA actuators. A novel ultra thin strain sensor is also designed using a superelastic SMA wire, which can be used to measure strain and forces for many surgical and intervention instruments. A da Vinci surgical instrument is sensorized with these sensors in order to validate their force sensing capability

Acoustic Radiation Force Impulse Imaging of Radiofrequency Ablation Lesions for Cardiac Ablation Procedures

<p>This dissertation investigates the use of intraprocedure acoustic radiation force impulse (ARFI) imaging for visualization of radiofrequency ablation (RFA) lesions during cardiac transcatheter ablation (TCA) procedures. Tens of thousands of TCA procedures are performed annually to treat atrial fibrillation (AF) and other cardiac arrhythmias. Despite the use of sophisticated electroanatomical mapping (EAM) techniques to validate the modification of the electrical substrate, post-procedure arrhythmia recurrence is common due to incomplete lesion delivery and electrical conduction through lesion line discontinuities. The clinical demand for an imaging modality that can visually confirm the presence and completeness of RFA lesion lines motivated this research.</p><p>ARFI imaging is an ultrasound-based technique that transmits radiation force impulses to locally displace tissue and uses the tissue deformation response to generate images of relative tissue stiffness. RF-induced heating causes irreversible tissue necrosis and contractile protein denaturation that increases the stiffness of the ablated region. Preliminary in vitro and in vivo feasibility studies determined RF ablated myocardium appears stiffer in ARFI images.</p><p>This thesis describes results for ARFI imaging of RFA lesions for three research milestones: 1) an in vivo experimental verification model, 2) a clinically translative animal study, and 3) a preliminary clinical feasibility trial in human patients. In all studies, 2-D ARFI images were acquired in normal sinus rhythm and during diastole to maximize the stiffness contrast between the ablated and unablated myocardium and to minimize the bulk cardiac motion during the acquisition time.</p><p>The first in vivo experiment confirmed there was a significant decrease in the measured ARFI-induced displacement at ablation sites during and after focal RFA; the displacements in the lesion border zone and the detected lesion area stabilized over the first several minutes post-ablation. The implications of these results for ARFI imaging methods and the clinical relevance of the findings are discussed.</p><p>The second and third research chapters of this thesis describe the system integration and implementation of a multi-modality intracardiac ARFI imaging-EAM system for intraprocedure lesion evaluation. EAM was used to guide the 2-D ARFI imaging plane to targeted ablation sites in the canine right atrium (RA); the presence of EAM lesions markers and conduction disturbances in the local activation time (LAT) maps were used to find the sensitivity and specificity of predicting the presence of RFA lesion with ARFI imaging. The contrast and contrast-to-noise ratio between RFA lesion and unablated myocardium were calculated for ARFI and conventional ICE images. The opportunities and potential developments for clinical translation are discussed. </p><p>The last research chapter in this thesis describes a feasibility study of intracardiac ARFI imaging of RFA lesions in clinical patients. ARFI images of clinically relevant ablation sites were acquired, and this pilot study determined ARFI-induced displacements in human myocardium decreased at targeted ablation sites after RF-delivery. The challenges and successes of this pilot study are discussed.</p><p>This work provides evidence that intraprocedure ARFI imaging is a promising technology for the visualization of RFA lesions during cardiac TCA procedures. The clinical significance of this research is discussed, as well as challenges and considerations for future iterations of this technology aiming for clinical translation.</p>Dissertatio

Statistical and Graph-Based Signal Processing: Fundamental Results and Application to Cardiac Electrophysiology

The goal of cardiac electrophysiology is to obtain information about the mechanism, function, and performance of the electrical activities of the heart, the identification of deviation from normal pattern and the design of treatments. Offering a better insight into cardiac arrhythmias comprehension and management, signal processing can help the physician to enhance the treatment strategies, in particular in case of atrial fibrillation (AF), a very common atrial arrhythmia which is associated to significant morbidities, such as increased risk of mortality, heart failure, and thromboembolic events. Catheter ablation of AF is a therapeutic technique which uses radiofrequency energy to destroy atrial tissue involved in the arrhythmia sustenance, typically aiming at the electrical disconnection of the of the pulmonary veins triggers. However, recurrence rate is still very high, showing that the very complex and heterogeneous nature of AF still represents a challenging problem. Leveraging the tools of non-stationary and statistical signal processing, the first part of our work has a twofold focus: firstly, we compare the performance of two different ablation technologies, based on contact force sensing or remote magnetic controlled, using signal-based criteria as surrogates for lesion assessment. Furthermore, we investigate the role of ablation parameters in lesion formation using the late-gadolinium enhanced magnetic resonance imaging. Secondly, we hypothesized that in human atria the frequency content of the bipolar signal is directly related to the local conduction velocity (CV), a key parameter characterizing the substrate abnormality and influencing atrial arrhythmias. Comparing the degree of spectral compression among signals recorded at different points of the endocardial surface in response to decreasing pacing rate, our experimental data demonstrate a significant correlation between CV and the corresponding spectral centroids. However, complex spatio-temporal propagation pattern characterizing AF spurred the need for new signals acquisition and processing methods. Multi-electrode catheters allow whole-chamber panoramic mapping of electrical activity but produce an amount of data which need to be preprocessed and analyzed to provide clinically relevant support to the physician. Graph signal processing has shown its potential on a variety of applications involving high-dimensional data on irregular domains and complex network. Nevertheless, though state-of-the-art graph-based methods have been successful for many tasks, so far they predominantly ignore the time-dimension of data. To address this shortcoming, in the second part of this dissertation, we put forth a Time-Vertex Signal Processing Framework, as a particular case of the multi-dimensional graph signal processing. Linking together the time-domain signal processing techniques with the tools of GSP, the Time-Vertex Signal Processing facilitates the analysis of graph structured data which also evolve in time. We motivate our framework leveraging the notion of partial differential equations on graphs. We introduce joint operators, such as time-vertex localization and we present a novel approach to significantly improve the accuracy of fast joint filtering. We also illustrate how to build time-vertex dictionaries, providing conditions for efficient invertibility and examples of constructions. The experimental results on a variety of datasets suggest that the proposed tools can bring significant benefits in various signal processing and learning tasks involving time-series on graphs. We close the gap between the two parts illustrating the application of graph and time-vertex signal processing to the challenging case of multi-channels intracardiac signals