Robotic System Development for Precision MRI-Guided Needle-Based Interventions

This dissertation describes the development of a methodology for implementing robotic systems for interventional procedures under intraoperative Magnetic Resonance Imaging (MRI) guidance. MRI is an ideal imaging modality for surgical guidance of diagnostic and therapeutic procedures, thanks to its ability to perform high resolution, real-time, and high soft tissue contrast imaging without ionizing radiation. However, the strong magnetic field and sensitivity to radio frequency signals, as well as tightly confined scanner bore render great challenges to developing robotic systems within MRI environment. Discussed are potential solutions to address engineering topics related to development of MRI-compatible electro-mechanical systems and modeling of steerable needle interventions. A robotic framework is developed based on a modular design approach, supporting varying MRI-guided interventional procedures, with stereotactic neurosurgery and prostate cancer therapy as two driving exemplary applications. A piezoelectrically actuated electro-mechanical system is designed to provide precise needle placement in the bore of the scanner under interactive MRI-guidance, while overcoming the challenges inherent to MRI-guided procedures. This work presents the development of the robotic system in the aspects of requirements definition, clinical work flow development, mechanism optimization, control system design and experimental evaluation. A steerable needle is beneficial for interventional procedures with its capability to produce curved path, avoiding anatomical obstacles or compensating for needle placement errors. Two kinds of steerable needles are discussed, i.e. asymmetric-tip needle and concentric-tube cannula. A novel Gaussian-based ContinUous Rotation and Variable-curvature (CURV) model is proposed to steer asymmetric-tip needle, which enables variable curvature of the needle trajectory with independent control of needle rotation and insertion. While concentric-tube cannula is suitable for clinical applications where a curved trajectory is needed without relying on tissue interaction force. This dissertation addresses fundamental challenges in developing and deploying MRI-compatible robotic systems, and enables the technologies for MRI-guided needle-based interventions. This study applied and evaluated these techniques to a system for prostate biopsy that is currently in clinical trials, developed a neurosurgery robot prototype for interstitial thermal therapy of brain cancer under MRI guidance, and demonstrated needle steering using both asymmetric tip and pre-bent concentric-tube cannula approaches on a testbed

Towards Closed-loop, Robot Assisted Percutaneous Interventions under MRI Guidance

Image guided therapy procedures under MRI guidance has been a focused research area over past decade. Also, over the last decade, various MRI guided robotic devices have been developed and used clinically for percutaneous interventions, such as prostate biopsy, brachytherapy, and tissue ablation. Though MRI provides better soft tissue contrast compared to Computed Tomography and Ultrasound, it poses various challenges like constrained space, less ergonomic patient access and limited material choices due to its high magnetic field. Even after, advancements in MRI compatible actuation methods and robotic devices using them, most MRI guided interventions are still open-loop in nature and relies on preoperative or intraoperative images. In this thesis, an intraoperative MRI guided robotic system for prostate biopsy comprising of an MRI compatible 4-DOF robotic manipulator, robot controller and control application with Clinical User Interface (CUI) and surgical planning applications (3DSlicer and RadVision) is presented. This system utilizes intraoperative images acquired after each full or partial needle insertion for needle tip localization. Presented system was approved by Institutional Review Board at Brigham and Women\u27s Hospital(BWH) and has been used in 30 patient trials. Successful translation of such a system utilizing intraoperative MR images motivated towards the development of a system architecture for close-loop, real-time MRI guided percutaneous interventions. Robot assisted, close-loop intervention could help in accurate positioning and localization of the therapy delivery instrument, improve physician and patient comfort and allow real-time therapy monitoring. Also, utilizing real-time MR images could allow correction of surgical instrument trajectory and controlled therapy delivery. Two of the applications validating the presented architecture; closed-loop needle steering and MRI guided brain tumor ablation are demonstrated under real-time MRI guidance

SMART IMAGE-GUIDED NEEDLE INSERTION FOR TISSUE BIOPSY

M.S

Full 3D motion control for programmable bevel-tip steerable needles

Minimally invasive surgery has been in the focus of many researchers due to its reduced intra- and post-operative risks when compared to an equivalent open surgery approach. In the context of minimally invasive surgery, percutaneous intervention, and particularly, needle insertions, are of great importance in tumour-related therapy and diagnosis. However, needle and tissue deformation occurring during needle insertion often results in misplacement of the needles, which leads to complications, such as unsuccessful treatment and misdiagnosis. To this end, steerable needles have been proposed to compensate for placement errors by allowing curvilinear navigation. A particular type of steerable needle is the programmable bevel-tip steerable needle (PBN), which is a bio-inspired needle that consists of relatively soft and slender segments. Due to its flexibility and bevel-tip segments, it can navigate through 3D curvilinear paths. In PBNs, steering in a desired direction is performed by actuating particular PBN segments. Therefore, the pose of each segment is needed to ensure that the correct segment is actuated. To this end, in this thesis, proprioceptive sensing methods for PBNs were investigated. Two novel methods, an electromagnetic (EM)-based tip pose estimation method and a fibre Bragg grating (FBG)-based full shape sensing method, were presented and evaluated. The error in position was observed to be less than 1.08 mm and 5.76 mm, with the proposed EM-based tip tracking and FBG-based shape reconstruction methods, respectively. Moreover, autonomous path-following controllers for PBNs were also investigated. A closed-loop, 3D path-following controller, which was closed via feedback from FBG-inscribed multi-core fibres embedded within the needle, was presented. The nonlinear guidance law, which is a well-known approach for path-following control of aerial vehicles, and active disturbance rejection control (ADRC), which is known for its robustness within hard-to-model environments, were chosen as the control methods. Both linear and nonlinear ADRC were investigated, and the approaches were validated in both ex vivo brain and phantom tissue, with some of the experiments involving moving targets. The tracking error in position was observed to be less than 6.56 mm.Open Acces

Modeling and simulation of an active robotic device for flexible needle insertion

Master'sMASTER OF ENGINEERIN

MR 유도 유방 바늘 중재시술 로봇을 위한 한정된 자유도 안에서 바늘 스티어링 전략

학위논문 (석사)-- 서울대학교 대학원 : 기계항공공학부, 2017. 2. 이건우.The MR-guided needle-based procedure is commonly performed for breast diagnosis and treatment. Accurate needle tip placement is important for the success of the procedure, because misplacement of the needle tip can lead to unsuccessful treatment and misdiagnosis. In addition, developing a needle steering robotic system with high precision and dexterity is required to avoid important organs, minimizing patients trauma. However, due to the strong magnetic field and relatively small MRI bore size, developing a high degrees of freedom (DOFs) robotic system is challenging. This work proposes a needle steering scheme that can be effectively utilized in an MR-guided breast needle intervention robot under limited space of MRI bore with minimizing system size increase. To overcome the space limitation and avoid critical structures in front of the lesion, a pivot is used to change the needle insertion direction. We devise the needle pivoting breast plate to increase needle tips DOFs and an estimation model of the needle deflection with a pivoted super-elastic flexible needle made of Nitinol. This computational model is based on large deflection beam theory and is employed for robot control. Open-loop needle targeting experiments under infrared tracking cameras are performed to verify the proposed scheme. The average targeting error and the standard deviation is 4.42 ± 2.58 mm.Chapter 1. Introduction 1 Chapter 2. Materials 4 2.1. MR-guided breast needle intervention robot system 4 2.2. Needle pivoting breast plate 7 Chapter 3. Methods 10 3.1. Needle Steering Procedure 10 3.2. Robot pose estimation 12 3.2.1. Large deflection beam theory 13 3.2.2. Estimation of external force 18 3.2.3. Measurement of bending stiffness 19 3.2.4. Define the robot movement direction 25 3.3. Optimal path selection scenario 27 Chapter 4. Results 30 4.1. In vitro test 30 4.1.1. Experiment setup 30 4.1.2. Target error 32 Chapter 5. Discussion 36 Bibliography 40 Abstract in Korean 43Maste

下腹部を対象とした極細針によるCTガイド下高正確度穿刺プランニング

早大学位記番号:新8149早稲田大

Evaluation of Haptic and Visual Cues for Repulsive or Attractive Guidance in Nonholonomic Steering Tasks.

Remote control of vehicles is a difficult task for operators. Support systems that present additional task information may assist operators, but their usefulness is expected to depend on several factors such as 1) the nature of conveyed information, 2) what modality it is conveyed through, and 3) the task difficulty. In an exploratory experiment, these three factors were manipulated to quantify their effects on operator behavior. Subjects ( $n = {{15}}$) used a haptic manipulator to steer a virtual nonholonomic vehicle through abstract environments, in which obstacles needed to be avoided. Both a simple support conveying near-future predictions of the trajectory of the vehicle and a more elaborate support that continuously suggests the path to be taken were designed (factor 1). These types of information were offered either with visual or haptic cues (factor 2). These four support systems were tested in four different abstracted environments with decreasing amount of allowed variability in realized trajectories (factor 3). The results show improvements for the simple support only when this information was presented visually, but not when offered haptically. For the elaborate support, equally large improvements for both modalities were found. This suggests that the elaborate support is better: additional information is key in improving performance in nonholonomic steering tasks

Image-Guided Robot-Assisted Needle Intervention Devices and Methods to Improve Targeting Accuracy

This dissertation addresses the development of medical devices, image-guided robots, and their application in needle-based interventions, as well as methods to improve accuracy and safety in clinical procedures. Needle access is an essential component of minimally invasive diagnostic and therapeutic procedures. Image-guiding devices are often required to help physicians handle the needle based on the images. Integrating robotic accuracy and precision with digital medical imaging has the potential to improve the clinical outcomes. The dissertation presents two robotic devices for interventions under Magnetic Resonance Imaging (MRI) respectively Computed Tomography (CT) – Ultrasound(US) cross modality guidance. The MRI robot is a MR Safe Remote Center of Motion (RCM) robot for direct image-guided needle interventions such as brain surgery. The dissertation also presents the integration of the robot with an intraoperative MRI scanner, and preclinical tests for deep brain needle access. The CT-Ultrasound guidance uses a robotic manipulator to handle an US probe within a CT scanner. The dissertation presents methods related to the co-registration of multi-image spaces with an intermediary frame, experiments for needle targeting. The dissertation also presents method on using optical tracking measurements specifically for medical robots. The method was derived to test the robots presented above. With advanced image-guidance, such as the robotic approaches, needle targeting accuracy may still be deteriorated by errors related to needle defections. Methods and associated devices for needle steering on the straight path are presented. These are a robotic approach that uses real-time ultrasound guidance to steer the needle; Modeling and testing of a method to markedly reduce targeting errors with bevel-point needles; Dynamic design, manufacturing, and testing of a novel core biopsy needle with straighter path, power assistance, reduced noise, and safer operation. Overall, the dissertation presents several developments that contribute to the field of medical devices, image-guided robots, and needle interventions. These include robot testing methods that can be used by other researchers, needle steering methods that can be used directly by physicians or for robotic devices, as well as several methods to improve the accuracy in image-guided interventions. Collectively, these contribute to the field and may have a significant clinical impact

Inverse kinematics solution for trajectory tracking using artificial neural networks for SCORBOT ER-4u

This paper presents the kinematic analysis of the SCORBOT-ER 4u robot arm using a Multi-Layered Feed-Forward (MLFF) Neural Network. The SCORBOT-ER 4u is a 5-DOF vertical articulated educational robot with revolute joints. The Denavit-Hartenberg and Geometrical methods are the forward kinematic algorithms used to generate data and train the neural network. The learning of forward-inverse mapping enables the inverse kinematic solution to be found. The algorithm is tested on hardware (SCORBOT-ER 4u) and reliable results are obtained. The modeling and simulations are done using MATLAB 8.0 software