1,119 research outputs found

    Respiratory Compensated Robot for Liver Cancer Treatment: Design, Fabrication, and Benchtop Characterization

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    Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related death in the world. Radiofrequency ablation (RFA) is an effective method for treating tumors less than 5 cm. However, manually placing the RFA needle at the site of the tumor is challenging due to the complicated respiratory induced motion of the liver. This paper presents the design, fabrication, and benchtop characterization of a patient mounted, respiratory compensated robotic needle insertion platform to perform percutaneous needle interventions. The robotic platform consists of a 4-DoF dual-stage cartesian platform used to control the pose of a 1-DoF needle insertion module. The active needle insertion module consists of a 3D printed flexible fluidic actuator capable of providing a step-like, grasp-insert-release actuation that mimics the manual insertion procedure. Force characterization of the needle insertion module indicates that the device is capable of producing 22.6 ± 0.40 N before the needle slips between the grippers. Static phantom targeting experiments indicate a positional error of 1.14 ± 0.30 mm and orientational error of 0.99° ± 0.36°. Static ex-vivo porcine liver targeting experiments indicate a positional error of 1.22 ± 0.31 mm and orientational error of 1.16° ± 0.44°. Dynamic targeting experiments with the proposed active motion compensation in dynamic phantom and ex-vivo porcine liver show 66.3% and 69.6% positional accuracy improvement, respectively. Future work will continue to develop this platform with the long-term goal of applying the system to RFA for HCC

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

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    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

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    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

    Medical robots for MRI guided diagnosis and therapy

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    Magnetic Resonance Imaging (MRI) provides the capability of imaging tissue with fine resolution and superior soft tissue contrast, when compared with conventional ultrasound and CT imaging, which makes it an important tool for clinicians to perform more accurate diagnosis and image guided therapy. Medical robotic devices combining the high resolution anatomical images with real-time navigation, are ideal for precise and repeatable interventions. Despite these advantages, the MR environment imposes constraints on mechatronic devices operating within it. This thesis presents a study on the design and development of robotic systems for particular MR interventions, in which the issue of testing the MR compatibility of mechatronic components, actuation control, kinematics and workspace analysis, and mechanical and electrical design of the robot have been investigated. Two types of robotic systems have therefore been developed and evaluated along the above aspects. (i) A device for MR guided transrectal prostate biopsy: The system was designed from components which are proven to be MR compatible, actuated by pneumatic motors and ultrasonic motors, and tracked by optical position sensors and ducial markers. Clinical trials have been performed with the device on three patients, and the results reported have demonstrated its capability to perform needle positioning under MR guidance, with a procedure time of around 40mins and with no compromised image quality, which achieved our system speci cations. (ii) Limb positioning devices to facilitate the magic angle effect for diagnosis of tendinous injuries: Two systems were designed particularly for lower and upper limb positioning, which are actuated and tracked by the similar methods as the first device. A group of volunteers were recruited to conduct tests to verify the functionality of the systems. The results demonstrate the clear enhancement of the image quality with an increase in signal intensity up to 24 times in the tendon tissue caused by the magic angle effect, showing the feasibility of the proposed devices to be applied in clinical diagnosis

    Lab-on-a-Chip Fabrication and Application

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    The necessity of on-site, fast, sensitive, and cheap complex laboratory analysis, associated with the advances in the microfabrication technologies and the microfluidics, made it possible for the creation of the innovative device lab-on-a-chip (LOC), by which we would be able to scale a single or multiple laboratory processes down to a chip format. The present book is dedicated to the LOC devices from two points of view: LOC fabrication and LOC application

    A Novel Minimally Invasive Tumour Localization Device

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    Lung cancer is one of the leading causes of death, by cancer. The usual treatment is surgical resection of tumours. However, patients who are weak or have poor pulmonary function are deemed unfit for surgery. For these patients, a minimally-invasive approach is desired. A major problem associated with minimally-invasive approaches is tumour localization in real time and accurate measurement of tool--tissue forces. This thesis describes the design, analysis, manufacturing and validation of a minimally-invasive instrument for tumour localization, named Palpatron. The instrument has an end effector that is able to support two previously designed jaws, one containing an ultrasound sensor and the other a tactile sensor. The jaws can move with two degrees of freedom to palpate tissue and rotate about the central axis of the instrument. The Palpatron has uncoupled jaw motion that allows for optimal alignment of sensors to improve data acquisition. The instrument can be easily assembled and disassembled allowing it to be cleaned and sterilized. The mechanism is articulated using push rods, each actuated by a motor. A semi-automatic control system was created for palpation. It is composed of a microcontroller that controls four motors via serial communication. In addition, the Palpatron has the ability to prevent tissue damage by measuring tool--tissue forces. Finite element analysis was used to guide material selection for designed components. Grade 5 titanium was selected for end effector links to provide a factor of safety of 1.2 against yielding under a 10 N point load at the tip of a jaw. The design was fabricated and validated by conducting experiments to test articulation and load carrying capacity. An 8-N force was applied to the instrument, which was successfully supported. The semi-automatic control system was used to perform basic maneuvering tasks to verify jaw motion capabilities. With positive testing results, the Palpatron forms the next step towards a comprehensive robotic-assisted palpation technology

    Design and Development of a Surgical Robot for Needle-Based Medical Interventions

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    Lung cancer is the leading cause of cancer related deaths. If diagnosed in a timely manner, the treatment of choice is surgical resection of the cancerous lesions followed by radiotherapy. However, surgical resection may be too invasive for some patients due to old age or weakness. An alternative is minimally invasive needle-based interventions for cancer diagnosis and treatment. This project describes the design, analysis, development and experimental evaluation of a modular, compact, patient-mounted robotic manipulator for lung cancer diagnosis and treatment. In this regard, a novel parallel Remote Centre of Motion (RCM) mechanism is proposed for minimally invasive delivery of needle-based interventions. The proposed robot provides four degrees of freedom (DOFs) to orient and move a surgical needle within a spherical coordinate system. There is an analytical solution for the kinematics of the proposed parallel mechanism and the end-effectors motion is well-conditioned within the required workspace. The RCM is located beneath the skin surface to minimize the invasiveness of the surgical procedure while providing the required workspace to target the cancerous lesions. In addition, the proposed robot benefits from a design capable of measuring the interaction forces between the needle and the tissue. The experimental evaluation of the robot has proved its capability to accurately orient and move a surgical needle within the required workspace. Although this robotic system has been designed for the treatment of lung cancer, it is capable of performing other procedures in the thoracic or abdominal cavity such as liver cancer diagnosis and treatment

    Surgical Subtask Automation for Intraluminal Procedures using Deep Reinforcement Learning

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    Intraluminal procedures have opened up a new sub-field of minimally invasive surgery that use flexible instruments to navigate through complex luminal structures of the body, resulting in reduced invasiveness and improved patient benefits. One of the major challenges in this field is the accurate and precise control of the instrument inside the human body. Robotics has emerged as a promising solution to this problem. However, to achieve successful robotic intraluminal interventions, the control of the instrument needs to be automated to a large extent. The thesis first examines the state-of-the-art in intraluminal surgical robotics and identifies the key challenges in this field, which include the need for safe and effective tool manipulation, and the ability to adapt to unexpected changes in the luminal environment. To address these challenges, the thesis proposes several levels of autonomy that enable the robotic system to perform individual subtasks autonomously, while still allowing the surgeon to retain overall control of the procedure. The approach facilitates the development of specialized algorithms such as Deep Reinforcement Learning (DRL) for subtasks like navigation and tissue manipulation to produce robust surgical gestures. Additionally, the thesis proposes a safety framework that provides formal guarantees to prevent risky actions. The presented approaches are evaluated through a series of experiments using simulation and robotic platforms. The experiments demonstrate that subtask automation can improve the accuracy and efficiency of tool positioning and tissue manipulation, while also reducing the cognitive load on the surgeon. The results of this research have the potential to improve the reliability and safety of intraluminal surgical interventions, ultimately leading to better outcomes for patients and surgeons
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