Courses

You will earn 6 research credits over 6 weeks, conducting a faculty-supervised, hands-on, directed study research projects with results that will culminate in the preparation of a research paper. You will complete a minimum of 240 hours on research in and out of the laboratory.

Faculty mentors will work closely with you to direct your continued growth and knowledge development in the chosen research topic discipline.

• Make sure your courses transfer back for credit with your home school – this is your responsibility.

Choosing Your Research Project

• Review Project titles and descriptions below.
• List 3 (in order of preference) in your Academic Preferences Form, using KING as your course code.
• Program is highly individualized, with limited enrollment.
• You will need to complete a brief Literature Review in consultation with your research supervisor prior to departure before the start of the program. More details here.
• We encourage you to contact Arcadia’s Associate Dean of Academic Access and Curricular Solutions, Rob Hallworth, to discuss your particular research interests further.

Biomedical Engineering at the School of Biomedical Engineering and Imaging Sciences (BMEIS) at King’s College London

Summer 2024 Research Projects

Development and evaluation of robot ablation catheter system for cardiac ablation therapy

Supervisors: kawal.rhode@kcl.ac.uk, zhouyang.xu@kcl.ac.uk

Description: Cardiac ablation is a possible treatment for arrhythmias. Ablation catheters are introduced through small incisions in peripheral blood vessels and used to destroy parts of the myocardium that are responsible for the arrhythmia. The catheters are manually controlled by cardiologists.

Aims: The project aims to develop and evaluate a robotic ablation catheter system with a view to automate cardiac ablation procedures. Our team has already developed and partially tested a robotic system that converts a standard ablation catheter into a robotic system. The project will involve refining the design of the robotic system, implementing control algorithms and carrying out evaluation in partnership with the cardiology team at St. Thomas’ hospital.

Skills developed: Knowledge, understanding and skills in cardiac arrhythmias, cardiac ablation procedures, mechatronics systems, CAD, clinical evaluation of healthcare technologies, and research methods.

Development and evaluation of robot trans-septal puncture system

Supervisors: kawal.rhode@kcl.ac.uk, aya.zeidan@kcl.ac.uk

Description: The atrial septum separates the right and left atria in the heart. During minimally-invasive procedures, access to the left atrium if often achieved by making a small hole in the atrial septum, a procedure known as trans-septal puncture. This procedure requires instruments that form the trans- septal puncture kit and is carried out by a skilled cardiologist using a combination of x-ray and ultrasound imaging. The procedure has a significant risk of complications that can be serious for the patient.

Aims: The project aims to develop and evaluate a robotic trans-septal puncture system with a view to automate this procedure and potentially reduce the risks to the patient. Our team has already designed a system that converts a standard trans-septal puncture kit into a robotic system. The project will involve constructing the system using additive manufacturing, implementing control algorithms and carrying out evaluation in partnership with the cardiology team at St. Thomas’ hospital.

Skills developed: Knowledge, understanding and skills in cardiac arrhythmias, cardiac ablation procedures, mechatronics systems, additive manufacturing, CAD, clinical evaluation of healthcare technologies, and research methods.

Figure to illustrate the current design of the trans-septal puncture robot.

Development and evaluation of cardiac phantoms for cardiac ablation therapy Simulation

Supervisors: kawal.rhode@kcl.ac.uk,carlo.saija@kcl.ac.uk

Description: Cardiac ablation is a possible treatment for arrhythmias. Ablation catheters are introduced through small incisions in peripheral blood vessels and used to destroy parts of the myocardium that are responsible for the arrhythmia. The catheters are manually controlled by cardiologists. These procedures require substantial training for cardiologists.

Aims: The project aims to develop and evaluate novel cardiac phantoms that can be used for training cardiologists for ablation procedures. The phantoms will be designed using patient images and additive manufacturing. Challenges include the use of flexible filaments for 3D printing and thermochromic paints for recording ablations, and simulation of electrical activity.

Skills developed: Knowledge, understanding and skills in human anatomy, cardiac arrhythmias, cardiac ablation procedures, image segmentation, CAD, additive manufacturing, clinical evaluation of healthcare technologies, and research methods.

Development and evaluation of a low-cost silicone 3D printer

Supervisors: kawal.rhode@kcl.ac.uk, zhouyang.xu@kcl.ac.uk

Description: Silicone is an ideal material for making anthropomorphic phantoms for testing and evaluation of healthcare technologies. Manufacturing of silicone phantoms is time-consuming and labourious. 3D printing offers a way to produce silicone models directly and at low-cost.

Aims: The project aims to develop and evaluate a low-cost 3D printer for direct printing of silicone structures. Our team has already developed a prototype and this project will aim to refine this prototype to achieve robust silicone printing. We will particularly focus the 3D printing of silicone cardiac valves for use in phantoms for the training and rehearsal of interventional procedures.

Skills developed: Knowledge, understanding and skills in human anatomy, image segmentation, CAD, additive manufacturing, mechatronics, clinical evaluation of healthcare technologies, and research methods.

Denoising X-ray fluoroscopy images using deep learning

Supervisors: kawal.rhode@kcl.ac.uk

Description: X-ray fluoroscopy is routinely used to guide interventional procedures. Radiation dose is of concern and keeping the dose as low as possible means that the images can be noisy.

Aims: The project aims to evaluate the use of deep learning algorithms to denoise X-ray fluoroscopy images. We have already developed a series of convolution neural networks to perform the image denoising and evaluated these. The project will focus on the evaluation of our latest networks in the clinical setting of the cardiac catheterisation laboratory.

Skills developed: Knowledge, understanding and skills in X-ray imaging, interventional procedures, signal processing using Matlab, deep learning, clinical evaluation of healthcare technologies, and research methods.

Evaluation of web-based teaching and learning of anatomy using medical imaging and 3D models

DISCIPLINE: BIOMEDICAL ENGINEERING

Supervisors: kawal.rhode@kcl.ac.uk, elsa-marie.otoo@kcl.ac.uk

Description:Web-based platforms for teaching and learning of anatomy have seen a substantial rise in interest since the covid-19 pandemic. These solutions provide an alternative or adjunct to traditional methods such as textbooks and dissection room sessions.

Aims:We have developed a novel solution for web-based teaching and learning of human anatomy using medical images and 3D models – King’s Virtual Anatomy & Histology. The project will aim to refine and evaluate this solution using cohorts of students undertaking anatomy modules at King’s. We will be specifically evaluating the use of autostereoscopic 3D displays and AR for teaching and learning.

Skills developed:Knowledge, understanding and skills in medical imaging, image segmentation, 3D computer models, web programming, evaluation of teaching and learning technologies, and research methods.

Figure to illustrate the King’s Virtual Anatomy & Histology Web App (left). The Looking Glass Portrait 3D display (right).

Evaluation of patient localisation using the Intel RealSense camera for robotic procedures

Supervisors: kawal.rhode@kcl.ac.uk, yixuan.zheng@kcl.ac.uk

Description: For the safe interaction of robotic systems with patients, the localisation of the patient is important. Examples include surgical robots and ultrasound scanning robots.

Aims: We aim to develop a robust solution to track a patient that may be supine on an operating or interventional table or on an ultrasound scanning couch. We have already trialled the Microsoft Kinetic for surface scanning of patients during robotic ultrasound scanning. The project will now move to the more recent and robust technology from Intel, the RealSense. We aim to develop and evaluate a real-time surface scanning solution that is robust to the clinical scenario, and which can be linked to robotic solutions, such as robotic ultrasound scanners.

Skills developed: Knowledge, understanding and skills in surface imaging, image processing, 3D computer models, computer programming, evaluation of technologies, and research methods.

Figure to illustrate the Intel RealSense camera (left). The project aims to capture the patient’s surface for localisation of the patient, for example, during ultrasound scanning (right).

Repairing and reproducing skeletons using 3D printing

Supervisors: kawal.rhode@kcl.ac.uk

Description: The Life Sciences Museum at Guy’s Hospital hosts a large collection of animal skeletons. Many of these have become damaged or are incomplete. Furthermore, many are too fragile to allow handling by students for teaching and learning.

Aims: This project will involve using state-of-the-art technology to repair and reproduce a range of animal skeletons for the Museum. We will use the Einscan Pro+ surface scanning system or computer tomography scanning to create 3D models of the skeletons. These will then be 3D printed using our range of additive manufacturing facilities at Guy’s and St. Thomas’ hospitals and ported to our online 3D viewing environment, King’s Virtual Anatomy & Histology. The models will be evaluated by our team of anatomists and used for teaching and learning in the School of Life Sciences and Medicine at King’s.

Skills developed: Knowledge, understanding and skills in surface imaging, CT scanning, image processing, 3D computer models, 3D printing, CAD, and research methods.

Figure to illustrate the surface scanning with the Einscan Pro+ of a chimpanzee skeleton (left). The reconstructed 3D model (right).

Robotic cardiac ultrasound scanning

Supervisors: kawal.rhode@kcl.ac.uk, weizhao.wang@kcl.ac.uk

Description: Medical robotic systems have been used clinically since the 1980s and have since proliferated in many different fields. We have recently developed a robotic system, as shown in the figure, for holding and controlling an extra-corporeal ultrasound probe. With its potential for high precision, dexterity, and repeatability, the self-tracked robotic system can be employed to improve the acquisition and utility of real-time ultrasound. This may include field of view extension resulted from the integration of several 2-D images, multi-modality image fusion for improved visualization and robotic-based advanced ultrasound-guided surgery.

Aims: This project will use the newly developed robotic system and a cardiac ultrasound phantom to explore the use of the robot in trans-thoracic echocardiography (TTE). The student will be guided to design and perform experiments to do the robot-to-probe calibration and then quantify the probe positioning accuracy using the robot. Based on these works, we will further explore the application of the robot in improving ultrasound imaging, such as the field of view extension of 2-D TTE and image fusion of TTE to other modalities. The results will be analysed and the clinical impacts on TTE will be assessed.

Skills developed: This project is suited to students who would like to be involved in interdisciplinary research between robotics and medical imaging. It will help to improve their knowledge of ultrasound imaging and robotic control, as well as develop experimental and problem-solving skills.

Figure to illustrate the dual-arm ultrasound scanning robot at St. Thomas’ hospital.

Development and evaluation of physical anatomical models for surgical simulation

Supervisors: kawal.rhode@kcl.ac.uk, antonia.pontiki@kcl.ac.uk

Description: Additive manufacturing, or 3D printing, has opened up new possibilities for recreating
human anatomy and physiology via high-fidelity anatomical models. These can be used for surgical
training, procedure rehearsal, medical device testing, and education. Anatomical models present a
more ethical and cost-effective alternative to cadavers or animal models.

Aims: The project will identify an area of need where anatomical models may be effective. We will
used medical image data to create computer models of the target anatomy. These will then be
manufactured using the knowhow and techniques that we have developed within the research team
over the last 10 years. An evaluation study will be formulated to measure the effectiveness of the
models in the target scenario.

Skills developed:Knowledge, understanding and skills in human anatomy, image segmentation, CAD, additive manufacturing, clinical evaluation of healthcare technologies, and research methods.

Figure to illustrate prototype of an upper respiratory tract phantom used for training ENT procedures

Grade Scale for the United Kingdom - AACRAO EDGE

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