MPHY3000/MPHYM000: Medical Physics Projects 2012/13

Below is a list of Medical Physics projects being offered for undergraduate students in the Department. To find out more about a project and/or to indicate your interest in taking it, please email the first supervisor by clicking on his/her name.

Deadlines

  • A Project Outline is due on Monday October 15, 2012. Your supervisor must also complete a Project Risk Assessment Form. Students are required to hand in the form with two copies of their outline to Mohini Nair in the Medical Physics Departmental Office (second floor of the Malet Place Engineering Building).
  • Project Progress Reports are due by Monday January 14, 2013. Two copies should be handed to Mohini Nair in the Medical Physics Departmental Office.
  • Project talks will be held on Wednesday March 13, 2013 in Room 2.14 of the Malet Place Engineering Building.
  • Final Reports are due by Friday March 22, 2013. Please hand in two copies to Mohini Nair in the Medical Physics Departmental Office.

Project information

Automated movement artifact rejection for NIRS data

Supervisors: Prof. Clare Elwell and Dr. Beth Jelfs

Student: Ryan Chung

Near infrared spectroscopy allows non-invasive collection of data which can provide information about oxygenation levels in the brain. In particular we are interested in developing a system for use at the bedside of patients with traumatic brain injury. Such a system requires the collection and preprocessing of data, followed by modelling and analysis of the data to provide a clinically relevant output, all of which needs to be performed in real time. The aim of this project is to look at the preprocessing aspect of the system in particular the occurrence of movement artifacts. When a patient moves this can cause abrupt changes in the data and also result in a shift in the baseline of the measurements, both of which can drastically affect the results of the subsequent data analysis. At present methods for artifact removal require input from the user to set thresholds for the current patient. The student will be required to build on the existing techniques to provide a statistical measure of the data which is consistent across patients and does not require input from the end user. Once artifacts have been identified an assessment needs to be performed as to the best approach to deal with the artifact and rectify any shifts in the baseline of the data. In line with the overall aim of using this system at the bedside the output from this project must also be suitable for use online in real time.

Atomic Force Microscope spectromicroscopy

Supervisors: Dr. Ben Cox and ???

Student: (Project available)

An atomic force microscope (AFM) is able to image topology with nanometre resolution but without any chemical specificity. Recently, a number of researchers have investigated whether an AFM can be used to detect the surface fluctuations following the absorption of an infra-red (IR) laser pulse. Measuring the AFM-IR spectrum might be one way in which it is possible to extend the capabilities of AFM so that it can differentiate between different chemical species. In this project the small but growing literature of AFM-IR research will be analysed, and the advantages and disadvantages of the various different approaches that have been used will be delineated. In addition, data on the sorts of targets that have been imaged will be collated, and similarities and differences noted with the aim of describing and characterising the attributes that a target (cell type, for example) must possess to be imaged successfully. Finally, the extent to which the literature addresses the following two related questions will be explored: 1) how much do subsurface absorbers affect the AFM-IR spectra measured at the surface? 2) is it possible to recover information about subsurface absorbers from the surface measurements?

Investigation of nanoparticle uptake in plant cells

Supervisors: Dr. Kate Ricketts and Prof. Gary Royle

Student: Katrina Prise

The main aim of this project is to optimise a suitable protocol for plant cell production and the uptake of nanoparticles. Currently, protocols are already set up and being readily used for nanoparticle uptake in animal cells. In animal cell uptake it was found that nanoparticles were similar enough to biomolecules that cells would regard them in the same way. Gold nanoparticle uptake in animal cells has been used in aiding the treatment of cancer. When nanoparticles are functionalised they are preferentially taken up by cancer cells they can be used as a contrast agent to assist with determining the stage and spread of the disease. The motivation behind this project is to apply the same techniques developed at UCL for medical purposes and, ultimately, be able to monitor environmental effects in the sea using the condition of algae as an indicator of various environmental factors, such as temperature change, pollutants, and oxygen concentration.

Improving MRI-based multi-atlas segmentation of the heart using outlier detection

Supervisors: Prof. Seb Ourselin and Maria Zuluaga

Student: (Project available)

According to the World Health Organization, cardiovascular diseases account for around 30% of deaths around the world. The use of medical image computing in clinical routine has shown a tremendous potential to reduce the death toll by allowing early diagnosis and treatment of the different pathologies. The aim of this project is to improve existing heart segmentation techniques that allow to extract the different structures of the heart (ventricles, myocardium, atria and great vessels) from magnetic resonance images (MRI), so that these can be analysed by the clinicians. At present, our method makes use of previously obtained segmentations to extract the heart structures of new images. However, when the images are not properly aligned, the final segmentation tends to be erroneous. In this project, the student will evaluate new algorithms that allow to identify misaligned images so that they can be removed from the segmentation process. The project will require the student to develop understanding of image registration. Some programming skills can be useful but are not mandatory.

Refinement of a method for measuring the bending stiffness of nonwoven fabrics

Supervisors: Prof. Alan Cottenden and Vasileios Asimakopoulos

Student: John Lee

We need to be able to measure the bending stiffness of nonwoven fabrics (the resistance they show to being bent into an arc) in order help us interpret our experimental results from measurements on friction between these fabrics and the curved surfaces of skin. We have a method for doing this which is robust in principle but labour intensive, fiddly and error-prone in practice. This project will involve refining the current method so that accurate data can be gathered and processed more easily. The project will be primarily experimental, and will require a student prepared to pay careful attention to detail in order to identify and address the various limitations of the current methodology. The project will be supervised by Alan Cottenden and another yet to be decided, and the experimental work will be based at the UCL Archway campus.

Mathematical modelling of water absorption by superabsorbent hydrogels

Supervisors: Prof. Alan Cottenden and Dr. Becky Shipley (Department of Mechanical Engineering)

Student: (Project available)

Superabsorbent polymer (SAP) hydrogels are remarkable materials that will absorb 100 times their own dry mass in water, a property exploited, for example, in absorbing body fluids in medical and hygiene products such as diapers and wound dressings, and in agriculture to retain water around germinating seeds and the roots of plants. However, the process of water flow between the SAP particles and diffusion into them is as yet poorly understood. We have a growing body of experimental data describing the kinetics of absorption under a variety of conditions and the aim of this project will be to develop mathematical models that capture the observed absorption behaviour. The student taking this project will need to have a strong mathematical background.

Development of a decision support tool for dementia

Supervisors: Prof. Jem Hebden and Dr. Kate McLeish (IXICO)

Student: Marta Caballero

Managing dementia, of which Alzheimer’s Disease is the most common, is a growing problem globally with an aging population. It is estimated that only 40% of sufferers are diagnosed in the UK today and that delays in diagnosing patients, even in the absence of disease modifying drugs, leads to a poorer quality of life. It has been shown that early diagnosis, followed by suitable interventions (generic drugs, support, assisted technologies) can add 18 months to independent life. The importance of improving early diagnosis has been recognised in the National Dementia Strategy and the Prime Minister’s Dementia Challenge.  IXICO is a company working with large pharma companies on the testing of new drugs for dementia and is now translating these clinical trial tools into the healthcare environment by developing medical devices to support diagnosis. One of the most established down-stream effects of dementia is shrinkage of the brain, and the amount of shrinkage and the relative shrinkage of different regions of the brain can assist in the diagnosis of dementia, including differential diagnosis between types of dementia. IXICO has image analysis technology that allows us to calculate the volumes of these regions from MRI data. This project will involve experimental work to test the performance of the image analysis technology on a variety of datasets that are already collected, in order to assess performance and robustness. The project may also collect data from new clinical deployments of the software, and do some feasibility assessments of the incorporation of cognitive testing data along with imaging in the decision support process.

Information for cancer patients in Western Africa

Supervisors: Prof. Gary Royle and Dr. Kate Ricketts

Students: Bhabika Gurung, Gibril Kallon, Mary Neal

Cancer is rapidly becoming a growing concern in developing countries. As preventable diseases such as malaria, TB and typhoid decline life expectancy increases, which results in more people developing cancer. The World Health organisation predicts that by 2017 cancer will result in more deaths in developing countries than HIV, malaria, TB and typhoid combined. There is an urgent need to tackle the situation and for those countries to offer a better cancer service. UCL’s Medical Physics department is running a programme which works alongside radiotherapy workers in Ghana. This project involves reviewing cancer patients in the region, identifying treatment outcomes and developing patient information to assist with this programme. This project can accommodate two students.

Image corrections for proton therapy emission images

Supervisors: Prof. Gary Royle and Catarina Veiga

Student: Mital Parsotamo

Proton therapy is an advanced form of cancer treatment proven to have lower secondary effects to patients. Treatments are aimed particularly at children and complex cancers. It is important to verify that the treatment is being delivered correctly. One method of achieving this is to monitor emissions from the patient generated as the proton beam passes through the patient. As the proton loses energy in the patient different interactions occur which means that the number of emissions does not translate to patient dose unless corrections are applied. This project will investigate, via computer simulation, a proton treatment and analysis the emission data in order to develop corrections.

Development of DICOM compatible images for radiotherapy treatment planning

Supervisors: Prof. Gary Royle and Catarina Veiga

Student: Rachel Atemie, Edward Basham

All clinical images are required to have a particular format, known as DICOM. This contains various important information. It is necessary that any simulated images must be translated into this format before they can be used for clinical research. This project will be joint with the radiotherapy department and will develop a programme to convert images to DICOM format for use on the treatment planning software.

Ergometer for therapy after spinal cord injury: calibrator for torque transducer

Supervisors: Prof. Nick Donaldson and Tim Perkins

Student: Zhihang Cheng

A special cycling exercise machine (ergometer) is being built for a clinical experiment in which patients with spinal cord injury exercise while being electrically stimulated. The ergometer includes a novel torque transducer that is intended to measure the effort being made by the patient. The transducers need to be tested and calibrated. Calibration is particularly important because the strain gauge transducers are actually measuring forces from which the torque is deduced (i.e. it is not a direct measurement). What is needed is a motor that can act in place of the patient, turning the crank shaft while we measure the speed and the torque. In this project, a motor and tachometer will be chosen, a torque load cell made, and a wireless connection designed and made so that the torque can be measured while the load cell is rotating. As several ergometers are to be produced, the calibrator will itself be arranged as a piece of equipment for use after manufacturing, and for subsequent checking of ergometers after they have been in use. The equipment must be arranged so that it can be connected without damage to the ergometer or risk to the operator.

An experimental therapy for spinal cord injury

Supervisors: Prof. Nick Donaldson and Clemens Eder (EE)

Student: James Cohen

The Implanted Devices Group and the Analogue Systems Group in the Electronic Engineering Department are is an EU project in which epidural stimulation of the spinal cord is to be tested as a therapy. One new experiment is called “Social Rats” because the stimulation will be applied while the rats are free to move around in a cage and interact socially with other rats. Making an implanted stimulator which is small enough and can withstand the movement made by the rat is difficult. A PhD student (Vasso Giagka) is hoping to meet these requirements by making the epidural electrode array with an embedded custom integrated circuit. The implant will also have some subcutaneous electronics and a head connector. The subcutaneous electronics will include a rechargeable battery and a programmable microcontroller. The program includes the stimulation parameters, such as pulse frequency and amplitude. In this way the battery can be recharged and the program modified while the rat is asleep but the rat will be unhindered when out in the social cage. In the project the student will prepare a specification for the subcutaneous electronics, choose a microcontroller, make a prototype of the hardware on a printed circuit board and write the program. The electronics will be tested separately and with the epidural array chip.

Ultrasound imaging phantoms with 3D polymer printing

Supervisors: Dr. Adrien Desjardins and Dr. Simeon West

Student(s): Ioannis Koutsakos

Ultrasound imaging is increasingly used to guide minimally invasive procedures in the human body. This imaging modality has many advantages, such as being real-time and non-ionising, but it can be challenging to interpret images and to plan an optimal path to the tissue target. There is an urgent need for better training tools for a wide range of patient anatomies. This project will involve creating an ultrasound phantom for percutaneous (needle-based) procedures in the spine and/or the upper arm. In particular, it will involve digitally segmenting 3D image volumes and creating polymer/silicone structures using cutting-edge 3D printing techniques. This project, which is co-supervised by an Anaesthetist at UCL Hospital, is an opportunity to gain hands-on experience with both medical image processing and ultrasound imaging in clinical practice. Two students can be accommodated on this project.

A mobile phone app for cycling

Supervisors: Dr. Terence Leung and Prof. Nick Donaldson

Student: Zara Sheikh

The aim of this project is to develop a mobile phone App to measure the power output of a person cycling. The App will be built on the Android platform using the graphical programming software App Inventer. This “cycling App” will exploit the accelerometer inside a smartphone to detect the cycling motion. By measuring the actual power output required for cycling with an ergometer, on which the “slope” is set by a brake, an algorithm will be developed to convert cycling motion and slope into a measure of power output. Data will also be collected from the phone’s orientation sensors to show that an actual slope, whether on a flat surface, uphill and downhill, can be measured. The measured slope and the algorithm can then be used to estimate the power output during outdoor cycling. Upon successful development, the cycling App could be used to monitor the rehabilitation of patients with spinal cord injuries. No previous programming experience is necessary but a desire to learn is essential. This project also involves a fair amount of data analysis and cycling experiments.

A mobile phone app for skin oxygenation measurement

Supervisors: Dr. Terence Leung and Prof. Clare Elwell

Student: Patrick Lancaster

The aim of this project is to develop a mobile phone App which can show the oxygenation distribution of the skin as a picture using visible spectroscopy. Oxygenated blood (more specifically oxy-haemoglobin) looks bright red while deoxygenated blood dark red. The colour or “redness” of the blood can therefore indicate the blood oxygenation. The App works by first taking a photo of the skin and then analysing the three base colour images (RGB: Red, Green and Blue) which are then converted into an oxygenation distribution of the skin based on the reflection spectra of oxy- and deoxy-haemoglobin in the visible range, a technique known as RGB reflectometry. The App will be developed on an Android platform using the graphical programming language App Inventor. No prior programming experience in App or other programming languages is necessary but a desire to learn is essential.

Understanding how bone behaves under load

Supervisors: Prof. Robert Speller and ????

Student: Kalumin Gunatilaka

Bone is a complex structure that plays several roles – it’s the body’s supply of calcium, it protects certain organs and it supports the body. Determining the quality of bone to carry out these functions has been a field of study for many years. One of the parameters that has recently been shown to be important in the measurement of bone quality is the 3-D distribution of Ca/P but why this is important is not known. This project is to develop techniques to try and answer that question. The work will involve using a microCT system, preparing bone samples, imaging samples with and without load and analysing images. Some computing maybe required.

Mapping radioisotope distributions

Supervisors: Prof. Robert Speller and George Randall

Student: Jenelle Rajroop

RadICAL is a detector system that has been developed at UCL for radioisotope mapping. It has successfully been used with relatively simple source distributions but needs to be evaluated with more complex arrays of sources. The project will involve collecting data for different source distributions and then developing ways to analyse the results. It will involve both experimental work and some computing. It is expected that the existing detector systems will be used but improvements in the detector system could be undertaken if the candidate has good experimental skills.

X-ray biopsy system for breast cancer

Supervisors: Prof. Robert Speller and Dr. Tasos Konstantinidis

Student: Meera Tailor

The usual procedure for breast screening in the UK means that after the initial examination the patient waits to hear if a follow-up is required, and if one is a further wait for results when a tissue biopsy sample is taken. At UCL we have developed an X-ray sensor called DyAMITe that can take a mammogram and during the examination take x-ray diffraction data on suspicious regions. Thus reducing the rather protracted investigation in current breast examinations to a single, non-invasive visit with conclusive results. This project will involve collecting images from tissue samples and analysing these images. The analysis will involve developing/adapting computer code.

HIFU lesion formation in a thermal regime

Supervisors: Dr. Ben Cox, Dr. Terence Leung, Dr. Bradley Treeby, and Dr. Dean Barratt

Student: Anna Zamir

High Intensity Focussed Ultrasound (HIFU) is a non-invasive ablative therapy with many potential clinical applications. At clinical HIFU intensities, cavitation and boiling will occur at the focus which may enhance lesion formation and may also be used as a means of passively monitoring lesion position. However, it also significantly increases acoustic backscattering thereby affecting the lesion shape and size. A HIFU regime where the effects are purely thermal may have advantages in some applications (e.g. where better control of lesion form, or localised heating without tissue damage, is required). This project will investigate how accurately the shapes and sizes of thermal lesions can be predicted by comparing experimentally produced lesions with those predicted by a model which accounts for acoustic propagation, thermal diffusion and time-dependent tissue damage.

Is functional magnetic susceptibility mapping feasible at a magnetic field strength of 3 Tesla?

Supervisors: Dr. Karin Shmueli and Dr. David Thomas

Student: Adam Tyson

Functional Magnetic Resonance Imaging (fMRI) is widely used for studying human brain function. It relies on changes in the magnitude of the complex MRI signal but the phase of the signal has also been shown to change on brain activation. Susceptibility mapping, developed by Dr Shmueli and others, is a technique to calculate maps of the tissue magnetic susceptibility which represents the physiological changes in blood oxygenation underlying fMRI. Preliminary functional susceptibility mapping is emerging at a field-strength of 7 Tesla which gives larger signal-to-noise ratios and allows detection of small signal changes. We will investigate whether functional changes in the tissue susceptibility can be measured at 3 Tesla: the workhorse field strength for human fMRI studies. The student will acquire and analyse fMRI data at 3T.

Respiration monitoring with an accelerometer

Supervisors: Dr. Nick Everdell and Dr. Adam Gibson

Student: (Project available)

We have built a novel respiration monitor based on an accelerometer. It is able to detect movement due to respiration but fails when there is other movement in the same frequency band. This project will investigate alternative methods of signal analysis and will aim to develop a technique for reliable tracking of a signal in the presence of artefacts. The project requires a student interested in signal processing.

Motion detection and analysis during seizure

Supervisors: Dr. Adam Gibson and Dr. Nick Everdell

Student: David Desai

It can be difficult to determine whether a seizure is epileptic in origin or not. It has been proposed that the appearance of movement during the seizure may help to distinguish between epileptic and non-epileptic seizures. In this project, you will build an accelerometer which can be placed on the arm during seizure and record arm movement. You will then analyse this arm movement to distinguish between different types of motion.

Modelling patient throughput in a radiotherapy department

Supervisors: Dr. Adam Gibson and Dr. Gary Royle

Student: Francesca Stoneley

The radiotherapy department in a hospital is busy, with patients moving from room to room for different scans and tests, and returning for repeated treatment fractions. In this project, you will develop a computer model of patient flow through the department, which will allow us to predict the impact of changes to working practise on the efficiency of the department. The project will involve writing and developing a computer model,  testing it against measured patient throughput and using it to predict the effect of new working practises.

Designing and constructing a life-size tissue-like infant head phantom for evaluating simultaneous EEG and optical imaging

Supervisors: Prof. Jem Hebden and Dr. Harsimrat Singh

Student: Aysha Alkhaja

Researchers within the UCL Biomedical Optics Research Laboratory (BORL) have developed a technique to simultaneously display the electrical and haemodynamic changes associated with brain activity. This work uses an optical imaging system which has an array of optical fibres placed in contact with the head, combined with an array of EEG electrodes. The aim of this project is to develop a suitable “phantom” which can be used to test the imaging system. A phantom is an object which simulates the properties of real human tissues. The project will initially involve designing and building a hollow infant head based on polyester resin. Thin conducting wires will be embedded within the resin so that both light and electrical currents can pass through the head. The head will then be filled with an optically-scattering / electrically-conducting liquid. Measurements will be made using optical fibres and electrodes placed on the surface of the head with a suitable target placed inside. Data will be analysed and images will be generated. This project is most suitable for a student who enjoys building mechanical and/or electrical devices and has good manual skills.

Imaging changes in optical properties produced by high-intensity focussed ultrasound

Supervisors: Prof. Jem Hebden and Dr. Terence Leung

Student: Dhriti Dosani

High-intensity focussed ultrasound (HIFU) is a therapeutic technique which involves heating a small internal region of tissue using a beam of high frequency sound waves. Heating the tissue enables cells to be destroyed, and thus HIFU is used to kill tumours inside the body without the patient requiring surgery. The high temperatures produced by HIFU also change the way in which the tissue absorbs and scatters light. UCL’s Biomedical Optics Research Laboratory (BORL) have developed a technique called optical topography which can image changes in optical absorption of tissues below the surface (click here for details). The aim of this project is to demonstrate that optical topography can be used to display changes produced in a tissue-simulating material irradiated with a HIFU device. The student will make a tissue-simulating “phantom” using silicone rubber, in which will be embedded a region containing a “thermochromic pigment”. This pigment changes colour when heated. The student will conduct imaging experiments on the phantom using the UCL optical topography system and a HIFU device.

Pseudo-spectral pentamode model for simulating acoustic invisibility cloaking

SupervisorsDr. Ben Cox and Bradley Treeby (Australian National University)

Student: Damon McNally

It has been shown that a class of metamaterials called 'pentamode' materials can be used for acoustic invisibility cloaking. Simulating cloaking when the domain size is many hundreds of wavelengths in size requires a computationally efficient model of wave propagation. In this project a pseudo-spectral model of wave propagation through a pentamode material will be modelled in Matlab, and used to investigate novel cloaking scenarios.

Control logic for a stimulator IC

Supervisors: Dr. Anne Vanhoest and Prof. Nick Donaldson

Student(s): (Project available)

This project is for one or two students with prior knowledge of electronic logic (and micro-controllers) and basic programming skills. There is currently a discrete control circuit for one of the IDG's stimulator IC that relies on a purpose-built FPGA. The students are to replace this circuit with a simpler and more user friendly logic controller, probably involving a micro-controller. Hence the pre-requisites of knowing some basic electronics, enough to understand the current circuit and design the new controller. It is open to either one student or a pair with good collaboration skills. For more information on the research carried on in the Implanted Devices Group click here.

Thick-film humidity sensors - a feasibility study

Supervisors: Dr. Anne Vanhoest and Prof. Nick Donaldson

Student: Ashok Chhabra

To study the feasibility of using standard thick-film methods to create an implantable humidity sensor. This project will first require a literature review, followed by a time in the lab, to characterize existing sensor candidates. If the progress are satisfactory and the student shows a good behaviour in the lab a second stage will involve researching other materials, suitable in terms of their bio-compatibility and sensing properties for the production of new sensors in the cleanroom. For more information on the research carried on in the Implanted Devices Group click here.

An interactive e-learning tool for electrical stimulation theory

Supervisors: Dr. Anne Vanhoest and Mr Nathaniel Dahan

Student(s): (Project available)

In a first stage the student(s) will undertake a literature review to understand the basics of the theory of electrical stimulation, including notions of rheobase and chronaxie, with a focus on stimulation optimisation from a point of view of charges and energy. This is of importance for future development of electrical stimulators as minimising the energy per stimuli would improve the power requirements of the stimulator while the charge delivered may be linked to potential nerve damage if it is excessive. If two students share this project, the theoretical findings shall be integrated in an interactive e-learning tool showing several stimulus waveforms with adjustable parameters and calculating the charge and energy requirements. This project does not involve any lab work and is therefore suitable for students living further away. No prior knowledge of electrical stimulation principles is required. The student(s) must be comfortable with integrations and derivations as the first phase of the project is theoretical. If the project is undertaken by two students , it is strongly advised that one of them at least show some previous experience of designing web-interfaces, with user interactions and animations. For more information on the research carried on in the Implanted Devices Group click here.

Explore the optical measurements of brain tissue oxygenation and haemodynamics during a hypoxic ischaemic insult.

Supervisors: Dr. Ilias Tachtsidis and Dr. Aaron Oliver-Taylor

Student: Vidushi Gor

Monitoring the tight balance of brain blood flow, oxygen delivery and brain tissue metabolic rate is a major aim in patient diagnosis and care. A patient’s health is in great danger when there is a prolonged lack of oxygen delivery to meet the metabolic demand of the tissue; for example in neonatal encephalopathy secondary to birth asphyxia. The Perinatal-Brain Magnetic-Resonance Group at UCLH has a well established programme of research characterising and monitoring neonatal brain injury. Recently as part of collaboration with the Biomedical Optics Research Lab (BORL) they have been measuring brain tissue oxygenation and haemodynamics in a brain injury animal model using an in-house developed near-infrared spectrometer. The main focus for this project will be the data analysis of physiological signals obtained before, during and after brain injury. The student will use novel software tools that will allow quantification of the near-infrared measurements and then will focus on analysing those in conjunction with systemic signals and possible magnetic resonance spectroscopy measurements. The larger scope of the analysis is to investigate the biophysical and biochemical changes that happen in birth asphyxiated infants. This project would be suitable for a student with an interest in physiology/pathophysiology, brain tissue biochemistry; and will involve data processing and statistical analysis.

Computational modelling of pH dynamics during brain tissue anoxia and ischaemia.

Supervisors: Dr. Ilias Tachtsidis and Ms Tharindi Hapuarachchi

Student: Mrudul Bhatt

In our pursuit to understand the brain tissue physiology, metabolism and regulation we have adopted a “systems biology” approach and developed a computational model (BRAINCIRC http://braincirc.sourceforge.net/ ) which we recently extended to include the neonatal brain physiology and metabolism (Brain model, http://www.ucl.ac.uk/~ucbptmo/index.html ). Intracellular pH varies as a function of flow, energy stores and oxygenation. Low pH can be a precursor of apoptosis and cell death. Thus, the characterization of pH dynamics may have predictive value for cell death for example in perinatal cerebral hypoxic-ischemia (HI) following birth asphyxiation, in traumatic brain injury and stroke. As part of this project the student will run simulations with our models to investigate the pH dynamics in the models and progress to suggest and develop possible submodels that describe the brain tissue pH dynamics. The ultimate aim will be to use this extended model to extract additional clinically useful information about pH brain regulation. This project would be suitable for students with an interest in brain tissue physiology/biochemistry and will involve data processing and some statistical analysis.

Analysis of coded-aperture based x-ray phase contrast images of tumours in breast tissue.

SupervisorsDr. Alessandro Olivo and Dr. Marco Endrizzi

Student: Aria Antoniadou

X-ray phase contrast imaging is a new imaging modality not based on x-ray attenuation, in which all details in an image are made more evident by intense edge-enhancing fringes running along their borders. This also results in making classically undetectable objects (as they oppose non absorption to x-rays) visible in the image. This method produced unprecedented results in the imaging of breast tissues, where it proved it could visualize lesions previously undetectable (or at a stage at which they are not yet detected by conventional methods). This result was obtained at synchrotrons, huge, complicated and very expensive facilities – only approximately 50 of which exist in the world. This notwithstanding, the above result was so revolutionary that it triggered the construction of the first in vivo station for x-ray phase contrast mammography at a synchrotron in Italy, despite the very limited number of patients that such station can handle. More recently, the UCL team has developed a method that could make similar results achievable with conventional sources. This could make the above result widely available in hospitals and clinics across the world, allowing an earlier detection of breast tumours and consequently a reduction in the mortality rate. The team is currently using the method to image a large number of breast tissue samples containing tumours to achieve statistical significance. The student would participate in the data analysis by comparing absorption and phase contrast images of the same breast tissue sample, and quantitatively assessing the improvements brought by the latter. If time allows, synchrotron images would also be provided to allow a comparison of the UCL images against the “gold standard”.  The student will gain skills in data and especially image analysis, and familiarize with some of the basic concepts of medical imaging. Basic computing skills are required.

Contrast and Signal-to-noise ratio in x-ray phase contrast imaging.

Supervisors: Dr. Marco Endrizzi and Dr. Alessandro Olivo

Student: Glafcos Havariyoun

X-ray phase contrast imaging is a new imaging modality not based on x-ray attenuation, in which all details in an image are made more evident by intense edge-enhancing fringes running along their borders. This also results in making classically undetectable objects (as they oppose non absorption to x-rays) visible in the image.The classic way of classifying detail visibility in an x-ray image is based on the concepts of contrast and signal-to-noise ratio (SNR). These quantities are somewhat based on the typical characteristics of a conventional, absorption-based x-ray image, in which the part of the image occupied by the detail of interest presents a lower or higher intensity with respect to the background. The different nature of phase contrast images requires a critical revision of these classic quantities. The student will be provided with a number of images of the same samples taken with absorption and phase contrast methods. He/she will investigate ways of improve/update the definitions of contrast and SNR in order to make them suitable to this new imaging modality. The ultimate aim will be to carry out a quantitative comparison between image quality provided by conventional absorption and phase contrast methods. The student will gain skills in data analysis, image analysis and familiarize with some of the basic concepts of medical imaging. Basic computing skills are required.

Investigation of the statistical nature of image contrast in coded aperture phase contrast imaging systems.

Supervisors: Dr. Alessandro Olivo and Dr. Paul Diemoz

Students: (Project available)

X-ray phase contrast imaging has the potential to effect the greatest change in the field of x-ray imaging since the invention of computed tomography. The majority of x-ray imaging systems employed in real world applications are sensitive to spatial variation of a sample's x-ray absorption characteristics. Most typical samples which need to be imaged by x-rays also exhibit spatial variation in the way the sample retards x-rays, generally resulting in the refraction of x-rays. Until recently, this effect could be observed only at Synchrotrons or with specialised laboratory sources with insufficient flux to be used in most real world applications. The radiation physics group within the department has, however, been developing a technique capable of observing x-ray phase contrast with standard x-ray sources. This technique is called coded aperture x-ray phase contrast imaging (CAXPCI). One of the attributes of this system is that the measured contrast depends upon where a sample is positioned relative to the imaging system. The imaging system thus has regions within its field of view which are more sensitive than others. The aim of this project is to obtain a statistical description of the contrast improvement which may be expected from the CAXPCI system when imaging cylindrical fibres.The project will entail understanding how the CAXPCI system is modelled. You will use a model which has already been developed to generate results according to a methodology which you will develop to determine the statistical nature of the contrast improvement offered by the CAXPCI system. It is also hoped that additional characteristics of the system, such as quantifying how different regions of the system's field of view differ in sensitivity, will be ascertained. An understanding of wave optics and scalar diffraction will be required for this project along with a good programming abilities. Understanding of x-ray phase contrast imaging will also be desirable.

Wave and ray-optics approaches to x-ray phase contrast imaging.

Supervisors: Dr. Paul Diemoz and Dr. Alessandro Olivo

Student: Shahab Shahipasand

X-ray phase contrast imaging is a new imaging modality not based on x-ray attenuation, in which all details in an image are made more evident by intense edge-enhancing fringes running along their borders. This also results in making classically undetectable objects (as they oppose non absorption to x-rays) visible in the image.There are two basic ways of describing x-ray phase contrast imaging theoretically: one is rather rigorous and is based on Fresnel/Kirchoff diffraction integrals, whereas ray-optics offer a substantially simplified approach. The phase contrast group at UCL has developed software to simulate phase contrast images following both approaches. The student will be provided with this software and will use it to investigate under what set of conditions ray optics can be considered a satisfying approximation.The student will gain skills in simulation methods, data analysis, image analysis and familiarize with the basic concepts of optics. Computing skills and a reasonably sound mathematical background are required.

Evaluation of inverse source modelling of the cortical evoked response in the anaesthetised rat in comparison with Electrical Impedance Tomography of fast neural activity

Supervisors: Prof. David Holder and Brett Packham.

Student: (Project available)

EIT is a novel medical imaging method, with which images of the electrical impedance of the head can be produced with a box about the size of a paperback book, laptop  and EEG electrodes on the head.  It is portable, safe, fast and inexpensive.  The supervisor’s research has been to develop its use in imaging functional activity in the brain. It could be used for imaging fast neural activity over milliseconds, which would constitute a major advance in neuroscience methods. Research into this is currently being undertaken in the anesthetized rat. The brain is exposed and recording is undertaken during repeated physiological stimulation of the sensory or visual systems. Recording is undertaken with a mat of 32 cortical electrodes about 6 mm square. EIT data is recorded at the same time as the brain’s own response as well as other data such as intrinsic optical imaging. Inverse source modelling of the EEG is a method in which the origin of electrical signals is calculated from boundary voltage signals – in this case, the evoked response signals recorded from the epicortical electrode array. In this project, inverse source modelling software from the SPM suite developed at UCL will be adapted for use with the EIT rat data. The results of source modelling will be compared with EIT data. Skills to be acquired:  programming in Matlab, learning SPM, signal processing, and data analysis. All data will be provided by medical researchers. The project is suitable for a student with a background in physics, engineering or computing, or a medical student with computing experience and an interest in programming.

Development of materials for realistic head-shaped tanks for Electrical Impedance Tomography of the head using a 3D printer

Supervisors: Prof. David Holder and Dr. Kirill Aristovich.

Student: (Project available)

EIT is a novel medical imaging method, with which images of the electrical impedance of the head can be produced with a box about the size of a paperback book, laptop  and EEG electrodes on the head.  It is portable, safe, fast and inexpensive.  The supervisor’s research has been to develop its use in imaging functional activity in the brain. One possible use could be to image changes in the brain during acute stroke over time as the brain pathology evolves. EIT has the unique potential to provide a bedside imaging method for this purpose which would alert medical staff to a deterioration and so lead to improvements in treatment. It could also be used for imaging fast neural activity over milliseconds. Research into this is currently being undertaken in the anesthetized rat. It is useful to use anatomically realistic tanks for testing and refining EIT systems. Until now, a real skull has been used for the human head tank. It would be desirable to be able to make tanks with the correct electrical properties in larger numbers for comparison across research groups. This could be achieved using 3D printers but it will be necessary to print porous materials which have the correct electrical properties. The project will be learn about bioimpedance and tissue properties, and also the methods for using a 3D printer. Different porous materials will be designed and evaluated. These will then be constructed into realistic head shaped tanks, either for the rat or human. If time permits, studies of their validity using EIT systems will be undertaken. Skill to be acquired : use of 3D printer; knowledge of relevant biophysics and material science; experimental design and  data and statistical analysis. The project would be suitable for a student with a background in physics, engineering, computing, or medicine. If medicine, familiarity with computing and some programming is desirable.

Evaluation of the optimum number of electrodes for imaging fast neural activity or acute stroke with Electrical Impedance Tomography : a simulation study

Supervisors: Prof. David Holder and Dr. Kirill Aristovich.

Student: (Project available)

EIT is a novel medical imaging method, with which images of the electrical impedance of the head can be produced with a box about the size of a paperback book, laptop  and EEG electrodes on the head.  It is portable, safe, fast and inexpensive.  The supervisor’s research has been to develop its use in imaging functional activity in the brain. One possible use could be to image changes in the brain during acute stroke over time as the brain pathology evolves. EIT has the unique potential to provide a bedside imaging method for this purpose which would alert medical staff to a deterioration and so lead to improvements in treatment. It could also be used for imaging fast neural activity over milliseconds. Research into this is currently being undertaken in the anesthetized rat. Until now, imaging has been undertaken with 16 or 32 electrodes but a new system for use in the rat has the capability to use 128 electrodes and this may expanded to 256. However, it is not clear how many electrodes are optimal. Image resolution increases with increased electrodes but after a certain number additional electrodes confer no additional benefit because of noise. The work will be to undertake computer simulation to estimate the optimal number of electrodes. The initial phase will be to become familiar with EIT imaging and the use of software for simulation of the imaging problem. Realistic values for noise and an accurate geometric model of the head will be used to determine the result. If time permits, this will be validated in studies in saline filled tanks. Skill to be acquired : : medical image reconstruction and computer simulation, data and statistical analysis. The project would be suitable for a student with a background in physics, engineering, computing, or medicine. If medicine, familiarity with computing and some programming is desirable.

Real-time implementation of an algorithm for removing artefact from the EEG in Electrical Impedance Tomography (EIT) of epileptic activity

Supervisors: Prof. David Holder and Dr. Gustavo Santos

Student: (Project available)

EIT is a novel medical imaging method, with which images of the electrical impedance of the head can be produced with a box about the size of a paperback book, laptop  and EEG electrodes on the head.  It is portable, safe, fast and inexpensive.  The supervisor’s research has been to develop its use in imaging functional activity in the brain. One exciting application lies in its use to image changes in the brain due to epileptic activity. In epilepsy, abnormal activity may occur in the form of seizures in which there is continuous abnormal activity lasting a minute or so.  EIT could be used to provide a uniquely new method for imaging brain activity in such seizures which could be used in surgery for epilepsy. In order for this be realised, EIT needs to be recorded at the same time as EEG over several days in patients on a ward who have been specially brought in for observation. Both are recorded with about 20 electrodes glued to the scalp. Unfortunately, the EIT injects an artefact into the EEG signal. A method for removing this has been developed but it currently takes several minutes of post-processing off-line after the EEG has been acquired. As some clinicians need to see real-time EEG at the bedside as it is collected, it is desirable to run the cleaning algorithm in real time. The purpose of the project will be to implement and test real-time implementation of the algorithm. Initially, the student will read relevant background literature and become familiar with the algorithm. They will then develop a way to run it in real time, initially on a PC running in parallel with commercial EEG software. If this is not sufficiently fast, then other methods to speed up processing will be investigated, such as the use of a parallel Graphical Processing Unit added to the PC. Skills to be acquired : programming in Matlab, C or C++, signal processing, and biomedical instrumentation. The project is suitable for a student with a background in physics, engineering or computing, or a medical student with experience and an interest in programming.

Electrical Impedance Tomography (EIT) of evoked physiological activity

Supervisors: Prof. David Holder and Dr. Gustavo Santos

Student: (Project available)

EIT is a novel medical imaging method, with which images of the electrical impedance of the head can be produced with a box about the size of a paperback book, laptop  and EEG electrodes on the head.  It is portable, safe, fast and inexpensive.  The supervisor’s research has been to develop its use in imaging functional activity in the brain. One possible use could be to image increases in blood volume which occur over some tens of seconds during normal brain activity, such as during the standard clinical techniques of stimulation of the visual system by flashing lights or the somatosensory system by mild electrical stimulation at the wrist. Such imaging can already be performed by fMRI (functional MRI); the advantages of EIT are that similar images could be acquired with portable much less expensive  technology which would increase its availability. EIT data has been collected in these situations before and led to a landmark publication in which reliable single channel data were observed but, unfortunately, the data was too noisy to form into reliable images. Since then, the electronics and imaging software have been improved – for example, we can now collect images at multiple frequencies whereas before they were only collected at one. This gives greater opportunities to reduce noise. To start with, the student will evaluate a new EIT imaging system, the Kyung Hee Mk 2 system, in a saline filled tank and compare its performance with an older UCLH EIT system. If time permits, then students will work together to collect EIT data during repeated evoked activity in about 10 healthy volunteers, and then will help produce images using Matlab code written for this purpose. Digital photos will be taken around the head, and then photogrammetric software will be used to localise their positions. Images will be reconstructed using an MRI of the patient’s head, which needs to be converted to a Finite Element model with software for segmenting medical images and meshing them. The accuracy of these images will be compared with similar studies using fMRI. Skills to be acquired: Students will spend time in the lab in Medical Physics at UCL learning relevant methods and analysing the data, and some time in Prof Holder’s department at UCH, learning how to collect evoked responses using scalp electrodes. Skills to be acquired will include one or more of: medical image reconstruction; photogrammetric software use; medical image segmentation and meshing software; EEG electrode placement and use; experimental design and data analysis. The project would be suitable for a single student or a team of 2 or 3, with a backgrounds in physics, engineering, computing, or medicine.

3D-image-guided biopsy and therapy for prostate cancer

Supervisors: Dr. Dean Barratt and Yipeng Hu

Student: Danielle Beachey

Prostate cancer is now the most common cancer in men in the UK, North America, Australasia and many parts of Europe. Ultrasound imaging is used routinely in hospitals to guide prostate biopsy, where tissue samples are collected to determine the presence of cancer, and minimally-invasive therapies, such as high-intensity focused ultrasound (HIFU) and brachytherapy (a procedure where small radioactive seeds are implanted into the prostate). In practice, however, accurately placing a biopsy needle tip or a therapy delivery device within a tumour is difficult because images obtained using conventional ultrasound scanners only provide two-dimensional, cross-sectional views of the prostate. Moreover, in general they do not show prostate cancer. These problems can be overcome by using three-dimensional (3D) ultrasound imaging, which allows imaging of the entire prostate and any instruments inserted into the prostate, and augmenting these images with co-registered information on the size, location, and shape of a target tumour from 3D magnetic resonance (MR) images obtained prior to the procedure. The aim of this project is to evaluate the accuracy of this new approach using physical prostate imaging phantoms. The project will require the student to develop a good understanding of image registration technology using to align MR and US image information, and how it is practically applied in different therapies. Some MATLAB programming with also be required to perform relevant image processing tasks and to analyse the numerical results. The accuracy validation experiments will be designed by the student and carried out in the UCL Centre for Medical Image Computing (CMIC) image-guided interventions laboratory using a state-of-the-art research ultrasound scanner.

Development of optimal clinical workflows for MR-directed prostate cancer interventions

Supervisors: Dr. Dean Barratt, Yipeng Hu and Mr. Hashim Ahmed (Urology)

Student: Rajit Wilfred Shail

Prostate cancer is now the most common cancer in men in the UK, North America, Australasia and many parts of Europe. Recent advances in magnetic resonance (MR) imaging have led to substantial clinical interest in using this technique to localise tumours within the prostate and using information of tumour location, size and shape to direct minimally-invasive interventions, such as high-intensity focused ultrasound (HIFU) and brachytherapy (a procedure where small radioactive seeds are implanted into the prostate). One approach to this is to augment ultrasound images that are used routinely to guide such procedures register (or align) with MR image information. This is achieved by using image registration (or fusion) software to align images. The aim of this project is to devise part of a clinically practical protocol for surgical workflows that incorporate MR-ultrasound image fusion based on quantitative analysis of the inter- and intra-observer variability associated with critical stages of the process (e.g. manual contouring of MR images of the prostate gland). This project will involve becoming familiar with the image registration software developed by the supervisor’s team, which superimposes a graphical representation of a target tumour, derived from MR images obtained prior to a surgical procedure, onto transrectal ultrasound (TRUS) images acquired during HIFU procedures. The project will involve working closely with urological surgeons from UCL/UCLH to understand the clinical constraints, and a basic knowledge of MATLAB programming for data analysis.