Medical
Image Computing is an exciting, interdisciplinary area of research and
the UK
has some of the largest medical imaging research groupings in the
world. In
January 2005, a new Centre for Medical Image Computing (CMIC) was
established
at University College London, which combines excellence in medical
imaging
sciences with innovative computational methodology. The new group is
one of the
strongest in the world and will launch a new MSc in Medical Image
Computing in
2007. The course director, David Atkinson, reports on medical
image
computing and how it is being used to benefit medical diagnosis and
therapies.
Within a few months of the discovery of X-rays by Wilhelm Röntgen
in 1895, X-ray images were used to plan and guide a surgical
intervention. In the field of medical imaging, the themes of innovation
in diagnosis and treatment have continued over the past century and the
UK has gained two Nobel prize winners; Godfrey Hounsfield for the
development of computer assisted tomography (CT) and Peter Mansfield
for discoveries concerning magnetic resonance imaging (MRI).
Hounsfield’s work used data from X-rays taken at different angles to
perform tomography – the calculation of image slices through the body.
MRI also produces three dimensional data but is based on magnetic
fields and radio waves rather than X-rays. MRI and CT are complementary
- each providing images sensitive to different types of tissue.
In addition to MRI and CT, we also have ultrasound imaging based on the
reflection of sound waves and positron emission tomography (PET) and
nuclear medicine that detect the decay of radio-isotopes. These
isotopes are added to compounds that concentrate at sites of specific
tissues or diseases enabling them to be visualized in imaging.
Furthermore, medical images come from surgical microscopes, endoscopic
examinations, photographs and video as well as emerging technologies
such as optical tomography whereby light is shone through the head at
multiple angles. This wealth of data brings new information and great
opportunities to apply computing methods for enhancing diagnosis,
helping plan, guide and assess therapies and for the investigation of
fundamental questions about the working of the human body.
Computers in Imaging
Acquisition systems
produce digital data that is converted to images and ultimately viewed
by
radiologists and surgeons. Present throughout this chain are computers,
not
just as convenient tools for storage, workflow and display, but also in
the
control of the scanning, the alignment of images, detection of
different tissue
types, calculation of quantitative measures, generation of new images
such as
maps of active regions in the brain and surgical guidance. Increasingly
the
hardware of scanners is under software control and we have the
opportunity to
produce algorithms that will intelligently enhance the image
acquisition by
responding in real time to patient data.
A
key tool
for generating new information is image registration, a field in which
the UK
has been very active in research. Registration algorithms compute the
transformation needed to align, or warp, one image into another. With
the
ability to align images, comparisons between images taken on different
days can
reveal small changes in tissue size, for example the slow shrinkage of
the
brain over many years due to dementia. Finding the transformation from
one
image to another can be used to measure motion, for example a cine
series of
cardiac images can show abnormalities in heart wall motion due to
tissue
damaged by a heart attack. In another application of registration,
images from
different patients are aligned into one common space. A representative
image or
atlas can then be computed, against which new patients can be compared.
Registration is used in the fusion of data from different scanners
leading to
enhanced understanding, for example, a PET image is sensitive to the
uptake of
glucose by tumours and an MRI image can show other anatomy in detail -
combining the two provides a richer source of information to guide
patient
care.
The UK is especially active in research into the workings and
connectivity of the brain. Brain activity and thoughts cause changes in
blood flow and oxygenation that show up as subtle differences in MRI
scans. After computer processing involving registration, segmentation
of relevant structures and statistical analysis, maps can be made
revealing brain regions that are active during various tasks. These
scans and processing are called functional MRI. Diffusion weighted MRI
provides an image contrast that is sensitive to cellular architecture.
Using this technique, we can now infer the directions of fibre bundles
within the brain; for example, we can see how the spinal column is
connected to the motor cortex.) In addition to enhancing our
fundamental understanding, this research has the potential to guide
brain surgery in order to avoid severing crucial nerve connections.
Obtaining quantitative measures is vital for enabling patient
information to be compared with existing knowledge or to assemble new
measures of anatomy and physiology. UK researchers have developed
methods for modelling shape to study structural and functional
variation in health and diseased states. Research is also using shape
information to find organs and bones in images and to guide surgery.
In surgery and interventions where a catheter is inserted through a
blood vessel into the heart, images from previous scans can be used to
help guide the operator during the procedure. Registration techniques,
and the 3D tracking of equipment, are used to visually present images
taken prior to the procedure, which are overlaid on the new surgical
scene. The world’s first MRI guided cardiac catheter intervention took
place recently at Guy’s Hospital, King’s College London.
Patient
movement resulting from involuntary motion, cardiac pulsation,
respiration and
flowing blood can all blur MR images. Novel algorithms for correcting
images
are being developed at Imperial College London and UCL to aid diagnosis.
Medical and Technological Drivers
Faster scans at higher resolution and with better image quality
are always in demand. Our enhanced understanding of the genome is
driving a desire to observe changes at the molecular scale whilst
wanting to consider the patient as a whole. A dream goal might be the
biological equivalent of Google Earth that enabled zooming from a whole
body image down to the cellular and then molecular levels.
Detector technology is improving and providing ever more data. In MRI,
the numbers of coils used to receive the signal has increased by an
order of magnitude. In CT, the detectors that acquire the X-ray signal
at each angle now have many more elements, generating much more data.
In PET imaging, modern scanners are now combined with a CT scanner and
in ultrasound, micro bubbles injected as contrast provide harmonic
signals in addition to the main signal.
These large quantities of data present challenges for computer
algorithms and are very demanding of memory requirements. The increased
availability of 64-bit machines and the ability to connect large
numbers of PCs to form a cluster are addressing these issues. For
example, the CMIC group at UCL have their own 60 node, 64-bit cluster
and there are e-science projects that use a national grid of computers.
One e-science project called IXI is collecting brain images from 600
people at three different sites. The aim is for a doctor to be able to
see at a glance the normal range of sizes and shapes of each brain
structure, overlaid on the patient’s own scan, assisting diagnosis. To
provide this information, the grid will access data that may be stored
in distributed places and perform the necessary calculations on
machines located anywhere on the grid network. Just like the
electricity grid, the user draws resources without concern for where
they are generated.
Imaging in clinical trials
Drug
discovery and
development can bring major advances in the treatment and management of
disease. The costs from discovery to launch of a successful drug are
estimated
to be in the region of £1 billion when failures of other drugs
are factored in.
There is a big incentive to gauge the effectiveness of a trial drug
early. In
studies of dementia such as Alzheimer’s, disease progression can take
decades
and computing and imaging techniques are being developed to quantify
small
changes in brain volume early in a trial to predict outcome. This use
of images
to indicate underlying biology is termed “biomarkers” and can save time
by
halting trials early. The endpoint of a standard clinical trial may
require
waiting decades to observe complete disease progression, there is hope
that imaging
might act as a surrogate endpoint whereby a drug can be assessed more
quickly
thus saving money and enabling the drug to be made available sooner.
Thriving Industry
University research groups have started to spin-out companies to market
algorithms and services for medical imaging. The university origins and
links of these companies benefit Postgraduates. Examples include
Siemens Molecular Imaging (formerly Mirada) in Oxford, iMorphics in
Manchester and IXICO in London. PhD and MSc projects are also sponsored
by companies such as Vision RT who are experts in real time 3D surface
imaging for radiotherapy applications, Kodak who are involved in the
whole imaging chain, DePuy who develop surgical technology, the
Wellcome Trust and the major medical equipment manufacturers such as
Philips, Siemens and GE Healthcare. Many of the global pharmaceutical
and healthcare companies have research sites in the UK. Notably, a new
£76 million Clinical Imaging Centre is under construction as a
joint venture between GlaxoSmithKline and Imperial College to use
imaging in drug discovery and development.
Postgraduate Opportunities
In
2007, UCL plans to start an MSc dedicated to Medical Image Computing.
The course can be taken full or part time and scholarships are
available to some
students.
The
UK
Engineering and Physical Sciences Research Council recognised the
strength of
medical imaging by funding a six-year project that now links Imperial
College
London, Kings College London, Manchester, Oxford and UCL. These groups,
and
others in the country, provide opportunities for obtaining a PhD in
medical
image computing. A bi-annual summer school brings together an
international
teaching faculty to provide lectures and workshops for Postgraduates
studying
in the UK and overseas.
Summary
Within
the
UK, university research in medical image computing is well-funded,
industrial
activity ranges from start-up companies to global pharmaceutical
organisations
and there is substantial investment by the government in the healthcare
sector.
This creates a healthy environment for Postgraduate study and research
and in a
subject that brings together computing, medicine, healthcare, biology,
maths,
engineering and physics for applications that benefit healthcare and
well-being.