Towards Reliable Diffusion MRI of Moving Organs

Lead Research Organisation: King's College London
Department Name: Imaging & Biomedical Engineering


Diffusion Magnetic Resonance Imaging (DMRI) is a clinical imaging technique that has the unique potential to provide clinically-relevant information without the use of ionising radiation or invasive procedures. Although DMRI is often used in brain imaging, it is not currently widely used in other parts of the body because of a series of technical challenges that this grant will address. Our approach will be to describe the challenges in a unified mathematical framework and solve this using new acquisition and image reconstruction techniques. The intensities in diffusion weighted MR images originate from the distances that water molecules can diffuse. These diffusion distances are affected by the local cellular environment and changes in the environment are reflected in images. Diffusion MRI can reveal the directionality of structures, such as the orientation of cardiac muscle cells and changes in cell density and organisation due to cancerous tumours. Cardiac disease and cancer are very significant health issues worldwide for which DMRI may provide key diagnostic or therapeutic information. Cardiac disease is the main cause of death (ca.30% worldwide), and cancer the third (ca.12%) with lung and liver cancer among the most common.The correct functioning of the cardiac muscle is dependent on the complex orientations of the fibres within the heart wall. Being able to image these in-vivo could lead to enhanced diagnosis, treatment and surgery planning for conditions such as heart failure, congenital defects or remodelling following a heart attack. In cancer, DMRI has the potential to improve diagnosis, aid localisation and grading of tumours, support treatment selection, better identify residual and recurrent disease following treatment, and even predict treatment outcome and reduce diagnostic errors. However, DMRI currently has a limited role outside of the brain because of five main technological restrictions; motion of organs, magnetic field variations due to the different magnetic properties of tissues such as fat, bone and air, magnetic field inaccuracies due to inherent MR scanner imperfections, long scan durations and the question of how to interpret the data. Previously we have described the effect of complex non-rigid motion on MR images using a clear mathematical framework and used this to correct for motion. In this grant, we propose to extend these methods to include the challenges limiting DMRI. Taking this general view allows the challenges to be solved collectively rather than sequentially. The techniques will improve the reliability of DMRI and thus widen its clinical uptake. At the same time, the techniques permit more efficient use of scan time, either to encode more information or to shorten scan durations. A general formalism provides a new way of viewing the problem and lends itself to making use of the tools available from other branches of computational mathematics. To support this approach, we will need measurements of magnetic field imperfections caused by MRI scanner inaccuracies. These will be provided by field mapping hardware, which will be installed for the first time in the UK. In addition, novel techniques such as compressed sensing and new models of tissue diffusion will be explored to reduce overall scan times, improve accuracy and provide better interpretation of data.

Planned Impact

The ultimate beneficiaries of this research will be patients who are suffering from some of the most common lethal diseases: cancer and cardiovascular disease. These diseases still have a significant morbidity despite recent advances. The better quality, more reliable and more widespread clinical applications resulting from this research are likely to have a significant impact on the management of these diseases. This impact is only likely to be realised longer term as there is a requirement for developed techniques to undergo comparative clinical trials and be adopted by scanner manufacturers and healthcare professionals. For patients to benefit, clinicians must have both the desire and ability to use the methods we develop. Creating clinical demand requires both publicity and more detailed comparative trials to prove clinical benefit. We will continue to publish in leading peer reviewed journals and present at major conferences. One of the RAs has 12 months of time allocated to validation, data handling and testing on small numbers of patients, as appropriate for EPSRC funding. UCL and KCL are also partners in a Comprehensive Cancer Imaging Centre. These structures provide an ideal environment for translation and thus impact through joint working, seminars and close clinical involvement. To make the methods clinically accessible, in the long term they need to be incorporated by scanner manufacturers into their products. We will work closely with Philips, one of the three principal MRI scanner manufacturers to ensure that pulse programming code we write is compatible with their software development plans. KCL has a close collaboration with Philips (via Dr A Wiethoff, Philips KCL based scientist). More general reconstruction code will be made open source and we have experience of this at UCL with a diffusion data analysis package ( ). The reconstruction code will also be advertised on the MATLAB File Exchange and on the new site provided by the main international society dedicated to providing an infrastructure to promote the rapid and robust development of advanced methods for data collection and image reconstruction in MRI. ( The pharmaceutical industry needs to evaluate responses to candidate drugs. More reliable, higher resolution, faster or validated diffusion imaging could act as a biomarker for response. Increased reliability reduces variation and thus enables the use of smaller sample sizes at reduced cost. More accurate data could enable drug response to be observed sooner and thus speed-up treatment, drug development and time to market. Also, our work will enable related techniques that use diffusion type imaging to infer microstructure and these could provide the pharmaceutical industry with more information about how their drugs are causing changes at the cellular level. Clinical researchers at our institutions and their immediate collaborators will have access to new imaging methods and reconstructions to form a better understanding of disease, treatment and the types of imaging required to optimise clinical management. Training will be one of the most immediate beneficiaries of this research programme. Those employed on the grant will be able to access the Post Graduate training at UCL and KCL (existing students and staff already attend relevant modules from courses such as the Medical Image Computing MSc and Medical Physicist training). The UK economic competitiveness will benefit through attracting further research funding. The groups of all three investigators have previously attracted investment and research contracts from Philips Medical Systems. Reliable imaging increases the chances that pharmaceutical companies will choose our clinical sites for their trials and this is a lucrative source of income for the UK and exploits the good research base already in the UK. Public engagement activites will enthuse a wider audience.


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Description We developed Magnetic Resonance sequences that can show us the directions of the muscle fibres within the in-vivo heart. The fibre directions are important because these muscle fibres are responsible for the beating of the heart and the pumping of blood around the body and do change in various relevant cardiovascular diseases. We were able to produce 3D visualizations of these cardiac muscle fibres of the in-vivo human heart for the first time.

For the kidney, we modified sequences to achieve high resolution diffusion imaging of the kidney during free breathing. Diffusion imaging in the kidney has the potential to provide information about the microstructural environment and health of the kidney.

With colleagues from the UCL Centre for Medical Image Computing, we developed diffusion sequences that reveal micro structural information about prostate cancer.

As well as developing novel sequences, we have provided insight into how to handle the inherent noise in diffusion scans and built models linking diffusion and other MR properties to histological findings in prostate cancer.

To elucidate microstructural changes in relation to cardiac remodelling in congenital and acquired heart diseases, we translated our imaging tools into the clinical setting and acquired data in patients with systemic right ventricles and in patients with dilated cardiomyopathies in cooperation with cardiology colleagues at KCL. Marked differences of cardiac muscle architecture was detected relative to data from healthy subjects indicating the potential of our method to improve the diagnosis of cardiac patients.

Beyond the visualisation and quantification of cardiac muscle architecture, we also explored the possibility to image tissue perfusion in the heart using diffusion weighted imaging. Such an approach may allow to replace contrast agent based perfusion imaging in the future.

We had access to one of the first commercial field cameras for the highly accurate mapping of magnetic fields within an MRI scanner. Using this we were able to characterise and publish some of the unwanted fields that compromise the accuracy of diffusion imaging. We further showed that knowledge of unwanted fields permits the correction of biases to yield accurate diffusion metrics.

With the availability of detailed information on in-vivo human cardiac muscle architecture, computer-based biomechanical modelling can be taken to the next level. To this end, collaborations with modelling experts at KCL have been initiated. It is expected that this work will lead to new insights regarding the mechanisms of congenital and failing hearts in the future.
Exploitation Route The MR sequences and acquisition strategies that we developed for imaging of the heart and kidney may be taken forward by other academic centres and industry, using the information that we have published. Single centre trials are starting using some of the techniques we developed, or contributed towards. An EU COST action on kidney imaging is in preparation by Leeds University. The distortion reduction methods have formed the basis of a Cancer Research UK grant awarded to UCL, in this case applied to prostate cancer imaging.

Our published findings using the field camera will inform academic and industrial development. Newer generations of the camera are being marketed by Skope Magnetic Resonance Technologies and benefiting researchers worldwide, including in the UK, Oxford and Nottingham Universities.

The measurement and reconstruction methods we developed for cardiac diffusion tensor imaging provide journal publications and datasets that will be available from a public repository. These will inform models of heart structure and function in disease that could provide new insights into cardiac disease mechanisms.
Sectors Healthcare

Description This was a highly technical project requiring persistence from skilled people to acquire, process and interpret data. In addition, considerable efforts were spent to translate the imaging technology into the experimental and clinical setting and provide first evidence of the value of diffusion imaging in patients. As a result of the work a number of tangible projects have been launched: * a single centre trial on 20 patients with aortic stenosis and 12 patients with dilated cardiomyopathy has started to reveal structural remodelling of the heart and its recovery after intervention. * a single centre trial of 360 patients on prostate cancer diagnosis has started. This trial uses a diffusion imaging acquisition developed by the PostDoc on this grant. * we expect the information we published on diffusion imaging from moving kidneys to become part of the normative data on healthy kidneys. * we are due to launch a cardiac atlas that will be available publicly providing data for in-depth analysis of cardiac mechanics. * we have initiated collaborations with cardiac modelling experts to gain further insights into the mechanisms leading to cardiac remodelling. * partly as a consequence of this work, we have contributed to the diffusion component of the developing international standard for MRI raw data that is independent of vendor. * some of the methods developed in this grant for the reduction of distortions in cardiac imaging have formed part of a successful grant application to Cancer Research UK for distortion correction in prostate MR imaging - something that frequently hampers cancer diagnosis. * the methods developed for imaging the heart have formed the basis to successfully recruit funding for investigating the efficacy of stem-cell based cardiac repair.
First Year Of Impact 2014
Sector Healthcare
Impact Types Societal

Title Cardiac DTI Atlas 
Description Comprehensive data set of in-vivo human cardiac myofiber architecture has been acquired and made available to the research community. 
Type Of Material Improvements to research infrastructure 
Year Produced 2016 
Provided To Others? Yes  
Impact The atlas provided allows detailed computational modeling of cardiac electrophysiology and cardiac mechanics. 
Description Harvard Medical School 
Organisation Harvard University
Department Harvard Medical School
Country United States 
Sector Academic/University 
PI Contribution Delivery of cardiac diffusion tensor data acquired in patients with myocardial infarction.
Collaborator Contribution Expertise in post-processing and visualization of cardiac diffusion tensor data.
Impact Scientific publication.
Start Year 2013