Projects & Collaborations
We are involved in several collaborative projects, both internally within the King's Imaging Sciences Division and with external academics and industry partners. Take a look at a brief overview below, and don't hesitate to get in touch if you are interested in working with us.
Computer Model Derived Indices for Optimal Patient-specific Treatment Selection and Planning in Heart Failure
The primary aim of VP2HF is to bring together image and data processing tools with statistical and integrated biophysical models mainly developed in previous VPH projects, into a single clinical workflow to improve therapy selection and treatment optimization in HF.
Clinical translation will be facilitated through the development of a software platform that incorporates the above tools within a decision tree framework. Prospective patient validation (n=50) will be undertaken within the lifetime of project.
VP2HF is a european-wide collaboration involving 6 institutions and 2 industrial partners, led by King's College London.
KCL Consortium Members
Prof. Reza Razavi
Prof. Phil Chowienczyk
Dr. Jessica Webb
Dr. Tom Jackson
Dr. Radomir Chabiniok (now at M3DISIM INRIA)
Understanding the Impact of the Microvasculature on Quantification of Fibre Orientation in the Heart Using Diffusion Spectrum MRI and Computer Models
The central goal of this project is to investigate whether cardiac microstructure assessed by diffusion magnetic resonance imaging is strongly influenced by microvessels, as opposed to the myofibres as traditionally thought. Such a finding would have implications under diseased conditions in which normal vessel-myofibre orientations may be disrupted.
To investigate this question, the project combines advanced MRI techniques as well as high-resolution microstructral imaging, experimental and computational models.
This project is a collaboration between the BHF Experimental Magnetic Resonance Unit at the University of Oxford, and King's College London.
Project Collaborators
Dr. Jurgen Schneider
Dr. Irvin Teh
Dr. Vincente Grau
Dr. Rebecca Burton
CHeart: A Multi-physics Parallel Computing Engine
CHeart is our homegrown scientific software for simulating the physics of the human heart and cardiovascular physiology. It features fast mpi-based code which leverages advanced supercomputing resources, as well as leading-edge GPU technologies.
CHeart is used to simulate the solid mechanics, ventricular & coronary fluid dynamics, and electrophysiology of the heart, as well as performing inverse parameter estimation of these problems. It is built from ground-up to target multiple coupled physics problems aimed at providing a flexible, extensible and scalable code for biomedical problems.
Project Collaborators
Dr. David Nordsletten
Dr. Liya Asner
Dr. Eric Kerfoot
Unified Visualiser and Analysis Environment for Medical Imaging Data and Biomedical Models
Streamlining image analysis and computational modelling to the clinical environment requires a software platform that is versatile, scalable and speedy. Such a tool is being produced currently at the Biomedical Engineering Department, in collaboration with Dr. Eric Kerfoot who is leading the code development. It aims to achieve a platform-independent, seamless 3D and 2D visualisation of multi-modality medical imaging data and computational models with integrated analysis functionalities, that can either be used as a general research tool, or be packaged up as a clinical workflow environment for specific translational applications.
Project Collaborators
Dr. Eric Kerfoot
Dr. Radomir Chabiniok
Dr. David Nordsletten
Dr. Rachel Clough
Prof. Reza Razavi
Flow-Contraction Mapping in the Heart for Interventional Cardiology Applications
Our ongoing collaboration with the Cardiovascular Division at King's College London, on the simultaneous LV-coronary data has led to several useful outcomes including the studies of mechanisms underpinning coronary wave intensities as well as the development of the integrated signal analysis tool.
Project Collaborators
Dr. Tiffany Patterson
Prof. Simon Redwood
Vascularised Tissue Characterisation Using Combined Magnetic Resonance Imaging and Computational Modelling
MR Elastography is a novel technique enabling in vivo characterisation of soft tissue mechanical properties. MRE in conjuction with diffusion imaging has the potential to probe sensitive microstructural changes in tissue under disease. This technology has a broad scope of application including cardiac wall diagnosis, tumour characterisation in internal organs, and novel treatment strategies. One of the challenges hindering a more sensitive detection is the unknown influence of the microvascular haemodynamics in determining the apparent mechanical properties of the bulk tissue. With the Biomechanics Group in the Department we are addressing this question with a combination of experimental, theoretical and computational approaches.
Project Collaborators
Prof. Ralph Sinkus
Dr. David Nordsletten
Validation of Absolute Quantification of Flow from Magnetic Resonance Perfusion Imaging
Magnetic Resonance Perfusion Imaging has several advantages over competing non-invasive perfusion imaging modalities (e.g. SPECT, PET) in that it offers superior imaging resolution without ionising radiation. However, its wider adoption in clinical practice is partially hindered by the fact that quantification of flow in absolute mL/min/g terms has not been fully validated, forcing semi-quantitative approaches to be employed instead. With the Cardiovascular Imaging Department at KCL and AMC Amsterdam, we are pursuing a validation of voxel-wise perfusion quantification of MR Perfusion Imaging through the gold-standard microsphere technique.
Project Collaborators
Dr. Amedeo Chiribiri
Dr. Jeroen van den Wijngaard
Prof. Jos Spaan
Prof. Maria Siebes