Explore our current research projects in the expandable areas below:

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Research projects

31P MRS

31p MRSWe are using 31P MRS to explore variations in cardiac muscle composition and function in a population cohort with genetic and phenotypic variants associated with cardiovascular disease. 

Contact:

Ben Statton (b.statton@imperial.ac.uk)

Pawel Tokarczuk (p.tokarczuk@lms.mrc.ac.uk)

4D Flow

4D FlowWe are using 4D flow MRI to examine the relationship between aortic blood flow patterns, wall shear stress and the severity of aortic wall degradation in patients with ascending aortic aneurysms (AsAA). We aim to develop a rupture prediction model for patients with AsAA’s. using the phase-contrast MRI and biomechanical data.

Contact:

Ben Statton (b.statton@imperial.ac.uk)

Pawel Tokarczuk (p.tokarczuk@lms.mrc.ac.uk)

Brain tumour biomarker development

Brain tumour biomarker developmentWe are investigating imaging biomarkers (diffusion MRI, perfusion MRI, MR Spectroscopy, choline PET) and developing the clinical tools needed to understand brain tumour growth and improve brain tumour diagnosis.

Contact:

Matthew Grech-Sollars (m.grech-sollars@imperial.ac.uk)

Brain tumour classification through machine learning

Brain tumour classificationWe are developing new machine learning tools to aid clinicians in diagnosing brain tumours through MRI and digital pathology.

Contact:

Matthew Grech-Sollars (m.grech-sollars@imperial.ac.uk)

DCE-MRI data modelling

DCE MRI data modellingWe are applying different pharmacokinetic models to DCE-MRI data to assess blood-brain barrier disruption and leakage in primary brain tumours.

Contact:

Marianna Inglese (marianna.inglese17@imperial.ac.uk)

Exercise Cardiac MRI

Exercise Cardiac MRIWe are using exercise cardiac MRI to explore variations in cardiac function in a population cohort with genetic and phenotypic variants associated with cardiovascular disease.

Contact:

Ben Statton (b.statton@imperial.ac.uk)

Pawel Tokarczuk (p.tokarczuk@lms.mrc.ac.uk)

MR Fingerprinting

MR fingerprintingWe are investigating MRF as a rapid and quantitative technique for characterising brain tumours.

Contact:

Matthew Grech-Sollars (m.grech-sollars@imperial.ac.uk)

Rebecca Quest (rebecca.quest@nhs.net)

MRI biomarker for the prediction of Alzheimer’s disease

MRI biomarker for the prediction of Alzheimer’s diseaseWe are developing a radiomic MRI analysis method for Alzheimer’s risk prediction.

Contact:

Marianna Inglese (marianna.inglese17@imperial.ac.uk)

Multiparametric analysis of brain tumours

Multiparametric analysis of brain tumoursWe are investigating the integration of different imaging (DCE-MRI, DWI-MRI, DSC-MRI and PET) techniques for the characterization of tumour tissue.

Contact:

Marianna Inglese (marianna.inglese17@imperial.ac.uk)

Matthew Grech-Sollars (m.grech-sollars@imperial.ac.uk)

Muscle changes post ACLR

ACLRWe are using a number of MRI measurements at Stanford University to investigate thigh muscle changes post ACL reconstruction.  We aim to develop a measure of muscle quality to assess early changes after surgery with different grafts.

Contact:

Karyn Chappell (k.chappell@imperial.ac.uk)

Oxygen-enhanced MRI

Oxygen enhanced MRIWe are investigating the use of oxygen-enhanced MRI ventilation mapping in combination with MR perfusion to provide increased diagnostic accuracy when compared with ventilation-perfusion SPECT scintigraphy in patients with pulmonary hypertension.

Contact:

Ben Statton (b.statton@imperial.ac.uk)

Pawel Tokarczuk (p.tokarczuk@lms.mrc.ac.uk)

Smart Imaging and Analysis for Cardiovascular MR

Smart imaging analysisA novel deep learning-based and ROI focused multi-scale super-resolution approach is proposed to improve the apparent spatial resolution of in vivo Diffusion Tensor Cardiovascular Magnetic Resonance (DT-CMR).

Contact:

Guang Yang (g.yang@imperial.ac.uk)

Super-resolution

Super-resolutionWe are developing new methods to enhance spatial resolution in MRI.

Contact:

Pete Lally (p.lally@imperial.ac.uk)

Transverse MRI for Magic Angle Directional Imaging (MADI)

MADIWe are creating a moveable assembly with 2 DOF that provides a 'roll' and 'yaw' motion. We aim to utilise this prototype scanner with moving B0 for Magic Angle Directional Imaging (MADI) in vivo.

Contact:

Karyn Chappell (k.chappell@imperial.ac.uk)

More information is available under the Mechanical Engineering webpage 'Magnetic resonance imaging'.