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Emerging Imaging, Affordable Imaging

Developing Useful Measures of Brain Tissue With MRI

Project ID: 2022_023

1st Supervisor: Shaihan Malik , King’s College London
2nd Supervisor: Joseph Hajnal, King’s College London
3rd Supervisor: Xavier Golay, UCL and Gold Standard Phantoms
Clinical Supervisor: Prof Alexander Hammers, King’s College London

Aim of the PhD Project:

  • Create useful MRI measures beyond simple relaxation times which are scanner and sequence independent 
  • Develop phantoms (test objects) that mimic tissue properties, enabling proper validation of MR neuroimaging

Project description/background:

Quantitative MRI (qMRI) is increasingly important for ‘precision’ medical imaging since it offers an objective means for characterizing tissue, as opposed to the traditional radiology approach of subjective interpretation of qualitative images. It is making inroads in the clinic, has been subject of major vendor investment, and has seen creation of burgeoning ‘third sector’ of image quantification and analysis firms, some of which are UK based. QMRI also promises to increase the power of AI-driven automated diagnosis by producing scanner independent measures allowing large-scale pooling of data.

The Problem
There are many types of qMRI though the term is often synonymous with ‘relaxometry’ – measurement of tissue relaxation times T1 and T2. However, despite a large body of research, qMRI has not achieved truly objective measurement of tissue properties, particularly in neuroimaging. Repeatable T1 and T2 measurements can be made using matched hardware and software but it is difficult to produce measures that can be compared across clinics or between studies.

There are many reasons for this, mostly stemming from the fact that relaxation times are phenomenological and not directly linked to specific physical tissue properties. They are known to be strongly dependent on the magnetic field strength (B0) of the scanner, and are also heavily influenced by the interaction between liquid water in tissue and protons in the ever-present ‘semisolid’ macromolecular tissue matrix. These issues mean that measurements of relaxation times depend on how they are made (i.e. they are not objective) and they are scanner dependent: this is particularly relevant today with clinically used scanners now operating at ultrahigh B0 fields (7T+) as well as low (~0.5T) and ultralow (<<0.5T) field strengths.

This project
We will look directly to the properties that are driving tissue relaxation – the semisolid tissue matrix- and aim to create measures that are objective and machine/method independent. We will use methods based on ‘magnetic resonance fingerprinting’ (MRF) which has revolutionised the field of quantitative MRI over the last decade, but alter these to directly quantify semisolid tissue properties, and optimize them using Machine Learning.

The project will have two major parts:

  1. Working on a range of cutting edge MRI scanners operating at a range of B0 field strengths (0.55T to 7T), all available at the St. Thomas’ campus, and with support from an experienced MRI physics research team, and the manufacturer (Siemens Healthineers).
  2. Developing test objects for validating quantitative methods in collaboration with Gold Standard Phantoms, a UK based company specialising in quantitative MRI test objects.

The project will involve a mixture of experiment, programming of scanners, and theoretical work, and will include working directly with industrial partners. It would be well suited to a candidate with background in physics or (biomedical) engineering and will be an excellent training opportunity for someone interested in either a career in academic biomedical engineering research or technical development within industry.


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