1st Supervisor: Fernando Zelaya, King’s College London
2nd Supervisor: Enrico De Vita, King’s College London
Clinical Champion: Alexander Hammers, King’s College London
Additional Supervisor: Daniel Rueckert, Imperial College
Aim of the PhD Project:
- Optimisation/modification of ASL pulse sequence to robustly measure cerebral perfusion on KCL’s hybrid PET-MR scanner.
- Development of a streamlined postprocessing pipeline.
- Construction of a healthy control perfusion template.
- Presentation of individual perfusion maps to clinicians alongside supporting statistical parametric maps and information from different acquired modalities; these will facilitate and support neuroradiological reporting.
Project Description / Background:
Measuring and monitoring cerebral perfusion levels is important in a number of brain diseases with vascular components. MRI can produce quantitative cerebral blood flow (CBF) maps using dynamic susceptibility contrast sequences and Gadolinium-based contrast agents. Some of these contrast agents have however been linked to nephrogenic systemic fibrosis and are contraindicated in patients with impaired kidney function; there is also concern about the retention of Gadolinium and its potential long-term health effects (Ramalho2017).
Arterial spin labelling (ASL) can measure perfusion completely non-invasively using blood water as an endogenous contrast agent. As such, ASL is suitable for longitudinal studies without the concerns associated with Gadolinium retention. ASL-based CBF maps have been shown to correlate to PET based metabolism maps and ASL is starting to be employed in selected clinical applications. However, the radiological detection of perfusion abnormalities in individual patients is complicated by within-subject variability (due to the subject’s physiological state at the time of scan) and subject-to-subject variability of cerebral perfusion, both of which are well documented even in healthy subjects (Clement2017).
For interpretation of PET images there exist databases of healthy controls stratified by age and gender that can support radiologists in their reporting (e.g. Neurostat, Minoshima2001). The final aim of this project is to build an equivalent healthy control database for cerebral perfusion, that will support and facilitate the detection of local or global perfusion abnormalities for individual subjects (Computer Aided Diagnosis, CADx).
One complicating issue is that ASL CBF maps are still often dependent on the particular scanner, sequence and protocol employed (Mutsaerts2017). PET-MR scanners have additional disadvantages compared to state-of-the-art MR-only scanners, namely larger bore size and reduced availability of PET-transparent receiver coils with large number of elements and potentially slower/less powerful imaging gradient inserts. As a consequence, sequences can be slower, there is limited scope for multiband acceleration and there is a resulting reduction in signal to noise ratio (SNR).
An important aim of this project is therefore the development of a dedicated ASL imaging sequence for the PET-MR scanner with sufficient spatial resolution and reproducibility to ensure that pathologically significant perfusion abnormalities can be detected at individual level with the support of a healthy control database plus information from any other acquired imaging modality.
CBF measurements simultaneous with PET acquisitions are particularly important. Indeed an active area of research is investigating whether CBF changes resulting from activation paradigms or pharmacological challenges can affect PET tracer uptake or washout and consequently whether they influence PET quantification of receptor binding [Sander2017].
Artefact levels, temporal SNR and scan-to-scan variability will be assessed for the most promising ASL sequences available. Candidate readouts include 2D-EPI, 3D-GRASE and 3D-stack-of-spirals (Vidorreta2014). Parallel Imaging and multiband methods will be considered as well as acquisitions with compressed sensing (Vidorreta2017). In-house pulse sequence development to incorporate desirable features is expected. Processing pipelines (testing alternative methods for motion correction, outlier rejection, partial volume correction and deblurring algorithms) will be evaluated in combination with each pulse sequence in order to achieve minimal between and within subject variance in the normal perfusion template.
The selected combination of acquisition sequence and postprocessing method will be then suggested for any subsequent research and clinical study, in order to generate a larger dataset for a more complete normal perfusion database.
Required candidate background: The candidate will have an academic background in Physics, Engineering, Maths or a similarly relevant subject with a strong interest in perfusion MRI measurements
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- Mutsaerts HJMM, Petr J, Thomas DL, De Vita E, et al., Comparison of arterial spin labeling registration strategies in the multi-center GENetic frontotemporal dementia initiative (GENFI). J Magn Reson Imaging. 2017 May 8. doi: 10.1002/jmri.25751.
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- Zhao MY, Mezue M, Segerdahl AR, Okell TW, et al., A systematic study of the sensitivity of partial volume correction methods for the quantification of perfusion from pseudo-continuous arterial spin labeling MRI. Neuroimage. 2017 Sep 5. pii: S1053-8119(17)30710-3.