In vivo characterisation of Hippocampal Neuroinflammatory Pathology in Patients with Multiple Sclerosis using novel Multimodal quantitative MR imaging

Student thesis: Doctoral Thesis


Evidence indicates that the hippocampus is a site of neuroinflammatory pathology and glial activation in Multiple Sclerosis (MS). Cognitive and affective sequelae of hippocampal involvement in MS are disabling and difficult-to-treat with available disease modifying treatments. Although hippocampal subregions display differential pathological vulnerability, clinical routine MR techniques are unable to characterise hippocampal subfields due to insufficient spatial resolution. The work presented in my thesis investigated the use of novel multi-modal MRI techniques to characterize hippocampal neuroinflammatory pathology in patients with MS.

In my PhD studies I tested two novel approaches: 1) the application of a post-acquisition resolution enhancing technique on diffusion-weighted MR imaging data to enable assessment of tissue microstructure separately across different hippocampal subfields. 2) the study of the hippocampus with diffusion-weighted Magnetic Resonance Spectroscopy (DWMRS), to detect cell-specific morphological alterations. My aim was to test whether the application of these imaging techniques to the hippocampus in MS patients is feasible and sensitive to detect neuroinflammatory changes.

Using collected MS and control data, I also intend to test the statistical significance amongst depression, cognitive and disability scores and explore correlations with imaging variables.

For my first study, I used diffusion-weighted imaging datasets (n=11) from the Human Connectome Project (HCP) database of healthy subjects, and I applied image quality transfer (IQT) to enhance post-acquisition resolution before segmentation of hippocampal subfields. Diffusion parameter estimates were obtained from diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) models. For my second study, I recruited a cohort of 15 MS patients (PPMS n=6; RRMS, n=9), and 10 healthy subjects and applied a similar imaging protocol to compare DTI and NODDI parameters across hippocampal subfields. In the third study, I applied DW-MRS to the same cohort to estimate hippocampal apparent diffusion coefficients (ADC) of cell-specific metabolites. Clinical outcomes, including cognitive and affective symptoms, were recorded.

The application of IQT protocol on DW imaging data enabled effective segmentation of hippocampal subfields on both HCP datasets and clinical cohort. There were significant differences in DTI and NODDI parameters between subfields. In the clinical study, I found differences in diffusivity parameters in specific subfields between PPMS and controls. The DW-MRS study provided preliminary evidence that assessment of hippocampal metabolites ADC was feasible, and potentially sensitive to detect differences in PPMS patients. Finally, I estimated effect sizes to inform power and sample size calculation for future studies.

My findings provide preliminary support to the utility of resolution-enhanced DTI and DW-MRS for the assessment of MS hippocampal pathology, particularly in PPMS. These results will inform design of future studies of therapeutics targeting symptoms related to hippocampal pathology.
Date of AwardFeb 2023
Original languageEnglish
Awarding Institution
  • University of Brighton
Supervisor Alessandro Colasanti (Supervisor), Mara Cercignani (Supervisor) & Andrew Barritt (Supervisor)

Cite this