Jierong Luo

Research Fellow

University College London

Jierong Luo is a postdoctoral researcher in the University College London Department of Medical Physics & Biomedical Engineering, UK. Currently working in Professor Karin Shmueli's Magnetic Resonance Imaging (MRI) research group, Jierong's research interests focus on MRI electromagnetic tissue properties mapping and its applications in diagnostic neuroimaging. She is developing and optimising new Magnetic Resonance Electrical Properties Tomography (MR-EPT) acquisition and processing techniques and investigating their potential to discover structural and functional biomarkers in Alzheimer’s disease.
 

Jierong holds an MSc in Biomedical Engineering and a PhD in Engineering from the University of Warwick, UK, where she worked with Professor Joanna Collingwood, investigating clinical and pre-clinical MRI techniques to quantify brain iron in normal ageing and neurodegeneration (Luo et al., 2022, J Neurosci Methods, doi: 10.1016/j.jneumeth.2022.109708). Jierong has won numerous awards and competitive scholarships from the International Society for Magnetic Resonance in Medicine, University of Warwick, and Hunan University, China (BSc).

The impact of amyloid-β and ferritin on ultra-high-field transverse relaxation rate (R₂ * ) and quantitative susceptibility mapping (QSM) magnetic resonance imaging (MRI)

Introduction: Magnetic resonance imaging (MRI) has shown the potential to detect amyloid plaques, an established hallmark of Alzheimer's disease. With strong magnetic susceptibility, the iron sequestered by the plaques is hypothesised to be underlying the MRI contrasts. However, challenges remain in quantifying the impact of amyloid plaques and associated iron on MRI.
 

Methods: To investigate the impact of aggregating amyloid on MRI, we synthesised in-vitro amyloid-β (Aβ) aggregates with and without ferritin-bound iron using our established incubation protocol. The incubated samples were embedded in agarose gel to be examined at ultra-high-field 9.4T MRI. We then optimised the MRI pulse sequence and the reconstruction techniques to acquire quantitative susceptibility maps (QSM) and the transverse relaxation rate (R₂ * ) of these samples (Fig. 1). We demonstrated the signal evolution with the amyloid aggregate formation and analysed the correlation between the signals and samples' concentrations.
 

Results: Magnitude images showed distinct contrast within the sample containing Aβ coaggregated with ferritin (Fig. 2), and R₂ * of co-incubated Aβ+ferritin increased with incubation time. Analysis of correlations between the MRI measurements and sample concentrations showed that R₂ * and QSM signal increases were mainly dependent on the iron-laden ferritin (Fig. 3).

Conclusions: We established a method to investigate the sources of MRI contrast from amyloid aggregates and associated iron, and the techniques to image their R₂ * and susceptibility using 9.4T MRI. Our findings deepen the understanding of the impact of Aβ and ferritin on MRI contrast and may aid sequence selection and interpretation for clinical MRI of amyloid pathology.