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Magnetic Resonance Imaging (MRI) is an important step in many clinical pathways, and a crucial resource in brain imaging research. Currently, up to 37% of patients undergoing MRI report moderate to high anxiety levels, with reasons including claustrophobia, loud acoustic noise, and length of scan, while up to 30% of in-patient or emergency MR examinations are corrupted beyond use due to motion artefacts, and 14% of subjects require sedation[1]. These issues waste significant quantities of money and can make recruitment of patients into long-term studies difficult. A simple way to reduce anxiety, and hence improve the patient experience, is to reduce the acoustic noise level of an MR scan. 

The physics team in the Department of Neuroimaging at Denmark Hill have together with collaborators at GE Healthcare pioneered development of novel MRI techniques with reduced acoustic noise. In the first half of 2020, we saw several projects in silent MRI come to a conclusion, marking an important step forward in our research in silent MRI. 

The project is largely divided into development of silent structural and silent functional MRI methods, both of which have demonstrated impressive leaps forward this year. 

Emil Ljungberg successfully defended his PhD thesis which focused on how to generate useful image contrast with silent MRI. Part of his thesis was published in Magnetic Resonance in Medicine, demonstrating silent T1 mapping using the VFA method [2]. Emil is now working on implementing motion correction into silent MRI in a postdoctoral fellowship supported by the CME. 

Postdoctoral CME fellow Dr. Tobias Wood published his first silent MRI paper, focusing on magnetisation transfer (MT), and more specifically on myelin-weighted imaging using the recently proposed inhomogeneous MT (ihMT) contrast [3]. 

Nikou Damestani, an NIHR Maudsley BRC PhD student, is working on the development of silent fMRI using a sequence known as Looping Star. She presented initial results of using Looping Star with an auditory oddball paradigm, highlighting the benefits of minimising the confound of acoustic noise [4]. 

In collaboration with GE Healthcare, our team has also demonstrated the utility of a multi-contrast silent method which can capture T1, T2, and proton density images in one combined acquisition[5]. 

The team is now busy wrapping up the year with some really exciting results to share early next year. Watch this space! 

References 

[1] Nguyen, X. V. et al. Prevalence and Financial Impact of Claustrophobia, Anxiety, Patient Motion, and Other Patient Events in Magnetic Resonance Imaging. Topics in Magnetic Resonance Imaging 29, 125–130 (2020). 

[2] E. Ljungberg et al., “Silent T1 mapping using the variable flip angle method with B1 correction,” Magn. Reson. Med., vol. 84, no. 2, pp. 813–824, 2020. 

[3] T. C. Wood et al., “Silent myelin-weighted magnetic resonance imaging [version 2; peer review: 2 approved , 2 approved with reservations],” Wellcome Open Res., vol. 5, no. 74, pp. 1–35, 2020. 

[4] N. L. Damestani et al., “Silent functional MRI for novel sound discrimination using the auditory oddball paradigm,” in Proc. Intl. Soc. Mag. Reson. Med 28, 2020, p. 3894. 

[5] F. Wiesinger et al., “PSST… Parameter mapping Swift and SilenT,” in Proc. Intl. Soc. Mag. Reson. Med 28, 2020. 

Figure 1: (Top)Enhanced MTR eMTR demonstrating strong white to gray matter contrast. (Bottom) Myelin weighted inverse inhomogeneous MTR showing strong myelin contrast. Reproduced from Ref [2], cropped from original figure.