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Abstract #2108

Drift-insensitive and motion-robust relaxometry using N-periodic SSFP

Coraline Beitone1, Krithika Balaji1, Karla L Miller2, Neal K Bangerter1,3, and Peter J Lally1,4
1Bioengineering, Imperial College London, London, United Kingdom, 2Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom, 3Electrical and Computer Engineering, Boise State University, Boise, ID, United States, 4Centre for Care Research and Technology, UK Dementia Research Institute, London, United Kingdom

Synopsis

Keywords: Quantitative Imaging, Relaxometry, bSSFP

Motivation: Relaxometry techniques based on RF-phase cycled bSSFP are highly SNR efficient but prone to bias due to their sensitivity to unwanted variation over the course of an experiment.

Goal(s): Propose an alternative short-TR relaxometry technique that is motion-robust and drift-insensitive.

Approach: An N-periodic SSFP acquisition is used to establish a single pseudo-steady-state, and the magnetisation behaviour is fit to an analytical model to yield tissue relaxivity estimates. This is compared to an established approach

Results: The proposed approach shows low bias in simulations across a range of realistic experimental conditions, and its performance is comparable to existing bSSFP approaches in vivo.

Impact: We introduce a novel and flexible approach for SSFP-based relaxometry, which shows advantages over existing approaches in its robustness to slow variations over an experiment.

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Keywords