Abstract #1015

Simulating MOLLI T1 mapping signals to remove variability caused by heart rate

Margot Roeth^1,2, Martin Craig^1,2, Dorothee Auer^1,2,3, Stamatios Sotiropoulos^1,2,3, Ali- Reza Mohammadi-Nejad^1,2,3, Eleanor Cox^1,2, and Sue Francis^1,2

¹SPMIC, University of Nottingham, Nottingham, United Kingdom, ²NIHR Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS trust and the University of Nottingham, Nottingham, United Kingdom, ³Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, United Kingdom

Synopsis

Keywords: Kidney, Relaxometry, Aging, Simulations

Motivation: To remove the heart rate (HR) dependence of abdominal ShMOLLI T₁ measures in the UK Biobank (UKBB) for improved accuracy of disease detection and organ age prediction.

Goal(s): To generate a Look-Up Table (LUT) to HR-correct abdominal ShMOLLI T₁ UKBB data.

Approach: Bloch simulation of UKBB ShMOLLI schemes to create a LUT for HR-correction of abdominal T₁ values. To study the influence of primary disease, and healthy kidney ageing on HR-corrected data.

Results: Simulations show HR-correction is important for kidney medulla and corticomedullary difference (CMD) in T₁. Kidney cortex T₁ and CMD in T₁ correlate with age.

Impact: Errors arise in measured ShMOLLI T₁ data when collected with ECG-triggering rather than with a fixed spacing. Removing the heart rate effect allows better comparison between health and disease groups, and to determine effects of ageing on kidney T₁ measures.

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