Parallel simulations for QUAntifying RElaxation magnetic resonance constants (SQUAREMR): an example towards accurate...

T1 mapping is widely used today in CMR, however, it underestimates true T1 values and its measurement error is influenced by several acquisition parameters. The purpose of this study was the extraction of accurate T1 data through the utilization of comprehensive, parallel Simulations for QUAntifying RElaxation Magnetic Resonance constants (SQUAREMR) of the MOLLI pulse sequence on a large population of spins with physiologically relevant tissue relaxation constants.

A CMR protocol consisting of different MOLLI schemes was performed on phantoms and healthy human volunteers. For every MOLLI experiment, the identical pulse sequence was simulated for a large range of physiological combinations of relaxation constants, resulting in a database of all possible outcomes. The unknown relaxation constants were then determined by finding the simulated signals in the database that produced the least squared difference to the measured signal intensities.

SQUAREMR demonstrated improvement of accuracy in phantom studies and consistent mean T1 values and consistent variance across the different MOLLI schemes in humans. This was true even for tissues with long T1s and MOLLI schemes with no pause between modified-Look-Locker experiments.

SQUAREMR enables quantification of T1 data obtained by existing clinical pulse sequences. SQUAREMR allows for correction of quantitative CMR data that have already been acquired whereas it is expected that SQUAREMR may improve data consistency and advance quantitative MR across imaging centers, vendors and experimental configurations. While this study is focused on a MOLLI-based T1-mapping technique, it could however be extended in other types of quantitative MRI throughout the body.