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Introduction to SQUAREMR

SQUAREMR stands for Simulations for QUAntifying RElaxation Magnetic Resonance constants. SQUAREMR is a new method that allows for extraction of quantitative tissue MR data from clinical pulse sequences with the aid of comprehensive, massively parallel MRI simulations of the Bloch equations on a large population of spins aiming to compute all possible outcomes of a pulse sequence for a range of physiologically relevant tissue relaxation times.

This novel method depends on extended and realistic MR simulations of already available clinical pulse sequences in order to build an extensive database of simulated signals identical (ideally) to the signals obtained from the MR scanner for the same experiment configuration. The recent publication in JCMR (Xanthis et al. JCMR 2015, 17:104) presented the concept of SQUAREMR whereas a MOLLI example was used in order to demonstrate the potential impact that this method may have in MR Relaxometry.

A CMR T1 mapping protocol was applied on three phantom setups and on twelve healthy volunteers demonstrating improvement of accuracy in phantom studies and consistent mean T1 values and consistent variance across the different MOLLI schemes in humans. Compared to conventional MOLLI post-processing, SQUAREMR showed high accuracy even for a MOLLI scheme of 5-0p-3, which is a MOLLI scheme with no pause between modified Look-Locker experiments.  Although the MOLLI scheme of 5-0p-3 is not clinically applicable, the accuracy that SQUAREMR demonstrated for this MOLLI scheme indicates potential value for myocardial tissue characterization within just 8 heart beats, even for tissues with long T1s. 

The utilization of multi-GPU technology allows simulations of realistic aspects of the MR experiment, such as incorporation of slice profile. In this study, approximately 100 spins were simulated across the slice thickness resulting in a total of approximately 64.000.000 simulations of the entire imaging pulse sequence and a total of approximately 600.000 database entries. The utilization of multi-GPU computer systems along with the technology advancements taking place on the GPU hardware suggest that this method has the potential to become a real-time routine on the MRI scanner in the future. Aside from that, SQUAREMR allows for correction of quantitative CMR data (e.g. MOLLI T1 maps) that have already been acquired by simulating the clinical pulse sequence that was used for the data acquisition.

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ACKNOWLEDGMENTS

This project is funded by the European Research Council (PIRG06-GA-2009-256569 FP7 MARIE CURIE IRG). Two NVIDIA Tesla C2070 GPU computing cards were donated from NVIDIA through the “Professor Partnership” program. The University of Thessaly funded hardware for this project. The United States National Library of Medicine (Bethesda, MD) for the Visible Human Project (VHP) dataset.