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Simulation-based quantification of native T1 and T2 of the myocardium using a modified MOLLI scheme and the importance of Magnetization Transfer

Quantitative cardiovascular Magnetic Resonance Imaging techniques are gaining wide acceptance within the MR community due to their potential to diagnose non-localized disease, guide therapy and improve patient outcome. During the last decade, there has been an increasing interest for developing new techniques that allow for simultaneous quantification of both T1 and T2 maps of myocardium. Newer studies demonstrated that the incorporation of MRI simulations could yield similar results to conventional mapping techniques in the myocardium. However, these simulation-based quantitative MR techniques usually compare the in-vivo T1 estimates against less accurate T1 techniques, whereas they present inconsistencies between simulation studies, phantom and in-vivo measurements. Moreover, these studies do not investigate the effect of Magnetization Transfer on the myocardial T1 and T2 estimates but are usually validated on phantoms where the MT effect is small.

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.

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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.