Cloud GPU-based simulations for SQUAREMR.

Quantitative Magnetic Resonance Imaging (MRI) is a research tool, used more and more in clinical practice, as it provides objective information with respect to the tissues being imaged. Pixel-wise T quantification (T mapping) of the myocardium is one such application with diagnostic significance. A number of mapping sequences have been developed for myocardial T mapping with a wide range in terms of measurement accuracy and precision.

Validation of T1 and T2 algorithms for quantitative MRI: performance by a vendor-independent software.

Background: Determination of the relaxation time constants T1 and T2 with quantitative magnetic resonance imaging is increasingly used for both research and clinical practice. Recently, groups have been formed within the Society of Cardiovascular Magnetic Resonance to address issues with relaxometry. However, so far they have avoided specific recommendations on methodology due to lack of consensus and current evolving research.

Parallel simulations for QUAntifying RElaxation magnetic resonance constants (SQUAREMR): an example towards accurate MOLLI T1 measurements.

Background: 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.

Methods: A CMR protocol consisting of different MOLLI schemes was performed on phantoms and healthy human volunteers.