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Abstract #4559

Precision in T1-Mapping and Estimation of Quality Maps

Peter Kellman1, Andrew E. Arai1, Hui Xue2

1NHLBI, NIH, Bethesda, MD, United States; 2Siemens Corporate Research, Princeton, NJ, United States

The sensitivity for detecting abnormal elevation of T1 is limited by the precision of T1 estimates, which is a function of the number and timing of measurements along the T1-recovery curve, the signal-to-noise ratio, tissue T1, and the method of fitting. It is proposed to produce a map calibrated in T1 units that represented the standard deviation (SD) of the T1 estimate, by transforming the SD of residual fitting error into the SD of the estimated parameters. Estimate of the T1 parameter error based on fit residuals is derived analytically, and validated by Monte-Carlo simulation. In-vivo examples demonstrate potential utility.

Keywords

abnormal abnormality abnormally absolute achieved although analytically apparent approaches approximated assumed calibrated chem circles close coil comparing compute confidence constant contrast corporate correction correspondence corresponds cost covariance curve decreased derivatives derived desired detect detecting deviation deviations diffuse disease distribution dots drop dropped elements elevated elevation equal error estimation evaluated example examples experimental extension extracellular fitting focal formulation fraction function generate graphed illustrates improve in vivo independent indicating influence intensities intensity inversion lateral limited locker longest look magnitude mapping maps matrix measured measuring median model myocardium namely noise note partial performance peter phantom pixel potential precision predicted processes produce producing proposed protocol quality quantifying readily readout reconstructed reconstruction recovery repeated represented represents residual residuals sampling scaling sensitivity septum significance simulation square statistical steady subject surface timing tissue transforming translated trials units utility validated validation variables variation various volume wall whereas written