Fast quantitative parameter maps without fitting: Integration yields accurate mono‐exponential signal decay rates. Issue 6 (30th October 2017) - Song, Ruitian; Loeffler, Ralf B.; Holtrop, Joseph L.; McCarville, M. Beth; Hankins, Jane S.; Hillenbrand, Claudia M.
Abstract : Purpose: To develop a computationally fast and accurate algorithm for mono‐exponential signal modelling and validate the new technique in the context of R 2 * mapping for iron overload assessment. Methods: An algorithm is introduced that directly calculates R 2 * values from a series of images based on integration of the mono‐exponential signal decay curve. The algorithm is fast, because fitting is avoided and only arithmetic computations without iterations are applied. Precision and accuracy of the method is determined in comparison to the conventional log‐linear (LL), nonlinear least‐squares‐based Levenberg–Marquardt (NLM), and squared nonlinear Levenberg–Marquardt (SQNLM) methods, which rely on iterative curve fitting. Results: In simulations, the signal integration based method consistently had the same or better accuracy than the LL, NLM, and SQNLM algorithms for R 2 * values ranging from 50 s −1 to 1200 s −1 . In phantoms and in vivo (12 participants), this method was robust over a wide range of R 2 * values and signal‐to‐noise ratios. Computation times were approximately 100, 1460, and 930 times faster than those of the LL, NLM, and SQNLM methods, respectively. Conclusions: The fast signal integration method accurately calculates R 2 * maps. It has the potential to replace conventional, mono‐exponential fitting methods for quantitative MRI such as R 2 * parameter mapping. Magn Reson Med 79:2978–2985, 2018. © 2017 International Society for Magnetic Resonance in Medicine.