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Purpose To compare the reliability and stability of the multicomponent-driven equilibrium single pulse observation of T1 and T2 (mcDESPOT) and Carl-Purcell-Meiboom-Gill (CPMG) approaches to parameter estimation. Methods The stability and reliability of mcDESPOT and CPMG-derived parameter estimates were compared through examination of energy surfaces, evaluation of model sloppiness, and Monte Carlo simulations. Comparisons were performed on an equal time basis and assuming a two-component system. Parameter estimation bias, reflecting accuracy, and dispersion, reflecting precision, were derived for a range of signal-to-noise ratios (SNRs) and relaxation parameters. Results The energy surfaces for parameters incorporated into the mcDESPOT signal model exhibit flatness, a complex structure of local minima, and instability to noise to a much greater extent than the corresponding surfaces for CPMG. Although both mcDESPOT and CPMG performed well at high SNR, the CPMG approach yielded parameter estimates of considerably greater accuracy and precision at lower SNR. Conclusion mcDESPOT and CPMG both permit high-quality parameter estimates under SNR that are clinically achievable under many circumstances, depending upon available hardware and resolution and acquisition time constraints. At moderate to high SNR, the mcDESPOT approach incorporating two-step phase increments can yield accurate parameter estimates while providing values for longitudinal relaxation times that are not available through CPMG. However, at low SNR, the CPMG approach is more stable and provides superior parameter estimates.

Purpose Previous work has evaluated the quality of different analytic methods for extracting relaxation times from magnitude imaging data exhibiting Rician noise. However, biexponential analysis of relaxation in tissue, including cartilage, and materials, is of increasing interest. We therefore analyzed biexponential transverse relaxation decay in the presence of Rician noise and assessed the accuracy and precision of several approaches to determining component fractions and apparent transverse relaxation times. Methods Comparisons of four different voxel-by-voxel fitting methods were performed using Monte Carlo simulations, and phantom and ex-vivo bovine nasal cartilage (BNC) experiments. In each case, preclinical and clinical imaging field strengths of 7T and 3T, respectively, and parameters, were investigated across a range of signal-to-noise ratios (SNR). Results were compared to Cramér-Rao lower bound calculations. Results As expected, at high SNR, all methods performed well. At lower SNR, fits explicitly incorporating the analytic form of the Rician noise maintained performance. The much more efficient correction scheme of Gudbjartsson and Patz performed almost as well in many cases. Ex-vivo experiments on phantoms and BNC were consistent with simulation results. Conclusion Explicit incorporation of Rician noise greatly improves accuracy and precision in the analysis of biexponential transverse decay data.