Literature DB >> 26140371

Analysis of mcDESPOT- and CPMG-derived parameter estimates for two-component nonexchanging systems.

Mustapha Bouhrara1, David A Reiter1, Hasan Celik1, Kenneth W Fishbein1, Richard Kijowski2, Richard G Spencer1.   

Abstract

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. Magn Reson Med 75:2406-2420, 2016.
© 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Entities:  

Keywords:  CPMG; energy surface, accuracy; mcDESPOT; precision; quantitative MRI; sloppiness

Mesh:

Year:  2015        PMID: 26140371      PMCID: PMC5958911          DOI: 10.1002/mrm.25801

Source DB:  PubMed          Journal:  Magn Reson Med        ISSN: 0740-3194            Impact factor:   4.668


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