| Summary: | A statistical analysis of the magnetic resonance imaging-based mcDESPOT method for characterizing two exchanging water proton pools--a seven-dimensional problem that fits to multiple flip angle measurements of both spoiled and refocused gradient echoes--is presented. Theoretical calculations of the Cramer-Rao lower bounds of the variance of fitted model parameters were made using a variety of model system parameters, meant to mimic those expected in human white matter. The results, validated by Monte Carlo simulations, indicated that mcDESPOT signals acquired at feasibly attainable signal to noise ratios cannot provide parameter estimates with useful levels of precision. Precision can be greatly improved by constraining solutions with a priori model information, although this will generally lead to biased parameter estimates with less specificity. These results indicate that previous, apparently successful applications of mcDESPOT to human white matter may have used data fitting methods that implicitly constrained parameter solutions, or that the two-pool model of white matter may not be sufficient to describe the observed water proton signal in mcDESPOT acquisitions. In either case, mcDESPOT-derived estimates of two-pool model parameters cannot yet be unambiguously related to specific tissue characteristics.
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