Many MRS paradigms produce 2D spectral‐temporal datasets, including diffusion‐weighted, functional, and hyperpolarized and enriched (carbon‐13, deuterium) experiments. Conventionally, temporal parameters—such as T 2, T 1, or diffusion constants—are assessed by first fitting each spectrum independently and subsequently fitting a temporal model (1D fitting). We investigated whether simultaneously fitting the entire dataset using a single spectral‐temporal model (2D fitting) would improve the precision of the relevant temporal parameter.
We derived a Cramer Rao lower bound for the temporal parameters for both 1D and 2D approaches for 2 experiments: a multi‐echo experiment designed to estimate metabolite T 2s, and a functional MRS experiment designed to estimate fractional change ( ) in metabolite concentrations. We investigated the dependence of the relative standard deviation (SD) of T 2 in multi‐echo and in functional MRS.
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