Parsing local signal evolution directly from a single-shot MRI signal: a new approach for fMRI.

In this work a new single-shot MRI method, single-shot parameter assessment by retrieval from signal encoding (SS-PARSE), is introduced. This method abandons a fundamental simplifying assumption that is used in conventional MRI methods. Established MRI methods implicitly assume that the local intrinsic signal does not change its amplitude or phase during signal acquisition, even though these changes may be substantial, especially during the relatively long signals used in single-shot image acquisitions. SS-PARSE, on the other hand, acknowledges local decay and phase evolution, and models each signal datum as a sample from (k,t)-space rather than k-space. Because of this more accurate signal model, SS-PARSE promises improved performance in terms of accuracy and robustness, but requires more intensive reconstruction computations. The theoretical properties of the method are discussed, and simulation results are presented that demonstrate more robust and accurate measurements of relaxation rate changes associated with brain activation in functional MRI (fMRI), freedom from geometric errors due to off-resonance frequencies, and better tolerance of the large susceptibility gradients that occur naturally in parts of the brain. In addition, this technique has the potential to assess nonexponential relaxation behavior during a single-shot signal.