Rapid mapping of flow velocity using a new PARSE method

Snapshot MR technique to measure OEF using rapid frequency mapping

Magnetic resonance (MR)-based oxygen extraction fraction (OEF) measurement techniques that use blood oxygen level-dependent (BOLD)-based approaches require the measurement of the R2' decay rate and deoxygenated blood volume to derive the local oxygen saturation in vivo. We describe here a novel approach to measure OEF using rapid local frequency mapping. By modeling the MR decay process in the static dephasing regime as two separate dissipative and oscillatory effects, we calculate the OEF from local frequencies measured across the brain by assuming that the biophysical mechanisms causing OEF-related frequency changes can be determined from the oscillatory effects. The Parameter Assessment by Retrieval from Signal Encoding (PARSE) technique was used to acquire the local frequency change maps. The PARSE images were taken on 11 normal volunteers, and 1 patient exhibiting hemodynamic stress. The mean MR-OEF in 11 normal subjects was 36.66±7.82%, in agreement with positron emission tomography (PET) literature. In regions of hemodynamic stress induced by vascular steal, OEF exhibits the predicted focal increases. These preliminary results show that it is possible to measure OEF using a rapid frequency mapping technique. Such a technique has numerous advantages including speed of acquisition, is noninvasive, and has sufficient spatial and temporal resolution.

Basic properties of SS-PARSE parameter estimates

Single shot parameter assessment by retrieval from signal encoding (SS-PARSE) is a recently introduced method to obtain quantitative parameter maps from a single-shot (typically 65 ms) magnetic resonance imaging (MRI) signal. Because it explicitly models local magnetization decay and phase evolution occurring during the signal 1) it can provide quantitative estimates of local transverse magnetization magnitude and phase, frequency, and relaxation rate and 2) it is free of geometric distortion or blurring due to field nonuniformities within the tissues. These properties promise to be advantageous in functional brain MRI (fMRI) and other dynamic imaging applications. In this paper, the basic phenomena underlying the performance of SS-PARSE in practice are discussed. Basic sources of bias errors in the parameter estimates are discussed, and performance of the method is characterized in terms of parameter estimates from simulation, experimental phantoms, and in vivo studies. Characteristics of the sum-of-square-error cost function and the iterative search algorithm are discussed, and their relative roles in determining estimation accuracy are described. Practical guidelines for use of the method are presented and discussed. In vivo parameter maps are also presented.

Validation of V-SS-PARSE for single-shot flow measurement

As a variant of Single-Shot Parameter Assessment by Retrieval from Signal Encoding, Velocity Single-Shot Parameter Assessment by Retrieval from Signal Encoding, a single-shot imaging method, has been developed to realize fast and straightforward flow quantification by solving inverse problems. A robust signal model, including its local magnetization and its phase evolution during signaling (resulting in a more precise representation of the sampled signal) is described here. Magnitude, velocity, relaxation rate and frequency information can be retrieved without any extra reference image acquisitions, as demonstrated by phantom studies. In the presence of stationary background, retrieved magnitude maps and velocity maps show results comparable to those obtained by phase-contrast methods (r>.99, P=.005), even with brief single-shot 70-ms acquisition.