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Longitudinal relaxation of brain water (1)H magnetization in mammalian brain in vivo is typically analyzed on a per-voxel basis using a monoexponential model, thereby assigning a single relaxation time constant to all (1)H magnetization within a given voxel. This approach was tested by obtaining inversion recovery (IR) data from gray matter of rats at 64 exponentially spaced recovery times. Using Bayesian probability for model selection, brain water data were best represented by a biexponential function characterized by fast and slow relaxation components. At 4.7T, the amplitude fraction of the rapidly relaxing component is 3.4% +/- 0.7% with a rate constant of 44 +/- 12 s(-1) (mean +/- SD; 174 voxels from four rats). The rate constant of the slow relaxing component is 0.66 +/- 0.04 s(-1). At 11.7T, the corresponding values are 6.9% +/- 0.9%, 19 +/- 5 s(-1), and 0.48 +/- 0.02 s(-1) (151 voxels from four rats). Several putative mechanisms for biexponential relaxation behavior were evaluated, and magnetization transfer (MT) between bulk water protons and nonaqueous protons was determined to be the source of biexponential longitudinal relaxation. MR methods requiring accurate quantification of longitudinal relaxation may need to take this effect explicitly into account.

Diffusion-based magnetic resonance imaging holds the potential to non-invasively demonstrate cellular-scale structural properties of brain. This method was applied to fixed baboon brains ranging from 90 to 185 days gestational age to characterize the changes in diffusion properties associated with brain development. Within each image voxel, a probability-theory-based approach was employed to choose, from a group of analytic equations, the one that best expressed water displacements. The resulting expressions contain eight or fewer adjustable parameters, indicating that relatively simple expressions are sufficient to obtain a complete description of the diffusion MRI signal in developing brain. The measured diffusion parameters changed systematically with gestational age, reflecting the rich underlying microstructural changes that take place during this developmental period. These changes closely parallel those of live, developing human brain. The information obtained from this primate model of cerebral microstructure is directly applicable to studies of human development.

The apparent diffusion coefficient (ADC) of Na(+) was determined in live rat brain. The brain extracellular-to-intracellular Na(+) content ratio is approximately 8:2, which is the inverse of that for water in these spaces. Consequently, the ADC of Na(+) is primarily affected by motion in the extracellular space, and Na(+) can be viewed as a reporter molecule for motion in that space. Likewise, water ADC is dominated by intracellular motion. The brain Na(+) ADC was 1.15 +/- 0.09 microm(2)/ms, which is 61% of the aqueous Na(+) free diffusion coefficient (D(free)) at 37 degrees C (1.9 microm(2)/ms), while the ADC for brain water is 28% of the water D(free) at 37 degrees C (3 microm(2)/ms). This suggests that the ADC of molecular species within the extracellular space is roughly twofold that within the intracellular space. In postmortem brain, both Na(+) and water decrease to 17% of the respective D(free) values. These results are consistent with Na(+) and water ADC values sharing the same biophysical determinants in postmortem brain. The observed difference between Na(+) and water ADC/D(free) ratios in living brain tissue may be attributable to the extracellular environment hindering molecular displacements twofold less than the intracellular environment., (Copyright 2005 Wiley-Liss, Inc.)

A general statistical model that can describe a rather large number of experimental results related to the structure of the diffusion-attenuated MR signal in biological systems is introduced. The theoretical framework relies on a phenomenological model that introduces a distribution function for tissue apparent diffusion coefficients (ADC). It is shown that at least two parameters--the position of distribution maxima (ADC) and the distribution width (sigma)--are needed to describe the MR signal in most regions of a human brain. A substantial distribution width, on the order of 36% of the ADC, was found for practically all brain regions examined. This method of modeling the MR diffusion measurement allows determination of an intrinsic tissue-specific ADC for a given diffusion time independent of the strength of diffusion sensitizing gradients. The model accounts for the previously found biexponential behavior of the diffusion-attenuated MR signal in CNS., (Copyright 2003 Wiley-Liss, Inc.)

This report describes the measurement of water preexchange lifetimes and intra/extracellular content in intact, functioning mammalian brain. Intra- and extracellular water magnetic resonance (MR) signals from rat brain in vivo were quantitatively resolved in the longitudinal relaxation domain following administration of an MR relaxation agent into the extracellular space. The estimated intracellular water content fraction was 81% +/- 8%, and the intra- to extracellular exchange rate constant was 1.81 +/- 0.89 s(-1) (mean +/- SD, N = 9), corresponding to an intracellular water preexchange lifetime of approximately 550 ms. These results provide a temporal framework for anticipating the water exchange regime (fast, intermediate, or slow) underlying a variety of compartment-sensitive measurements. The method also supplies a means by which to evaluate membrane water permeability and intra/extracellular water content serially in intact tissue. The data are obtained in an imaging mode that permits detection of regional variations in these parameters., (Copyright 2003 Wiley-Liss, Inc.)

Diffusion imaging aims to non-invasively characterize the anatomy and integrity of the brain's white matter fibers. We evaluated the accuracy and reliability of commonly used diffusion imaging methods as a function of data quantity and analysis method, using both simulations and highly sampled individual-specific data (927-1442 diffusion weighted images [DWIs] per individual). Diffusion imaging methods that allow for crossing fibers (FSL's BedpostX [BPX], DSI Studio's Constant Solid Angle Q-Ball Imaging [CSA-QBI], MRtrix3's Constrained Spherical Deconvolution [CSD]) estimated excess fibers when insufficient data were present and/or when the data did not match the model priors. To reduce such overfitting, we developed a novel Bayesian Multi-tensor Model-selection (BaMM) method and applied it to the popular ball-and-stick model used in BedpostX within the FSL software package. BaMM was robust to overfitting and showed high reliability and the relatively best crossing-fiber accuracy with increasing amounts of diffusion data. Thus, sufficient data and an overfitting resistant analysis method enhance precision diffusion imaging. For potential clinical applications of diffusion imaging, such as neurosurgical planning and deep brain stimulation (DBS), the quantities of data required to achieve diffusion imaging reliability are lower than those needed for functional MRI.