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We studied compartmentally specific characteristics of water diffusion in excised frog sciatic nerve by combining T1 or T2 selective acquisitions with pulse-gradient spin-echo (PGSE) diffusion weighting, with the specific objective of characterizing myelin water diffusion. Combining a PGSE with a Carr-Purcell-Meiboom-Gill (CPMG) acquisition provided apparent diffusion coefficients (ADCs) for each of the three T2 components found in nerve, including the short-lived component believed to be derived from myelin water. Double-inversion-recovery (DIR) preparation provided an alternate means of discriminating myelin water, and in combination with PGSE provided somewhat different measures of ADC. The DIR measures yielded myelin water ADCs of 0.37 microm2/ms (parallel to nerve) and 0.13 microm2/ms (perpendicular to nerve). These ADC estimates were postulated to be more accurate than those based on T2 discrimination, although the difference between the two findings is not clear.
Copyright 2006 Wiley-Liss, Inc.
Diffusion tensor tractography suffers from the effects of noise and partial volume averaging (PVA). For reliable reconstruction of fiber pathways, tracking algorithms that are robust to these artifacts are called for. To meet this need, the present study establishes a novel Bayesian regularization framework for fiber tracking that takes into account the effects of noise and PVA, thereby improving tracking accuracy and precision. With this framework, the propagation of a fiber path follows an optimal vector determined by Bayes decision rule; the probability functions involved are modeled on the basis of multivariate normal distributions of diffusion tensor elements, which allows the optimal solution with maximum a posteriori probability to be derived analytically. Parameters for the probability functions are estimated from the uncertainty of tensor elements and the variance among tensors within an oriented sampling volume weighted by fractional anisotropy. Experiments with Monte Carlo simulations, synthetic, and in vivo human diffusion tensor data demonstrate that this specialized scheme enhances the immunity of fiber tracking to noise and PVA, and hence enables fibers to be more faithfully reconstructed.
The theory of temporal diffusion spectra is reviewed. In contrast to q-space spectroscopy, which measures the displacement spectrum of spins in a spatial domain, the spectral density of the velocity correlation function (VCF) in the temporal domain is considered. It is demonstrated that casting diffusion in this domain may facilitate measurements of microscopic geometry and the decomposition of the diffusion signal into components due to disperse flow and restricted diffusion. An oscillating gradient (OG) method of diffusion spectroscopy was developed and implemented. Microscopic pore sizes, surface-to-volume ratios (S/Vs), and diffusion path tortuosities were extracted from model systems using this method. Cases are discussed in which this type of experiment may allow the characterization of pore geometry when spatial domain experiments fail. OGs may be combined with imaging sequences to map complex patterns of diffusion and flow. Moreover, scalar apparent diffusion coefficient (ADC) measurements in complex biological systems may be subtly dependent on specific pulse sequence parameters. Thus, scalar ADC measurements using gradient pulses with different frequency spectra may give different results. Conversely, the frequency dependence of motion-sensitizing gradient pulses may be exploited to deduce the origin of ADC changes.
The study of rotational and translational diffusion requires the measurement of both T2 and apparent diffusion coefficient (ADC), quantities that are typically measured in separate experiments. The exploitation of echoes generated via multiple coherence transfer pathways offers an opportunity for measuring T2 and ADC values simultaneously in a single experiment. A series of RF pulses can generate multiple echoes via different coherence pathways with each one being uniquely encoded. Here, we demonstrate one pulse sequence that uses an initial theta; RF pulse to generate three coherence orders (C = 0, -1, +1). In the particular version of the method discussed here only two are used (C = 0, +1). Each order is encoded with a different b value from which the ADC is derived. The coherence order echo C = 0 is refocused to quantify T2. The performance of the method--dubbed simultaneous measurement of ADC and relaxation time (SMART)--is demonstrated on a set of samples differing in T2 and ADC achieved by varying the relative volume fractions in mixtures of gadolinium-doped H2O and D2O. The regional SMART derived T2 and ADC agree well with those obtained with conventional double-spin-echo and pulsed gradient spin-echo methods.
To improve the accuracy of tissue structural and architectural characterization with diffusion tensor imaging, a novel smoothing technique is developed for reducing noise in diffusion tensor images. The technique extends the traditional anisotropic diffusion filtering method by allowing isotropic smoothing within homogeneous regions and anisotropic smoothing along structure boundaries. This is particularly useful for smoothing diffusion tensor images in which direction information contained in the tensor needs to be restored following noise corruption and preserved around tissue boundaries. The effectiveness of this technique is quantitatively studied with experiments on simulated and human in vivo diffusion tensor data. Illustrative results demonstrate that the anisotropic smoothing technique developed can significantly reduce the impact of noise on the direction as well as anisotropy measures of the diffusion tensor images.
Oscillating gradients were used to probe the diffusion-time/frequency dependence of water diffusion in the gray matter of normal and globally ischemic rat brain. In terms of a conventional definition of diffusion time, the oscillating gradient measurements provided the apparent diffusion coefficient (ADC) of water with diffusion times between 9.75 ms and 375 micros, an order of magnitude shorter than previously studied in vivo. Over this range, ADCs increased as much as 24% in vivo and 50% postmortem, depending on the nature of the oscillating gradient waveform used. Novel waveforms were employed to sample narrow frequency bands of the so-called diffusion spectrum. This spectral description of ADC includes the effects of restriction and/or flow, and is independent of experimental parameters, such as diffusion time. The results in rat brain were found to be consistent with restricted diffusion and the known micro-anatomy of gray matter. Differences between normal and postmortem data were consistent with an increase in water restriction and/or a decrease in flow, and tentatively suggest that physical changes following the onset of ischemia occur on a scale of about 2 microm, similar to a typical cellular dimension in gray matter.
Copyright 2003 Wiley-Liss, Inc.