Quantitative diffusion-tensor anisotropy brain MR imaging: normative human data and anatomic analysis.

PURPOSE: To obtain normative human cerebral data and evaluate the anatomic information in quantitative diffusion anisotropy magnetic resonance (MR) imaging. MATERIALS AND METHODS: Quantitative diffusion anisotropy MR images were obtained in 13 healthy adults by using single-shot echo-planar MR imaging and a combination of tetrahedral and orthogonal gradient encoding (whole-brain coverage in about 1 minute). White matter (WM) anatomy was assessed at visual inspection, and values were measured in various brain regions. Different anisotropy measures, including total anisotropy (A sigma), were compared on the basis of information content, rotational invariance, and susceptibility to noise. Partial volume and noise effects were simulated. RESULTS: Anisotropy MR images depicted WM features not typically seen on conventional MR images (e.g., external capsule, thalamic substructures, basal ganglia, occipital WM, thickness of the internal capsule). Statistically significant anisotropy differences occurred across brain regions, which were reproducible within and across subjects. A sigma was highest in commissural WM and progressively lower in projection and association WM. This order paralleled that of known resistance to spread of vasogenic edema, which suggested that anisotropy may be sensitive to WM histologic structure. Gray matter (GM) A sigma data were consistent with zero anisotropy, and partial volume WM-GM effects were approximately linear. A sigma image quality could be effectively improved by means of averaging. CONCLUSION: Quantitative diffusion anisotropy images can be obtained rapidly and demonstrate subtle WM anatomy. Different histologic types of WM have significant and reproducible anisotropy differences.

Normal brain in human newborns: apparent diffusion coefficient and diffusion anisotropy measured by using diffusion tensor MR imaging.

PURPOSE: To establish quantitative standards for the directionally averaged water apparent diffusion coefficient (D) and quantitative diffusion anisotropy (A sigma) of normal brains in newborns by using diffusion tensor magnetic resonance (MR) imaging. MATERIALS AND METHODS: Diffusion tensor MR imaging was performed during the first 36 hours of life in 22 newborns (gestational age range, 31-41 weeks). Values of D and A sigma were measured in regions of interest chosen in the cortical gray matter, centrum semiovale, caudate nuclei, lentiform nuclei, thalami, internal capsules, and cerebellar hemispheres. RESULTS: The D values in the gray and white matter in newborns are considerably higher than those in adults. There is a striking correlation between gestational age and D, with D decreasing as gestational age increases. The A sigma values in the white matter in newborns are lower than those in adults. Values of A sigma show statistically significant correlations with gestational age only in the white matter of the centrum semiovale, in which A sigma values increase sharply near term. CONCLUSION: The D values primarily reflect overall brain water content. The A sigma values are more sensitive to tissue microstructure (e.g., white matter packing and myelination). The D and A sigma images reveal information and not apparent on T1- and T2-weighted images.

Diffusion MRI: precision, accuracy and flow effects.

After a decade of evolution and application of diffusion imaging, a large body of literature has been accumulated. It is in this context that the accuracy and precision of diffusion-weighted and quantitative diffusion MRI are reviewed. The emphasis of the review is on practical methods for clinical human imaging, particularly in the brain. The requirements for accuracy and precision are reviewed for various clinical and basic science applications. The methods of measuring and calculating diffusion effects with MRI are reviewed. The pulse gradient spin echo (PGSE) methods are emphasized as these methods are used most commonly in the clinical setting. Processing of PGSE data is reviewed. Various PGSE encoding schemes are also reviewed in terms of the accuracy and precision of isotropic and anisotropic diffusion measurements. The broad range of factors impacting the accuracy of the PGSE methods and other encoding schemes is then considered. Firstly, system inaccuracies such as background imaging gradients, gradient linearity, refocusing RF pulses, eddy currents, image misregistration, noise and dynamic range are considered. A second class of inaccuracies is contributed by the bulk effects of the imaged object, and include sample background gradients, subject motion of cerebrospinal fluid and organs, and aperiodic organ motion. A final category of potential inaccuracies is classified as being contributed by microscopic, biophysical tissue properties and include partial volume effects, anisotropy, restriction, diffusion distance, compartmentation, exchange, multiexponential diffusion decay, T2 weighting and microvascular perfusion. Finally, the application of diffusion methods to studies of blood flow in the microvasculature (i.e. the arterioles, capillaries and venules) are reviewed in detail, particularly in terms of feasibility and the stringent accuracy and precision requirements. Recent provocative studies examining the use of PGSE approaches to suppress microvascular signals in brain functional MRI (fMRI) are also reviewed.

Automated method for characterization of diastolic transmitral Doppler velocity contours: late atrial filling.

We develop an automated method of characterizing the late atrial filling phase of diastole by fitting a kinematic model for diastolic filling to the clinical Doppler A-wave contour. The result is a set of model parameters which completely characterizes the contour. We have previously derived a parameterized diastolic filling (PDF) model, which predicts the time-dependent transmitral blood flow velocity obtained by Doppler echocardiography. An automated method to determine the PDF model parameters for early rapid filling from the clinical Doppler E-wave has also been developed and validated. The method consists of digitizing the acoustic Doppler waveform, recreating the Doppler velocity profile, extracting the maximum velocity envelope, and fitting the PDF model for early filling to the envelope. In the current work, we apply the same general approach for PDF parameter determination for the late atrial filling phase of diastole. To assess the presence and significance of near-degeneracies in the model parameter set, numerical experiments (consisting of fitting the model to a model-generated contour to which Gaussian noise was added) were performed. These revealed a two-dimensional degeneracy in four-dimensional parameter space which could be removed by using two kinematic simplifications: critical damping and resonant forcing. We show that these degeneracy-eliminating approximations do not limit the ability of the model to predict clinical A-wave contours.