In vivo three-dimensional reconstruction of rat brain axonal projections by diffusion tensor imaging

Validation of diffusion tensor magnetic resonance axonal fiber imaging with registered manganese-enhanced optic tracts

Noninvasive mapping of white matter tracts using diffusion tensor magnetic resonance imaging (DTMRI) is potentially useful in revealing anatomical connectivity in the human brain. However, a gold standard for validating DTMRI in defining axonal fiber orientation is still lacking. This study presents the first validation of the principal eigenvector of the diffusion tensor in defining axonal fiber orientation by superimposing DTMRI with manganese-enhanced MRI of optic tracts. A rat model was developed in which optic tracts were enhanced by manganese ions. Manganese ion (Mn(2+)) is a potent T1-shortening agent and can be uptaken and transported actively along the axon. Based on this property, we obtained enhanced optic tracts with a T1-weighted spin-echo sequence 10 h after intravitreal injection of Mn(2+). The images were compared with DTMRI acquired with exact spatial registration. Deviation angles between tangential vectors of the enhanced tracts and the principal eigenvectors of the diffusion tensor were then computed pixel by pixel. We found that under signal-to-noise (SNR) of 30, the variance of deviation angles was (13.27 degrees). In addition, the dependence of this variance on SNR obeys stochastic behavior if SNR is greater than 10. Based on this relation, we estimated that an rms deviation of less than 10 degrees could be achieved with DTMRI when SNR is 40 or greater. In conclusion, our method bypasses technical difficulties in conventional histological approach and provides an in vivo gold standard for validating DTMRI in mapping white matter tracts.

Diffusion tensor imaging and axonal tracking in the human brainstem

Diffusion tensor MRI was used to demonstrate in vivo anatomical mapping of brainstem axonal connections. It was possible to identify the corticospinal tract (CST), medial lemniscus, and the superior, medial, and inferior cerebellar peduncles. In addition, the cerebral peduncle could be subparcellated into component tracts, namely, the frontopontine tract, the CST, and the temporo-/parieto-/occipitopontine tract. Anatomical landmarks and tracking thresholds were established for each fiber and, using these standards, reproducibility of automated tracking as assessed by intra- and interrater reliability was found to be high (kappa > 0.82). Reconstructed fibers corresponded well to existing anatomical knowledge, validating the tracking. Information on the location of individual tracts was coregistered with quantitative MRI maps to automatically measure MRI parameters on a tract-by-tract basis. The results reveal that each tract has a unique spatial signature in terms of water relaxation and diffusion anisotropy.

Diffusion tensor imaging of the developing mouse brain

It is shown that diffusion tensor MR imaging (DTI) can discretely delineate the microstructure of white matter and gray matter in embryonic and early postnatal mouse brains based on the existence and orientation of ordered structures. This order was found not only in white matter but also in the cortical plate and the periventricular zone, which are precursors of the cerebral cortex. This DTI-based information could be used to accomplish the automated spatial definition of the cortical plate and various axonal tracts. The DTI studies also revealed a characteristic evolution of diffusion anisotropy in the cortex of the developing brain. This ability to detect changes in the organization of the brain during development will greatly enhance morphological studies of transgenic and knockout models of cortical dysfunction. Magn Reson Med 46:18-23, 2001.

Single-shot diffusion trace (1)H NMR spectroscopy

Ignoring diffusion anisotropy can severely hamper the quantitative determination of water and metabolite diffusion in complex tissues. The measurement of the trace of the diffusion tensor provides unambiguous and rotationally invariant ADC values, but usually requires three separate experiments. A single-shot technique developed earlier, originally designed for diffusion trace MR imaging (Mori and van Zijl, Magn Reson Med 1995;33:41-52), was improved and adapted for diffusion trace MR spectroscopy. A double spin-echo pulse sequence was incorporated with four pairs of bipolar gradients with specific predetermined relative signs in each of the three orthogonal directions. The combination of gradient directions leads to cancellation of all off-diagonal tensor elements while constructively adding the diagonal elements. Furthermore, the pulse scheme provides complete compensation for cross-terms between static magnetic field gradients and the applied diffusion gradients, while simultaneously avoiding cross-terms with localization gradients. The sequence was tested at 4.7 T in vivo on rat brain for MRI and on rat skeletal muscle and brain for MRS. It is shown that the average ADC as determined from the measurement of the ADCs in the three orthogonal directions is in close agreement with the ADC obtained along the trace of the diffusion tensor in a single acquisition, for both water and metabolite diffusion. The large differences in water and metabolite diffusion coefficients as measured in the individual orthogonal directions illustrate the need for diffusion trace measurements when accurate and rotationally invariant diffusion quantitation is required. The pulse scheme presented here may be applied for such purposes in MRS and MRI studies.

Apparent diffusion tensor measurements in myelin-deficient rat spinal cords

The apparent diffusion tensor (ADT) was measured in excised and fixed spinal cords from myelin-deficient (md) rats and age-matched controls. These data were used to obtain the principal diffusivities of the ADT, and also the scalar invariant parameters _D (averaged principal diffusivity) and A(sigma) (anisotropy index) for four white matter and two gray matter regions. The results for white matter regions showed that the principal diffusivities were significantly higher for md animals, and while the _D was increased in tissue from md animals, the A(sigma) was found to be decreased. Grey matter _D was measured to be between those of white matter from control and md animals, and the A(sigma) was much smaller than that of white matter from both sets of animals, indicating that diffusion in md white matter is more anisotropic than in gray matter. The results show that while myelination is not a prerequisite for diffusion anisotropy, it does influence the magnitude of the observed anisotropy. Magn Reson Med 45:191-195, 2001.

Superresolution in MRI: application to human white matter fiber tract visualization by diffusion tensor imaging

A superresolution algorithm was applied to spatially shifted, single-shot, diffusion-weighted brain images to generate a new image with increased spatial resolution. Detailed two-dimensional white matter fiber tract maps of the human brain resulting from application of the technique are shown. The method provides a new means for improving the resolution in cases where k-space segmentation is difficult to implement. Diffusion-weighted imaging and diffusion tensor imaging in vivo stand to benefit in particular because the necessity of obtaining high-resolution scans is matched by the difficulty in obtaining them. Magn Reson Med 45:29-35, 2001.

Condition number as a measure of noise performance of diffusion tensor data acquisition schemes with MRI

Diffusion tensor mapping with MRI can noninvasively track neural connectivity and has great potential for neural scientific research and clinical applications. For each diffusion tensor imaging (DTI) data acquisition scheme, the diffusion tensor is related to the measured apparent diffusion coefficients (ADC) by a transformation matrix. With theoretical analysis we demonstrate that the noise performance of a DTI scheme is dependent on the condition number of the transformation matrix. To test the theoretical framework, we compared the noise performances of different DTI schemes using Monte-Carlo computer simulations and experimental DTI measurements. Both the simulation and the experimental results confirmed that the noise performances of different DTI schemes are significantly correlated with the condition number of the associated transformation matrices. We therefore applied numerical algorithms to optimize a DTI scheme by minimizing the condition number, hence improving the robustness to experimental noise. In the determination of anisotropic diffusion tensors with different orientations, MRI data acquisitions using a single optimum b value based on the mean diffusivity can produce ADC maps with regional differences in noise level. This will give rise to rotational variances of eigenvalues and anisotropy when diffusion tensor mapping is performed using a DTI scheme with a limited number of diffusion-weighting gradient directions. To reduce this type of artifact, a DTI scheme with not only a small condition number but also a large number of evenly distributed diffusion-weighting gradients in 3D is preferable.

Regularization of diffusion-based direction maps for the tracking of brain white matter fascicles

Magnetic resonance diffusion tensor imaging (DTI) provides information about fiber local directions in brain white matter. This paper addresses inference of the connectivity induced by fascicles made up of numerous fibers from such diffusion data. The usual fascicle tracking idea, which consists of following locally the direction of highest diffusion, is prone to erroneous forks because of problems induced by fiber crossing. In this paper, this difficulty is partly overcomed by the use of a priori knowledge of the low curvature of most of the fascicles. This knowledge is embedded in a model of the bending energy of a spaghetti plate representation of the white matter used to compute a regularized fascicle direction map. A new tracking algorithm is then proposed to highlight putative fascicle trajectories from this direction map. This algorithm takes into account potential fan shaped junctions between fascicles. A study of the tracking behavior according to the influence given to the a priori knowledge is proposed and concrete tracking results obtained with in vivo human brain data are illustrated. These results include putative trajectories of some pyramidal, commissural, and various association fibers.

Biochemical, cellular, and molecular mechanisms in the evolution of secondary damage after severe traumatic brain injury in infants and children: Lessons learned from the bedside

OBJECTIVE: To present a state-of-the-art review of mechanisms of secondary injury in the evolution of damage after severe traumatic brain injury in infants and children. DATA SOURCES: We reviewed 152 peer-reviewed publications, 15 abstracts and proceedings, and other material relevant to the study of biochemical, cellular, and molecular mechanisms of damage in traumatic brain injury. Clinical studies of severe traumatic brain injury in infants and children were the focus, but reports in experimental models in immature animals were also considered. Results from both clinical studies in adults and models of traumatic brain injury in adult animals were presented for comparison. DATA SYNTHESIS: Categories of mechanisms defined were those associated with ischemia, excitotoxicity, energy failure, and resultant cell death cascades; secondary cerebral swelling; axonal injury; and inflammation and regeneration. CONCLUSIONS: A constellation of mediators of secondary damage, endogenous neuroprotection, repair, and regeneration are set into motion in the brain after severe traumatic injury. The quantitative contribution of each mediator to outcome, the interplay between these mediators, and the integration of these mechanistic findings with novel imaging methods, bedside physiology, outcome assessment, and therapeutic intervention remain an important target for future research.

Noise considerations in the determination of diffusion tensor anisotropy

In this study the noise sensitivity of various anisotropy indices has been investigated by Monte-Carlo computer simulations and magnetic resonance imaging (MRI) measurements in a phantom and 5 healthy volunteers. Particularly, we compared the noise performance of indices defined solely in terms of eigenvalues and those based on both the eigenvalues and eigenvectors. It is found that anisotropy indices based on both eigenvalues and eigenvectors are less sensitive to noise, and spatial averaging with neighboring pixels can further reduce the standard deviation. To reduce the partial volume effect caused by the spatial averaging with neighboring voxels, an averaging method in the time domain based on the orientation coherence of eigenvectors in repeated experiments has been proposed.