Wen-Yih Isaac Tseng

Mapping complex tissue architecture with diffusion spectrum magnetic resonance imaging.

Methods are presented to map complex fiber architectures in tissues by imaging the 3D spectra of tissue water diffusion with MR. First, theoretical considerations show why and under what conditions diffusion contrast is positive. Using this result, spin displacement spectra that are conventionally phase‐encoded can be accurately reconstructed by a Fourier transform of the measured signals modulus. Second, studies of in vitro and in vivo samples demonstrate correspondence between the orientational maxima of the diffusion spectrum and those of the fiber orientation density at each location. In specimens with complex muscular tissue, such as the tongue, diffusion spectrum images show characteristic local heterogeneities of fiber architectures, including angular dispersion and intersection. Cerebral diffusion spectra acquired in normal human subjects resolve known white matter tracts and tract intersections. Finally, the relation between the presented model‐free imaging technique and other available diffusion MRI schemes is discussed. Magn Reson Med, 2005.

Diffusion spectrum magnetic resonance imaging (DSI) tractography of crossing fibers.

MRI tractography is the mapping of neural fiber pathways based on diffusion MRI of tissue diffusion anisotropy. Tractography based on diffusion tensor imaging (DTI) cannot directly image multiple fiber orientations within a single voxel. To address this limitation, diffusion spectrum MRI (DSI) and related methods were developed to image complex distributions of intravoxel fiber orientation. Here we demonstrate that tractography based on DSI has the capacity to image crossing fibers in neural tissue. DSI was performed in formalin-fixed brains of adult macaque and in the brains of healthy human subjects. Fiber tract solutions were constructed by a streamline procedure, following directions of maximum diffusion at every point, and analyzed in an interactive visualization environment (TrackVis). We report that DSI tractography accurately shows the known anatomic fiber crossings in optic chiasm, centrum semiovale, and brainstem; fiber intersections in gray matter, including cerebellar folia and the caudate nucleus; and radial fiber architecture in cerebral cortex. In contrast, none of these examples of fiber crossing and complex structure was identified by DTI analysis of the same data sets. These findings indicate that DSI tractography is able to image crossing fibers in neural tissue, an essential step toward non-invasive imaging of connectional neuroanatomy.

The Geometric Structure of the Brain Fiber Pathways

Building the Brain Brain connectivity is often described as a network of discrete independent cables analogous to a switchboard, but how is the physical structure of the brain constructed (see the Perspective by Zilles and Amunts)? Wedeen et al. (p. 1628) used high-resolution diffusion tensor imaging in humans and four species of nonhuman primates to identify and compare the geometric structure of large fiber tracts in the brain. Fiber tracts followed a highly constrained and regular geometry, which may provide an efficient solution for pathfinding during ontogenetic development. Much of development occurs through elaboration and assembly of semiautonomous building blocks. Chen et al. (p. 1634) applied statistical analysis to the form of the human cortex in brain-imaging studies that compared more than 400 di- and mono-zygotic twins. The findings suggest that the structure of the human cortex is defined by genetics. The macroscopic pathways of human brain nerve fibers are organized according to a single, highly curved three-dimensional grid. The structure of the brain as a product of morphogenesis is difficult to reconcile with the observed complexity of cerebral connectivity. We therefore analyzed relationships of adjacency and crossing between cerebral fiber pathways in four nonhuman primate species and in humans by using diffusion magnetic resonance imaging. The cerebral fiber pathways formed a rectilinear three-dimensional grid continuous with the three principal axes of development. Cortico-cortical pathways formed parallel sheets of interwoven paths in the longitudinal and medio-lateral axes, in which major pathways were local condensations. Cross-species homology was strong and showed emergence of complex gyral connectivity by continuous elaboration of this grid structure. This architecture naturally supports functional spatio-temporal coherence, developmental path-finding, and incremental rewiring with correlated adaptation of structure and function in cerebral plasticity and evolution.

Generalized

Based on the Fourier transform relation between diffusion magnetic resonance (MR) signals and the underlying diffusion displacement, a new relation is derived to estimate the spin distribution function (SDF) directly from diffusion MR signals. This relation leads to an imaging method called generalized q-sampling imaging (GQI), which can obtain the SDF from the shell sampling scheme used in q-ball imaging (QBI) or the grid sampling scheme used in diffusion spectrum imaging (DSI). The accuracy of GQI was evaluated by a simulation study and an in vivo experiment in comparison with QBI and DSI. The simulation results showed that the accuracy of GQI was comparable to that of QBI and DSI. The simulation study of GQI also showed that an anisotropy index, named quantitative anisotropy, was correlated with the volume fraction of the resolved fiber component. The in vivo images of GQI demonstrated that SDF patterns were similar to the ODFs reconstructed by QBI or DSI. The tractography generated from GQI was also similar to those generated from QBI and DSI. In conclusion, the proposed GQI method can be applied to grid or shell sampling schemes and can provide directional and quantitative information about the crossing fibers.

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Background— Diffusion tensor magnetic resonance imaging (DT-MRI) provides a means for nondestructive characterization of myocardial architecture. We used DT-MRI to investigate changes in direction-dependent water diffusivity to reflect alterations in tissue integrity (trace apparent diffusion coefficients [ADCs] and fractional anisotropy [FA]), as well as indicators of remodeling of fiber helix angles, in patients after myocardial infarction. Methods and Results— Thirty-seven patients (35 men, 2 women; median age, 59) after acute myocardial infarction (median interval from onset, 26 days) were enrolled. DT-MRI was performed at the midventricular level to measure trace ADC, FA, and helix angles of myofibers. Helix angles were grouped into left-handed helical fibers, circumferential fibers, and right-handed helical fibers. Measurements were correlated with viability and regional wall motion assessed by contrast-delay-enhancement and cine MRI, respectively. The infarct zone showed significantly increased trace ADC and decreased FA than the remote zone. The percentage of left-handed helical fibers increased from the remote zone (mean±SD, 13.3±5.8%) to the adjacent zone (19.2±9.7%) and infarct zone (25.8±18.4%) (MANOVA, P=0.004). The percentage of right-handed helical fibers decreased from the remote zone (35.0±9.0%) to the adjacent zone (25.5±11.5%) and infarct zone (15.9±9.2%) (P<0.001). Multiple linear regression showed that the percentage of left-handed helical fibers of the infarct zone was the strongest correlate of infarct size and predictor of ejection fraction. Conclusions— In vivo DT-MRI of postinfarct myocardium revealed a significant increase in trace ADC and a decrease in FA, indicating altered tissue integrity. The redistribution of fiber architecture correlated with infarct size and left ventricular function. This technique may help us understand structural correlates of functional remodeling after infarction.

-Sampling Imaging

Diffusion MRI tractography has emerged as a useful and popular tool for mapping connections between brain regions. In this study, we examined the performance of quantitative anisotropy (QA) in facilitating deterministic fiber tracking. Two phantom studies were conducted. The first phantom study examined the susceptibility of fractional anisotropy (FA), generalized factional anisotropy (GFA), and QA to various partial volume effects. The second phantom study examined the spatial resolution of the FA-aided, GFA-aided, and QA-aided tractographies. An in vivo study was conducted to track the arcuate fasciculus, and two neurosurgeons blind to the acquisition and analysis settings were invited to identify false tracks. The performance of QA in assisting fiber tracking was compared with FA, GFA, and anatomical information from T1-weighted images. Our first phantom study showed that QA is less sensitive to the partial volume effects of crossing fibers and free water, suggesting that it is a robust index. The second phantom study showed that the QA-aided tractography has better resolution than the FA-aided and GFA-aided tractography. Our in vivo study further showed that the QA-aided tractography outperforms the FA-aided, GFA-aided, and anatomy-aided tractographies. In the shell scheme (HARDI), the FA-aided, GFA-aided, and anatomy-aided tractographies have 30.7%, 32.6%, and 24.45% of the false tracks, respectively, while the QA-aided tractography has 16.2%. In the grid scheme (DSI), the FA-aided, GFA-aided, and anatomy-aided tractographies have 12.3%, 9.0%, and 10.93% of the false tracks, respectively, while the QA-aided tractography has 4.43%. The QA-aided deterministic fiber tracking may assist fiber tracking studies and facilitate the advancement of human connectomics.

Diffusion Tensor Magnetic Resonance Imaging Mapping the Fiber Architecture Remodeling in Human Myocardium After Infarction Correlation With Viability and Wall Motion

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.

Deterministic Diffusion Fiber Tracking Improved by Quantitative Anisotropy

To test the hypothesis that the primary, secondary, and tertiary eigenvectors of the diffusion tensor (DT) measured with DT‐MRI correspond to the fiber, sheet, and sheet normal directions, respectively, we compared DT‐MRI data with the texture visible in the cut face of fresh bovine myocardium.

Validation of Diffusion Tensor Magnetic Resonance Axonal Fiber Imaging with Registered Manganese-Enhanced Optic Tracts

To examine the relationship between myofiber disarray and myocardial hypokinesis in human hypertrophic cardiomyopathy (HCM) using noninvasive cardiac diffusion and strain MRI.

Diffusion tensor MRI of myocardial fibers and sheets: correspondence with visible cut-face texture.

We present a high angular resolution brain atlas constructed by averaging 90 diffusion spectrum imaging (DSI) datasets in the ICBM-152 space. The spatial normalization of the diffusion information was conducted by a novel q-space diffeomorphic reconstruction method, which reconstructed the spin distribution function (SDF) in the ICBM-152 space from the diffusion MR signals. The performance of this method was examined by a simulation study modeling nonlinear transformation. The result showed that the reconstructed SDFs can resolve crossing fibers and that the accumulated quantitative anisotropy can reveal the relative ratio of the fiber populations. In the in vivo study, the SDF of the constructed atlas was shown to resolve crossing fiber orientations. Further, fiber tracking showed that the atlas can be used to present the pathways of fiber bundles, and the termination locations of the fibers can provide anatomical localization of the connected cortical regions. This high angular resolution brain atlas may facilitate future connectome research on the complex structure of the human brain.