Diffusion tensor fiber tracking of human brain connectivity: aquisition methods, reliability analysis and biological results

We present a description, biological results and a reliability analysis for the method of diffusion tensor tracking (DTT) of white matter fiber pathways. In DTT, diffusion-tensor MRI (DT-MRI) data are collected and processed to visualize the line trajectories of fiber bundles within white matter (WM) pathways of living humans. A detailed description of the data acquisition is given. Technical aspects and experimental results are illustrated for the geniculo-calcarine tract with broad projections to visual cortex, occipital and parietal U-fibers, and the temporo-calcarine ventral pathway. To better understand sources of error and to optimize the method, accuracy and precision were analyzed by computer simulations. In the simulations, noisy DT-MRI data were computed that would be obtained for a WM pathway having a helical trajectory passing through gray matter. The error vector between the real and ideal track was computed, and random errors accumulated with the square root of track length consistent with a random-walk process. Random error was most dependent on signal-to-noise ratio, followed by number of averages, pathway anisotropy and voxel size, in decreasing order. Systematic error only occurred for a few conditions, and was most dependent on the stepping algorithm, anisotropy of the surrounding tissue, and non-equal voxel dimensions. Both random and systematic errors were typically below the voxel dimension. Other effects such as track rebound and track recovery also depended on experimental conditions. The methods, biological results and error analysis herein may improve the understanding and optimization of DTT for use in various applications in neuroscience and medicine.

Diffusion-tensor MR imaging of gray and white matter development during normal human brain maturation

BACKGROUND AND PURPOSE

Conventional MR imaging findings of human brain development are thought to result from decreasing water content, increasing macromolecular concentration, and myelination. We use diffusion-tensor MR imaging to test theoretical models that incorporate hypotheses regarding how these maturational processes influence water diffusion in developing gray and white matter.

METHODS

Experimental data were derived from diffusion-tensor imaging of 167 participants, ages 31 gestational weeks to 11 postnatal years. An isotropic diffusion model was applied to the gray matter of the basal ganglia and thalamus. A model that assumes changes in the magnitude of diffusion while maintaining cylindrically symmetric anisotropy was applied to the white matter of the corpus callosum and internal capsule. Deviations of the diffusion tensor from the ideal model predictions, due to measurement noise, were estimated by using Monte Carlo simulations.

RESULTS

Developing gray matter of the basal ganglia and developing white matter of the internal capsule and corpus callosum largely conformed to theory, with only small departures from model predictions in older children. However, data from the thalamus substantially diverged from predicted values, with progressively larger deviations from the model with increasing participant age.

CONCLUSION

Changes in water diffusion during maturation of central gray and white matter structures can largely be explained by theoretical models incorporating simple assumptions regarding the influence of brain water content and myelination, although deviations from theory increase as the brain matures. Diffusion-tensor MR imaging is a powerful method for studying the process of brain development, with both scientific and clinical applications.

A prospective, longitudinal diffusion tensor imaging study of brain injury in newborns

OBJECTIVE

To establish the magnitude and time course of the changes in water diffusion coefficient (D(av)) following newborn infant brain injury.

METHODS

Ten newborn infants at high risk for perinatal brain injury were recruited from the neonatal intensive care unit. Conventional and diffusion tensor MRI was performed on three occasions during the first week of life. Regions of injury were determined by evaluating conventional MR images (T1, T2, fluid-attenuated inversion recovery) at 1 week after injury. D(av) values were determined for these regions for all three scans.

RESULTS

D(av) values were decreased in most infants 1 day after injury, but injury was not evident or underestimated in 4 of 10 infants despite the presence of injury on conventional imaging at 1 week. By the third day, D(av) values were decreased in injured areas in all infants, reaching a nadir of approximately 35% less than normal values. By the seventh day after injury, D(av) values were returning to normal (pseudonormalization).

CONCLUSIONS

MR diffusion images (for which contrast is determined by changes in D(av)) obtained on the first day after injury do not necessarily show the full extent of ultimate injury in newborn infants. Images obtained between the second and fourth days of life reliably indicate the extent of injury. By the seventh day, diffusion MR is less sensitive to perinatal brain injury than conventional MR because of transient pseudonormalization of D(av). Overall, diffusion MR may not be suitable as a gold standard for detection of brain injury during the first day after injury in newborn infants.

Normal brain maturation during childhood: developmental trends characterized with diffusion-tensor MR imaging

PURPOSE

To characterize the maturational changes in water diffusion within central gray matter nuclei and central white matter pathways of the human brain by using diffusion-tensor magnetic resonance (MR) imaging.

MATERIALS AND METHODS

Retrospective analysis of normal MR examination findings in 153 subjects (age range, 1 day to 11 years) referred for clinical neuroimaging was performed. All studies included diffusion tensor-encoded echo-planar MR imaging. Isotropic diffusion coefficient (D) and diffusion anisotropy (A(sigma)) were measured in the corpus callosum, internal capsule, caudate nucleus, lentiform nucleus, and thalamus.

RESULTS

exhibited biexponential decay with age in gray and white matter regions, except for monoexponential decay in the genu of the corpus callosum. There was a steep nonlinear increase of A(sigma) in white matter tracts that paralleled the time course of the decline in D. In basal ganglia, only a small linear increase in A(sigma) was observed in patients. A(sigma) changes in the thalamus were intermediate between basal ganglia and white matter structures.

CONCLUSION

Changes in magnitude and anisotropy of water diffusion follow stereotypical time courses during brain development that can be empirically described with multiexponential regression models, which suggests that quantitative scalar parameters derived from diffusion-tensor MR imaging may provide clinically useful developmental milestones for brain maturity.

Differences between gray matter and white matter water diffusion in stroke: diffusion-tensor MR imaging in 12 patients

PURPOSE

To investigate differences in water diffusion between white matter and gray matter in acute to early subacute stroke with diffusion-tensor magnetic resonance (MR) imaging.

MATERIALS AND METHODS

Twelve patients with unilateral middle cerebral arterial infarcts were examined with diffusion tensor-encoded echo-planar MR imaging 17 hours to 5 days after stroke onset. Isotropic diffusion coefficient (D) and diffusion anisotropy (A(sigma)) images were computed. (D) values were measured in ischemic and contralateral gray matter and white matter by using A(sigma) images to differentiate white matter from gray matter. (D) images were compared with unidirectional and directionally averaged diffusion-weighted images.

RESULTS

In all patients, (D) images showed two distinct levels of diffusion reduction in the infarct; more severe reduction occurred exclusively in white matter. (D) values were significantly less in infarcted white matter than in infarcted gray matter, whereas (D) values in the contralateral white matter and gray matter were not significantly different. Relative to the contralateral side, (D) values in the infarct were reduced by 46% in white matter and by 31% in gray matter (P <.001). Diffusion-weighted imaging caused underestimation of the magnitude and, in some cases, the spatial extent of the white matter diffusion abnormality.

CONCLUSION

Isotropic diffusion is more reduced in white matter than in gray matter in acute to early subacute middle cerebral arterial stroke. Diffusion-tensor imaging may be more sensitive than diffusion-weighted imaging to white matter ischemia.

The abdominal compartment syndrome: CT findings

OBJECTIVE

The abdominal compartment syndrome is a potentially fatal condition resulting from pathologic elevation of intraabdominal pressure. We evaluated preoperative abdominal CT scans of four patients with proven abdominal compartment syndrome to identify signs of increased intraabdominal pressure.

CONCLUSION

CT findings common to all four patients included tense infiltration of the retroperitoneum out of proportion to peritoneal disease, extrinsic compression of the inferior vena cava by retroperitoneal hemorrhage or exudate, and massive abdominal distention with an increased ratio of anteroposterior-to-transverse abdominal diameter (positive round belly sign; ratio > .80; p < .001). Direct renal compression or displacement, bowel wall thickening with enhancement, and bilateral inguinal herniation were each present in two of the four patients. Radiologists should be aware of this life-threatening syndrome. In the appropriate clinical setting, CT findings of increased intraabdominal pressure should be swiftly communicated to other physicians involved in treating the patient because the abdominal compartment syndrome requires emergent surgical decompression.

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.

Tracking neuronal fiber pathways in the living human brain

Functional imaging with positron emission tomography and functional MRI has revolutionized studies of the human brain. Understanding the organization of brain systems, especially those used for cognition, remains limited, however, because no methods currently exist for noninvasive tracking of neuronal connections between functional regions [Crick, F. & Jones, E. (1993) Nature (London) 361, 109-110]. Detailed connectivities have been studied in animals through invasive tracer techniques, but these invasive studies cannot be done in humans, and animal results cannot always be extrapolated to human systems. We have developed noninvasive neuronal fiber tracking for use in living humans, utilizing the unique ability of MRI to characterize water diffusion. We reconstructed fiber trajectories throughout the brain by tracking the direction of fastest diffusion (the fiber direction) from a grid of seed points, and then selected tracks that join anatomically or functionally (functional MRI) defined regions. We demonstrate diffusion tracking of fiber bundles in a variety of white matter classes with examples in the corpus callosum, geniculo-calcarine, and subcortical association pathways. Tracks covered long distances, navigated through divergences and tight curves, and manifested topological separations in the geniculo-calcarine tract consistent with tracer studies in animals and retinotopy studies in humans. Additionally, previously undescribed topologies were revealed in the other pathways. This approach enhances the power of modern imaging by enabling study of fiber connections among anatomically and functionally defined brain regions in individual human subjects.

A multiple echo pulse sequence for diffusion tensor imaging and its application in excised rat spinal cords

A new imaging sequence for rapid determination of the apparent self-diffusion tensor of water was developed and tested on fixed excised rat spinal cords. To reduce the time required to determine the tensor, the sequence utilized a new single-shot approach with multiple spin echoes. An assumption of cylindrical symmetry in the sample was made, thus requiring the measurement of only four of the six unique elements of the tensor. This assumption was found experimentally to be valid, and the results obtained using the new sequence were found to be quantitatively the same as results obtained using a standard spin-echo sequence.