A preliminary study of the effects of trigger timing on diffusion tensor imaging of the human spinal cord.

BACKGROUND AND PURPOSE: Diffusion tensor and diffusion-weighted spinal cord imaging remain relatively unexplored techniques despite demonstrations that such images can be obtained and may yield clinically relevant findings. In this study, we examined the temporal dynamics of spinal cord motion and their impact on diffusion tensor image quality. METHODS: Four healthy volunteers underwent phase contrast-based velocity mapping and segmented echo-planar diffusion tensor scans of the cervical spinal cord. Regions of interest in the cord were used to identify the temporal patterns of motion. The delay of data acquisition after the cardiac trigger was varied to correspond to either quiescence or motion of the cord. RESULTS: The cervical spinal cord consistently displayed maximal velocities in the range of 0.5 cm/s and accelerations of up to 25 cm/s(2). In both these respects, the cervical cord values were greater than those of the medulla. Despite this pronounced motion, approximately 40% of the cardiac cycle can be described as relatively calm, with absolute velocities and accelerations less than 20% of the maximum values. Confining image acquisition to this window reduced ghosting artifacts and increased the consistency with which the dominant direction of diffusion was along the rostral-caudal axis in both gray and white matter of the spine. Preliminary clinical application and fiber tracking in pathologic cases was feasible, and alterations of the diffusion properties by multiple sclerosis lesions, tumor, and syringomyelia were seen. CONCLUSIONS: Acquiring DTI data during the quiescent phase of spinal cord motion can reduce ghosting artifacts and improve fiber tracking.

Combining fMRI and DTI: a framework for exploring the limits of fMRI-guided DTI fiber tracking and for verifying DTI-based fiber tractography results.

A powerful, non-invasive technique for estimating and visualizing white matter tracts in the human brain in vivo is white matter fiber tractography that uses magnetic resonance diffusion tensor imaging. The success of this method depends strongly on the capability of the applied tracking algorithm and the quality of the underlying data set. However, DTI-based fiber tractography still lacks standardized validation. In the present work, a combined fMRI/DTI study was performed, both to develop a setup for verifying fiber tracking results using fMRI-derived functional connections and to explore the limitations of fMRI based DTI fiber tracking. Therefore, a minor fiber bundle that features several fiber crossings and intersections was examined: The striatum and its connections to the primary motor cortex were examined by using two approaches to derive the somatotopic organization of the striatum. First, an fMRI-based somatotopic map of the striatum was reconstructed, based on fMRI activations that were provoked by unilateral motor tasks. Second, fMRI-guided DTI fiber tracking was performed to generate DTI-based somatotopic maps, using a standard line propagation and an advanced fast marching algorithm. The results show that the fiber connections reconstructed by the advanced fast marching algorithm are in good agreement with known anatomy, and that the DTI-revealed somatotopy is similar to the fMRI somatotopy. Furthermore, the study illustrates that the combination of fMRI with DTI can supply additional information in order to choose reasonable seed regions for generating functionally relevant networks and to validate reconstructed fibers.

Preliminary experience with visualization of intracortical fibers by focused high-resolution diffusion tensor imaging.

BACKGROUND AND PURPOSE: The inherent low anisotropy of gray matter and the lack of adequate imaging sensitivity and resolution has, so far, impeded depiction of axonal fibers to their intracortical origin or termination. We tested the hypothesis that an experimental approach with high-resolution diffusion tensor imaging (DTI) provides anisotropic data for fiber tractography with sufficient sensitivity to visualize in vivo the fine distribution of white matter bundles at the intracortical level. MATERIALS AND METHODS: We conducted phantom measurements of signal-to-noise ratio (SNR) and obtained diffusion tensor maps of the occipital lobe in 6 healthy volunteers using a dedicated miniature phased array detector at 3T. We reconstructed virtual fibers using a standard tracking algorithm. RESULTS: The coil array provided a SNR of 8.0 times higher at the head surface compared with a standard quadrature whole head coil. Diffusion tensor maps could be obtained with an in-plane resolution of 0.58 x 0.58 mm(2). The axonal trajectories reconstructed from the diffusion data penetrate into the cortical ribbon perpendicular to the pial surface. This is the expected pattern for the terminations of thalamocortical afferent fibers to the middle layers of the occipital cortex and is consistent with the known microstructural organization of the mammalian cerebral cortex. CONCLUSION: High-resolution DTI reveals intracortical anisotropy with a distinct parallel geometrical order, perpendicular to the pial surface, consistent with structures that may be identified as the terminal afferents in cortical gray matter.

Influence of SENSE on image properties in high-resolution single-shot echo-planar DTI.

Limited spatial resolution is a key obstacle to the study of brain white matter structure with diffusion tensor imaging (DTI). In its frequent implementation with single-excitation spin-echo echo-planar sequences, DTI's ability to resolve small structures is strongly restricted by T2 and T2* decay, B0 inhomogeneity, and limited signal-to-noise ratio (SNR). In this work the influence of sensitivity encoding (SENSE) on diffusion-weighted (DW) image properties is investigated. Computer simulations showed that the PSF becomes narrower with increasing SENSE reduction factors, R, enhancing the intrinsic resolution. After a brief theoretical discussion, we describe the estimation of SNR on a pixel-by-pixel basis as a function of R. The mean image SNR behavior is manifold: SENSE is capable of increasing SNR efficiency by reducing the echo time (TE). Each SNR(R) curve reveals a maximum that depends on the amount of partial Fourier encoding used. The overall best SNR efficiency for an eight-element head coil array and a b-factor of 1000 s/mm2 is achieved at R = 2.1 and partial Fourier encoding of 60%. In vivo tensor maps of volunteers and a patient, with an in-plane resolution of 0.78 x 0.78 mm2, are also presented to demonstrate the practical implementation of the parallel approach.

Resolving fiber crossing using advanced fast marching tractography based on diffusion tensor imaging.

Magnetic resonance diffusion tensor tractography is a powerful tool for the non-invasive depiction of the white matter architecture in the human brain. However, due to limitations in the underlying tensor model, the technique is often unable to reconstruct correct trajectories in heterogeneous fiber arrangements, such as axonal crossings. A novel tractography method based on fast marching (FM) is proposed which is capable of resolving fiber crossings and also permits trajectories to branch. It detects heterogeneous fiber arrangements by incorporating information from the entire diffusion tensor. The FM speed function is adapted to the local tensor characteristics, allowing in particular to maintain the front evolution direction in crossing situations. In addition, the FM's discretization error is reduced by increasing the number of considered possible front evolution directions. The performance of the technique is demonstrated in artificial data and in the healthy human brain. Comparisons with standard FM tractography and conventional line propagation algorithms show that, in the presence of interfering structures, the proposed method is more accurate in reconstructing trajectories. The in vivo results illustrate that the elucidated major white matter pathways are consistent with known anatomy and that multiple crossings and tract branching are handled correctly.

Attention and interhemispheric transfer: a behavioral and fMRI study.

When both detections and responses to visual stimuli are performed within one and the same hemisphere, manual reaction times (RTs) are faster than when the two operations are carried out in different hemispheres. A widely accepted explanation for this difference is that it reflects the time lost in callosal transmission. Interhemispheric transfer time can be estimated by subtracting RTs for uncrossed from RTs for crossed responses (crossed-uncrossed difference, or CUD). In the present study, we wanted to ascertain the role of spatial attention in affecting the CUD and to chart the brain areas whose activity is related to these attentional effects on interhemispheric transfer. To accomplish this, we varied the proportion of crossed and uncrossed trials in different blocks. With this paradigm subjects are likely to focus attention either on the hemifield contralateral to the responding hand (blocks with 80% crossed trials) or on the ipsilateral hemifield (blocks with 80% uncrossed trials). We found an inverse correlation between the proportion of crossed trials in a block and the CUD and this effect can be attributed to spatial attention. As to the imaging results, we found that in the crossed minus uncrossed subtraction, an operation that highlights the neural processes underlying interhemispheric transfer, there was an activation of the genu of the corpus callosum as well as of a series of cortical areas. In a further commonality analysis, we assessed those areas which were activated specifically during focusing of attention onto one hemifield either contra- or ipsilateral to the responding hand. We found an activation of a number of cortical and subcortical areas, notably, parietal area BA 7 and the superior colliculi. We believe that the main thrust of the present study is to have teased apart areas important in interhemispheric transmission from those involved in spatial attention.

Identification of multiple nonprimary motor cortical areas with simple movements.

The human cortex reportedly contains at least five nonprimary motor areas: in the frontolateral convexity, the dorsal and ventral premotor cortex (PMd and PMv), and in the frontomesial wall, the presupplementary and supplementary motor areas (pre-SMA and SMA), and the rostral, dorsal and ventral cingulate areas (CMAr, CMAd, and CMAv). Activation of these regions in neuroimaging studies has been generally associated either with the performance of complex motor tasks or with reorganization occurring with motor recovery in the presence of pathology. Recent evidence from neuroimaging studies suggests that the same areas are activated with well controlled simple movements in healthy subjects providing support to the observation that their contribution may be more quantitative rather than exclusively specific to a certain aspect of motor behaviour. An important consequence of this observation is that activation of multiple nonprimary motor areas during simple motor tasks should not be considered unique to patients with upper or lower motoneuron lesions but rather as a normal physiological process.

SENSE-DTI at 3 T.

While holding vast potential, diffusion tensor imaging (DTI) with single-excitation protocols still faces serious challenges. Limited spatial resolution, susceptibility to magnetic field inhomogeneity, and low signal-to-noise ratio (SNR) may be considered the most prominent limitations. It is demonstrated that all of these shortcomings can be effectively mitigated by the transition to parallel imaging technology and high magnetic field strength. Using the sensitivity encoding (SENSE) technique at 3 T, brain DTI was performed in nine healthy volunteers. Despite enhanced field inhomogeneity, parallel acquisition permitted both controlling geometric distortions and enhancing spatial resolution up to 0.8 mm in-plane. Heightened SNR requirements were met in part by high base sensitivity at 3 T. A further significant increase in SNR efficiency was accomplished by SENSE acquisition, exploiting enhanced encoding speed for echo time reduction. Based on the resulting image data, high-resolution tensor mapping is demonstrated.