Novel Cost Function Definition for Minimum-Cost Tractography in MR Diffusion Tensor Imaging.

Magnetic resonance imaging (MRI) is an established clinical technique that measures diffusion-weighted signals, applied primarily in brain studies. Diffusion tensor imaging (DTI) is a technique that uses the diffusion-weighted signals to obtain information about tissue connectivity, which recently started to become established in clinical use. The extraction of tracts (tractography) is an issue under active research. In this work we present an algorithm for recovering tracts, based on Dijkstra's minimum-cost path. A novel cost definition algorithm is presented that allows tract reconstruction, considering the tract's curvature, as well as its alignment with the diffusion vector field. The proposed cost function is able to adapt to linear, planar, and spherical diffusion. Thus, it can handle issues of fiber crossing, which pose considerable problems to tractography algorithms. A simple method for generating synthetic diffusion - weighted MR signals from known fibers - is also presented and utilized in this work. Results are shown for two (2D)- and three-dimensional (3D) synthetic data, as well as for a clinical MRI-DTI brain study.

Antisocial behavior with callous-unemotional traits is associated with widespread disruptions to white matter structural connectivity among low-income, urban males.

Antisocial behavior (AB), including violence, criminality, and substance abuse, is often linked to deficits in emotion processing, reward-related learning, and inhibitory control, as well as their associated neural networks. To better understand these deficits, the structural connections between brain regions implicated in AB can be examined using diffusion tensor imaging (DTI), which assesses white matter microstructure. Prior studies have identified differences in white matter microstructure of the uncinate fasciculus (UF), primarily within offender samples. However, few studies have looked beyond the UF or determined whether these relationships are present dimensionally across the range of AB and callous-unemotional (CU) traits. In the current study, we examined associations between AB and white matter microstructure from major fiber tracts, including the UF. Further, we explored whether these associations were specific to individuals high on CU traits. Within a relatively large community sample of young adult men from low-income, urban families (N = 178), we found no direct relations between dimensional, self-report measures of either AB or CU traits and white matter microstructure. However, we found significant associations between AB and white matter microstructure of several tracts only for those with high co-occurring levels of CU traits. In general, these associations did not differ according to race, socioeconomic status, or comorbid psychiatric symptoms. The current results suggest a unique neural profile of severe AB in combination with CU traits, characterized by widespread differences in white matter microstructure, which differs from either AB or CU traits in isolation and is not specific to hypothesized tracts (i.e., the UF).

Advanced magnetic resonance imaging techniques in the preterm brain: methods and applications.

Brain development and brain injury in preterm infants are areas of active research. Magnetic resonance imaging (MRI), a non-invasive tool applicable to both animal models and human infants, provides a wealth of information on this process by bridging the gap between histology (available from animal studies) and developmental outcome (available from clinical studies). Moreover, MRI also offers information regarding diagnosis and prognosis in the clinical setting. Recent advances in MR methods - diffusion tensor imaging, volumetric segmentation, surface based analysis, functional MRI, and quantitative metrics - further increase the sophistication of information available regarding both brain structure and function. In this review, we discuss the basics of these newer methods as well as their application to the study of premature infants.

Cost function evaluation for the registration of clinical DTI images onto the ICBM DTI81 white matter atlas.

BACKGROUND AND PURPOSE: Various algorithms are available for the analysis of diffusion tensor (DTI) images. Many of these stand alone software packages require time-intensive user interactions not yet suited for routine clinical application Here, we demonstrate the use of the 'Analysis of Functional NeuroImages' (AFNI) software package, a standard for the analysis of functional magnetic resonance images (fMRI), to automatically align clinical DTI images onto the ICBM DTI81 atlas potentially enabling the combined presentation of fMRI and DTI results. METHODS: Fractional anisotropy (FA) maps from seven patients diagnosed with video/EEG defined complex partial seizures were retrospectively analyzed. Affine transformations parameters for seven different cost functions provided by the 3dAllineate software tool were calculated. Alignment quality and variations of the transformation parameters were assessed. RESULTS: Best alignment between the FA maps for each subject and the ICBM DTI81 atlas was achieved with cost functions utilizing the cost ratio (CR) (symmetrized* CR, symmetrized+ CR and unsymmetrized CR). Symmetrized* CR performed slightly better, in particular for lateral white matter structures. Relatively small variations in the transformation parameters emphasize the robustness of the transformations. CONCLUSIONS: Good alignment of FA maps to the ICBM DTI81 white matter atlas can be achieved using an automated affine transformation with software tools provided by AFNI potentially enabling the combined presentation of fMRI and DTI information. This procedure maybe readily be applied in clinical practice.