Diffusion tensor imaging of the human kidney: Does image registration permit scanning without respiratory triggering?

PURPOSE To investigate if image registration of diffusion tensor imaging (DTI) allows omitting respiratory triggering for both transplanted and native kidneys MATERIALS AND METHODS: Nine kidney transplant recipients and eight healthy volunteers underwent renal DTI on a 3T scanner with and without respiratory triggering. DTI images were registered using a multimodal nonrigid registration algorithm. Apparent diffusion coefficient (ADC), the contribution of perfusion (FP ), and the fractional anisotropy (FA) were determined. Relative root mean square errors (RMSE) of the fitting and the standard deviations of the derived parameters within the regions of interest (SDROI ) were evaluated as quality criteria. RESULTS Registration significantly reduced RMSE in all DTI-derived parameters of triggered and nontriggered measurements in cortex and medulla of both transplanted and native kidneys (P < 0.05 for all). In addition, SDROI values were lower with registration for all 16 parameters in transplanted kidneys (14 of 16 SDROI values were significantly reduced, P < 0.04) and for 15 of 16 parameters in native kidneys (9 of 16 SDROI values were significantly reduced, P < 0.05). Comparing triggered versus nontriggered DTI in transplanted kidneys revealed no significant difference for RMSE (P > 0.14) and for SDROI (P > 0.13) of all parameters. In contrast, in native kidneys relative RMSE from triggered scans were significantly lower than those from nontriggered scans (P < 0.02), while SDROI was slightly higher in triggered compared to nontriggered measurements in 15 out of 16 comparisons (significantly for two, P < 0.05). CONCLUSION Registration improves the quality of DTI in native and transplanted kidneys. Diffusion parameters in renal allografts can be measured without respiratory triggering. In native kidneys, respiratory triggering appears advantageous. J. Magn. Reson. Imaging 2016.

In-vivo diffusion tensor imaging of rat spinal cord with a phased array coil at 7T

Magnetic resonance imaging (MRI) is a non-invasive technique that offers excellent soft tissue contrast for characterizing soft tissue pathologies. Diffusion tensor imaging (DTI) is an MRI technique that has shown to have the sensitivity to detect subtle pathology that is not evident on conventional MRI. ^ Rats are commonly used as animal models in characterizing the spinal cord pathologies including spinal cord injury (SCI), cancer, multiple sclerosis, etc. These pathologies could affect both thoracic and cervical regions and complete characterization of these pathologies using MRI requires DTI characterization in both the thoracic and cervical regions. Prior to the application of DTI for investigating the pathologic changes in the spinal cord, it is essential to establish DTI metrics in normal animals. ^ To date, in-vivo DTI studies of rat spinal cord have used implantable coils for high signal-to-noise ratio (SNR) and spin-echo pulse sequences for reduced geometric distortions. Implantable coils have several disadvantages including: (1) the invasive nature of implantation, (2) loss of SNR due to frequency shift with time in the longitudinal studies, and (3) difficulty in imaging the cervical region. While echo planar imaging (EPI) offers much shorter acquisition times compared to spin-echo imaging, EPI is very sensitive to static magnetic field inhomogeneities and the existing shimming techniques implemented on the MRI scanner do not perform well on spinal cord because of its geometry. ^ In this work, an integrated approach has been implemented for in-vivo DTI characterization of rat spinal cord in the thoracic and cervical regions. A three element phased array coil was developed for improved SNR and extended spatial coverage. A field-map shimming technique was developed for minimizing the geometric distortions in EPI images. Using these techniques, EPI based DWI images were acquired with optimized diffusion encoding scheme from 6 normal rats and the DTI-derived metrics were quantified. ^ The phantom studies indicated higher SNR and smaller bias in the estimated DTI metrics than the previous studies in the cervical region. In-vivo results indicated no statistical difference in the DTI characteristics of either gray matter or white matter between the thoracic and cervical regions. ^

Diffusion Tensor Imaging in Alzheimer's disease

Attentional control and Information processing speed are central concepts in cognitive psychology and neuropsychology. Functional neuroimaging and neuropsychological assessment have depicted theoretical models considering attention as a complex and non-unitary process. One of its component processes, Attentional set-shifting ability, is commonly assessed using the Trail Making Test (TMT). Performance in the TMT decreases with increasing age in adults, Mild Cognitive Impairment (MCI) and Alzheimer’s Disease (AD). Besides, speed of information processing (SIP) seems to modulate attentional performance. While neural correlates of attentional control have been widely studied, there are few evidences about the neural substrates of SIP in these groups of patients. Different authors have suggested that it could be a property of cerebral white matter, thus, deterioration of the white matter tracts that connect brain regions related to set-shifting may underlie the age-related, MCI and AD decrease in performance. The aim of this study was to study the anatomical dissociation of attentional and speed mechanisms. Diffusion tensor imaging (DTI) provides a unique insight into the cellular integrity of the brain, offering an in vivo view into the microarchitecture of cerebral white matter. At the same time, the study of ageing, characterized by white matter decline, provides the opportunity to study the anatomical substrates speeded or slowed information processing. We hypothesized that FA values would be inversely correlated with time to completion on Parts A and B of the TMT, but not the derived scores B/A and B-A.

Three-dimensional brain fiber tracking modeling in diffusion tensor imaging

This dissertation establishes the foundation for a new 3-D visual interface integrating Magnetic Resonance Imaging (MRI) to Diffusion Tensor Imaging (DTI). The need for such an interface is critical for understanding brain dynamics, and for providing more accurate diagnosis of key brain dysfunctions in terms of neuronal connectivity. ^ This work involved two research fronts: (1) the development of new image processing and visualization techniques in order to accurately establish relational positioning of neuronal fiber tracts and key landmarks in 3-D brain atlases, and (2) the obligation to address the computational requirements such that the processing time is within the practical bounds of clinical settings. The system was evaluated using data from thirty patients and volunteers with the Brain Institute at Miami Children's Hospital. ^ Innovative visualization mechanisms allow for the first time white matter fiber tracts to be displayed alongside key anatomical structures within accurately registered 3-D semi-transparent images of the brain. ^ The segmentation algorithm is based on the calculation of mathematically-tuned thresholds and region-detection modules. The uniqueness of the algorithm is in its ability to perform fast and accurate segmentation of the ventricles. In contrast to the manual selection of the ventricles, which averaged over 12 minutes, the segmentation algorithm averaged less than 10 seconds in its execution. ^ The registration algorithm established searches and compares MR with DT images of the same subject, where derived correlation measures quantify the resulting accuracy. Overall, the images were 27% more correlated after registration, while an average of 1.5 seconds is all it took to execute the processes of registration, interpolation, and re-slicing of the images all at the same time and in all the given dimensions. ^ This interface was fully embedded into a fiber-tracking software system in order to establish an optimal research environment. This highly integrated 3-D visualization system reached a practical level that makes it ready for clinical deployment. ^

Improved delineation of short cortical association fibers and gray/white matter boundary using whole-brain three-dimensional diffusion tensor imaging at submillimeter spatial resolution.

Recent emergence of human connectome imaging has led to a high demand on angular and spatial resolutions for diffusion magnetic resonance imaging (MRI). While there have been significant growths in high angular resolution diffusion imaging, the improvement in spatial resolution is still limited due to a number of technical challenges, such as the low signal-to-noise ratio and high motion artifacts. As a result, the benefit of a high spatial resolution in the whole-brain connectome imaging has not been fully evaluated in vivo. In this brief report, the impact of spatial resolution was assessed in a newly acquired whole-brain three-dimensional diffusion tensor imaging data set with an isotropic spatial resolution of 0.85 mm. It was found that the delineation of short cortical association fibers is drastically improved as well as the definition of fiber pathway endings into the gray/white matter boundary-both of which will help construct a more accurate structural map of the human brain connectome.

Corpus callosum in maltreated children with posttraumatic stress disorder: A diffusion tensor imaging study

Contrary to expectations derived from preclinical studies of the effects of stress, and imaging studies of adults with posttraumatic stress disorder (PTSD), there is no evidence of hippocampus atrophy in children with PTSD. Multiple pediatric studies have reported reductions in the corpus callosum - the primary white matter tract in the brain. Consequently, in the present study, diffusion tensor imaging was used to assess white matter integrity in the corpus callosum in 17 maltreated children with PTSD and 15 demographically matched normal controls. Children with PTSD had reduced fractional anisotropy in the medial and posterior corpus, a region which contains interhemispheric projections from brain structures involved in circuits that mediate the processing of emotional stimuli and various memory functions - core disturbances associated with a history of trauma. Further exploration of the effects of stress on the corpus callosum and white matter development appears a promising strategy to better understand the pathophysiology of PTSD in children. (C) 2007 Elsevier Ireland Ltd. All rights reserved.

Quantitative diffusion tensor imaging detects dopaminergic neuronal degeneration in a murine model of Parkinson's disease.

Early diagnosis of Parkinson's disease (PD) is required to improve therapeutic responses. Indeed, a clinical diagnosis of resting tremor, rigidity, movement and postural deficiencies usually reflect >50% loss of the nigrostriatal system in disease. In a step to address this, quantitative diffusion tensor magnetic resonance imaging (DTI) was used to assess nigrostriatal degeneration in the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) intoxication model of dopaminergic nigral degeneration. We now demonstrate increased average diffusion (p<0.005) and decreased fractional anisotropy (p<0.03) in the substantia nigra (SN) of 5- to 7-day MPTP-treated animals when compared to saline controls. Transverse diffusivity demonstrated the most significant differences (p < or = 0.002) and correlated with the numbers of SN dopaminergic neurons (r=-0.75, p=0.012). No differences were found in the striatum, corpus callosum, cerebral cortex, or ventricles. These results demonstrate that DTI may be used as a surrogate biomarker of nigral dopaminergic neuronal degeneration.

Digital processing of diffusion-tensor images of avascular tissues

Diffusion is the process that leads to the mixing of substances as a result of spontaneous and random thermal motion of individual atoms and molecules. It was first detected by the English botanist Robert Brown in 1827, and the phenomenon became known as ‘Brownian motion’. More specifically, the motion observed by Brown was translational diffusion – thermal motion resulting in random variations of the position of a molecule. This type of motion was given a correct theoretical interpretation in 1905 by Albert Einstein, who derived the relationship between temperature, the viscosity of the medium, the size of the diffusing molecule, and its diffusion coefficient. It is translational diffusion that is indirectly observed in MR diffusion-tensor imaging (DTI). The relationship obtained by Einstein provides the physical basis for using translational diffusion to probe the microscopic environment surrounding the molecule.

Fluid registration of diffusion tensor images using information theory

We apply an information-theoretic cost metric, the symmetrized Kullback-Leibler (sKL) divergence, or $J$-divergence, to fluid registration of diffusion tensor images. The difference between diffusion tensors is quantified based on the sKL-divergence of their associated probability density functions (PDFs). Three-dimensional DTI data from 34 subjects were fluidly registered to an optimized target image. To allow large image deformations but preserve image topology, we regularized the flow with a large-deformation diffeomorphic mapping based on the kinematics of a Navier-Stokes fluid. A driving force was developed to minimize the $J$-divergence between the deforming source and target diffusion functions, while reorienting the flowing tensors to preserve fiber topography. In initial experiments, we showed that the sKL-divergence based on full diffusion PDFs is adaptable to higher-order diffusion models, such as high angular resolution diffusion imaging (HARDI). The sKL-divergence was sensitive to subtle differences between two diffusivity profiles, showing promise for nonlinear registration applications and multisubject statistical analysis of HARDI data.

Active fibers: Matching deformable tract templates to diffusion tensor images

Reliable quantitative analysis of white matter connectivity in the brain is an open problem in neuroimaging, with common solutions requiring tools for fiber tracking, tractography segmentation and estimation of intersubject correspondence. This paper proposes a novel, template matching approach to the problem. In the proposed method, a deformable fiber-bundle model is aligned directly with the subject tensor field, skipping the fiber tracking step. Furthermore, the use of a common template eliminates the need for tractography segmentation and defines intersubject shape correspondence. The method is validated using phantom DTI data and applications are presented, including automatic fiber-bundle reconstruction and tract-based morphometry. © 2009 Elsevier Inc. All rights reserved.

Prefrontal white matter abnormalities in young adult with major depressive disorder: A diffusion tensor imaging study

Prefrontal impairments have been hypothesized to be most strongly associated with the cognitive and emotional dysfunction in depression. Recently, white matter microstructural abnormalities in prefrontal lobe have been reported in elderly patients with ma

Visualitzation and processing of diffusion tensor MRI

Diffusion Tensor Imaging (DTI) is a new magnetic resonance imaging modality capable of producing quantitative maps of microscopic natural displacements of water molecules that occur in brain tissues as part of the physical diffusion process. This technique has become a powerful tool in the investigation of brain structure and function because it allows for in vivo measurements of white matter fiber orientation. The application of DTI in clinical practice requires specialized processing and visualization techniques to extract and represent acquired information in a comprehensible manner. Tracking techniques are used to infer patterns of continuity in the brain by following in a step-wise mode the path of a set of particles dropped into a vector field. In this way, white matter fiber maps can be obtained.

Abnormal Corpus Callosum Integrity in Bipolar Disorder: A Diffusion Tensor Imaging Study

Objective: Abnormalities in the anterior interhemispheric connections provided by the corpus callosum (CC) have long been implicated in bipolar disorder (BID). In this study, we used complementary diffusion tensor imaging methods to study the structural integrity of the CC and localization of potential abnormalities in BD. Methods: Subjects included 33 participants with BID and 40 healthy comparison participants. Fractional anisotropy (FA) measures were compared between groups with region of interest (ROD methods to investigate the anterior, middle, and posterior CC and voxel-based methods to further localize abnormalities. Results: In ROI-based analyses, FA was significantly decreased in the anterior and middle CC in the BID group (p <.05). Voxel-based analyses similarly localized group differences to the genu, rostral body, and anterior midbody of CC (p <.05, corrected). Conclusion: The findings demonstrate abnormalities in the structural integrity of the anterior CC in BID that might contribute to altered interhemispheric connectivity in this disorder.