Diffusion tensor imaging and aging - a review

Diffusion-tensor imaging (DTI) non-invasively provides maps of microscopic structural information of oriented tissue in vivo, which is finding utility in studies of the aging population. In contrast to the white matter maturation process, investigators have observed significant declines in the white matter ordering in normal as well as in abnormal aging. These studies suggest that water proton non-random, anisotropic diffusion measured by DTI is highly sensitive to otherwise subtle disease processes not normally seen with conventional MRI tissue contrast mechanisms.     

Diffusion tensor imaging and histology of developing hearts

Diffusion tensor imaging (DTI) has emerged as a promising method for noninvasive quantification of myocardial microstructure. However, the origin and behavior of DTI measurements during myocardial normal development and remodeling remain poorly understood. In this work, conventional and bicompartmental DTI in addition to three‐dimensional histological correlation were performed in a sheep model of myocardial development from third trimester to postnatal 5 months of age. Comparing the earliest time points in the third trimester with the postnatal 5 month group, the scalar transverse diffusivities preferentially increased in both left ventricle (LV) and right ventricle (RV): secondary eigenvalues D₂ increased by 54% (LV) and 36% (RV), whereas tertiary eigenvalues D₃ increased by 85% (LV) and 67% (RV). The longitudinal diffusivity D₁ changes were small, which led to a decrease in fractional anisotropy by 41% (LV) and 33% (RV) in 5 month versus fetal hearts. Histological analysis suggested that myocardial development is associated with hyperplasia in the early stages of the third trimester followed by myocyte growth in the later stages up to 5 months of age (increased average myocyte width by 198%, myocyte length by 128%, and decreased nucleus density by 70% between preterm and postnatal 5 month hearts.) In a few histological samples (N = 6), correlations were observed between DTI longitudinal diffusivity and myocyte length (r = 0.86, P < 0.05), and transverse diffusivity and myocyte width (r = 0.96, P < 0.01). Linear regression analysis showed that transverse diffusivities are more affected by changes in myocyte size and nucleus density changes than longitudinal diffusivities, which is consistent with predictions of classical models of diffusion in porous media. Furthermore, primary and secondary DTI eigenvectors during development changed significantly. Collectively, the findings demonstrate a role for DTI to monitor and quantify myocardial development, and potentially cardiac disease. Copyright © 2016 John Wiley & Sons, Ltd.     

Diffusion tensor imaging in spinal cord: methods and applications - a review

The spinal cord is a clinically eloquent site within the central nervous system, containing important sensorimotor tracts confined within a small cross-sectional area. Damage to the spinal cord may be caused by a wide range of pathologies, and can result in profound functional disability. Characterization of the structural integrity of the spinal cord can be assessed using diffusion tensor imaging methods. Development and application of this technique may improve our understanding of the nature and evolution of structural damage in spinal cord disease. Possible developments include improved detection of ischaemic lesions, clarification of the relationship between clinical disability and structural damage to the cord and monitoring of anti-inflammatory or neuroprotective therapies. In this review current technical aspects, clinical applications and the suggested future development of spinal cord diffusion imaging are discussed.     

Diffusion tensor imaging reveals evolution of primate brain architectures

Evolution of the brain has been an inherently interesting problem for centuries. Recent studies have indicated that neuroimaging is a powerful technique for studying brain evolution. In particular, a variety of reports have demonstrated that consistent white matter fiber connection patterns derived from diffusion tensor imaging (DTI) tractography reveal common brain architecture and are predictive of brain functions. In this paper, based on our recently discovered 358 dense individualized and common connectivity-based cortical landmarks (DICCCOL) defined by consistent fiber connection patterns in DTI datasets of human brains, we derived 65 DICCCOLs that are common in macaque monkey, chimpanzee and human brains and 175 DICCCOLs that exhibit significant discrepancies amongst these three primate species. Qualitative and quantitative evaluations not only demonstrated the consistencies of anatomical locations and structural fiber connection patterns of these 65 common DICCCOLs across three primates, suggesting an evolutionarily preserved common brain architecture but also revealed regional patterns of evolutionarily induced complexity and variability of those 175 discrepant DICCCOLs across the three species.     

Diffusion tensor imaging in fixed brain tissue at 7.0 T

The purpose of this work is to assess the feasibility of performing quantitative in vitro brain tissue diffusion tensor imaging (DTI) measurements and to examine their comparability to in vivo measurements. DTI of fixed tissue at high field strength is potentially a very valuable investigative tool as very high spatial resolution can be achieved. DTI was applied to human and mouse brain fixed tissue samples as well as in vivo measurements of the mouse brain. T(1) and T(2) relaxography of the fixed tissue samples was also performed to provide further characterization of the tissue. All experiments were performed at 7 T. The fractional anisotropy (FA) of the human fixed brain tissue samples is found to be higher in the corpus callosum than in the occipital white matter region, consistent with in vivo measurements reported in the literature. Our FA measurements of the corpus callosum of a mouse brain are also found to be the same both in vitro and in vivo. This preliminary work supports the use of DTI in both fixed human and fixed animal brain tissue as a valid investigative tool. With the increased availability of brain banks in different brain disorders, DTI in fixed tissue may prove to be a very useful method for the study of white matter abnormalities.     

Diffusion tensor imaging of diffuse axonal injury in a rat brain trauma model

Diffusion tensor imaging (DTI) was used to study traumatic brain injury. The impact-acceleration trauma model was used in rats. Here, in addition to diffusivities (mean, axial and radial), fractional anisotropy (FA) was used, in particular, as a parameter to characterize the cerebral tissue early after trauma. DTI was implemented at 7 T using fast spiral k-space sampling and the twice-refocused spin echo radiofrequency sequence for eddy current minimization. The method was carefully validated on different phantom measurements. DTI of a trauma group (n = 5), as well as a sham group (n = 5), was performed at different time points during 6 h following traumatic brain injury. Two cerebral regions, the cortex and corpus callosum, were analyzed carefully. A significant decrease in diffusivity in the trauma group versus the sham group was observed, suggesting the predominance of cellular edema in both cerebral regions. No significant FA change was detected in the cortex. In the corpus callosum of the trauma group, the FA indices were significantly lower. A net discontinuity in fiber reconstructions in the corpus callosum was observed by fiber tracking using DTI. Histological analysis using Hoechst, myelin basic protein and Bielschowsky staining showed fiber disorganization in the corpus callosum in the brains of the trauma group. On the basis of our histology results and the characteristics of the impact-acceleration model responsible for the presence of diffuse axonal injury, the detection of low FA caused by a drastic reduction in axial diffusivity and the presence of fiber disconnections of the DTI track in the corpus callosum were considered to be related to the presence of diffuse axonal injury.     

Diffusion tensor imaging using multiple coils for mouse brain connectomics

The correlation between brain connectivity and psychiatric or neurological diseases has intensified efforts to develop brain connectivity mapping techniques on mouse models of human disease. The neural architecture of mouse brain specimens can be shown non‐destructively and three‐dimensionally by diffusion tensor imaging, which enables tractography, the establishment of a connectivity matrix and connectomics. However, experiments on cohorts of animals can be prohibitively long. To improve throughput in a 7‐T preclinical scanner, we present a novel two‐coil system in which each coil is shielded, placed off‐isocenter along the axis of the magnet and connected to a receiver circuit of the scanner. Preservation of the quality factor of each coil is essential to signal‐to‐noise ratio (SNR) performance and throughput, because mouse brain specimen imaging at 7 T takes place in the coil‐dominated noise regime. In that regime, we show a shielding configuration causing no SNR degradation in the two‐coil system. To acquire data from several coils simultaneously, the coils are placed in the magnet bore, around the isocenter, in which gradient field distortions can bias diffusion tensor imaging metrics, affect tractography and contaminate measurements of the connectivity matrix. We quantified the experimental alterations in fractional anisotropy and eigenvector direction occurring in each coil. We showed that, when the coils were placed 12 mm away from the isocenter, measurements of the brain connectivity matrix appeared to be minimally altered by gradient field distortions. Simultaneous measurements on two mouse brain specimens demonstrated a full doubling of the diffusion tensor imaging throughput in practice. Each coil produced images devoid of shading or artifact. To further improve the throughput of mouse brain connectomics, we suggested a future expansion of the system to four coils. To better understand acceptable trade‐offs between imaging throughput and connectivity matrix integrity, studies may seek to clarify how measurement variability, post‐processing techniques and biological variability impact mouse brain connectomics.     

正常成人近段坐骨神经的弥散张量成像**

背景：弥散张量成像及神经纤维束示踪的出现为外周神经细微结构的显示及定量分析提供了新的方法。 目的：前瞻性分析健康成人大腿近段坐骨神经纤维束示踪、弥散张量成像的可行性及最佳成像参数。 方法：采用单次激发自旋回波-平面回波技术对28名健康志愿者双侧坐骨神经进行弥散张量成像及神经纤维束示踪,b值分别为1 200,1 400,1 600 s/mm2。 结果与结论：弥散张量成像及神经纤维束示踪成功者26名,成功率93%,神经纤维束示踪图上能清晰显示近段坐骨神经,与T1WI上解剖图像融合较好。两侧坐骨神经具有相同的弥散特征：随着b 值增加,信噪比逐渐减少,b值为1 200 s/mm2,信噪比值最大为142.72±32.25,神经纤维束长度最长,所占体素最大,但不同b值的弥散张量参数无差异(P > 0.05),且两侧坐骨神经弥散张量参数无差异。说明正常成人大腿近段坐骨神经的弥散张量成像及经纤维束示踪是可行的,可清晰显示坐骨神经走行及弥散特征;最佳b值为1 200 s/mm2。 关键词：弥散张量成像;坐骨神经;磁共振成像;神经纤维束示踪术;成年人 doi:10.3969/j.issn.1673-8225.2012.09.030     

The role of diffusion tensor imaging in the evaluation of ischemic brain injury - a review

Water diffusion in brain tissue is affected by the presence of barriers to translational motion such as cell membranes and myelin fibers. The measured water apparent diffusion coefficient (ADC) value is therefore frequently anisotropic and varies depending upon the orientation of restricting barriers (such as white matter tracts) relative to the diffusion-sensitive-gradient direction. Anisotropic water diffusion can be specified using indices of diffusion anisotropy [e.g. standard deviation of the individual ADC values, fractional anisotropy (FA), lattice index (LI)], which are derived from measurements of the full diffusion tensor. The rotationally invariant nature of particular diffusion anisotropy indices (e.g. FA, LI) allows orientation-independent comparisons of these parameters between different subjects. Pathophysiological processes (such as cerebral ischemia) that modify the integrity of the tissue microstructure result in significant alterations in tissue anisotropy and make this metric a useful endpoint for characterizing the temporal evolution of the disease. Diffusion-tensor imaging (DTI) studies of both experimental and human stroke suggest that DTI may provide additional information about the evolution of the disease that is not available from diffusion-weighted MRI (DWI) alone. Acute reductions in the average diffusivity [ = (lambda(1) + lambda(2) + lambda(3))/3 where lambda(1), lambda(2), and lambda(3) are the eigenvalues of the diffusion tensor] following the onset of cerebral ischemia are often accompanied by increases in diffusion anisotropy. In the transition from acute to sub-acute and chronic stroke, renormalizes and subsequently increases whereas diffusion anisotropy measures (e.g. FA) decline and remained reduced in chronic infarcts. Overall isotropic ADC changes during infarct evolution have been observed to be greater in white matter (WM) than in gray matter (GM) lesions (although there have been conflicting reports on this issue) and GM lesions tend to renormalize prior to WM lesions as the infarct evolves. Ischemic WM exhibits a significant decrease in diffusion anisotropy (relative to normal WM) during ischemic evolution whereas that of ischemic GM remains statistically unchanged. Furthermore, the percentage decrease in ischemic WM is largely determined by reductions in lambda(1), the eigenvalue that coincides with the long axis of the WM fiber tract. Variations in unidirectional ADC or over the ischemic time course limit the usefulness of this parameter alone as a predictor of ischemic injury. Consequently, ADC information has been combined with that of other MR parameters (including DTI) to unambiguously stage and predict ischemic brain injury over its entire temporal evolution. Combined and diffusion anisotropy measurements have identified three phases of diffusion abnormality: (1) reduced and elevated anisotropy; (2) reduced and reduced anisotropy; and (3) elevated and reduced anisotropy. However, variations in the differential patterns of and diffusion anisotropy evolution have been observed by a number of investigators and more work is needed to clarify the role of these measurements in characterizing the severity of the ischemic insult as well as the potential outcome in response to the initial ischemic injury. The use of DTI, in combination with more sophisticated analysis methods for performing multiparametric segmentation, such as multispectral analysis, may enhance the use of MRI for accurate diagnosis and prognosis of stroke. Furthermore, these techniques may also play an important role in the clinical evaluation of new stroke treatments.     

Mammillothalamic tract in human brain: Diffusion tensor tractography study

The mammillothalamic tract (MTT) is a part of the Papez circuit and connects the mammillary body and anterior thalamus. No studies of the MTT have been performed using diffusion tensor tractography (DTT). In the current study, we attempted to identify the MTT in the human brain using DTT. We recruited 25 healthy volunteers for this study. Diffusion tensor images (DTIs) were scanned using 1.5-T, and the MTT was obtained using FMRIB software. Values of fractional anisotropy (FA), mean diffusicity (MD), and tract volume of the MTT were measured. The location of the highest probability point of the MTT was measured at the bicommissural level. MTTs of all subjects, which originated from the mammillary body, ascended posteriorly to the bicommissural level, along the third ventricle, and then ascended to the anterior thalamus in the antero-lateral direction. Average location of the MTT was 37.15% from the most posterior border of the anterior commissure to the most posterior border of the third ventricle at the bicommissural level. We identified the MTT in the human brain using DTT. These methods and results would be helpful to both clinicians and researchers in this field.     

Diffusion tensor MR imaging of principal directions: a tensor tomography approach

A novel approach to reconstructing the principal directions of a diffusion tensor field directly from magnetic resonance imaging (MRI) data using a tensor tomography data acquisition approach was developed. If tensor eigenvalues are assumed to be known, the reconstruction of principal directions requires fewer measurements than the reconstruction of the full tensor field. The tensor tomography data acquisition method (rotating diffusion gradients) leads to a unique reconstruction of principal directions, whereas the conventional MRI acquisition technique (stationary diffusion gradients) leads to an ambiguous reconstruction of principal directions when the same number of measurements are used. A computer-generated phantom was used to simulate the diffusion tensor field in the mid-ventricular region of the myocardium. The principal directions of the diffusion tensor field were assumed to align with the fibre structure of the myocardium. An iterative algorithm was used to reconstruct the principal directions. Computer simulations verify that the proposed method provides accurate reconstruction of the principal directions of a diffusion tensor field.     

Feasibility of developing a method of imaging neuronal activity in the human brain: a theoretical review

A theoretical analysis has been performed to suggest directions for research into the development of a device which could image neuronal electrical activity in the human brain in three dimensions. Proposed criteria for the device are a spatial resolution of 1 mm³ and temporal resolution, after averaging to a repeated stimulus, of 1 ms for events related to the action potential, or 1 s for metabolic changes. It is proposed that, for the rapid changes related to the action potential, electron spin resonance using a potential-sensitive spin, label, impedance imaging and NMR are suitable in principle but that only ESR and impedance methods may have sufficient sensitivity and these merit further assessment. For metabolic changes, NMR and PET may be used as at present, and ESR may be developed in time, but images based on these changes would have limited value in that they could only give an indirect, index of neuronal discharge. Unique reconstructions based on the EEG or MEG are theoretically, impossible, and imaging using X-rays, microwaves, or ultrasound may be possible in principle but these techniques would not be sufficiently sensitive.     

Diffusion tensor imaging detects axonal injury in a mouse model of repetitive closed-skull traumatic brain injury

Mild traumatic brain injuries (TBI) are common in athletes, military personnel, and the elderly, and increasing evidence indicates that these injuries have long-term health effects. However, the difficulty in detecting these mild injuries in vivo is a significant impediment to understanding the underlying pathology and treating mild TBI. In the following experiments, we present the results of diffusion tensor imaging (DTI) and histological analysis of a model of mild repetitive closed-skull brain injury in mouse. Histological markers used included silver staining and amyloid precursor protein (APP) immunohistochemistry to detect axonal injury, and Iba-1 immunohistochemistry to assess microglial activation. At 24h post-injury, before silver staining or microglial abnormalities were apparent by histology, no significant changes in any of the DTI parameters were observed within white matter. At 7 days post-injury we observed a reduction in axial and mean diffusivity. Relative anisotropy at 7 days correlated strongly with the degree of silver staining. Interestingly, APP was not observed at any timepoint examined. In addition to the white matter alterations, mean diffusivity was elevated in ipsilateral cortex at 24h but returned to sham levels by 7 days. Altogether, this demonstrates that DTI is a sensitive method for detecting axonal injury despite a lack of conventional APP pathology. Further, this reflects a need to better understand the histological basis for DTI signal changes in mild TBI.     

Diffusion tensor imaging shows white matter tracts between human auditory and visual cortex

Although it is known that sounds can affect visual perception, the neural correlates for crossmodal interactions are still disputed. Previous tracer studies in non-human primates revealed direct anatomical connections between auditory and visual brain areas. We examined the structural connectivity of the auditory cortex in normal humans by diffusion-weighted tensor magnetic resonance imaging and probabilistic tractography. Tracts were seeded in Heschl's region or the planum temporale. Fibres crossed hemispheres at the posterior corpus callosum. Ipsilateral fibres seeded in Heschl's region projected to the superior temporal sulcus, the supramarginal gyrus and intraparietal sulcus and the occipital cortex including the calcarine sulcus. Fibres seeded in the planum temporale terminated primarily in the superior temporal sulcus, the supramarginal gyrus, the central sulcus and adjacent regions. Our findings suggest the existence of direct white matter connections between auditory and visual cortex--in addition to subcortical, temporal and parietal connections.     

Preservation of diffusion tensor properties during spatial normalization by use of tensor imaging and fibre tracking on a normal brain database

White matter connectivity in the human brain can be mapped by diffusion tensor magnetic resonance imaging (DTI). After reconstruction, the diffusion tensors, the diffusion amplitude and the diffusion direction can be displayed on a morphological background. Consequently, diffusion tensor fibre tracking can be applied as a non-invasive in vivo technique for the delineation and quantification of specific white matter pathways. The aim of this study was to show that normalization to the Montreal Neurological Institute (MNI) stereotaxic standard space preserves specific diffusion features. Therefore, techniques for tensor imaging and fibre tracking were applied to the normalized brains as well as to the group averaged brain data. A normalization step of individual data was included by registration to a scanner- and sequence-specific DTI template data set which was created from a normal database transformed to MNI space. The algorithms were tested and validated for a group of 13 healthy controls.     

Diffusion tensor imaging of deep gray matter brain structures: effects of age and iron concentration

Diffusion tensor imaging (DTI) of the brain has become a mainstay in the study of normal aging of white matter, and only recently has attention turned to the use of DTI to examine aging effects in gray matter structures. Of the many changes in the brain that occur with advancing age is increased presence of iron, notable in selective deep gray matter structures. In vivo detection and measurement of iron deposition is possible with magnetic resonance imaging (MRI) because of iron's effect on signal intensity. In the process of a DTI study, a series of diffusion-weighted images (DWI) is collected, and while not normally considered as a major dependent variable in research studies, they are used clinically and they reveal striking conspicuity of the globus pallidus and putamen caused by signal loss in these structures, presumably due to iron accumulation with age. These iron deposits may in turn influence DTI metrics, especially of deep gray matter structures. The combined imaging modality approach has not been previously used in the study of normal aging. The present study used legacy DTI data collected in 10 younger (22-37 years) and 10 older (65-79 years) men and women at 3.0T and fast spin-echo (FSE) data collected at 1.5T and 3.0T to derive an estimate of the field-dependent relaxation rate increase (the "FDRI estimate") in the putamen, caudate nucleus, globus pallidus, thalamus, and a frontal white matter sample comparison region. The effect of age on the diffusion measures in the deep gray matter structures was distinctly different from that reported in white matter. In contrast to lower anisotropy and higher diffusivity typical in white matter of older relative to younger adults observed with DTI, both anisotropy and diffusivity were higher in the older than younger group in the caudate nucleus and putamen; the thalamus showed little effect of age on anisotropy or diffusivity. Signal intensity measured with DWI was lower in the putamen of elderly than young adults, whereas the opposite was observed for the white matter region and thalamus. As a retrospective study based on legacy data, the FDRI estimates were based on FSE sequences, which underestimated the classical FDRI index of brain iron. Nonetheless, the differential effects of age on DTI metrics in subcortical gray matter structures compared with white matter tracts appears to be related, at least in part, to local iron content, which in the elderly of the present study was prominent in the FDRI estimate of the putamen and visibly striking in the diffusion-weighted image of the basal ganglia structures.     

Diffusion tensor imaging analysis of optic radiation using readout-segmented echo-planar imaging

Purpose

To investigate the diffusion tensor imaging parameters of the optic radiation and surrounding structures using the high-resolution readout-segmented diffusion tensor imaging method.

Materials and methods

Coronal readout-segmented diffusion tensor images were acquired in 15 healthy volunteers. On three slices of each image, eigenvalue 1, fractional anisotropy, radial diffusivity, apparent diffusion coefficient, and signal intensity on T2-weighted images were measured in the lateral inferior longitudinal fasciculus, external and internal layers of the optic radiation, and the tapetum within regions of interest delineated by two independent observers. Profile curve analysis of regions of interest across the optic radiation and surrounding structures was performed for a representative typical case.

Results

Significant differences in fractional anisotropy, radial diffusivity and apparent diffusion coefficient were observed between external and internal layers of the optic radiation, while there was no significant difference in eigenvalue 1. In fractional anisotropy maps, two low signal bands were observed between the inferior longitudinal fasciculus, the optic radiation and the tapetum. Profile curve analysis showed a minimum on the fractional anisotropy and eigenvalue 1 images and a maximum in the radial diffusivity image.

Conclusion

Readout-segmented diffusion tensor imaging revealed significant differences in the diffusion tensor imaging parameters between internal and external layers of the optic radiation.