Aging effects on cerebral asymmetry: a voxel-based morphometry and diffusion tensor imaging study

The hemispheres of the human brain are functionally and structurally asymmetric. The purpose of this study was to evaluate the effects of aging on gray and white matter asymmetry. Two hundred twenty-six right-handed normal volunteers aged 21–71 years were included in this study. The effects of aging on gray matter volume asymmetry and white matter fractional anisotropy asymmetry were evaluated with use of voxel-based morphometry and voxel-based analysis of fractional anisotropy maps derived from diffusion tensor imaging (DTI), respectively. The voxel-based morphometry showed no significant correlation between age and gray matter volume asymmetry. The voxel-based analysis of DTI also showed no significant correlation between age and white matter fractional anisotropy asymmetry. Our results showed no significant effects of aging on either gray matter volume asymmetry or white matter fractional anisotropy asymmetry.     

Exploratory voxel-based analysis of diffusion indices and hemispheric asymmetry in normal aging

Age-related microstructural changes in brain white matter can be studied by utilizing indices derived from diffusion tensor imaging (DTI): apparent diffusion coefficient (ADC) and fractional anisotropy (FA). The objective of this study is to examine alterations in FA and ADC by employing exploratory voxel-based analysis (VBA) and region(s) of interest (ROI)-based analysis. A highly nonlinear registration algorithm was used to align the ADC and FA image volumes of different subjects to perform accurate voxel-level statistics for two age groups, as well as for hemispheric asymmetry for both age groups. VBA shows significant age-related decline in FA with frontal predominance (frontal white matter, and genu and anterior body of the corpus callosum), superior portions of a splenium and highly oriented fibers of the posterior limb of the internal capsule and the anterior and posterior limbs of the external capsule. Hemispheric asymmetry of FA, as assessed by VBA, showed that for the young-age group, significant right-greater-than-left asymmetry exists in the genu, splenium and body of the corpus callosum and that left-greater-than-right asymmetry exists in the anterior limb of the external capsule and in the posterior limb of the internal capsule, thalamus, cerebral peduncle and temporal-parietal regions. VBA of the hemispheric asymmetry of the middle-age group revealed much less asymmetry. Regions showing age-related changes and hemispheric asymmetry from VBA were, for a majority of the findings, in conformance with ROI analysis and with the known pattern of development and age-related degradation of fiber tracks. The study shows the feasibility of the VBA of DTI indices for exploratory investigations of subtle differences in population cohorts, especially when findings are not localized and/or known a priori.     

A diffusion gradient optimization framework for spinal cord diffusion tensor imaging

The uncertainty in the estimation of diffusion model parameters in diffusion tensor imaging (DTI) can be reduced by optimally selecting the diffusion gradient directions utilizing some prior structural information. This is beneficial for spinal cord DTI, where the magnetic resonance images have low signal-to-noise ratio and thus high uncertainty in diffusion model parameter estimation. Presented is a gradient optimization scheme based on D-optimality, which reduces the overall estimation uncertainty by minimizing the Rician Cramer-Rao lower bound of the variance of the model parameter estimates. The tensor-based diffusion model for DTI is simplified to a four-parameter axisymmetric DTI model where diffusion transverse to the principal eigenvector of the tensor is assumed isotropic. Through simulations and experimental validation, we demonstrate that an optimized gradient scheme based on D-optimality is able to reduce the overall uncertainty in the estimation of diffusion model parameters for the cervical spinal cord and brain stem white matter tracts.     

Evaluation of diffusion models of fiber tracts using diffusion tensor magnetic resonance imaging

Modeling of water diffusion in white matter is useful for revealing microstructure of the brain tissue and hence diagnosis and evaluation of white matter diseases. Researchers have modeled diffusion in white matter using mathematical and mechanical analysis at the cellular level. However, less work has been devoted to evaluate these models using macroscopic real data such as diffusion tensor magnetic resonance imaging (DTMRI) data. DTMRI is a noninvasive tool for evaluating white matter microstructure by measuring random motion of water molecules referred to as diffusion. It reflects directional information of microscopic structures such as fibers. Thus, it is applicable for evaluation and modification of mathematical models of white matter. Nevertheless, a realistic relation between a fiber model and imaging data does not exist. This work opens a promising avenue for relating DTMRI data to microstructural parameters of white matter. First, we propose a strategy for relating DTMRI and fiber model parameters to evaluate mathematical models in light of real data. The proposed strategy is then applied to evaluate and extend an existing model of white matter based on clinically available DTMRI data. Next, the proposed strategy is used to estimate microstructural characteristics of fiber tracts. We illustrate this approach through its application to approximation of myelin sheath thickness and fraction of volume occupied by fibers. Using sufficiently small imaging voxels, the proposed approach is capable of estimating model parameters with desirable precision.     

Effect of B-value in revealing postinfarct myocardial microstructural remodeling using MR diffusion tensor imaging

Nonmonoexponential diffusion behavior has been previously reported to exist in some biological tissues, making quantification of diffusion tensor imaging (DTI) indices dependent on diffusion sensitivity of b-value. This study aims to investigate the effect of b-value in revealing postinfarct myocardial microstructural remodeling in ex vivo hearts. DTI scans were performed on heart samples 1, 3, 5, and 7 days after infarction induction as well as intact controls with b-values of 500 to 2500 s/mm². DTI indices, including fractional anisotropy (FA), and mean and directional diffusivities, were measured in infarct, adjacent and remote regions with zero and each non-zero b-values respectively using conventional DTI analysis. Experimental results showed that these DTI indices decreased gradually with b-values in all regions and groups. Optimal b-values were found to vary with targeted DTI indices, and could strengthen DTI ability in revealing myocardium degradation with using conventional DTI approach. Specifically, FA showed the most sensitive detection of fiber integrity degradation at moderate b-values (≈ 1500 to 2000 s/mm²), and the greatest ability of mean and directional diffusivities in monitoring diffusivity alteration occurred at relatively small b-values (≤ 1500 s/mm²) during the necrotic and fibrotic phases. These findings may provide useful information for DTI protocol parameter optimization in assessing heart microstructures at other pathological or in vivo states in the future.     

Distinguishing and quantification of the human visual pathways using high-spatial-resolution diffusion tensor tractography

Quantification of the living human visual system using MRI methods has been challenging, but several applications demand a reliable and time-efficient data acquisition protocol. In this study, we demonstrate the utility of high-spatial-resolution diffusion tensor fiber tractography (DTT) in reconstructing and quantifying the human visual pathways. Five healthy males, age range 24–37 years, were studied after approval of the institutional review board (IRB) at The University of Texas Health Science Center at Houston. We acquired diffusion tensor imaging (DTI) data with 1-mm slice thickness on a 3.0-Tesla clinical MRI scanner and analyzed the data using DTT with the fiber assignment by continuous tractography (FACT) algorithm. By utilizing the high-spatial-resolution DTI protocol with FACT algorithm, we were able to reconstruct and quantify bilateral optic pathways including the optic chiasm, optic tract, optic radiations free of contamination from neighboring white matter tracts.     

Glaucoma classification based on visual pathway analysis using diffusion tensor imaging

Most of the existing methods for diagnosing glaucoma analyze the eye with a main focus on the retina, despite the transsynaptic nature of the fiber degeneration caused by glaucoma. Thus, they ignore a significant part of the visual system represented by the visual pathway in the brain. The advances in neuroimaging, especially diffusion tensor imaging (DTI), enable the identification and characterization of white matter fibers. In this work, we propose a system based on DTI analysis of the visual pathway fibers in the optic radiation for detecting and discriminating different glaucoma entities. The optic radiation is identified semi-automatically. DTI provides information about the fiber orientation as well as a set of derived parameters describing the degree of diffusion anisotropy and diffusivity. Features for each DTI derived measure are extracted from a specified region of interest on the optic radiation. The features are grouped into three sets: Histogram, co-occurrence matrices, and Laws features. For feature selection, the features are ranked using a support vector machine classifier. The highest ranked features are used for classification. A support vector machine classifier is used for classification in a 10-fold cross validation setup. The system is applied to three age-matched subjects’ categories containing 27 healthy, 39 primary open angle glaucoma (POAG), and 18 normal tension glaucoma (NTG) subjects. The discrimination accuracy between healthy and glaucoma (POAG and NTG) subjects is 94.1% with an area under the ROC of 0.97. Classification accuracy of 92.4% is obtained for the normal and the POAG groups while it increased to 100% in case of healthy and NTG groups. In addition, the system could differentiate between glaucoma types (POAG and NTG) with an accuracy of 98.3%. A complementary analysis was performed to estimate the selection bias in the obtained accuracy. The bias ranged from 10% to 20% depending on the group pair under consideration. The classification results indicate the high performance of the system compared to retina-based glaucoma detection systems. The proposed approach utilizes visual pathway analysis rather than the conventional eye analysis which presents a new trend in glaucoma detection. Analyzing the entire visual system could provide significant information that can improve the glaucoma examination flow and treatment.     

Keyhole and zero-padding approaches for reduced-encoding diffusion tensor imaging of the mouse brains

Keyhole diffusion tensor imaging (keyhole DTI) was previously proposed in cardiac imaging to reconstruct DTI maps from the reduced phase-encoding images. To evaluate the feasibility of keyhole DTI in brain imaging, keyhole and zero-padding DTI algorithms were employed on in vivo mouse brain. The reduced phase-encoding portion, also termed as the sharing rate, was varied from 50% to 90% of the full k-space. Our data showed that zero-padding DTI resulted in decreased fractional anisotropy (FA) and decreased mean apparent diffusion coefficient (mean ADC) in white matter (WM) regions. Keyhole DTI showed a better edge preservation on mean ADC maps but not on FA maps as compared to the zero-padding DTI. When increasing the sharing rate in keyhole approach, an underestimation of FA and an over- or underestimation of mean ADC were measured in WM depending on the selected reference image. The inconsistency of keyhole DTI may add a challenge for the wide use of this modality. However, with a carefully selected directive diffusion-weighted image to serve as the reference image in the keyhole approach, this study demonstrated that one may obtain DTI indices of reduced-encoding images with high consistency to those derived with full k-space DTI.     

On the effects of dephasing due to local gradients in diffusion tensor imaging experiments: relevance for diffusion tensor imaging fiber phantoms

The effect of susceptibility differences between fluid and fibers on the properties of DTI fiber phantoms was investigated. Thereto, machine-made, easily producible and inexpensive DTI fiber phantoms were constructed by winding polyamide fibers of 15 microm diameter around a circular acrylic glass spindle. The achieved fractional anisotropy was 0.78+/-0.02. It is shown by phantom measurements and Monte Carlo simulations that the transversal relaxation time T(2) strongly depends on the angle between the fibers and the B(0) field if the susceptibilities of the fibers and fluid are not identical. In the phantoms, the measured T(2) time at 3 T decreased by 60% for fibers running perpendicular to B(0). Monte Carlo simulations confirmed this result and revealed that the exact relaxation time depends strongly on the exact packing of the fibers. In the phantoms, the measured diffusion was independent of fiber orientation. Monte Carlo simulations revealed that the measured diffusion strongly depends on the exact fiber packing and that field strength and -orientation dependencies of measured diffusion may be minimal for hexagonal packing while the diffusion can be underestimated by more than 50% for cubic packing at 3 T. To overcome these effects, the susceptibilities of fibers and fluid were matched using an aqueous sodium chloride solution (83 g NaCl per kilogram of water). This enables an orientation independent and reliable use of DTI phantoms for evaluation purposes.     

Voxel- and atlas-based analysis of diffusion tensor imaging may reveal focal axonal injuries in mild traumatic brain injury -- comparison with diffuse axonal injury

Background

The diagnosis and management of mild traumatic brain injury (MTBI) continue to be subjects of debate, with varying opinions regarding the extent to which tissue-based impairments versus the impacts of other stressors cause ongoing disability. Detecting areas of the brain with abnormalities that can explain symptoms and behavior in patients with MTBI is important in order to confirm the diagnosis of MTBI.

Methods

In this study, we calculated diffusion maps from results of diffusion tensor imaging (DTI) performed in an apparently healthy control group. We then compared these maps with those of patients with MTBI (MTBI group) or diffuse axonal injury (DAI group). All diffusion maps were normalized to the International Consortium for Brain Mapping atlas for atlas-based analysis and were segmented and normalized by the Diffeomorphic Anatomical Registration Through Exponentiated Lie tool in SPM8 to reduce misregistration.

Results

All diffusion measures in the DAI group were lower than in the control group. There were significant differences in the body and splenium of the corpus callosum, fornix and right cerebral peduncle in the DAI group compared with the control group (P<.001). The MTBI group had higher axial diffusivity than the control group in the right corticospinal tract, left medial lemniscus, left inferior cerebellar peduncle, bilateral anterior limb of the internal capsule, right anterior corona radiata, bilateral cingulum (cingulate gyrus) and left superior frontooccipital fasciculus (P<.05).

Conclusions

Voxel- and atlas-based analysis of DTI might suggest that patients with MTBI have focal axonal injury and that the pathophysiology is significantly different from that of DAI. These findings will help in the diagnosis of patients with MTBI.     

Study of myocardial fiber pathway using magnetic resonance diffusion tensor imaging

The purpose of this study was to investigate myocardial fiber pathway distribution in order to provide supplemental information on myocardial fiber architecture and cardiac mechanics. Diffusion tensor imaging (DTI) with medium diffusion resolution (15 directions) was performed on normal canine heart samples (N=6) fixed in formalin. With the use of diffusion tensor fiber tracking, left ventricle (LV) myocardial fiber pathways and helix angles were computed pixel by pixel at short-axis slices from base to apex. Distribution of DTI-tracked fiber pathway length and number was analyzed quantitatively as a function of fiber helix angle in step of 9 degrees . The long fiber pathways were found to have small helix angles. They are mostly distributed in the middle myocardium and run circumferentially. Fiber pathways tracked at the middle and upper LV are generally longer than those near the apex. Majority of fiber pathways have small helix angles between -20 degrees and 20 degrees , dominating the fiber architecture in myocardium. Likely, such myocardial fiber pathway measurement by DTI may reflect the spatial connectiveness or connectivity of elastic myofiber bundles along their preferential pathway of electromechanical activation. The dominance of the long and circumferentially running fiber pathways found in the study may explain the circumferential predominance in left ventricular contraction.     

Alteration of diffusion tensor parameters in postmortem brain

In autopsy of humans, there is usually an interval of hours to days between death and tissue fixation, during which the cadaver is stored below room temperature to retard tissue autolysis. We have attempted to model this process and evaluate the alteration in diffusion indices of the postmortem brain in pigs, which were kept at 4°C. The pigs were scanned prior to death and at 3, 6, 9, 12, 18, 24, 30, 36, 42, 48 and 72 h postmortem. Regions of interest were placed in the corpus callosum, internal capsule, periventricular and subcortical white matter anteriorly and posteriorly. There was a slight increase in fractional anisotropy (FA) in the first 3 h postmortem. The FA remained stable up to 72 h postmortem. There was a marked decrease in trace, eigenmajor (λmajor), eigenmedium (λmedium) and eigenminor (λminor), particularly in the first 3 h following death. This study supports the utility of measuring diffusion anisotropy if the time elapsed between death and tissue fixation is within 3 days. However, trace and eigenvalues decreased markedly within the first few hours postmortem. Therefore trace and eigenvalues obtained from ex vivo studies cannot be extrapolated to in vivo studies.     

Validation of the anisotropy index ellipsoidal area ratio in diffusion tensor imaging

A new diffusion anisotropy index, ellipsoidal area ratio (EAR), was described recently and proved to be less noise-sensitive than fractional anisotropy (FA) by theory and simulation. Here we show that EAR has higher signal-to-noise ratios than FA in average diffusion tensor imaging data from 40 normal subjects. EAR was also more sensitive than FA in detecting white matter abnormalities in a patient with widespread diffuse axonal injury. Monte Carlo simulation showed that EAR's mean values are more biased by noise than FA when anisotropy is small, both for single fiber tracts and when fiber tracts cross. However, the improved signal-to-noise ratio of EAR relative to FA suggests that EAR may be a superior measure of anisotropy both in quantifying both deep white matter with relatively uniform fiber tracts and pericortical white matter structure with relatively low anisotropy and fiber crossings.     

In vivo structural analysis of articular cartilage using diffusion tensor magnetic resonance imaging

Purpose

The articular cartilage is a small tissue with a matrix structure of three layers between which the orientation of collagen fiber differs. A diffusion-weighted twice-refocused spin-echo echo-planar imaging (SE-EPI) sequence was optimized for the articular cartilage, and the structure of the three layers of human articular cartilage was imaged in vivo from diffusion tensor images.

Materials and Methods

The subjects imaged were five specimens of swine femur head after removal of the flesh around the knee joint, five specimens of swine articular cartilage with flesh present and the knee cartilage of five adult male volunteers. Based on diffusion-weighted images in six directions, the mean diffusivity (MD) and the fractional anisotropy (FA) values were calculated.

Results

Diffusion tensor images of the articular cartilage were obtained by sequence optimization. The MD and FA value of the specimens (each of five examples) under different conditions were estimated. Although the articular cartilage is a small tissue, the matrix structure of each layer in the articular cartilage was obtained by SE-EPI sequence with GRAPPA. The MD and FA values of swine articular cartilage are different between the synovial fluid and saline. In human articular cartilage, the load of the body weight on the knee had an effect on the FA value of the surface layer of the articular cartilage.

Conclusion

This method can be used to create images of the articular cartilage structure, not only in vitro but also in vivo. Therefore, it is suggested that this method should support the elucidation of the in vivo structure and function of the knee joint and might be applied to clinical practice.     

Cerebral infarction associated with moyamoya disease: histogram-based quantitative analysis of diffusion tensor imaging -- a preliminary study

Moyamoya disease (MMD) is a rare disorder of unknown etiology in which terminal portions of the internal carotid arteries become steno-occlusive, with fine collateral "moyamoya vessels" formed secondarily, resulting in serial ischemic strokes throughout its clinical course. Whole-brain histogram (WBH) of diffusion tensor imaging (WBH-DTI) is an analytical tool whose feasibility has been ascertained in various pathologies. To elucidate whether WBH-DTI could detect any difference between ischemic MMD and normal controls, we examined 27 consecutive MMD patients without hemorrhage and 48 normal controls in this prospective study using a 3.0-T magnetic resonance scanner. WBHs of fractional anisotropy (FA) (WBH-FA) and mean diffusivity (MD) (WBH-MD) were compared among three groups: Group 1, MMD patients with infarct (n=15); Group 2, MMD patients without infarct (n=12); and Group 3, normal controls (n=48). Group 1 showed significantly higher peak height and significantly lower mean value on WBH-FA, as well as significantly lower peak height and significantly higher mean value on WBH-MD, compared with Groups 2 and 3. No significant difference was seen in parameters at either WBH-FA or WBH-MD between Groups 2 and 3. These results might reflect the pathological severity of each group, and WBH-DTI could feasibly detect differences between ischemic MMD with infarction and MMD without infarction and normal controls.     

Optimal real-time estimation in diffusion tensor imaging

Diffusion tensor imaging (DTI) constitutes the most used paradigm among the diffusion-weighted magnetic resonance imaging (DW-MRI) techniques due to its simplicity and application potential. Recently, real-time estimation in DW-MRI has deserved special attention, with several proposals aiming at the estimation of meaningful diffusion parameters during the repetition time of the acquisition sequence. Specifically focusing on DTI, the underlying model of the noise present in the acquired data is not taken into account, leading to a suboptimal estimation of the diffusion tensor. In this paper, we propose an optimal real-time estimation framework for DTI reconstruction in single-coil acquisitions. By including an online estimation of the time-changing noise variance associated to the acquisition process, the proposed method achieves the sequential best linear unbiased estimator. Results on both synthetic and real data show that our method outperforms those so far proposed, reaching the best performance of the existing proposals by processing a substantially lower number of diffusion images.     

An image-processing toolset for diffusion tensor tractography

Diffusion tensor imaging (DTI)-based fiber tractography holds great promise in delineating neuronal fiber tracts and, hence, providing connectivity maps of the neural networks in the human brain. An array of image-processing techniques has to be developed to turn DTI tractography into a practically useful tool. To this end, we have developed a suite of image-processing tools for fiber tractography with improved reliability. This article summarizes the main technical developments we have made to date, which include anisotropic smoothing, anisotropic interpolation, Bayesian fiber tracking and automatic fiber bundling. A primary focus of these techniques is the robustness to noise and partial volume averaging, the two major hurdles to reliable fiber tractography. Performance of these techniques has been comprehensively examined with simulated and in vivo DTI data, demonstrating improvements in the robustness and reliability of DTI tractography.     

Diffusional kurtosis imaging of cingulate fibers in Parkinson disease: Comparison with conventional diffusion tensor imaging

Objective

The pathological changes in Parkinson disease begin in the brainstem; reach the limbic system and ultimately spread to the cerebral cortex. In Parkinson disease (PD) patients, we evaluated the alteration of cingulate fibers, which comprise part of the limbic system, by using diffusional kurtosis imaging (DKI).

Methods

Seventeen patients with PD and 15 age-matched healthy controls underwent DKI with a 3-T MR imager. Diffusion tensor tractography images of the anterior and posterior cingulum were generated. The mean kurtosis (MK) and conventional diffusion tensor parameters measured along the images in the anterior and posterior cingulum were compared between the groups. Receiver operating characteristic (ROC) analysis was also performed to compare the diagnostic abilities of the MK and conventional diffusion tensor parameters.

Results

The MK and fractional anisotropy (FA) in the anterior cingulum were significantly lower in PD patients than in healthy controls. The area under the ROC curve was 0.912 for MK and 0.747 for FA in the anterior cingulum. MK in the anterior cingulum had the best diagnostic performance (mean cutoff, 0.967; sensitivity, 0.87; specificity, 0.94).

Conclusions

DKI can detect alterations of the anterior cingulum in PD patients more sensitively than can conventional diffusion tensor imaging. Use of DKI can be expected to improve the ability to diagnose PD.     

Removal of partial volume averaging with free water in MR diffusion tensor imaging using inversion recovery for b0 image

Purpose

To remove the partial volume averaging effect of free water in MR diffusion imaging of neural tissues by use of the fluid attenuated inversion recovery (FLAIR) without the penalty of an extended scan time.

Materials and methods

The magnetic resonance images were obtained from a normal volunteer in a coronal slice orientation at 3 T with the 20-channel rf coil. In diffusion imaging only the b0 images were obtained with the FLAIR contrast while the diffusion weighted images were obtained without the FLAIR contrast. A composition of FLAIR b0 and non-FLAIR diffusion weighted images was used in calculating the diffusion tensor and fractional anisotropy after compensating the reduced signal amplitude due to the inversion recovery in the FLAIR b0 images. The fractional anisotropy of the non-FLAIR, FLAIR, and the composite methods were analyzed for the mean and histogram in the corpus callosum, cervical spine, and the fornix tracts.

Results

The partial volume averaging effect was observed in the corpus callosum, the cervical spine, and the fornix tracts in the non-FLAIR b0 and diffusion images. The partial volume averaging effect was removed in the FLAIR diffusion images which took more than twice the scan time than the non-FLAIR diffusion imaging. The proposed composite FLAIR diffusion imaging removed the partial volume averaging effect as in the FLAIR diffusion imaging. The distribution of the FA histogram was very different between the non-FLAIR and FLAIR diffusion images, while it was very similar between the FLAIR and the composite FLAIR after correcting the white matter signal in the FLAIR b0 images.

Conclusions

The proposed composite FLAIR diffusion imaging method was equally effective in removing the partial volume averaging effect as the FLAIR diffusion imaging at a limited increase of the scan time since only a small number of b0 images needed to be obtained with the FLAIR contrast.     

Geometric analysis of the b-dependent effects of Rician signal noise on diffusion tensor imaging estimates and determining an optimal b value

The optimal diffusion weighting (DW) factor, b, for use in diffusion tensor imaging (DTI) studies remains uncertain. In this study, the geometric relations of DW quantities are examined, in particular, the effects of Rician noise in the measured magnetic resonance signal. This geometric analysis is used to make theoretical predictions for selecting a b value to reduce the influence of noise. It is shown that the optimal b value for DTI studies in healthy human parenchyma is approximately b=1200 s mm⁻², with a simple relation given as well for a given expected apparent diffusion coefficient. Monte-Carlo simulations on sets of realistic DTI measures are then performed, verifying the optimal DW for minimizing estimate errors. The effects of noise on various DTI parameters such as anisotropy indices (fractional anisotropy and scaled relative anisotropy), mean diffusivity, radial diffusivity, eigenvalues and the direction of the first eigenvector are investigated as well.