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Subcortical nuclei and other deep brain structures are known to play an important role in the regulation of the central and peripheral nervous systems. It can be difficult to identify and delineate many of these nuclei and their finer subdivisions in conventional MRI due to their small size, buried location, and often subtle contrast compared to neighboring tissue. To address this problem, we applied a multi-modal approach in ex vivo non-human primate (NHP) brain that includes high-resolution mean apparent propagator (MAP)-MRI and five different histological stains imaged with high-resolution microscopy in the brain of the same subject. By registering these high-dimensional MRI data to high-resolution histology data, we can map the location, boundaries, subdivisions, and micro-architectural features of subcortical gray matter regions in the macaque monkey brain. At high spatial resolution, diffusion MRI in general, and MAP-MRI in particular, can distinguish a large number of deep brain structures, including the larger and smaller white matter fiber tracts as well as architectonic features within various nuclei. Correlation with histology from the same brain enables a thorough validation of the structures identified with MAP-MRI. Moreover, anatomical details that are evident in images of MAP-MRI parameters are not visible in conventional T 1 -weighted images. We also derived subcortical template "SC21" from segmented MRI slices in three-dimensions and registered this volume to a previously published anatomical template with cortical parcellation (Reveley et al., 2017; Saleem and Logothetis, 2012), thereby integrating the 3D segmentation of both cortical and subcortical regions into the same volume. This newly updated three-dimensional D99 digital brain atlas (V2.0) is intended for use as a reference standard for macaque neuroanatomical, functional, and connectional imaging studies, involving both cortical and subcortical targets. The SC21 and D99 digital templates are available as volumes and surfaces in standard NIFTI and GIFTI formats., (Copyright © 2021. Published by Elsevier Inc.)

Introduction: The aim of our study was to evaluate intracerebral network changes in epilepsy patients demonstrating secondary bilateral synchrony (SBS) in EEG by applying a new Diffusion Tensor Imaging (DTI) method using an energy-based global tracking algorithm., Materials and Methods: 10 MRI negative epilepsy patients demonstrating SBS in 10-20 surface EEG were included. EEG findings were analyzed for irritative zones characterized by focal interictal epileptiform discharges (IEDs) triggering SBS. In addition, DTI including an energy-based global tracking algorithm was applied to analyze fiber tract alterations in irritative zones. To measure the deviation of a certain cortical connection in comparison to healthy controls, normalized differences of fiber tract streamline counts (SC) and their p-values were evaluated in comparison to corresponding fibers of the control group., Results: In 6 patients the irritative zone initiating SBS was located in the frontal lobe, in 3 patients in the temporal lobe and in 1 patient in the region surrounding the right central sulcus. All patients demonstrated significantly altered SC in brain lobes where the irritative zone triggering SBS was located (p ≤ 0.05). Seven out of 10 patients demonstrated SC alterations in tracts connecting brain lobes between the ipsilateral and the contralateral hemisphere (p ≤ 0.05)., Conclusion: Our data demonstrate that alterations in fiber tracts in irritative zones triggering SBS are not necessarily associated with intracerebral lesions visible in high resolution MRI. Our study gives evidence that diffusion tensor imaging is a promising non-invasive additive tool for intracerebral network analyses even in MRI-negative epilepsy patients., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Background: The temporal lobe is an important and complex anatomic region of the brain. Accurate knowledge of anatomic relationships becomes extremely relevant when deciding surgical strategy, such as epilepsy or oncologic surgery, involving this lobe. To our knowledge, there is no strong literature highlighting the relationship between white matter tracts and craniometric landmarks applied to temporal lobe surgery. We aim to describe the topographic relationship between the craniometric points and white matter tracts of the temporal lobe through dissection of cadaveric specimens and describe the potential preoperative usefulness of diffusion tensor imaging in relation to the anatomic features found during the dissections., Methods: Fifteen formalin-fixed whole cadaveric heads were dissected by the Klingler technique in a stepwise manner across the temporal and sphenoid bone windows. The white matter pathways were identified in their different planes and their position was described in relation to craniometric landmarks. Diffusion tensor studies were performed in 2 healthy volunteers to analyze the temporal fasciculi in vivo., Results: We identified the topographic relationships between craniometric points and relevant association tracts that lie within the cranial corridors (superior and inferior frontal, parietal, occipital, sphenoidal, and temporal). Important landmarks were defined in correspondence to these different fasciculi., Conclusions: Through this kind of microsurgical anatomic study, a better understanding of the different anatomic layers of the temporal region might be achieved. This factor is essential in planning adequate surgery and strategies to operate in the temporal lobe, improving surgical results and minimizing functional deficits., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Magnetoencephalography (MEG) is a noninvasive imaging method for localization of focal epileptiform activity in patients with epilepsy. Diffusion tensor imaging (DTI) is a noninvasive imaging method for measuring the diffusion properties of the underlying white matter tracts through which epileptiform activity is propagated. This study investigates the relationship between the cerebral functional abnormalities quantified by MEG coherence and structural abnormalities quantified by DTI in mesial temporal lobe epilepsy (mTLE). Resting state MEG data was analyzed using MEG coherence source imaging (MEG-CSI) method to determine the coherence in 54 anatomical sites in 17 adult mTLE patients with surgical resection and Engel class I outcome, and 17 age- and gender- matched controls. DTI tractography identified the fiber tracts passing through these same anatomical sites of the same subjects. Then, DTI nodal degree and laterality index were calculated and compared with the corresponding MEG coherence and laterality index. MEG coherence laterality, after Bonferroni adjustment, showed significant differences for right versus left mTLE in insular cortex and both lateral orbitofrontal and superior temporal gyri (p < 0.017). Likewise, DTI nodal degree laterality, after Bonferroni adjustment, showed significant differences for right versus left mTLE in gyrus rectus, insular cortex, precuneus and superior temporal gyrus (p < 0.017). In insular cortex, MEG coherence laterality correlated with DTI nodal degree laterality ([Formula: see text] in the cases of mTLE. None of these anatomical sites showed statistically significant differences in coherence laterality between right and left sides of the controls. Coherence laterality was in agreement with the declared side of epileptogenicity in insular cortex (in 82 % of patients) and both lateral orbitofrontal (88 %) and superior temporal gyri (88 %). Nodal degree laterality was also in agreement with the declared side of epileptogenicity in gyrus rectus (in 88 % of patients), insular cortex (71 %), precuneus (82 %) and superior temporal gyrus (94 %). Combining all significant laterality indices improved the lateralization accuracy to 94 % and 100 % for the coherence and nodal degree laterality indices, respectively. The associated variations in diffusion properties of fiber tracts quantified by DTI and coherence measures quantified by MEG with respect to epileptogenicity possibly reflect the chronic microstructural cerebral changes associated with functional interictal activity. The proposed methodology for using MEG and DTI to investigate diffusion abnormalities related to focal epileptogenicity and propagation may provide a further means of noninvasive lateralization.

Introduction: Q-ball imaging (QBI) is one of the typical data models for quantifying white matter (WM) anisotropy in diffusion-weighted MRI (DwMRI) studies. Brain and spinal investigation by high angular resolution DwMRI (high angular resolution imaging (HARDI)) protocols exhibits higher angular resolution in diffusion imaging compared to low angular resolution models, although with longer acquisition times. We aimed to assess the difference between QBI-derived anisotropy values from high and low angular resolution DwMRI protocols and their potential advantages or shortcomings in neuroradiology., Methods: Brain DwMRI data sets were acquired in seven healthy volunteers using both HARDI (b = 3000 s/mm(2), 54 gradient directions) and low angular resolution (b = 1000 s/mm(2), 32 gradient directions) acquisition schemes. For both sequences, tract of interest tractography and generalized fractional anisotropy (GFA) measures were extracted by using QBI model and were compared between the two data sets., Results: QBI tractography and voxel-wise analyses showed that some WM tracts, such as corpus callosum, inferior longitudinal, and uncinate fasciculi, were reconstructed as one-dominant-direction fiber bundles with both acquisition schemes. In these WM tracts, mean percent different difference in GFA between the two data sets was less than 5%. Contrariwise, multidirectional fiber bundles, such as corticospinal tract and superior longitudinal fasciculus, were more accurately depicted by HARDI acquisition scheme., Conclusion: Our results suggest that the design of optimal DwMRI acquisition protocols for clinical investigation of WM anisotropy by QBI models should consider the specific brain target regions to be explored, inducing researchers to a trade-off choice between angular resolution and acquisition time.

While major depression has been linked to changes in white matter architecture, it remains unclear whether risk factors for depression are directly associated with these alterations. We reexamined white matter fiber tracts in individuals with depressive symptoms and investigated the connection between genetic and environmental risk for depression and structural changes in the brain. We included 19,183 participants from the UK Biobank imaging cohort, with depression status and adverse life experience based on questionnaire data and genetic liability for depression quantified by polygenic scores. The integrity of 27 white matter tracts was assessed using mean fractional anisotropy derived from diffusion magnetic resonance imaging. White matter integrity was reduced, particularly in thalamic and intracortical fiber tracts, in individuals with depressive symptoms, independent of current symptom status. In a group of healthy individuals without depression, increasing genetic risk and increasing environmental risk were associated with reduced integrity in relevant fiber tracts, particularly in thalamic radiations. This association was stronger than expected based on statistical dependencies between samples, as confirmed by subsequent in silico simulations and permutation tests. White matter alterations in thalamic and association tracts are associated with depressive symptoms and genetic risk for depression in unaffected individuals, suggesting an intermediate phenotype at the brain level. [ABSTRACT FROM AUTHOR]

White matter makes up about fifty percent of the human brain. Maturation of white matter accompanies biological development and undergoes the most dramatic changes during childhood and adolescence. Despite the advances in neuroimaging techniques, controversy concerning spatial, and temporal patterns of myelination, as well as the degree to which the microstructural characteristics of white matter can vary in a healthy brain as a function of age, gender and cognitive abilities still exists. In a selective review we describe methods of assessing myelination and evaluate effects of age and gender in nine major fiber tracts, highlighting their role in higher-order cognitive functions. Our findings suggests that myelination indices vary by age, fiber tract, and hemisphere. Effects of gender were also identified, although some attribute differences to methodological factors or social and learning opportunities. Findings point to further directions of research that will improve our understanding of the complex myelination-behavior relation across development that may have implications for educational and clinical practice. [ABSTRACT FROM AUTHOR]

Purpose: The arcuate fasciculus (AF) is a white matter fibers tract that links the lateral temporal with the frontal cortex. The AF can be divided into three components: two superficial indirect short tracts (anterior and posterior) and one deep direct long tract. Both DTI and white matter dissections studies find differences regarding the anatomy of the AF, especially its cortical connections. This paper aims at providing a comprehensive anatomical classification of the AF, using the terminologia anatomica. Methods: Articles (n = 478) were obtained from a systematical PRISMA review. Studies which focused on primates, unhealthy subjects, as well as studies without cortical termination description and review articles were excluded from the analysis. One hundred and ten articles were retained for full-text examination, of which 19 finally fulfilled our criteria to be included in this review. Results: We classified main descriptions and variations of each segment of the AF according to fiber orientation and cortical connections. Three types of connections were depicted for each segment of the AF. Concerning the anterior segment, most of the frontal fibers (59.35%) ran from the ventral portion of the precentral gyrus and the posterior part of the pars opercularis, to the supramarginal gyrus (85.0%). Main fibers of the posterior segment of the AF ran from the posterior portion of the middle temporal gyrus (100%) to the angular gyrus (92.0%). In main descriptions of the long segment of the AF, fibers ran from both the ventral portion of the precentral gyrus and posterior part of the pars opercularis (63.9%) to the middle and inferior temporal gyrus (60.3%). Minor subtypes were described in detail in the article. Conclusion: We provide a comprehensive classification of the anatomy of the AF, regarding the orientation and cortical connections of its fibers. Although fiber orientation is very consistent, cortical endings of the AF may be different from one study to another, or from one individual to another which is a key element to understand the anatomical basis of current models of language or to guide intraoperative stimulation during awake surgery. [ABSTRACT FROM AUTHOR]

Aerobic fitness has been found to play a positive role in brain and cognitive health of children. Yet, many of the neural biomarkers related to aerobic fitness remain unknown. Here, using diffusion tensor imaging (DTI), we demonstrated that higher aerobic fitness was related to greater estimates of white matter microstructure in children. Higher fit 9- and 10-year-old children showed greater fractional anisotropy (FA) in sections of the corpus callosum, corona radiata, and superior longitudinal fasciculus, compared to lower fit children. The FA effects were primarily characterized by aerobic fitness differences in radial diffusivity (RD), thereby raising the possibility that estimates of myelination may vary as a function of individual differences in fitness during childhood. White matter structure may be another potential neural mechanism of aerobic fitness that assists in efficient communication between gray matter regions as well as the integration of regions into networks.

We present a visualization technique for brain fiber tracts from DTI data that provides insight into the structure of white matter through visual abstraction. We achieve this abstraction by analyzing the local similarity of tract segment directions at different scales using a stepwise increase of the search range. Next, locally similar tract segments are moved toward each other in an iterative process, resulting in a local contraction of tracts perpendicular to the local tract direction at a given scale. This not only leads to the abstraction of the global structure of the white matter as represented by the tracts, but also creates volumetric voids. This increase of empty space decreases the mutual occlusion of tracts and, consequently, results in a better understanding of the brain’s three-dimensional fiber tract structure. Our implementation supports an interactive and continuous transition between the original and the abstracted representations via various scale levels of similarity. We also support the selection of groups of tracts, which are highlighted and rendered with the abstracted visualization as context. [ABSTRACT FROM AUTHOR]

Over 2 million people are diagnosed with concussion each year in the USA, resulting in substantial individual and societal burdens. Although 'routine' clinical neuroimaging is useful for the diagnosis of more severe forms of traumatic brain injury, it is insensitive for detecting pathology associated with concussion. Diffusion tensor imaging (DTI) and blood-oxygenation-level-dependent (BOLD) resting-state functional connectivity magnetic resonance imaging (rs-fMRI) are techniques that allow for investigation of brain structural and functional connectivity patterns. DTI and rs-fMRI may be more sensitive than routine neuroimaging for detecting brain sequelae of concussion. This review summarizes recent DTI and rs-fMRI findings of altered structural and functional connectivity patterns in concussed patients. [ABSTRACT FROM AUTHOR]

Diffusion weighted imaging (DWI) has provided unparalleled insight into the microscopic structure and organization of the central nervous system. Diffusion tensor imaging (DTI) and other models of the diffusion MRI signal extract microstructural properties of tissues with relevance to the normal and injured brain. Despite the prevalence of such techniques and applications, accurate and large-scale validation has proven difficult, particularly in the human brain. In this report, human brain sections obtained from a digital public brain bank were employed to quantify anisotropy and fiber orientation using structure tensor analysis. The derived maps depict the intricate complexity of white matter fibers at a resolution not attainable with current DWI experiments. Moreover, the effects of multiple fiber bundles (i.e. crossing fibers) and intravoxel fiber dispersion were demonstrated. Examination of the cortex and hippocampal regions validated specific features of previous in vivo and ex vivo DTI studies of the human brain. Despite the limitation to two dimensions, the resulting images provide a unique depiction of white matter organization at resolutions currently unattainable with DWI. The method of analysis may be used to validate tissue properties derived from DTI and alternative models of the diffusion signal.

Aerobic fitness has been found to play a positive role in brain and cognitive health of children. Yet, many of the neural biomarkers related to aerobic fitness remain unknown. Here, using diffusion tensor imaging, we demonstrated that higher aerobic fitness was related to greater estimates of white matter microstructure in children. Higher fit 9- and 10-year-old children showed greater fractional anisotropy (FA) in sections of the corpus callosum, corona radiata, and superior longitudinal fasciculus, compared to lower fit children. The FA effects were primarily characterized by aerobic fitness differences in radial diffusivity, thereby raising the possibility that estimates of myelination may vary as a function of individual differences in fitness during childhood. White matter structure may be another potential neural mechanism of aerobic fitness that assists in efficient communication between gray matter regions as well as the integration of regions into networks. [ABSTRACT FROM AUTHOR]

Abstract: Diffusion tensor tractography is increasingly used to examine structural connectivity in the brain in various conditions, but its test–retest reliability is understudied. The main purposes of this study were to evaluate 1) the reliability of quantitative measurements of diffusion tensor tractography and 2) the effect on reliability of the number of gradient sampling directions and scan repetition. Images were acquired from ten healthy participants. Ten fiber regions of nine major fiber tracts were reconstructed and quantified using six fiber variables. Intra- and inter-session reliabilities were estimated using intraclass correlation coefficient (ICC) and coefficient of variation (CV), and were compared to pinpoint major error sources. Additional pairwise comparisons were made between the reliability of images with 30 directions and NEX 2 (DTI30-2), 30 directions and NEX 1 (DTI30-1), and 15 directions and NEX 2 (DTI15-2) to determine whether increasing gradient directions and scan repetition improved reliability. Of the 60 tractography measurements, 43 showed intersession CV≤10%, ICC≥.70, or both for DTI30-2, 40 measurements for DTI30-1, and 37 for DTI15-2. Most of the reliable measurements were associated with the tracts corpus callosum, cingulum, cerebral peduncular fibers, uncinate fasciculus, and arcuate fasciculus. These reliable measurements included factional anisotropy (FA) and mean diffusivity of all 10 fiber regions. Intersession reliability was significantly worse than intra-session reliability for FA, mean length, and tract volume measurements from DTI15-2, indicating that the combination of MRI signal variation and physiological noise/change over time was the major error source for this sequence. Increasing the number of gradient directions from 15 to 30 while controlling the scan time, significantly affected values for all six variables and reduced intersession variability for mean length and tract volume measurements. Additionally, while increasing scan repetition from 1 to 2 had no significant effect on the reliability for DTI with 30 directions, this significantly reduced the upward bias in FA values from all 10 fiber regions and fiber count, mean length, and tract volume measurements from 5 to 7 fiber regions. In conclusion, diffusion tensor tractography provided many measurements with high test–retest reliability across different fiber variables and various fiber tracts even for images with 15 directions (NEX 2). Increasing the number of gradient directions from 15 to 30 with equivalent scan time reduced variability whereas increasing repetition from 1 to 2 for 30-direction DTI improved the accuracy of tractography measurements. [Copyright &y& Elsevier]

Abstract: Objective: In bipolar disorder, white matter abnormalities have been reported with region-of-interest and voxel-based methods; however, deficits in specific white matter tracts cannot be localized by these methods. Therefore, in this study, we aimed to investigate the white matter tracts that mediate connectivity of the frontal cortex using diffusion tensor imaging (DTI) tractography. Methods: Eighteen patients with bipolar disorder and sixteen age- and gender-matched healthy subjects underwent DTI examinations. Frontal cortex white matter tracts, including the anterior thalamic radiation (ATR), uncinate fasciculus (UF), superior longitudinal fasciculus (SLF), cingulum, and inferior fronto-occipital fasciculus (IFO) were reconstructed by DTI tractography, and we calculated the mean fractional anisotropy (FA) for each fiber tract. The values were compared between groups by repeated measures analysis of variance with age and gender as covariates, which allowed us to investigate significant differences between the tracts. Results: When compared with healthy controls, the patients with bipolar disorder showed significantly decreased FA in the ATR and UF, and a trend towards lower FA in the SLF and cingulum. However, there were no FA differences between groups in the IFO. Conclusions: Our study indicates that bipolar patients show abnormalities within white matter tracts connecting the frontal cortex with the temporal and parietal cortices and the fronto-subcortical circuits. These findings suggest that alterations in the connectivity of white matter tracts in the frontal cortex might contribute to the neuropathology of bipolar disorder. [Copyright &y& Elsevier]

Abstract: In recent years, diffusion tensor imaging (DTI) has become the modality of choice to investigate white matter pathology in the developing brain. To study neonate Krabbe disease with DTI, we evaluate the performance of linear and non-linear DTI registration algorithms for atlas based fiber tract analysis. The DTI scans of 10 age-matched neonates with infantile Krabbe disease are mapped into an atlas for the analysis of major fiber tracts — the genu and splenium of the corpus callosum, the internal capsules tracts and the uncinate fasciculi. The neonate atlas is based on 377 healthy control subjects, generated using an unbiased diffeomorphic atlas building method. To evaluate the performance of one linear and seven nonlinear commonly used registration algorithms for DTI we propose the use of two novel evaluation metrics: a regional matching quality criterion incorporating the local tensor orientation similarity, and a fiber property profile based metric using normative correlation. Our experimental results indicate that the whole tensor based registration method within the DTI-ToolKit (DTI-TK) shows the best performance for our application. [Copyright &y& Elsevier]

Abstract: 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. [Copyright &y& Elsevier]

Abstract: Obsessive–compulsive disorder (OCD) is thought to involve large-scale brain systems but the anatomical connectivity via association fibers has not been specifically investigated yet. We evaluated organization and directionality of the major fiber bundles in a subpopulation of OCD, including washers and checkers who presented decision making deficits, by measuring MRI parameters related to water self-diffusion (Fractional Anisotropy, FA) and fiber directionality (Principal Diffusion Direction, PDD) in 15 OCD and 16 control subjects. OCD patients showed significantly lower FA and altered PDD along the corpus callosum, cingulum, superior longitudinal fasciculus, and inferior fronto-occipital fasciculus bilaterally. The track-based analysis of the inferior fronto-occipital fasciculus confirmed a significant bilateral FA reduction. Lower FA values in the inferior fronto-occipital fasciculus, superior longitudinal fasciculus and corpus callosum correlated with symptom severity and neuropsychological performance. This multi-parameter MRI study revealed specific white matter abnormalities in OCD suggesting tract disorganization as main feature, reflected by local changes in fiber directionality. This altered anatomical connectivity might play a specific role in OCD pathophysiology. [Copyright &y& Elsevier]

Abstract: Both post-mortem and neuroimaging studies have contributed significantly to what we know about the brain and schizophrenia. MRI studies of volumetric reduction in several brain regions in schizophrenia have confirmed early speculations that the brain is disordered in schizophrenia. There is also a growing body of evidence suggesting that a disturbance in connectivity between different brain regions, rather than abnormalities within the separate regions themselves, are responsible for the clinical symptoms and cognitive dysfunctions observed in this disorder. Thus an interest in white matter fiber tracts, subserving anatomical connections between distant, as well as proximal, brain regions, is emerging. This interest coincides with the recent advent of diffusion tensor imaging (DTI), which makes it possible to evaluate the organization and coherence of white matter fiber tracts. This is an important advance as conventional MRI techniques are insensitive to fiber tract direction and organization, and have not consistently demonstrated white matter abnormalities. DTI may, therefore, provide important new information about neural circuitry, and it is increasingly being used in neuroimaging studies of psychopathological disorders. Of note, in the past five years 18 DTI studies in schizophrenia have been published, most describing white matter abnormalities. Questions still remain, however, regarding what we are measuring that is abnormal in this disease, and how measures obtained using one method correspond to those obtained using other methods? Below we review the basic principles involved in MR-DTI, followed by a review of the different methods used to evaluate diffusion. Finally, we review MR-DTI findings in schizophrenia. [Copyright &y& Elsevier]

Structural high‐resolution imaging of the brainstem can be of high importance in clinical practice. However, ultra‐high field magnetic resonance imaging (MRI) is still restricted in use due to limited availability. Therefore, quantitative MRI techniques (quantitative susceptibility mapping [QSM], relaxation measurements [ R2*, R1], diffusion tensor imaging [DTI]) and T2‐ and proton density (PD)‐weighted imaging in the human brainstem at 3 T and 7 T are compared. Five healthy volunteers (mean age: 21.5 ± 1.9 years) were measured at 3 T and 7 T using multi‐echo gradient echo sequences for susceptibility mapping and R2* relaxometry, magnetization‐prepared 2 rapid acquisition gradient echo sequences for R1 relaxometry, turbo‐spin echo sequences for PD‐ and T2‐weighted imaging and readout‐segmented echo planar sequences for DTI. Susceptibility maps were computed using Laplacian‐based phase unwrapping, V‐SHARP for background field removal and the streaking artifact reduction for QSM algorithm for dipole inversion. Contrast‐to‐noise ratios (CNRs) were determined at 3 T and 7 T in ten volumes of interest (VOIs). Data acquired at 7 T showed higher CNR. However, in four VOIs, lower CNR was observed for R2* at 7 T. QSM was shown to be the contrast with which the highest number of structures could be identified. The depiction of very fine tracts such as the medial longitudinal fasciculus throughout the brainstem was only possible in susceptibility maps acquired at 7 T. DTI effectively showed the main tracts (crus cerebri, transverse pontine fibers, corticospinal tract, middle and superior cerebellar peduncle, pontocerebellar tract, and pyramid) at both field strengths. Assessing the brainstem with quantitative MRI methods such as QSM, R2*, as well as PD‐ and T2‐weighted imaging with great detail, is also possible at 3 T, especially when using susceptibility mapping calculated from a gradient echo sequence with a wide range of echo times from 10.5 to 52.5 ms. However, tracing smallest structures strongly benefits from imaging at ultra‐high field. [ABSTRACT FROM AUTHOR]

The authors comment on the article "Interpreting functional diffusion tensor imaging," by J. A. Autio and R. E. Roberts in the 2014 issue regarding their article on functional diffusion tensor imaging (fDTI) entitled "Functional Diffusion Tensor Imaging at 3 Tesla" in the 2013 issue. They say that Autio and Roberts suggest that blood-oxygen-level dependent (BOLD) signal from gray matter could partly explain the reported task-related fractional anisotropy (FA) changes in white matter.