Reconstruction of the Corticospinal Tract in Patients with Motor-Eloquent High-Grade Gliomas Using Multilevel Fiber Tractography Combined with Functional Motor Cortex Mapping.

BACKGROUND AND PURPOSE: Tractography of the corticospinal tract is paramount to presurgical planning and guidance of intraoperative resection in patients with motor-eloquent gliomas. It is well-known that DTI-based tractography as the most frequently used technique has relevant shortcomings, particularly for resolving complex fiber architecture. The purpose of this study was to evaluate multilevel fiber tractography combined with functional motor cortex mapping in comparison with conventional deterministic tractography algorithms. MATERIALS AND METHODS: Thirty-one patients (mean age, 61.5 [SD, 12.2] years) with motor-eloquent high-grade gliomas underwent MR imaging with DWI (TR/TE = 5000/78 ms, voxel size = 2 × 2 × 2 mm3, 1 volume at b = 0 s/mm2, 32 volumes at b = 1000 s/mm2). DTI, constrained spherical deconvolution, and multilevel fiber tractography-based reconstruction of the corticospinal tract within the tumor-affected hemispheres were performed. The functional motor cortex was enclosed by navigated transcranial magnetic stimulation motor mapping before tumor resection and used for seeding. A range of angular deviation and fractional anisotropy thresholds (for DTI) was tested. RESULTS: For all investigated thresholds, multilevel fiber tractography achieved the highest mean coverage of the motor maps (eg, angular threshold = 60°; multilevel/constrained spherical deconvolution/DTI, 25% anisotropy threshold = 71.8%, 22.6%, and 11.7%) and the most extensive corticospinal tract reconstructions (eg, angular threshold = 60°; multilevel/constrained spherical deconvolution/DTI, 25% anisotropy threshold = 26,485 mm3, 6308 mm3, and 4270 mm3). CONCLUSIONS: Multilevel fiber tractography may improve the coverage of the motor cortex by corticospinal tract fibers compared with conventional deterministic algorithms. Thus, it could provide a more detailed and complete visualization of corticospinal tract architecture, particularly by visualizing fiber trajectories with acute angles that might be of high relevance in patients with gliomas and distorted anatomy.

Indices of callosal axonal density and radius from diffusion MRI relate to upper and lower limb motor performance.

Understanding the relationship between human brain structure and functional outcome is of critical importance in systems neuroscience. Diffusion MRI (dMRI) studies show that fractional anisotropy (FA) is predictive of motor control, underscoring the importance of white matter (WM). However, as FA is a surrogate marker of WM, we aim to shed new light on the structural underpinnings of this relationship by applying a multi-compartment microstructure model providing axonal density/radius indices. Sixteen young adults (7 males / 9 females), performed a hand/foot tapping task and a Multi Limb Reaction Time task. Furthermore, diffusion (STEAM &HARDI) and fMRI (localizer hand/foot activations) data were obtained. Sphere ROIs were placed on activation clusters with highest t value to guide interhemispheric WM tractography. Axonal radius/density indices of callosal parts intersecting with tractography were calculated from STEAM, using the diffusion-time dependent AxCaliber model, and correlated with behavior. Results indicated a possible association between larger apparent axonal radii of callosal motor fibers of the hand and higher tapping scores of both hands, and faster selection-related processing (normalized reaction) times (RTs) on diagonal limb combinations. Additionally, a trend was present for faster selection-related processing (normalized reaction) times for lower limbs being related with higher axonal density of callosal foot motor fibers, and for higher FA values of callosal motor fibers in general being related with better tapping and faster selection-related processing (normalized reaction) times. Whereas FA is sensitive in demonstrating associations with motor behavior, axon radius/density (i.e., fiber geometry) measures are promising to explain the physiological source behind the observed FA changes, contributing to deeper insights into brain-behavior interactions.

Fast and accurate Slicewise OutLIer Detection (SOLID) with informed model estimation for diffusion MRI data.

The accurate characterization of the diffusion process in tissue using diffusion MRI is greatly challenged by the presence of artefacts. Subject motion causes not only spatial misalignments between diffusion weighted images, but often also slicewise signal intensity errors. Voxelwise robust model estimation is commonly used to exclude intensity errors as outliers. Slicewise outliers, however, become distributed over multiple adjacent slices after image registration and transformation. This challenges outlier detection with voxelwise procedures due to partial volume effects. Detecting the outlier slices before any transformations are applied to diffusion weighted images is therefore required. In this work, we present i) an automated tool coined SOLID for slicewise outlier detection prior to geometrical image transformation, and ii) a framework to naturally interpret data uncertainty information from SOLID and include it as such in model estimators. SOLID uses a straightforward intensity metric, is independent of the choice of the diffusion MRI model, and can handle datasets with a few or irregularly distributed gradient directions. The SOLID-informed estimation framework prevents the need to completely reject diffusion weighted images or individual voxel measurements by downweighting measurements with their degree of uncertainty, thereby supporting convergence and well-conditioning of iterative estimation algorithms. In comprehensive simulation experiments, SOLID detects outliers with a high sensitivity and specificity, and can achieve higher or at least similar sensitivity and specificity compared to other tools that are based on more complex and time-consuming procedures for the scenarios investigated. SOLID was further validated on data from 54 neonatal subjects which were visually inspected for outlier slices with the interactive tool developed as part of this study, showing its potential to quickly highlight problematic volumes and slices in large population studies. The informed model estimation framework was evaluated both in simulations and in vivo human data.

Diffusion imaging markers of bipolar versus general psychopathology risk in youth at-risk.

Bipolar disorder (BD) is highly heritable. Thus, studies in first-degree relatives of individuals with BD could lead to the discovery of objective risk markers of BD. Abnormalities in white matter structure reported in at-risk individuals could play an important role in the pathophysiology of BD. Due to the lack of studies with other at-risk offspring, however, it remains unclear whether such abnormalities reflect BD-specific or generic risk markers for future psychopathology. Using a tract-profile approach, we examined 18 major white matter tracts in 38 offspring of BD parents, 36 offspring of comparison parents with non-BD psychopathology (depression, attention-deficit/hyperactivity disorder), and 41 offspring of healthy parents. Both at-risk groups showed significantly lower fractional anisotropy (FA) in left-sided tracts (cingulum, inferior longitudinal fasciculus, forceps minor), and significantly greater FA in right-sided tracts (uncinate fasciculus and inferior longitudinal fasciculus), relative to offspring of healthy parents (P < 0.05). These abnormalities were present in both healthy and affected youth in at-risk groups. Only offspring (particularly healthy offspring) of BD parents showed lower FA in the right superior longitudinal fasciculus relative to healthy offspring of healthy parents (P < 0.05). We show, for the first time, important similarities, and some differences, in white matter structure between offspring of BD and offspring of non-BD parents. Findings suggest that lower left-sided and higher right-sided FA in tracts important for emotional regulation may represent markers of risk for general, rather than BD-specific, psychopathology. Lower FA in the right superior longitudinal fasciculus may protect against development of BD in offspring of BD parents.

Anatomical integration and rich-club connectivity in euthymic bipolar disorder.

BACKGROUND: Although repeatedly associated with white matter microstructural alterations, bipolar disorder (BD) has been relatively unexplored using complex network analysis. This method combines structural and diffusion magnetic resonance imaging (MRI) to model the brain as a network and evaluate its topological properties. A group of highly interconnected high-density structures, termed the 'rich-club', represents an important network for integration of brain functioning. This study aimed to assess structural and rich-club connectivity properties in BD through graph theory analyses. METHOD: We obtained structural and diffusion MRI scans from 42 euthymic patients with BD type I and 43 age- and gender-matched healthy volunteers. Weighted fractional anisotropy connections mapped between cortical and subcortical structures defined the neuroanatomical networks. Next, we examined between-group differences in features of graph properties and sub-networks. RESULTS: Patients exhibited significantly reduced clustering coefficient and global efficiency, compared with controls globally and regionally in frontal and occipital regions. Additionally, patients displayed weaker sub-network connectivity in distributed regions. Rich-club analysis revealed subtly reduced density in patients, which did not withstand multiple comparison correction. However, hub identification in most participants indicated differentially affected rich-club membership in the BD group, with two hubs absent when compared with controls, namely the superior frontal gyrus and thalamus. CONCLUSIONS: This graph theory analysis presents a thorough investigation of topological features of connectivity in euthymic BD. Abnormalities of global and local measures and network components provide further neuroanatomically specific evidence for distributed dysconnectivity as a trait feature of BD.

Antibody-Induced Internalization of the Human Respiratory Syncytial Virus Fusion Protein.

Respiratory syncytial virus (RSV) infections remain a major cause of respiratory disease and hospitalizations among infants. Infection recurs frequently and establishes a weak and short-lived immunity. To date, RSV immunoprophylaxis and vaccine research is mainly focused on the RSV fusion (F) protein, but a vaccine remains elusive. The RSV F protein is a highly conserved surface glycoprotein and is the main target of neutralizing antibodies induced by natural infection. Here, we analyzed an internalization process of antigen-antibody complexes after binding of RSV-specific antibodies to RSV antigens expressed on the surface of infected cells. The RSV F protein and attachment (G) protein were found to be internalized in both infected and transfected cells after the addition of either RSV-specific polyclonal antibodies (PAbs) or RSV glycoprotein-specific monoclonal antibodies (MAbs), as determined by indirect immunofluorescence staining and flow-cytometric analysis. Internalization experiments with different cell lines, well-differentiated primary bronchial epithelial cells (WD-PBECs), and RSV isolates suggest that antibody internalization can be considered a general feature of RSV. More specifically for RSV F, the mechanism of internalization was shown to be clathrin dependent. All RSV F-targeted MAbs tested, regardless of their epitopes, induced internalization of RSV F. No differences could be observed between the different MAbs, indicating that RSV F internalization was epitope independent. Since this process can be either antiviral, by affecting virus assembly and production, or beneficial for the virus, by limiting the efficacy of antibodies and effector mechanism, further research is required to determine the extent to which this occurs in vivo and how this might impact RSV replication.IMPORTANCE Current research into the development of new immunoprophylaxis and vaccines is mainly focused on the RSV F protein since, among others, RSV F-specific antibodies are able to protect infants from severe disease, if administered prophylactically. However, antibody responses established after natural RSV infections are poorly protective against reinfection, and high levels of antibodies do not always correlate with protection. Therefore, RSV might be capable of interfering, at least partially, with antibody-induced neutralization. In this study, a process through which surface-expressed RSV F proteins are internalized after interaction with RSV-specific antibodies is described. One the one hand, this antigen-antibody complex internalization could result in an antiviral effect, since it may interfere with virus particle formation and virus production. On the other hand, this mechanism may also reduce the efficacy of antibody-mediated effector mechanisms toward infected cells.

Choosing the polarity of the phase-encoding direction in diffusion MRI: Does it matter for group analysis?

Notorious for degrading diffusion MRI data quality are so-called susceptibility-induced off-resonance fields, which cause non-linear geometric image deformations. While acquiring additional data to correct for these distortions alleviates the adverse effects of this artifact drastically - e.g., by reversing the polarity of the phase-encoding (PE) direction - this strategy is often not an option due to scan time constraints. Especially in a clinical context, where patient comfort and safety are of paramount importance, acquisition specifications are preferred that minimize scan time, typically resulting in data obtained with only one PE direction. In this work, we investigated whether choosing a different polarity of the PE direction would affect the outcome of a specific clinical research study. To address this methodological question, fractional anisotropy (FA) estimates of FreeSurfer brain regions were obtained in civilian and combat controls, remitted posttraumatic stress disorder (PTSD) patients, and persistent PTSD patients before and after trauma-focused therapy and were compared between diffusion MRI data sets acquired with different polarities of the PE direction (posterior-to-anterior, PA and anterior-to-posterior, AP). Our results demonstrate that regional FA estimates differ on average in the order of 5% between AP and PA PE data. In addition, when comparing FA estimates between different subject groups for specific cingulum subdivisions, the conclusions for AP and PA PE data were not in agreement. These findings increase our understanding of how one of the most pronounced data artifacts in diffusion MRI can impact group analyses and should encourage users to be more cautious when interpreting and reporting study outcomes derived from data acquired along a single PE direction.

PCA-based groupwise image registration for quantitative MRI.

Quantitative magnetic resonance imaging (qMRI) is a technique for estimating quantitative tissue properties, such as the T1 and T2 relaxation times, apparent diffusion coefficient (ADC), and various perfusion measures. This estimation is achieved by acquiring multiple images with different acquisition parameters (or at multiple time points after injection of a contrast agent) and by fitting a qMRI signal model to the image intensities. Image registration is often necessary to compensate for misalignments due to subject motion and/or geometric distortions caused by the acquisition. However, large differences in image appearance make accurate image registration challenging. In this work, we propose a groupwise image registration method for compensating misalignment in qMRI. The groupwise formulation of the method eliminates the requirement of choosing a reference image, thus avoiding a registration bias. The method minimizes a cost function that is based on principal component analysis (PCA), exploiting the fact that intensity changes in qMRI can be described by a low-dimensional signal model, but not requiring knowledge on the specific acquisition model. The method was evaluated on 4D CT data of the lungs, and both real and synthetic images of five different qMRI applications: T1 mapping in a porcine heart, combined T1 and T2 mapping in carotid arteries, ADC mapping in the abdomen, diffusion tensor mapping in the brain, and dynamic contrast-enhanced mapping in the abdomen. Each application is based on a different acquisition model. The method is compared to a mutual information-based pairwise registration method and four other state-of-the-art groupwise registration methods. Registration accuracy is evaluated in terms of the precision of the estimated qMRI parameters, overlap of segmented structures, distance between corresponding landmarks, and smoothness of the deformation. In all qMRI applications the proposed method performed better than or equally well as competing methods, while avoiding the need to choose a reference image. It is also shown that the results of the conventional pairwise approach do depend on the choice of this reference image. We therefore conclude that our groupwise registration method with a similarity measure based on PCA is the preferred technique for compensating misalignments in qMRI.

Diffusion Tensor Imaging and Fiber Tractography in Children with Craniosynostosis Syndromes.

BACKGROUND AND PURPOSE: Patients with craniosynostosis syndromes caused by mutations in FGFR-2, FGFR-3, and TWIST1 genes are characterized by having prematurely fused skull sutures and skull base synchondroses, which result in a skull deformity and are accompanied by brain anomalies, including altered white matter microarchitecture. In this study, the reliability and reproducibility of DTI fiber tractography was investigated in these patients. The outcomes were compared with those of controls. MATERIALS AND METHODS: DTI datasets were acquired with a 1.5T MR imaging system with 25 diffusion gradient orientations (voxel size = 1.8 × 1.8 × 3.0 mm(3), b-value = 1000 s/mm(2)). White matter tracts studied included the following: corpus callosum, cingulate gyrus, fornix, corticospinal tracts, and medial cerebellar peduncle. Tract pathways were reconstructed with ExploreDTI in 58 surgically treated patients with craniosynostosis syndromes and 7 controls (age range, 6-18 years). RESULTS: Because of the brain deformity and abnormal ventricular shape and size, DTI fiber tractography was challenging to perform in patients with craniosynostosis syndromes. To provide reliable tracts, we adapted standard tracking protocols. Fractional anisotropy was equal to that in controls (0.44 versus 0.45 ± 0.02, P = .536), whereas mean, axial, and radial diffusivity parameters of the mean white matter were increased in patients with craniosynostosis syndromes (P < .001). No craniosynostosis syndrome-specific difference in DTI properties was seen for any of the fiber tracts studied in this work. CONCLUSIONS: Performing DTI fiber tractography in patients with craniosynostosis syndromes was difficult due to partial volume effects caused by an anisotropic voxel size and deformed brain structures. Although these patients have a normal fiber organization, increased diffusivity parameters suggest abnormal microstructural tissue properties of the investigated white matter tracts.

Decoupling of structural and functional brain connectivity in older adults with white matter hyperintensities.

Age-related impairments in the default network (DN) have been related to disruptions in connecting white matter tracts. We hypothesized that the local correlation between DN structural and functional connectivity is negatively affected in the presence of global white matter injury. In 125 clinically normal older adults, we tested whether the relationship between structural connectivity (via diffusion imaging tractography) and functional connectivity (via resting-state functional MRI) of the posterior cingulate cortex (PCC) and medial prefrontal frontal cortex (MPFC) of the DN was altered in the presence of white matter hyperintensities (WMH). A significant correlation was observed between microstructural properties of the cingulum bundle and MPFC-PCC functional connectivity in individuals with low WMH load, but not with high WMH load. No correlation was observed between PCC-MPFC functional connectivity and microstructure of the inferior longitudinal fasciculus, a tract not passing through the PCC or MPFC. Decoupling of connectivity, measured as the absolute difference between structural and functional connectivity, in the high WMH group was related to poorer executive functioning and memory performance. These results suggest that such decoupling may reflect reorganization of functional networks in response to global white matter pathology and may provide an early marker of clinically relevant network alterations.

Effective electric fields along realistic DTI-based neural trajectories for modelling the stimulation mechanisms of TMS.

In transcranial magnetic stimulation (TMS), an applied alternating magnetic field induces an electric field in the brain that can interact with the neural system. It is generally assumed that this induced electric field is the crucial effect exciting a certain region of the brain. More specifically, it is the component of this field parallel to the neuron's local orientation, the so-called effective electric field, that can initiate neuronal stimulation. Deeper insights on the stimulation mechanisms can be acquired through extensive TMS modelling. Most models study simple representations of neurons with assumed geometries, whereas we embed realistic neural trajectories computed using tractography based on diffusion tensor images. This way of modelling ensures a more accurate spatial distribution of the effective electric field that is in addition patient and case specific. The case study of this paper focuses on the single pulse stimulation of the left primary motor cortex with a standard figure-of-eight coil. Including realistic neural geometry in the model demonstrates the strong and localized variations of the effective electric field between the tracts themselves and along them due to the interplay of factors such as the tract's position and orientation in relation to the TMS coil, the neural trajectory and its course along the white and grey matter interface. Furthermore, the influence of changes in the coil orientation is studied. Investigating the impact of tissue anisotropy confirms that its contribution is not negligible. Moreover, assuming isotropic tissues lead to errors of the same size as rotating or tilting the coil with 10 degrees. In contrast, the model proves to be less sensitive towards the not well-known tissue conductivity values.

Bimanual motor deficits in older adults predicted by diffusion tensor imaging metrics of corpus callosum subregions.

Age-related changes in the microstructural organization of the corpus callosum (CC) may explain declines in bimanual motor performance associated with normal aging. We used diffusion tensor imaging in young (n = 33) and older (n = 33) adults to investigate the microstructural organization of seven specific CC subregions (prefrontal, premotor, primary motor, primary sensory, parietal, temporal and occipital). A set of bimanual tasks was used to assess various aspects of bimanual motor functioning: the Purdue Pegboard test, simultaneous and alternating finger tapping, a choice reaction time test and a complex visuomotor tracking task. The older adults showed age-related deficits on all measures of bimanual motor performance. Correlation analyses within the older group showed that white matter fractional anisotropy of the CC occipital region was associated with bimanual fine manipulation skills (Purdue Pegboard test), whereas better performance on the other bimanual tasks was related to higher fractional anisotropy in the more anterior premotor, primary motor and primary sensory CC subregions. Such associations were less prominent in the younger group. Our findings suggest that structural alterations of subregional callosal fibers may account for bimanual motor declines in normal aging.

Choice of diffusion tensor estimation approach affects fiber tractography of the fornix in preterm brain.

BACKGROUND AND PURPOSE: Neonatal DTI enables quantitative assessment of microstructural brain properties. Although its use is increasing, it is not widely known that vast differences in tractography results can occur, depending on the diffusion tensor estimation methodology used. Current clinical work appears to be insufficiently focused on data quality and processing of neonatal DTI. To raise awareness about this important processing step, we investigated tractography reconstructions of the fornix with the use of several estimation techniques. We hypothesized that the method of tensor estimation significantly affects DTI tractography results. MATERIALS AND METHODS: Twenty-eight DTI scans of infants born <29 weeks of gestation, acquired at 30-week postmenstrual age and without intracranial injury observed, were prospectively collected. Four diffusion tensor estimation methods were applied: 1) linear least squares; 2) weighted linear least squares; 3) nonlinear least squares, and 4) robust estimation of tensors by outlier rejection. Quality of DTI data and tractography results were evaluated for each method. RESULTS: With nonlinear least squares and robust estimation of tensors by outlier rejection, significantly lower mean fractional anisotropy values were obtained than with linear least squares and weighted linear least squares. Visualized quality of tract reconstruction was significantly higher by use of robust estimation of tensors by outlier rejection and correlated with quality of DTI data. CONCLUSIONS: Quality assessment and choice of processing methodology have considerable impact on neonatal DTI analysis. Dedicated acquisition, quality assessment, and advanced processing of neonatal DTI data must be ensured before performing clinical analyses, such as associating microstructural brain properties with patient outcome.

White matter organization in relation to upper limb motor control in healthy subjects: exploring the added value of diffusion kurtosis imaging.

Diffusion tensor imaging (DTI) characterizes white matter (WM) microstructure. In many brain regions, however, the assumption that the diffusion probability distribution is Gaussian may be invalid, even at low b values. Recently, diffusion kurtosis imaging (DKI) was suggested to more accurately estimate this distribution. We explored the added value of DKI in studying the relation between WM microstructure and upper limb coordination in healthy controls (N = 24). Performance on a complex bimanual tracking task was studied with respect to the conventional DTI measures (DKI or DTI derived) and kurtosis metrics of WM tracts/regions carrying efferent (motor) output from the brain, corpus callosum (CC) substructures and whole brain WM. For both estimation models, motor performance was associated with fractional anisotropy (FA) of the CC-genu, CC-body, the anterior limb of the internal capsule, and whole brain WM (r s range 0.42-0.63). Although DKI revealed higher mean, radial and axial diffusivity and lower FA than DTI (p < 0.001), the correlation coefficients were comparable. Finally, better motor performance was associated with increased mean and radial kurtosis and kurtosis anisotropy (r s range 0.43-0.55). In conclusion, DKI provided additional information, but did not show increased sensitivity to detect relations between WM microstructure and bimanual performance in healthy controls.

Altered structural networks and executive deficits in traumatic brain injury patients.

Recent research on traumatic brain injury (TBI) has shown that impairments in cognitive and executive control functions are accompanied by a disrupted neural connectivity characterized by white matter damage. We constructed binary and weighted brain structural networks in 21 patients with chronic TBI and 17 healthy young adults utilizing diffusion tensor tractography and calculated topological properties of the networks using a graph theoretical method. Executive function was assessed with the local global task and the trail making task, requiring inhibition, updating, and switching. The results revealed that TBI patients were less successful than controls on the executive tasks, as shown by the higher reaction times, higher switch costs, and lower accuracy rates. Moreover, both TBI patients and controls exhibited a small world topology in their white matter networks. More importantly, the TBI patients demonstrated increased shortest path length and decreased global efficiency of the structural network. These findings suggest that TBI patients have a weaker globally integrated structural brain network, resulting in a limited capacity to integrate information across brain regions. Furthermore, we showed that the white matter networks of both groups contained highly connected hub regions that were predominately located in the parietal cortex, frontal cortex, and basal ganglia. Finally, we showed significant correlations between switching performance and network property metrics within the TBI group. Specifically, lower scores on the switching tasks corresponded to a lower global efficiency. We conclude that analyzing the structural brain network connectivity provides new insights into understanding cognitive control changes following brain injury.

White matter microstructural abnormalities in families multiply affected with bipolar I disorder: a diffusion tensor tractography study.

BACKGROUND: White matter (WM) abnormalities are proposed as potential endophenotypic markers of bipolar disorder (BD). In a diffusion tensor imaging (DTI) voxel-based analysis (VBA) study of families multiply affected with BD, we previously reported that widespread abnormalities of fractional anisotropy (FA) are associated with both BD and genetic liability for illness. In the present study, we further investigated the endophenotypic potential of WM abnormalities by applying DTI tractography to specifically investigate tracts implicated in the pathophysiology of BD. METHOD: Diffusion magnetic resonance imaging (MRI) data were acquired from 19 patients with BD type I from multiply affected families, 21 of their unaffected first-degree relatives and 18 healthy volunteers. DTI tractography was used to identify the cingulum, uncinate fasciculus (UF), arcuate portion of the superior longitudinal fasciculus (SLF), inferior longitudinal fasciculus (ILF), corpus callosum, and the anterior limb of the internal capsule (ALIC). Regression analyses were conducted to investigate the effect of participant group and genetic liability on FA and radial diffusivity (RD) in each tract. RESULTS: We detected a significant effect of group on both FA and RD in the cingulum, SLF, callosal splenium and ILF driven by reduced FA and increased RD in patients compared to controls and relatives. Increasing genetic liability was associated with decreased FA and increased RD in the UF, and decreased FA in the SLF, among patients. CONCLUSIONS: WM microstructural abnormalities in limbic, temporal and callosal pathways represent microstructural abnormalities associated with BD whereas alterations in the SLF and UF may represent potential markers of endophenotypic risk.

Recent advancements in diffusion MRI for investigating cortical development after preterm birth-potential and pitfalls.

Preterm infants are born during a critical period of brain maturation, in which even subtle events can result in substantial behavioral, motor and cognitive deficits, as well as psychiatric diseases. Recent evidence shows that the main source for these devastating disabilities is not necessarily white matter (WM) damage but could also be disruptions of cortical microstructure. Animal studies showed how moderate hypoxic-ischemic conditions did not result in significant neuronal loss in the developing brain, but did cause significantly impaired dendritic growth and synapse formation alongside a disturbed development of neuronal connectivity as measured using diffusion magnetic resonance imaging (dMRI). When using more advanced acquisition settings such as high-angular resolution diffusion imaging (HARDI), more advanced reconstruction methods can be applied to investigate the cortical microstructure with higher levels of detail. Recent advances in dMRI acquisition and analysis have great potential to contribute to a better understanding of neuronal connectivity impairment in preterm birth. We will review the current understanding of abnormal preterm cortical development, novel approaches in dMRI, and the pitfalls in scanning vulnerable preterm infants.

Acquisition guidelines and quality assessment tools for analyzing neonatal diffusion tensor MRI data.

Diffusion tensor imaging is a valuable measure in clinical settings to assess diagnosis and prognosis of neonatal brain development. However, obtaining reliable images is not straightforward because of the tissue characteristics of the neonatal brain and the high likelihood of motion artifacts. In this review, we present guidelines on how to acquire DTI data of the neonatal brain and recommend high-quality data acquisition and processing as an essential means to obtain accurate and robust parametric maps. Sudden head movements are problematic for DTI in neonates, and these may lead to incorrect values. We describe strategies to minimize the corrupting effects both in terms of acquisition (eg, more gradient directions) and postprocessing (eg, tensor estimation methods). In addition, tools are described that can help assess whether a dataset is of sufficient quality for further assessment.

Reduced fractional anisotropy in the uncinate fasciculus in patients with major depression carrying the met-allele of the Val66Met brain-derived neurotrophic factor genotype.

Experimental studies support a neurotrophic hypothesis of major depressive disorder (MDD). The aim of this study was to determine the effect of Val66Met brain-derived neurotrophic factor (BDNF) polymorphism on the white matter fiber tracts connecting hippocampus and amygdala with the prefrontal lobe in a sample of patients with MDD and healthy controls. Thirty-seven patients with MDD and 42 healthy volunteers were recruited. Diffusion tensor imaging (DTI) data with 61 diffusion directions were obtained with MRI 3 Tesla scanner. Deterministic tractography was applied with ExploreDTI and Val66Met BDNF SNP (rs6265) was genotyped. Fiber tracts connecting the hippocampus and amygdala with the prefrontal lobe, namely uncinate fasciculus (UF), fornix, and cingulum were analyzed. A significant interaction was found in the UF between BDNF alleles and diagnosis. Patients carrying the BDNF met-allele had smaller fractional anisotropy (FA) in the UF compared to those patients homozygous for val-allele and compared to healthy subjects carrying the met-allele. A significant three-way interaction was detected between region of the cingulum (dorsal, rostral, and parahippocampal regions), brain hemisphere and BDNF genotype. Larger FA was detectable in the left rostral cingulum for met-allele carriers when compared to val/val alelle carriers. We provide evidence for the importance of the neurotrophic involvement in limbic and prefrontal connections. The met-allele of the BDNF polymorphism seems to render subjects more vulnerable for dysfunctions associated with the UF, a tract known to be related to negative emotional-cognitive processing bias, declarative memory problems, and autonoetic self awareness.

A DTI-based model for TMS using the independent impedance method with frequency-dependent tissue parameters.

Accurate simulations on detailed realistic head models are necessary to gain a better understanding of the response to transcranial magnetic stimulation (TMS). Hitherto, head models with simplified geometries and constant isotropic material properties are often used, whereas some biological tissues have anisotropic characteristics which vary naturally with frequency. Moreover, most computational methods do not take the tissue permittivity into account. Therefore, we calculate the electromagnetic behaviour due to TMS in a head model with realistic geometry and where realistic dispersive anisotropic tissue properties are incorporated, based on T1-weighted and diffusion-weighted magnetic resonance images. This paper studies the impact of tissue anisotropy, permittivity and frequency dependence, using the anisotropic independent impedance method. The results show that anisotropy yields differences up to 32% and 19% of the maximum induced currents and electric field, respectively. Neglecting the permittivity values leads to a decrease of about 72% and 24% of the maximum currents and field, respectively. Implementing the dispersive effects of biological tissues results in a difference of 6% of the maximum currents. The cerebral voxels show limited sensitivity of the induced electric field to changes in conductivity and permittivity, whereas the field varies approximately linearly with frequency. These findings illustrate the importance of including each of the above parameters in the model and confirm the need for accuracy in the applied patient-specific method, which can be used in computer-assisted TMS.