Diffusion tensor MR imaging and fiber tractography: technical considerations

Advanced MRI techniques in abdominal imaging

Magnetic resonance imaging (MRI) is a crucial modality for abdominal imaging evaluation of focal lesions and tissue properties. However, several obstacles, such as prolonged scan times, limitations in patients' breath-hold capacity, and contrast agent-associated artifacts, remain in abdominal MR images. Recent techniques, including parallel imaging, three-dimensional acquisition, compressed sensing, and deep learning, have been developed to reduce the scan time while ensuring acceptable image quality or to achieve higher resolution without extending the scan duration. Quantitative measurements using MRI techniques enable the noninvasive evaluation of specific materials. A comprehensive understanding of these advanced techniques is essential for accurate interpretation of MRI sequences. Herein, we therefore review advanced abdominal MRI techniques.

Diffusion Tensor Imaging in Boys With Adrenoleukodystrophy: Identification of Cerebral Disease and Association With Neurocognitive Outcomes

BACKGROUND AND OBJECTIVES

Childhood cerebral adrenoleukodystrophy (C-ALD) is a severe inflammatory demyelinating disease that must be treated at an early stage to prevent permanent brain injury and neurocognitive decline. In standard clinical practice, C-ALD lesions are detected and characterized by a neuroradiologist reviewing anatomical MRI scans. We aimed to assess whether diffusion tensor imaging (DTI) is sensitive to the presence and severity of C-ALD lesions and to investigate associations with neurocognitive outcomes after hematopoietic cell therapy (HCT).

METHODS

In this retrospective cohort study, we analyzed high-resolution anatomical MRI, DTI, and neurocognitive assessments from boys with C-ALD undergoing HCT at the University of Minnesota between 2011 and 2021. Longitudinal DTI data were compared with an age-matched group of boys with ALD and no lesion (NL-ALD). DTI metrics were obtained for atlas-based regions of interest (ROIs) within 3 subdivisions of the corpus callosum (CC), corticospinal tract (CST), and total white matter (WM). Between-group baseline and slope differences in fractional anisotropy (FA) and axial (AD), radial (RD), and mean (MD) diffusivities were compared using analysis of covariance accounting for age, MRI severity (Loes score), and lesion location.

RESULTS

Among patients with NL-ALD (n = 14), stable or increasing FA, stable AD, and stable or decreasing RD and MD were generally observed during the 1-year study period across all ROIs. In comparison, patients with mild posterior lesions (Loes 1-2; n = 13) demonstrated lower baseline FA in the CC splenium (C-ALD 0.50 ± 0.08 vs NL-ALD 0.58 ± 0.04; pBH = 0.022 adjusted Benjamini-Hochberg p-value), lower baseline AD across ROIs (e.g., C-ALD 1.34 ± 0.03 ×10-9 m2/s in total WM vs NL-ALD 1.38 ± 0.04 ×10-9 m2/s; pBH = 0.005), lower baseline RD in CC body and CST, and lower baseline MD across ROIs except CC splenium. Longitudinal slopes in CC splenium showed high sensitivity and specificity in differentiating early C-ALD from NL-ALD. Among all patients with C-ALD (n = 38), baseline Loes scores and DTI metrics were associated with post-HCT neurocognitive functions, including processing speed (e.g., FA WM Spearman correlation coefficient R = 0.64) and visual-motor integration (e.g., FA WM R = 0.71).

DISCUSSION

DTI was sensitive to lesion presence and severity as well as clinical neurocognitive effects of C-ALD. DTI metrics quantify C-ALD even at an early stage.

Positive Effects of Uric Acid on White Matter Microstructures and Treatment Response in Patients With Schizophrenia

BACKGROUND AND HYPOTHESIS

Schizophrenia involves microstructural changes in white matter (WM) tracts. Oxidative stress is a key factor causing WM damage by hindering oligodendrocyte development and myelin maturation. Uric acid (UA), an endogenous antioxidant, may protect against oxidative stress. We investigated the effect of UA on WM connectivity in antipsychotic-naive or -free patients with early- or chronic-stage schizophrenia.

STUDY DESIGN

A total of 192 patients with schizophrenia (122 recent-onset [ROS] and 70 chronic [CS]) and 107 healthy controls (HCs) participated in this study. Diffusion tensor imaging data and serum UA levels at baseline were obtained.

STUDY RESULTS

Fractional anisotropy was lower in the widespread WM regions across the whole brain, and diffusivity measures were higher in both schizophrenia groups than in HCs. The CS group showed lower diffusivity in some WM tracts than the ROS or HC groups. The linear relationship of serum UA levels with axial and mean diffusivity in the right frontal region was significantly different between schizophrenia stages, which was driven by a negative association in the CS group. WM diffusivity associated with serum UA levels correlated with 8-week treatment responses only in patients with CS, suggesting UA to be protective against long-term schizophrenia.

CONCLUSIONS

UA may protect against the WM damage associated with the progression of schizophrenia by reducing oxidative stress and supporting WM repair against oxidative damage. These results provide insights into the positive role of UA and may facilitate the development of novel disease-modifying therapies.

Image-based predictive modelling frameworks for personalised drug delivery in cancer therapy

Personalised drug delivery enables a tailored treatment plan for each patient compared to conventional drug delivery, where a generic strategy is commonly employed. It can not only achieve precise treatment to improve effectiveness but also reduce the risk of adverse effects to improve patients' quality of life. Drug delivery involves multiple interconnected physiological and physicochemical processes, which span a wide range of time and length scales. How to consider the impact of individual differences on these processes becomes critical. Multiphysics models are an open system that allows well-controlled studies on the individual and combined effects of influencing factors on drug delivery outcomes while accommodating the patient-specific in vivo environment, which is not economically feasible through experimental means. Extensive modelling frameworks have been developed to reveal the underlying mechanisms of drug delivery and optimise effective delivery plans. This review provides an overview of currently available models, their integration with advanced medical imaging modalities, and code packages for personalised drug delivery. The potential to incorporate new technologies (i.e., machine learning) in this field is also addressed for development.

Impact of Deep Learning Denoising Algorithm on Diffusion Tensor Imaging of the Growth Plate on Different Spatial Resolutions

To assess the impact of a deep learning (DL) denoising reconstruction algorithm applied to identical patient scans acquired with two different voxel dimensions, representing distinct spatial resolutions, this IRB-approved prospective study was conducted at a tertiary pediatric center in compliance with the Health Insurance Portability and Accountability Act. A General Electric Signa Premier unit (GE Medical Systems, Milwaukee, WI) was employed to acquire two DTI (diffusion tensor imaging) sequences of the left knee on each child at 3T: an in-plane 2.0 × 2.0 mm2 with section thickness of 3.0 mm and a 2 mm3 isovolumetric voxel; neither had an intersection gap. For image acquisition, a multi-band DTI with a fat-suppressed single-shot spin-echo echo-planar sequence (20 non-collinear directions; b-values of 0 and 600 s/mm2) was utilized. The MR vendor-provided a commercially available DL model which was applied with 75% noise reduction settings to the same subject DTI sequences at different spatial resolutions. We compared DTI tract metrics from both DL-reconstructed scans and non-denoised scans for the femur and tibia at each spatial resolution. Differences were evaluated using Wilcoxon-signed ranked test and Bland-Altman plots. When comparing DL versus non-denoised diffusion metrics in femur and tibia using the 2 mm × 2 mm × 3 mm voxel dimension, there were no significant differences between tract count (p = 0.1, p = 0.14) tract volume (p = 0.1, p = 0.29) or tibial tract length (p = 0.16); femur tract length exhibited a significant difference (p < 0.01). All diffusion metrics (tract count, volume, length, and fractional anisotropy (FA)) derived from the DL-reconstructed scans, were significantly different from the non-denoised scan DTI metrics in both the femur and tibial physes using the 2 mm3 voxel size (p < 0.001). DL reconstruction resulted in a significant decrease in femorotibial FA for both voxel dimensions (p < 0.01). Leveraging denoising algorithms could address the drawbacks of lower signal-to-noise ratios (SNRs) associated with smaller voxel volumes and capitalize on their better spatial resolutions, allowing for more accurate quantification of diffusion metrics.

MaPPeRTrac: A Massively Parallel, Portable, and Reproducible Tractography Pipeline

Large-scale diffusion MRI tractography remains a significant challenge. Users must orchestrate a complex sequence of instructions that requires many software packages with complex dependencies and high computational costs. We developed MaPPeRTrac, an edge-centric tractography pipeline that simplifies and accelerates this process in a wide range of high-performance computing (HPC) environments. It fully automates either probabilistic or deterministic tractography, starting from a subject's magnetic resonance imaging (MRI) data, including structural and diffusion MRI images, to the edge density image (EDI) of their structural connectomes. Dependencies are containerized with Singularity (now called Apptainer) and decoupled from code to enable rapid prototyping and modification. Data derivatives are organized with the Brain Imaging Data Structure (BIDS) to ensure that they are findable, accessible, interoperable, and reusable following FAIR principles. The pipeline takes full advantage of HPC resources using the Parsl parallel programming framework, resulting in the creation of connectome datasets of unprecedented size. MaPPeRTrac is publicly available and tested on commercial and scientific hardware, so it can accelerate brain connectome research for a broader user community. MaPPeRTrac is available at: https://github.com/LLNL/mappertrac .

Advanced Abdominal MRI Techniques and Problem-Solving Strategies

MRI plays an important role in abdominal imaging because of its ability to detect and characterize focal lesions. However, MRI examinations have several challenges, such as comparatively long scan times and motion management through breath-holding maneuvers. Techniques for reducing scan time with acceptable image quality, such as parallel imaging, compressed sensing, and cutting-edge deep learning techniques, have been developed to enable problem-solving strategies. Additionally, free-breathing techniques for dynamic contrast-enhanced imaging, such as extra-dimensional-volumetric interpolated breath-hold examination, golden-angle radial sparse parallel, and liver acceleration volume acquisition Star, can help patients with severe dyspnea or those under sedation to undergo abdominal MRI. We aimed to present various advanced abdominal MRI techniques for reducing the scan time while maintaining image quality and free-breathing techniques for dynamic imaging and illustrate cases using the techniques mentioned above. A review of these advanced techniques can assist in the appropriate interpretation of sequences.

Tractography with T1-weighted MRI and associated anatomical constraints on clinical quality diffusion MRI

Diffusion MRI (dMRI) streamline tractography, the gold-standard for in vivo estimation of white matter (WM) pathways in the brain, has long been considered as a product of WM microstructure. However, recent advances in tractography demonstrated that convolutional recurrent neural networks (CoRNN) trained with a teacher-student framework have the ability to learn to propagate streamlines directly from T1 and anatomical context. Training for this network has previously relied on high resolution dMRI. In this paper, we generalize the training mechanism to traditional clinical resolution data, which allows generalizability across sensitive and susceptible study populations. We train CoRNN on a small subset of the Baltimore Longitudinal Study of Aging (BLSA), which better resembles clinical scans. We define a metric, termed the epsilon ball seeding method, to compare T1 tractography and traditional diffusion tractography at the streamline level. We show that under this metric T1 tractography generated by CoRNN reproduces diffusion tractography with approximately three millimeters of error.

Diffusion tensor imaging of optic neuropathies: a narrative review

Background and Objective

Diffusion tensor imaging (DTI) has been implemented in a breadth of scientific investigations of optic neuropathies, though it has yet to be fully adopted for diagnosis or prognosis. This is potentially due to a lack of standardization and weak replication of results. The aim of this investigation was to review DTI results from studies specific to three distinct optic neuropathies in order to probe its current clinical utility.

Methods

We reviewed the DTI literature specific to primary open-angle glaucoma (POAG), optic neuritis (ON), and traumatic optic neuropathy (TON) by systematically searching the PubMed database on March 1st, 2023. Four distinct DTI metrics are considered: fractional anisotropy (FA), along with mean diffusivity (MD, axial diffusivity (AD), and radial diffusivity (RD). Results from within-group, between-group, and correlational studies were thoroughly assessed.

Key Content and Findings

POAG studies most consistently report a decrease in FA, especially in the optic radiations, followed in prevalence by an increase in RD and then MD, whilst AD yields conflicting results between studies. It is notable that there is not an equal distribution of investigated DTI metrics, with FA utilized the most, followed by MD, RD, and AD. Studies of ON are similar in that the most consistent findings are specific to FA, RD, and MD. These results are specific to the optic nerve and radiation since only one study measured the intermediary regions. More studies are needed to assess the effect that ON has on the tracts of the visual system. Finally, only three studies assessing DTI of TON have been performed to date, displaying low to moderate replicability of results. To improve the level of agreement between studies assessing each optic neuropathy, an increased level of standardization is recommended.

Conclusions

Both POAG and ON studies have yielded some prevalent DTI findings, both for contrast and correlation-based assessments. Although the clinical need is high for TON, considering the limitations of the current diagnostic tools, too few studies exist to make confident conclusions. Future use of standardized and longitudinal DTI, along with the foreseen methodological and technical improvements, is warranted to effectively study optic neuropathies.

Mapping mesoscale connectivity within the human hippocampus

The connectivity of the hippocampus is essential to its functions. To gain a whole system view of intrahippocampal connectivity, ex vivo mesoscale (100 μm isotropic resolution) multi-shell diffusion MRI (11.7T) and tractography were performed on entire post-mortem human right hippocampi. Volumetric measurements indicated that the head region was largest followed by the body and tail regions. A unique anatomical organization in the head region reflected a complex organization of the granule cell layer (GCL) of the dentate gyrus. Tractography revealed the volumetric distribution of the perforant path, including both the tri-synaptic and temporoammonic pathways, as well as other well-established canonical connections, such as Schaffer collaterals. Visualization of the perforant path provided a means to verify the borders between the pro-subiculum and CA1, as well as between CA1/CA2. A specific angularity of different layers of fibers in the alveus was evident across the whole sample and allowed a separation of afferent and efferent connections based on their origin (i.e. entorhinal cortex) or destination (i.e. fimbria) using a cluster analysis of streamlines. Non-canonical translamellar connections running along the anterior-posterior axis were also discerned in the hilus. In line with "dentations" of the GCL, mossy fibers were bunching together in the sagittal plane revealing a unique lamellar organization and connections between these. In the head region, mossy fibers projected to the origin of the fimbria, which was distinct from the body and tail region. Mesoscale tractography provides an unprecedented systems view of intrahippocampal connections that underpin cognitive and emotional processing.

The Influence of Nonaerated Paranasal Sinuses on DTI Parameters of the Brain in 6- to 9-Year-Old Children

BACKGROUND AND PURPOSE

DTI is prone to susceptibility artifacts. Air in the paranasal sinuses can cause field inhomogeneity, thus affecting measurements. Children often have mucus in their sinuses or no pneumatization of them. This study investigated the influence of lack of air in the paranasal sinuses on measurements of WM diffusion characteristics.

MATERIALS AND METHODS

The study was embedded in the Generation R Study, a prospective population-based birth cohort in Rotterdam (the Netherlands). Brain MR imaging studies (1070 children, 6-9 years of age) were evaluated for mucosal thickening of the paranasal sinuses. Nonaeration of the paranasal sinuses (modified Lund-Mackay score) was compared with that in a randomly selected control group. The relationship between nonaerated paranasal sinuses and fractional anisotropy and mean diffusivity in the DTI fiber tracts was evaluated using ANCOVA and independent t tests.

RESULTS

The prevalence of mucosal thickening was 10.2% (109/1070). The mean modified Lund-Mackay score was 6.87 (SD, 3.76). In 52.3% (57/109), ≥ 1 paranasal sinus was not pneumatized. The results are reported in effect sizes (Cohen's d). Lower mean fractional anisotropy values were found in the uncinate fasciculus (right uncinate fasciculus/right frontal sinus, d = -0.60), superior longitudinal fasciculus (right superior longitudinal fasciculus/right ethmoid sinus, d = -0.56; right superior longitudinal fasciculus/right sphenoid sinus, d = -2.09), and cingulate bundle (right cingulum bundle/right sphenoid sinus, d = -1.28; left cingulum bundle/left sphenoid sinus, d = -1.49). Higher mean diffusivity values were found in the forceps major/right and left sphenoid sinuses, d = 0.78.

CONCLUSIONS

Nonaeration of the paranasal sinuses is a common incidental finding on pediatric MR imaging brain scans. The amount of air in the paranasal sinuses can influence fractional anisotropy and, to a lesser degree, mean diffusivity values of WM tracts and should be considered in DTI studies in pediatric populations.

A power efficient actively shielded two-channel transverse MRI gradient coil numerical design

Large and fast electrical current pulses are typically applied to conventional single-channel transverse MR gradient coils. However, these pulses result in a significant amount of power losses and heating of the coils. Previously, we presented a cylindrical multi-channel Z-gradient coil design that has better power efficiency compared to the single-channel design. In this work, we further investigate the DC power advantage for a two-channel actively-shielded transverse cylindrical gradient coil over the single-channel design. The conventional coil quadrants are radially divided into two sections, one for each channel, for both the primary and shielding surfaces. The symmetric inner sections of both the primary and shielding coils are assigned to the first channel, while the outer enclosing sections for each quadrant are assigned to the second channel. Discrete wire design is employed, where quasi-elliptic functions are used to parameterize the turns of each section. The coil geometric parameters, section size, number of turns, and turn locations are used as the design optimization parameters. The coils are optimized to maximize the coil's efficiency while keeping the linearity error less than 10% and the shielding ratio above 85%. The design procedure is employed to design both the single and two-channel transverse gradient coils for comparison. Eleven different two-channel configurations having different section sizes were investigated. Results show that the power used to drive the most power-efficient two-channel coil is less than that of the single-channel design by ∼25%. Moreover, the two-channel configuration showed slightly better shielding efficiency.

A narrative review of the anatomy and function of the white matter tracts in language production and comprehension

Much is known about the role of cortical areas in language processing. The shift towards network approaches in recent years has highlighted the importance of uncovering the role of white matter in connecting these areas. However, despite a large body of research, many of these tracts' functions are not well-understood. We present a comprehensive review of the empirical evidence on the role of eight major tracts that are hypothesized to be involved in language processing (inferior longitudinal fasciculus, inferior fronto-occipital fasciculus, uncinate fasciculus, extreme capsule, middle longitudinal fasciculus, superior longitudinal fasciculus, arcuate fasciculus, and frontal aslant tract). For each tract, we hypothesize its role based on the function of the cortical regions it connects. We then evaluate these hypotheses with data from three sources: studies in neurotypical individuals, neuropsychological data, and intraoperative stimulation studies. Finally, we summarize the conclusions supported by the data and highlight the areas needing further investigation.

To Explore the Changes and Differences of Microstructure of Vocal Fold in Vocal Fold Paralysis and Cricoarytenoid Joint Dislocation by Diffusion Tensor Imaging

OBJECTIVE

The diffusion characteristics of water molecules were measured in the vocal folds of canines exhibiting unilateral vocal fold paralysis and unilateral cricoarytenoid joint dislocation. These characteristics were used in conjunction with a histological examination of the microstructural changes of vocal fold muscle fibers to explore the feasibility of diffusion tensor imaging (DTI) in distinguishing unilateral vocal fold paralysis and unilateral cricoarytenoid joint dislocation as well as evaluating microstructural changes.

METHODS

Ten beagles were randomly divided into three groups: four in the unilateral vocal fold paralysis group, four in the unilateral cricoarytenoid joint dislocation group, and two in the normal group. Unilateral recurrent laryngeal nerve resection was performed in the vocal fold paralysis group. Unilateral cricoarytenoid joint dislocation surgery was performed in the dislocation group. No intervention was performed in the normal group. Four months postintervention, the larynges were excised and put into a magnetic resonance imaging (MRI) system (9.4T BioSpec MRI, Bruker, German) for scanning, followed by an analysis of diffusion parameters among the different groups for statistical significance. After MRI scanning, the vocal folds were cut into sections, stained with hematoxylin and eosin, and scanned digitally. The mean cross-sectional area of muscle fibers, and the mean diameter of muscle fibers in the vocal folds were calculated by target detection and extraction technology. Mean values of each measurement were used to compare the differences among the three groups. Pearson correlation analysis was performed on the DTI parameters and the results from histological section extraction.

RESULTS

The paralysis group had significantly higher Fractional Anisotropy (FA) compared to the dislocation group and normal group (P = 0.004). The paralysis group also had a significantly lower Tensor Trace value compared to the dislocation group and normal group (P = 0.000). The average cross-sectional area of vocal fold muscle fibers in the paralysis group was significantly smaller than the dislocation group and normal group (P = 0.000). Pearson correlation analysis yielded values of, r = -0.785, P = 0.01 between the average cross-sectional area of vocal muscle fibers and FA, and values of r = 0.881, P = 0.00 between Tensor Trace and the average cross-sectional area of vocal muscle.

CONCLUSION

FA and Tensor Trace can be used as effective parameters to reflect the changes of microstructure in vocal fold paralysis and cricoarytenoid joint dislocation. DTI is an objective and quantitative method to effectively evaluate unilateral vocal fold paralysis and unilateral cricoarytenoid joint dislocation, also capable of noninvasively evaluating vocal fold muscle fiber microstructure.

Both noise-floor and tissue compartment difference in diffusivity contribute to FA dependence on b-value in diffusion MRI

Noninvasive diffusion magnetic resonance imaging (dMRI) has been widely employed in both clinical and research settings to investigate brain tissue microstructure. Despite the evidence that dMRI-derived fractional anisotropy (FA) correlates with white matter properties, the metric is not specific. Recent studies have reported that FA is dependent on the b-value, and its origin has primarily been attributed to either the influence of microstructure or the noise-floor effect. A systematic investigation into the inter-relationship of these two effects is however still lacking. This study aims to quantify contributions of the reported differences in intra- and extra-neurite diffusivity to the observed changes in FA, in addition to the noise in measurements. We used in-vivo and post-mortem human brain imaging, as well as numerical simulations and histological validation, for this purpose. Our investigations reveal that the percentage difference of FA between b-values (pdFA) has significant positive associations with neurite density index (NDI), which is derived from in-vivo neurite orientation dispersion and density imaging (NODDI), or Bielschowsky's silver impregnation (BIEL) staining sections of fixed post-mortem human brain samples. Furthermore, such an association is found to be varied with Signal-to-Noise Ratio (SNR) level, indicating a nonlinear interaction effect between tissue microstructure and noise. Finally, a multicompartment model simulation revealed that these findings can be driven by differing diffusivities of intra- and extra-neurite compartments in tissue, with the noise-floor further amplifying the effect. In conclusion, both the differences in intra- and extra-neurite diffusivity and noise-floor effects significantly contribute to the FA difference associated with the b-value.

Visualization of human optic nerve by diffusion tensor mapping and degree of neuropathy

Diffusion-weighted magnetic resonance imaging of the human optic nerve and tract is technically difficult because of its small size, the inherent strong signal generated by the surrounding fat and the cerebrospinal fluid, and due to eddy current-induced distortions and subject movement artifacts. The effects of the bone canal through which the optic nerve passes, and the proximity of blood vessels, muscles and tendons are generally unknown. Also, the limited technical capabilities of the scanners and the minimization of acquisition times result in poor quality diffusion-weighted images. It is challenging for current tractography methods to accurately track optic pathway fibers that correspond to known anatomy. Despite these technical limitations and low image resolution, here we show how to visualize the optic nerve and tract and quantify nerve atrophy. Our visualization method based on the analysis of the diffusion tensor shows marked differences between a healthy male subject and a male subject with progressive optic nerve neuropathy. These differences coincide with diffusion scalar metrics and are not visible on standard morphological images. A quantification of the degree of optic nerve atrophy in a systematic way is provided and it is tested on 9 subjects from the Human Connectome Project.

Structural connectivity mapping in human hippocampal-subfields using super-resolution hybrid diffusion imaging: a feasibility study

PURPOSE

The goal of the current study was to introduce a new methodology that holds a promise to be used in hippocampus-aging studies using sub-millimeter super-resolution hybrid diffusion imaging (HYDI) MRI.

METHODS

HYDI diffusion data were acquired in two groups of older and younger healthy participants recruited from the Indiana Alzheimer's Disease Research Center and community. These data were then transformed into super-resolution diffusion images before the hippocampal subfield analyses. We studied the correlation between the subjects' age and the structural connectivity involving the hippocampal subfields and the connectivity between the whole hippocampus and the cerebral cortex.

RESULTS

Structural integrity derived from the tractography streamlines between the hippocampal subfields was reduced in older than younger adults.

CONCLUSION

The findings offered a new promising framework, and they opened avenues for future studies to explore the relationship between the structural connectivity in the hippocampal area and different types of dementia.

Mapping brain-wide excitatory projectome of primate prefrontal cortex at submicron resolution and comparison with diffusion tractography

Resolving trajectories of axonal pathways in the primate prefrontal cortex remains crucial to gain insights into higher-order processes of cognition and emotion, which requires a comprehensive map of axonal projections linking demarcated subdivisions of prefrontal cortex and the rest of brain. Here, we report a mesoscale excitatory projectome issued from the ventrolateral prefrontal cortex (vlPFC) to the entire macaque brain by using viral-based genetic axonal tracing in tandem with high-throughput serial two-photon tomography, which demonstrated prominent monosynaptic projections to other prefrontal areas, temporal, limbic, and subcortical areas, relatively weak projections to parietal and insular regions but no projections directly to the occipital lobe. In a common 3D space, we quantitatively validated an atlas of diffusion tractography-derived vlPFC connections with correlative green fluorescent protein-labeled axonal tracing, and observed generally good agreement except a major difference in the posterior projections of inferior fronto-occipital fasciculus. These findings raise an intriguing question as to how neural information passes along long-range association fiber bundles in macaque brains, and call for the caution of using diffusion tractography to map the wiring diagram of brain circuits.

In the brain is a web of interconnected nerve cells that send messages to one another via spindly projections called axons. These axons join together at junctions called synapses to create circuits of nerve cells which connect neighboring or distant brain regions. Notably, long-range neural connections underpin higher-order cognitive skills (such as planning and emotion regulation) which make humans distinct from our primate relatives. Only by untangling these far-reaching networks can researchers begin to delineate what sets the human brain apart from other species.

Researchers deploy a range of imaging techniques to map neural networks: scanning entire brains using MRI machines, or imaging thin slices of fluorescently labelled brain tissue using powerful microscopes. However, tracing long-range axons at a high resolution is challenging, and has stirred up debate about whether some neural tracts, such as the inferior fronto-occipital fasciculus, are present in all primates or only humans.

To address these discrepancies, Yan, Yu et al. employed a two-pronged approach to map neural circuits in the brains of macaques. First, two techniques – called viral tracing and two-photon microscopy – were used to create a three-dimensional, fine-grain map showing how the ventrolateral prefrontal cortex (vlPFC), which regulates complex behaviors, connects to the rest of the brain. This revealed prominent axons from the vlPFC projecting via a single synapse to distant brain regions involved in higher-order functions, such as encoding memories and processing emotion. However, there were no direct, monosynaptic connections between the vlPFC and the occipital lobe, the brain’s visual processing center at the back of the head.

Next, Yan, Yu et al. used a specialized MRI scanner to create an atlas of neural circuits connected to the vlPFC, and compared these results to a technique tracing axons stained with a fluorescent dye. In general, there was good agreement between the two methods, except for major differences in the rear-end projections that typically form the inferior fronto-occipital fasciculus. This suggests that this long-range neural pathway exists in monkeys, but it connects via multiple synapses instead of a single junction as was previously thought.

The findings of Yan, Yu et al. provide new insights on the far-reaching neural pathways connecting distant parts of the macaque brain. It also suggests that atlases of neural circuits from whole brain scans should be taken with caution and validated using neural tracing experiments.

The Utilization of Diffusion Tensor Imaging as an Image-Guided Tool in Brain Tumor Resection Surgery: A Systematic Review

The diffusion tensor imaging technique has been recognized as a neuroimaging tool for in vivo visualization of white matter tracts. However, DTI is not a routine procedure for preoperative planning for brain tumor resection. Our study aimed to systematically evaluate the effectiveness of DTI and the outcomes of surgery. The electronic databases, PubMed/MEDLINE and Scopus, were searched for relevant studies. Studies were systematically reviewed based on the application of DTI in pre-surgical planning, modification of operative planning, re-evaluation of preoperative DTI data intraoperatively, and the outcome of surgery decisions. Seventeen studies were selected based on the inclusion and exclusion criteria. Most studies agreed that preoperative planning using DTI improves postoperative neuro-deficits, giving a greater resection yield and shortening the surgery time. The results also indicate that the re-evaluation of preoperative DTI intraoperatively assists in a better visualization of white matter tract shifts. Seven studies also suggested that DTI modified the surgical decision of the initial surgical approach and the rate of the GTR in tumor resection surgery. The utilization of DTI may give essential information on white matter tract pathways, for a better surgical approach, and eventually reduce the risk of neurologic deficits after surgery.

Modeling the Properties of White Matter Tracts Using Diffusion Tensor Imaging to Characterize Patterns of Injury in Aging and Neurodegenerative Disease

Diffusion tensor imaging (DTI) is a relatively novel magnetic resonance-based imaging methodology that can provide valuable insight into the microstructure of white matter tracts of the brain. In this paper, we evaluated the reliability and reproducibility of deriving a semi-automated pseudo-atlas DTI tractography method vs. standard atlas-based analysis alternatives, for use in clinical cohorts with neurodegeneration and ventriculomegaly. We showed that the semi-automated pseudo-atlas DTI tractography method was reliable and reproducible across different cohorts, generating 97.7% of all tracts. However, DTI metrics obtained from both methods were significantly different across the majority of cohorts and white matter tracts (p < 0.001). Despite this, we showed that both methods produced patterns of white matter injury that are consistent with findings reported in the literature and with DTI profiles generated from these methodologies. Scatter plots comparing DTI metrics obtained from each methodology showed that the pseudo-atlas method produced metrics that implied a more preserved neural structure compared to its counterpart. When comparing DTI metrics against a measure of ventriculomegaly (i.e., Evans' Index), we showed that the standard atlas-based method was able to detect decreasing white matter integrity with increasing ventriculomegaly, while in contrast, metrics obtained using the pseudo-atlas method were sensitive for stretch or compression in the posterior limb of the internal capsule. Additionally, both methods were able to show an increase in white matter disruption with increasing ventriculomegaly, with the pseudo-atlas method showing less variability and more specificity to changes in white matter tracts near to the ventricles. In this study, we found that there was no true gold-standard for DTI methodologies or atlases. Whilst there was no congruence between absolute values from DTI metrics, differing DTI methodologies were still valid but must be appreciated to be variably sensitive to different changes within white matter injury occurring concurrently. By combining both atlas and pseudo-atlas based methodologies with DTI profiles, it was possible to navigate past such challenges to describe white matter injury changes in the context of confounders, such as neurodegenerative disease and ventricular enlargement, with transparency and consistency.

Multimodal Presurgical Evaluation of Medically Refractory Focal Epilepsy in Adults: An Update for Radiologists

Surgery is a potentially curative treatment option for patients with medically refractory focal epilepsy. Advanced neuroimaging modalities often improve surgical outcomes by contributing key information during the highly individualized surgical planning process and intraoperative localization. Hence, neuroradiologists play an integral role as part of the multidisciplinary management team. In this review, we initially present the conceptual background and practical framework of the presurgical evaluation process, including a description of the surgical treatment approaches in medically refractory focal epilepsy in adults. This background is followed by an overview of the advanced modalities commonly used during the presurgical workup at level IV epilepsy centers including diffusion imaging techniques, blood oxygen level dependent (BOLD) functional MRI (fMRI), PET, SPECT, and subtraction ictal SPECT, as well as by introductions to 7-T MRI and electrophysiologic techniques including electroencephalography (EEG) and magnetoencephalography (MEG). We also provide illustrative case examples of multimodal neuroimaging including PET/MRI, PET/MRI-DTI, subtraction ictal SPECT, and image-guided stereotactic planning with fMRI-DTI.

Cumulative strain-based metrics for predicting subconcussive head impact exposure-related imaging changes in a cohort of American youth football players

OBJECTIVE

Youth football athletes are exposed to repetitive subconcussive head impacts during normal participation in the sport, and there is increasing concern about the long-term effects of these impacts. The objective of the current study was to determine if strain-based cumulative exposure measures are superior to kinematic-based exposure measures for predicting imaging changes in the brain.

METHODS

This prospective, longitudinal cohort study was conducted from 2012 to 2017 and assessed youth, male football athletes. Kinematic data were collected at all practices and games from enrolled athletes participating in local youth football organizations in Winston-Salem, North Carolina, and were used to calculate multiple risk-weighted cumulative exposure (RWE) kinematic metrics and 36 strain-based exposure metrics. Pre- and postseason imaging was performed at Wake Forest School of Medicine, and diffusion tensor imaging (DTI) measures, including fractional anisotropy (FA), and its components (CL, CP, and CS), and mean diffusivity (MD), were investigated. Included participants were youth football players ranging in age from 9 to 13 years. Exclusion criteria included any history of previous neurological illness, psychiatric illness, brain tumor, concussion within the past 6 months, and/or contraindication to MRI.

RESULTS

A total of 95 male athletes (mean age 11.9 years [SD 1.0 years]) participated between 2012 and 2017, with some participating for multiple seasons, resulting in 116 unique athlete-seasons. Regression analysis revealed statistically significant linear relationships between the FA, linear coefficient (CL), and spherical coefficient (CS) and all strain exposure measures, and well as the planar coefficient (CP) and 8 strain measures. For the kinematic exposure measures, there were statistically significant relationships between FA and RWE linear (RWEL) and RWE combined probability (RWECP) as well as CS and RWEL. According to area under the receiver operating characteristic (ROC) curve (AUC) analysis, the best-performing metrics were all strain measures, and included metrics based on tensile, compressive, and shear strain.

CONCLUSIONS

Using ROC curves and AUC analysis, all exposure metrics were ranked in order of performance, and the results demonstrated that all the strain-based metrics performed better than any of the kinematic metrics, indicating that strain-based metrics are better discriminators of imaging changes than kinematic-based measures. Studies relating the biomechanics of head impacts with brain imaging and cognitive function may allow equipment designers, care providers, and organizations to prevent, identify, and treat injuries in order to make football a safer activity.

Dementia Risk Factors Modify Hubs but Leave Other Connectivity Measures Unchanged in Asymptomatic Individuals: A Graph Theoretical Analysis

Background: Alzheimer's disease (AD) is the most common form of dementia with genetic and environmental risk contributing to its development. Graph theoretical analyses of brain networks constructed from structural and functional magnetic resonance imaging (MRI) measurements have identified connectivity changes in AD and individuals with mild cognitive impairment. However, brain connectivity in asymptomatic individuals at risk of AD remains poorly understood. Methods: We analyzed diffusion-weighted MRI data from 161 asymptomatic individuals (38-71 years) from the Cardiff Ageing and Risk of Dementia Study (CARDS). We calculated white matter tracts and constructed whole-brain, default mode network (DMN) and visual structural brain networks that incorporate multiple structural metrics as edge weights. We then calculated the relationship of three AD risk factors, namely Apolipoprotein-E ɛ4 (APOE4) genotype, family history of dementia (FH), and central obesity (Waist-Hip-Ratio [WHR]), on graph theoretical measures and hubs. Results: We observed no risk-related differences in clustering coefficients, characteristic path lengths, eccentricity, diameter, and radius across the whole-brain, DMN or visual system. However, a hub in the right paracentral lobule was present in all the high-risk groups (FH, APOE4, obese), but absent in low-risk groups (no FH, APOE4-ve, healthy WHR). Discussion: We identified no risk-related effects on graph theoretical metrics in the structural brain networks of cognitively healthy individuals. However, high risk was associated with a hub in the right paracentral lobule, a medial fronto-parietal cortical area with motor and sensory functions. This finding is consistent with accumulating evidence for right parietal cortex contributions in AD. If this phenotype is shown to predict symptom development in longitudinal studies, it could be used as an early biomarker of AD. Impact statement Alzheimer's disease (AD) is a common form of dementia that to date has no cure. Identifying early biomarkers will aid the discovery and development of treatments that may slow AD progression in the future. In this article, we report that asymptomatic individuals at heightened risk of dementia due to their family history, Apolipoprotein-E ɛ4 genotype, and central adiposity have a hub in the right paracentral lobule, which is absent in low-risk groups. If this phenotype were to predict the development of symptoms in a longitudinal study of the same cohort, it could provide an early biomarker of disease progression.

DIFFnet: Diffusion Parameter Mapping Network Generalized for Input Diffusion Gradient Schemes and b-Value

In MRI, deep neural networks have been proposed to reconstruct diffusion model parameters. However, the inputs of the networks were designed for a specific diffusion gradient scheme (i.e., diffusion gradient directions and numbers) and a specific b-value that are the same as the training data. In this study, a new deep neural network, referred to as DIFFnet, is developed to function as a generalized reconstruction tool of the diffusion-weighted signals for various gradient schemes and b-values. For generalization, diffusion signals are normalized in a q-space and then projected and quantized, producing a matrix (Qmatrix) as an input for the network. To demonstrate the validity of this approach, DIFFnet is evaluated for diffusion tensor imaging (DIFFnet_DTI) and for neurite orientation dispersion and density imaging (DIFFnet_NODDI). In each model, two datasets with different gradient schemes and b-values are tested. The results demonstrate accurate reconstruction of the diffusion parameters at substantially reduced processing time (approximately 8.7 times and 2240 times faster processing time than conventional methods in DTI and NODDI, respectively; less than 4% mean normalized root-mean-square errors (NRMSE) in DTI and less than 8% in NODDI). The generalization capability of the networks was further validated using reduced numbers of diffusion signals from the datasets and a public dataset from Human Connection Project. Different from previously proposed deep neural networks, DIFFnet does not require any specific gradient scheme and b-value for its input. As a result, it can be adopted as an online reconstruction tool for various complex diffusion imaging.

Financial decision-making and self-awareness for financial decision-making is associated with white matter integrity in older adults

Financial decision-making (FDM) and awareness of the integrity of one's FDM abilities (or financial awareness) are both critical for preventing financial mistakes. We examined the white matter correlates of these constructs and hypothesized that the tracts connecting the temporal-frontal regions would be most strongly correlated with both FDM and financial awareness. Overall, 49 healthy older adults were included in the FDM analysis and 44 in the financial awareness analyses. The Objective Financial Competency Assessment Inventory was used to measure FDM. Financial awareness was measured by integrating metacognitive ratings into this inventory and was calculated as the degree of overconfidence or underconfidence. Diffusion tensor imaging data were processed with Tracts Constrained by Underlying Anatomy distributed as part of the FreeSurfer analytic suite, which produced average measures of fractional anisotropy and mean diffusivity in 18 white matter tracts along with the overall tract average. As expected, FDM showed the strongest negative associations with average mean diffusivity measure of the superior longitudinal fasciculus -temporal (SLFT; r = -.360, p = .011) and -parietal (r = -.351, p = .014) tracts. After adjusting for FDM, only the association between financial awareness and average mean diffusivity measure of the right SLFT (r = .310, p = .046) was significant. Overlapping white matter tracts were involved in both FDM and financial awareness. More importantly, these preliminary findings reinforce emerging literature on a unique role of right hemisphere temporal connections in supporting financial awareness.

Utilizing the TractSeg Tool for Automatic Corticospinal Tract Segmentation in Patients With Brain Pathology

Purpose: White-matter tract segmentation in patients with brain pathology can guide surgical planning and can be used for tissue integrity assessment. Recently, TractSeg was proposed for automatic tract segmentation in healthy subjects. The aim of this study was to assess the use of TractSeg for corticospinal-tract (CST) segmentation in a large cohort of patients with brain pathology and to evaluate its consistency in repeated measurements. Methods: A total of 649 diffusion-tensor-imaging scans were included, of them: 625 patients and 24 scans from 12 healthy controls (scanned twice for consistency assessment). Manual CST labeling was performed in all cases, and by 2 raters for the healthy subjects. Segmentation results were evaluated based on the Dice score. In order to evaluate consistency in repeated measurements, volume, Fractional Anisotropy (FA), and Mean Diffusivity (MD) values were extracted and correlated for the manual versus automatic methods. Results: For the automatic CST segmentation Dice scores of 0.63 and 0.64 for the training and testing datasets were obtained. Higher consistency between measurements was detected for the automatic segmentation, with between measurements correlations of volume = 0.92/0.65, MD = 0.94/0.75 for the automatic versus manual segmentation. Conclusions: The TractSeg method enables automatic CST segmentation in patients with brain pathology. Superior measurements consistency was detected for the automatic in comparison to manual fiber segmentation, which indicates an advantage when using this method for clinical and longitudinal studies.

Effects of Angular Resolution and b Value on Diffusion Tensor Imaging in Knee Joint

OBJECTIVE

To investigate the influences of the diffusion gradient directions (angular resolution) and the strength of the diffusion gradient (b value) on diffusion tensor imaging (DTI) metrics and tractography of various connective tissues in knee joint.

DESIGN

Two rat knee joints were scanned on a preclinical 9.4-T system using a 3-dimensional diffusion-weighted spin echo pulse sequence. One protocol with b value of 500, 1500, and 2500 s/mm² were acquired separately using 43 diffusion gradient directions. The other protocol with b value of 1000 s/mm² was performed using 147 diffusion gradient directions. The in-plane resolution was 45 µm isotropic. Fractional anisotropy (FA) and mean diffusivity (MD) were compared at different angular resolution. Tractography was quantitatively evaluated at different b values and angular resolutions in cartilage, ligament, meniscus, and growth plate.

RESULTS

The ligament showed higher FA value compared with growth plate and cartilage. The FA values were largely overestimated at the angular resolution of 6. Compared with FA, MD showed less sensitivity to the angular resolution. The fiber tracking was failed at low angular resolution (6 diffusion gradient directions) or high b value (2500 s/mm²). The quantitative measurements of tract length and track volume were strongly dependent on angular resolution and b value.

CONCLUSIONS

To obtain consistent DTI outputs and tractography in knee joint, the scan may require a proper b value (ranging from 500 to 1500 s/mm²) and sufficient angular resolution (>14) with signal-to-noise ratio >10.

Reliability of the freehand region-of-interest method in quantitative cerebral diffusion tensor imaging

Background

Diffusion tensor imaging (DTI) is a magnetic resonance imaging (MRI) technique used for evaluating changes in the white matter in brain parenchyma. The reliability of quantitative DTI analysis is influenced by several factors, such as the imaging protocol, pre-processing and post-processing methods, and selected diffusion parameters. The region-of-interest (ROI) method is most widely used of the post-processing methods because it is found in commercial software. The focus of our research was to study the reliability of the freehand ROI method using various intra- and inter-observer analyses.

Methods

This study included 40 neurologically healthy participants who underwent diffusion MRI of the brain with a 3 T scanner. The measurements were performed at nine different anatomical locations using a freehand ROI method. The data extracted from the ROIs included the regional mean values, intra- and inter-observer variability and reliability. The used DTI parameters were fractional anisotropy (FA), the apparent diffusion coefficient (ADC), and axial (AD) and radial (RD) diffusivity.

Results

The average intra-class correlation coefficient (ICC) of the intra-observer was found to be 0.9 (excellent). The single ICC results were excellent (> 0.8) or adequate (> 0.69) in eight out of the nine regions in terms of FA and ADC. The most reliable results were found in the frontobasal regions. Significant differences between age groups were also found in the frontobasal regions. Specifically, the FA and AD values were significantly higher and the RD values lower in the youngest age group (18–30 years) compared to the other age groups.

Conclusions

The quantitative freehand ROI method can be considered highly reliable for the average ICC and mostly adequate for the single ICC. The freehand method is suitable for research work with a well-experienced observer. Measurements should be performed at least twice in the same region to ensure that the results are sufficiently reliable. In our study, reliability was slightly undermined by artifacts in some regions such as the cerebral peduncle and centrum semiovale. From a clinical point of view, the results are most reliable in adults under the age of 30, when age-related changes in brain white matter have not yet occurred.

Diffuse axonal injury has a characteristic multidimensional MRI signature in the human brain

Axonal injury is a major contributor to the clinical symptomatology in patients with traumatic brain injury. Conventional neuroradiological tools, such as CT and MRI, are insensitive to diffuse axonal injury (DAI) caused by trauma. Diffusion tensor MRI parameters may change in DAI lesions; however, the nature of these changes is inconsistent. Multidimensional MRI is an emerging approach that combines T1, T2, and diffusion, and replaces voxel-averaged values with distributions, which allows selective isolation of specific potential abnormal components. By performing a combined post-mortem multidimensional MRI and histopathology study, we aimed to investigate T1-T2-diffusion changes linked to DAI and to define their histopathological correlates. Corpora callosa derived from eight subjects who had sustained traumatic brain injury, and three control brain donors underwent post-mortem ex vivo MRI at 7 T. Multidimensional, diffusion tensor, and quantitative T1 and T2 MRI data were acquired and processed. Following MRI acquisition, slices from the same tissue were tested for amyloid precursor protein (APP) immunoreactivity to define DAI severity. A robust image co-registration method was applied to accurately match MRI-derived parameters and histopathology, after which 12 regions of interest per tissue block were selected based on APP density, but blind to MRI. We identified abnormal multidimensional T1-T2, diffusion-T2, and diffusion-T1 components that are strongly associated with DAI and used them to generate axonal injury images. We found that compared to control white matter, mild and severe DAI lesions contained significantly larger abnormal T1-T2 component (P = 0.005 and P < 0.001, respectively), and significantly larger abnormal diffusion-T2 component (P = 0.005 and P < 0.001, respectively). Furthermore, within patients with traumatic brain injury the multidimensional MRI biomarkers differentiated normal-appearing white matter from mild and severe DAI lesions, with significantly larger abnormal T1-T2 and diffusion-T2 components (P = 0.003 and P < 0.001, respectively, for T1-T2; P = 0.022 and P < 0.001, respectively, for diffusion-T2). Conversely, none of the conventional quantitative MRI parameters were able to differentiate lesions and normal-appearing white matter. Lastly, we found that the abnormal T1-T2, diffusion-T1, and diffusion-T2 components and their axonal damage images were strongly correlated with quantitative APP staining (r = 0.876, P < 0.001; r = 0.727, P < 0.001; and r = 0.743, P < 0.001, respectively), while producing negligible intensities in grey matter and in normal-appearing white matter. These results suggest that multidimensional MRI may provide non-invasive biomarkers for detection of DAI, which is the pathological substrate for neurological disorders ranging from concussion to severe traumatic brain injury.

Tractography-Pathology Correlations in Traumatic Brain Injury: A TRACK-TBI Study

Diffusion tractography magnetic resonance imaging (MRI) can infer changes in network connectivity in patients with traumatic brain injury (TBI), but the pathological substrates of disconnected tracts have not been well defined because of a lack of high-resolution imaging with histopathological validation. We developed an ex vivo MRI protocol to analyze tract terminations at 750-μm isotropic resolution, followed by histopathological evaluation of white matter pathology, and applied these methods to a 60-year-old man who died 26 days after TBI. Analysis of 74 cerebral hemispheric white matter regions revealed a heterogeneous distribution of tract disruptions. Associated histopathology identified variable white matter injury with patchy deposition of amyloid precursor protein (APP), loss of neurofilament-positive axonal processes, myelin dissolution, astrogliosis, microgliosis, and perivascular hemosiderin-laden macrophages. Multiple linear regression revealed that tract disruption strongly correlated with the density of APP-positive axonal swellings and neurofilament loss. Ex vivo diffusion MRI can detect tract disruptions in the human brain that reflect axonal injury.

Improving distortion correction for isotropic high-resolution 3D diffusion MRI by optimizing Jacobian modulation

PURPOSE

To improve distortion correction for isotropic high-resolution whole-brain 3D diffusion MRI when in a time-saving acquisition scenario.

THEORY AND METHODS

Data were acquired using simultaneous multi-slab (SMSlab) acquisitions, with a b = 0 image pair encoded by reversed polarity gradients (RPG) for phase encoding (PE) and diffusion weighted images encoded by a single PE direction. Eddy current-induced distortions were corrected first. During the following susceptibility distortion correction, image deformation was first corrected by the field map estimated from the b = 0 image pair. Intensity variation was subsequently corrected by Jacobian modulation. Two Jacobian modulation methods were compared. They calculated the Jacobian modulation map from the field map, or from the deformation corrected b = 0 image pair, termed as J_Field and J_RPG , respectively. A modified version of the J_RPG method, with proper smoothing, was further proposed for improved correction performance, termed as J_RPG-smooth .

RESULTS

Compared to J_Field modulation, less remaining distortions are observed when using the J_RPG and J_RPG-smooth methods, especially in areas with large B0 field inhomogeneity. The original J_RPG method causes signal-to-noise ratio (SNR) deficiency problem, which manifests as degraded SNR of the diffusion weighted images, while the J_RPG-smooth method maintains the original image SNR. Less estimation errors of diffusion metrics are observed when using the J_RPG-smooth method.

CONCLUSION

This study improves the distortion correction for isotropic high-resolution whole-brain 3D diffusion MRI by optimizing Jacobian modulation. The optimized method outperforms the conventional J_Field method regarding intensity variation correction and accuracy of diffusion metrics estimation, and outperforms the original J_RPG method regarding SNR performance.

Shared and distinct white matter abnormalities in schizophrenia and bipolar disorder

While white matter impairments play an integral part in the pathophysiology of schizophrenia and bipolar disorder, the literature on white matter abnormality differences between the two disorders is insufficient. The University of California Los Angeles Consortium for Neuropsychiatric Phenomic LA5c public dataset, including 47 patients with schizophrenia, 47 with bipolar disorder, and 115 healthy controls, was obtained via OpenNeuro. Whole-brain tractography was performed using Unscented Kalman filter-based two-tensor tractography and White Matter Query Language. Diffusion indices, including fractional anisotropy (FA), axial diffusivity, radial diffusivity (RD), and trace (TR), were used to compare subject groups. Spearman's partial correlation with a covariate of age was used for correlation with clinical variables. Both patient groups exhibited significantly higher RD in the left external capsule and TR in the right extreme capsule. Significantly lower FA in the left external capsule, right thalamo-occipital and thalamo-parietal tracts were found in the schizophrenia group in comparison with bipolar disorder and healthy control groups. Compared with healthy controls, patients with schizophrenia had significantly lower FA in the left-to-right lateral orbitofrontal commissural tract. There were possible associations of the FA and RD of the left external capsule with the anxiety-depression score of the Brief Psychiatric Rating Scale in patients with schizophrenia. The white matter alterations identified in schizophrenia and bipolar disorder may be a neurobiological basis contributing to characterization of the two disorders.

Predicting MEG resting-state functional connectivity from microstructural information

Understanding how human brain microstructure influences functional connectivity is an important endeavor. In this work, magnetic resonance imaging data from 90 healthy participants were used to calculate structural connectivity matrices using the streamline count, fractional anisotropy, radial diffusivity, and a myelin measure (derived from multicomponent relaxometry) to assign connection strength. Unweighted binarized structural connectivity matrices were also constructed. Magnetoencephalography resting-state data from those participants were used to calculate functional connectivity matrices, via correlations of the Hilbert envelopes of beamformer time series in the delta, theta, alpha, and beta frequency bands. Nonnegative matrix factorization was performed to identify the components of the functional connectivity. Shortest path length and search-information analyses of the structural connectomes were used to predict functional connectivity patterns for each participant. The microstructure-informed algorithms predicted the components of the functional connectivity more accurately than they predicted the total functional connectivity. This provides a methodology to understand functional mechanisms better. The shortest path length algorithm exhibited the highest prediction accuracy. Of the weights of the structural connectivity matrices, the streamline count and the myelin measure gave the most accurate predictions, while the fractional anisotropy performed poorly. Overall, different structural metrics paint very different pictures of the structural connectome and its relationship to functional connectivity.

Diffusion tensor imaging of the anterior cruciate ligament following primary repair with internal bracing: A longitudinal study

Diffusion tensor imaging (DTI) provides information about tissue microstructure and its degree of organization by quantifying water diffusion. We aimed to monitor longitudinal changes in DTI parameters (fractional isotropy, FA; mean diffusivity, MD; axial diffusivity, AD; radial diffusivity, RD) of the anterior cruciate ligament (ACL) following primary repair with internal bracing (IBLA). Fourteen patients undergoing IBLA were enrolled prospectively and scheduled for clinical follow-up, including instrumented laxity testing, and DTI at 3, 6, 12, and 24 months postoperatively. DTI was also performed in seven healthy subjects. Fiber tractography was used for 3D segmentation of the whole ACL volume, from which median DTI parameters were calculated. The posterior cruciate ligament (PCL) served as a control. Longitudinal DTI changes were assessed using a linear mixed model, and repeated measures correlations were calculated between DTI parameters and clinical laxity tests. At follow-up, thirteen patients had a stable knee and one patient sustained an ACL rerupture after 12 months postoperatively. The ACL repair showed a significant decrease of FA within the first 12 months after surgery, followed by stable FA values thereafter, while ACL diffusivities decreased over time returning towards normal values at 24 months postoperatively. For PCL there were no significant DTI changes over time. There was a significant correlation between ACL FA and laxity tests (r = -0.42, P = .017). This study has shown the potential of DTI to longitudinally monitor diffusion changes in the ACL following IBLA. The DTI findings suggest that healing of the ACL repair is incomplete at 24 months postoperatively.

Prediction of Motor Recovery after Stroke by Assessment of Corticospinal Tract Wallerian Degeneration Using Diffusion Tensor Imaging

Aim of the Study To predict motor recovery after stroke by detection of diffusion tensor imaging (DTI) fractional anisotropy (FA) changes of corticospinal tract (CST) and correlate findings with clinical scores to provide more effective treatment and rehabilitation.

Subjects and Methods Thirty patients with cerebral stroke were enrolled and underwent conventional magnetic resonance imaging and DTI at admission and 1 month after stroke. Mean diffusivity (MD), FA, FA ratio (rFA), and fiber number (FN) values of CST were calculated at the pons at admission and after 1 month of stroke. Three-dimensional reconstruction of bilateral CST and the structural changes of fibrous bands were observed. Severity of limb weakness was assessed by using the motor sub-index scores of the National Institutes of Health Stroke Scale (NIHSS) at admission, and after 1, 6, and 9 months for severity of limb weakness.

Results The mean age of our patients was 61.32 ± 4.34 years, 17/30 (56.6%) were females, and 13/30 (43.4%) were males. In our study, 18/30 (60%) were hypertensive, 19/30 (63.3%) were diabetic, and 12/30 (40%) were smokers. A significant negative correlation was found between rFA and FN in the ipsilateral CST of the cerebral infarction at the rostral part of pons after 1 month of infarction and NIHSS score at 6 months ( r = 0.377, p = 0.04 and r = 0.237, p = 0.02, respectively). However, a positive insignificant correlation was found between MD and NIHSS ( r = 0.345, p = 0.635). The initial NIHSS score at the time of injury was 19.2 ± 4.3, which changed to 7.9 ± 2.4, 4.6 ± 1.9, and 3.3 ± 1.4 at 1, 6, and 9 months, respectively.

Conclusion DTI is a sensitive tool for early detection of Wallerian degeneration in the CST after stroke, and can predict motor performance to provide effective treatment and rehabilitation to improve quality of life.

Neuroimaging and DNA Methylation: An Innovative Approach to Study the Effects of Early Life Stress on Developmental Plasticity

DNA methylation plays a key role in neural cell fate and provides a molecular link between early life stress and later-life behavioral phenotypes. Here, studies that combine neuroimaging methods and DNA methylation analysis in pediatric population with a history of adverse experiences were systematically reviewed focusing on: targeted genes and neural correlates; statistical models used to examine the link between DNA methylation and neuroimaging data also considering early life stress and behavioral outcomes. We identified 8 studies that report associations between DNA methylation and brain structure/functions in infants, school age children and adolescents faced with early life stress condition (e.g., preterm birth, childhood maltreatment, low socioeconomic status, and less-than optimal caregiving). Results showed that several genes were investigated (e.g., OXTR, SLC6A4, FKBP5, and BDNF) and different neuroimaging techniques were performed (MRI and f-NIRS). Statistical model used ranged from correlational to more complex moderated mediation models. Most of the studies (n = 5) considered DNA methylation and neural correlates as mediators in the relationship between early life stress and behavioral phenotypes. Understanding what role DNA methylation and neural correlates play in interaction with early life stress and behavioral outcomes is crucial to promote theory-driven studies as the future direction of this research fields.

The utility of diffusion tractography for speech preservation in laser ablation of the dominant insula: illustrative case

BACKGROUND

Open surgical treatment of insular epilepsy holds particular risk of injury to middle cerebral artery branches, the operculum (through retraction), and adjacent language-related white matter tracts in the language-dominant hemisphere. Magnetic resonance imaging (MRI)-guided laser interstitial thermal therapy (LITT) is a surgical alternative that allows precise lesioning with potentially less operative risk. The authors presented the case of a 13-year-old girl with intractable, MRI-negative, left (dominant hemisphere) insular epilepsy that was treated with LITT. Diffusion tensor imaging (DTI) tractography was used to aid full posterior insular lesioning in the region of stereo electroencephalography–determined seizure onset while avoiding thermal injury to the language-related superior longitudinal fasciculus (SLF)/arcuate fasciculus (AF) and inferior fronto-occipital fasciculus (IFOF).

OBSERVATIONS

DTI tractography was used successfully in planning insular LITT and facilitated a robust insular ablation with sharp margins at the interfaces with the SLF/AF and IFOF. These tracts were spared, and no neurological deficits were induced through LITT.

LESSONS

Although it is technically demanding and has important limitations that must be understood, clinically available DTI tractography adds precision and confidence to insular laser ablation when used to protect important language-related white matter tracts.

White matter microstructural changes in short-term learning of a continuous visuomotor sequence

Efficient neural transmission is crucial for optimal brain function, yet the plastic potential of white matter (WM) has long been overlooked. Growing evidence now shows that modifications to axons and myelin occur not only as a result of long-term learning, but also after short training periods. Motor sequence learning (MSL), a common paradigm used to study neuroplasticity, occurs in overlapping learning stages and different neural circuits are involved in each stage. However, most studies investigating short-term WM plasticity have used a pre-post design, in which the temporal dynamics of changes across learning stages cannot be assessed. In this study, we used multiple magnetic resonance imaging (MRI) scans at 7 T to investigate changes in WM in a group learning a complex visuomotor sequence (LRN) and in a control group (SMP) performing a simple sequence, for five consecutive days. Consistent with behavioral results, where most improvements occurred between the two first days, structural changes in WM were observed only in the early phase of learning (d1-d2), and in overall learning (d1-d5). In LRNs, WM microstructure was altered in the tracts underlying the primary motor and sensorimotor cortices. Moreover, our structural findings in WM were related to changes in functional connectivity, assessed with resting-state functional MRI data in the same cohort, through analyses in regions of interest (ROIs). Significant changes in WM microstructure were found in a ROI underlying the right supplementary motor area. Together, our findings provide evidence for highly dynamic WM plasticity in the sensorimotor network during short-term MSL.

Application of Diffusion Weighted Imaging and Diffusion Tensor Imaging in the Pretreatment and Post-treatment of Brain Tumor

Diffusion MR imaging exploits the diffusion properties of water to generate contrast between normal tissue and pathology. Diffusion is an essential component of nearly all brain tumor MR imaging examinations. This review covers the important clinical applications of diffusion weighted imaging in the pretreatment diagnosis and grading of brain tumors and assessment of treatment response. Diffusion imaging improves the accuracy of identifying treatment-related effects that may mimic tumor improvement or worsening. Fiber tractography models of eloquent white matter pathways are generated using diffusion tensor imaging. A practical and concise tractography guide is provided for anyone new to preoperative surgical mapping.

Diffusion Tensor Imaging of the Spinal Cord

Spinal cord often is regarded as one of the last territories in the central nervous system where diffusion tensor imaging (DTI) can be used to probe white matter architecture. This article reviews current progress in spinal cord DTI, starting with anatomic properties and technical challenges that make spinal cord DTI a difficult task. Several possibilities offered by advanced pulse sequences that might overcome the difficulties are addressed, with associated trade-offs and limitations. Potential clinical assistance also is discussed in various spinal cord pathologies, such as myelopathy due to external compression, spinal cord tumors, acute ischemia, traumatic injury, and so forth.

Molecular and Diffusion Tensor Imaging Biomarkers of Traumatic Brain Injury: Principles for Investigation and Integration

The last 20 years have seen the advent of new technologies that enhance the diagnosis and prognosis of traumatic brain injury (TBI). There is recognition that TBI affects the brain beyond initial injury, in some cases inciting a progressive neuropathology that leads to chronic impairments. Medical researchers are now searching for biomarkers to detect and monitor this condition. Perhaps the most promising developments are in the biomolecular and neuroimaging domains. Molecular assays can identify proteins indicative of neuronal injury and/or degeneration. Diffusion imaging now allows sensitive evaluations of the brain's cellular microstructure. As the pace of discovery accelerates, it is important to survey the research landscape and identify promising avenues of investigation. In this review, we discuss the potential of molecular and diffusion tensor imaging (DTI) biomarkers in TBI research. Integration of these technologies could advance models of disease prognosis, ultimately improving care. To date, however, few studies have explored relationships between molecular and DTI variables in patients with TBI. Here, we provide a short primer on each technology, review the latest research, and discuss how these biomarkers may be incorporated in future studies.

Clinical Imaging of Cerebral Cavernous Malformations: Computed Tomography and Magnetic Resonance Imaging

This is a review of imaging techniques used to evaluate cerebral cavernous malformations (CCMs) and imaging findings associated with CCMs. This chapter includes discussion of computed tomography and magnetic resonance imaging sequences, appearance of CCMs and associated hemorrhage and key features to evaluate on imaging studies.

Additive and Synergistic Cardiovascular Disease Risk Factors and HIV Disease Markers' Effects on White Matter Microstructure in Virally Suppressed HIV

BACKGROUND

It is unclear whether intermediate to high cardiovascular disease (CVD) risk and HIV disease status may have additive (ie, independent statistical effects concomitantly tested) or synergistic effects on white matter microstructure and cognition in virally suppressed HIV-infected (HIV+) men relative to sex and age-matched controls.

SETTING

Tertiary health care observational cohort.

METHODS

Eighty-two HIV+ men (mean age 55 ± 6 years, 10%-30% on various CVD drugs; 20% with previous CVD) and 40 HIV-uninfected (HIV-) men (none with previous CVD; 10%-20% on various CVD drugs) underwent diffusion tensor imaging and neuropsychological testing. A standard classification of intermediate to high CVD risk (CVD+ group) was based on the Framingham score ≥15% cutoff and/or a history of CVD. Fractional anisotropy (FA) and mean diffusivity (MD) were quantified in 11 white matter tracts.

RESULTS

Within the HIV- group, the CVD+ group had lower FA (P = 0.03) and higher MD (P = 0.003) in the corona radiata and higher MD in the corpus callosum (P = 0.02) and superior fasciculi (P = 0.03) than the CVD- group. Within the HIV+ group, the CVD+ group had lower FA in the superior fasciculi (P = 0.04) and higher MD in the uncinate fasciculus (P = 0.04), and lower FA (P = 0.01) and higher MD (P = 0.03) in the fornix than the CVD- group. The fornix alterations were also abnormal compared with the HIV- groups. The HIV+ CVD+ was more likely to have HIV-associated dementia. Older age, antihypertensive use, longer HIV duration, and higher C-reactive protein associated with lower FA and higher MD. Higher blood CD4 lymphocyte count and CD4/CD8 ratio associated with higher FA and lower MD.

CONCLUSIONS

In virally suppressed HIV, CVD risk factors have a mostly additive contribution to white matter microstructural alterations, leading to a different distribution of injury in HIV- and HIV+ persons with CVD. There was also evidence of a synergistic effect of CVD and HIV factors on the fornix white matter injury.

An overview of fractional anisotropy as a reliable quantitative measurement for the corticospinal tract (CST) integrity in correlation with a Fugl-Meyer assessment in stroke rehabilitation

[Purpose] Understanding the essential mechanisms in post-stroke recovery not only provides important basic insights into brain function and plasticity but can also guide the development of new therapeutic approaches for stroke patients. This review aims to give an overview of how various variables of Magnetic Resonance-Diffusion Tensor Imaging (MR-DTI) metrics of fractional anisotropy (FA) can be used as a reliable quantitative measurement and indicator of corticospinal tract (CST) changes, particularly in relation to functional motor outcome correlation with a Fugl-Meyer assessment in stroke rehabilitation. [Methods] PubMed electronic database was searched for the relevant literature, using key words of diffusion tensor imaging (dti), corticospinal tract, and stroke. [Results] We reviewed the role of FA in monitoring CST remodeling and its role of predicting motor recovery after stroke. We also discussed the mechanism of CST remodeling and its modulation from the value of FA and FMA-UE. [Conclusion] Heterogeneity of post-stroke brain disorganization and motor impairment is a recognized challenge in the development of accurate indicators of CST integrity. DTI-based FA measurements offer a reliable and evidence-based indicator for CST integrity that would aid in predicting motor recovery within the context of stroke rehabilitation.

Secondary Degeneration of White Matter After Focal Sensorimotor Cortical Ischemic Stroke in Rats

Ischemic lesions could lead to secondary degeneration in remote regions of the brain. However, the spatial distribution of secondary degeneration along with its role in functional deficits is not well understood. In this study, we explored the spatial and connectivity properties of white matter (WM) secondary degeneration in a focal unilateral sensorimotor cortical ischemia rat model, using advanced microstructure imaging on a 14 T MRI system. Significant axonal degeneration was observed in the ipsilateral external capsule and even remote regions including the contralesional external capsule and corpus callosum. Further fiber tractography analysis revealed that only fibers having direct axonal connections with the primary lesion exhibited a significant degeneration. These results suggest that focal ischemic lesions may induce remote WM degeneration, but limited to fibers tied to the primary lesion. These “direct” fibers mainly represent perilesional, interhemispheric, and subcortical axonal connections. At last, we found that primary lesion volume might be the determining factor of motor function deficits.

Myelin development in visual scene-network tracts beyond late childhood: A multimethod neuroimaging study

The visual scene-network-comprising the parahippocampal place area (PPA), retrosplenial cortex (RSC), and occipital place area (OPA)-shows a prolonged functional development. Structural development of white matter that underlies the scene-network has not been investigated despite its potential influence on scene-network function. The key factor for white matter maturation is myelination. However, research on myelination using the gold standard method of post-mortem histology is scarce. In vivo alternatives diffusion-weighted imaging (DWI) and myelin water imaging (MWI) so far report broad-scale findings that prohibit inferences concerning the scene-network. Here, we combine MWI, DWI tractography, and fMRI to investigate myelination in scene-network tracts in middle childhood, late childhood, and adulthood. We report increasing myelin from middle childhood to adulthood in right PPA-OPA, and trends towards increases in the left and right RSC-OPA tracts. Investigating tracts to regions highly connected with the scene-network, such as early visual cortex and the hippocampus, did not yield any significant age group differences. Our findings indicate that structural development coincides with functional development in the scene-network, possibly enabling structure-function interactions.

In vivo detection of microstructural spinal cord lesions in dogs with degenerative myelopathy using diffusion tensor imaging

Background

Degenerative myelopathy (DM) in dogs is a progressive neurodegenerative condition that causes white matter spinal cord lesions. These lesions are undetectable on standard magnetic resonance imaging (MRI), limiting diagnosis and monitoring of the disease. Spinal cord lesions cause disruption to the structural integrity of the axons causing water diffusion to become more random and less anisotropic. These changes are detectable by the technique of diffusion tensor imaging (DTI) which is highly sensitive to diffusion alterations secondary to white matter lesion development.

Objective

Perform spinal DTI on cohorts of dogs with and without DM to identify if lesions caused by DM will cause a detectable alteration in spinal cord diffusivity that correlates with neurological status.

Animals

Thirteen dogs with DM and 13 aged‐matched controls.

Methods

All animals underwent MRI with DTI of the entire spine. Diffusivity parameters fractional anisotropy (FA) and mean diffusivity (MD) were measured at each vertebral level and statistically compared between groups.

Results

Dogs with DM had significant decreases in FA within the regions of the spinal cord that had high expected lesion load. Decreases in FA were most significant in dogs with severe forms of the disease and correlated with neurological grade.

Conclusions and Clinical Importance

Findings suggest that FA has the potential to be a biomarker for spinal cord lesion development in DM and could play an important role in improving diagnosis and monitoring of this condition.

High-Resolution 3D in vivo Brain Diffusion Tensor Imaging at Ultrahigh Fields: Following Maturation on Juvenile and Adult Mice

Diffusion tensor imaging (DTI) is a well-established technique for mapping brain microstructure and white matter tracts in vivo. High resolution DTI, however, is usually associated with low intrinsic sensitivity and therefore long acquisition times. By increasing sensitivity, high magnetic fields can alleviate these demands, yet high fields are also typically associated with significant susceptibility-induced image distortions. This study explores the potential arising from employing new pulse sequences and emerging hardware at ultrahigh fields, to overcome these limitations. To this end, a 15.2 T MRI instrument equipped with a cryocooled surface transceiver coil was employed, and DTI experiments were compared between SPatiotemporal ENcoding (SPEN), a technique that tolerates well susceptibility-induced image distortions, and double-sampled Spin-Echo Echo-Planar Imaging (SE-EPI) methods. Following optimization, SE-EPI afforded whole brain DTI maps at 135 μm isotropic resolution that possessed higher signal-to-noise ratios (SNRs) than SPEN counterparts. SPEN, however, was a better alternative to SE-EPI when focusing on challenging regions of the mouse brain -including the olfactory bulb and the cerebellum. In these instances, the higher robustness of fully refocused SPEN acquisitions coupled to its built-in zooming abilities, provided in vivo DTI maps with 75 μm nominal isotropic spatial resolution. These DTI maps, and in particular the mean diffusion direction (MDD) details, exhibited variations that matched very well the anatomical features known from histological brain Atlases. Using these capabilities, the development of the olfactory bulb (OB) in live mice was followed from week 1 post-partum, until adulthood. The diffusivity of this organ showed a systematic decrease in its overall isotropic value and increase in its fractional anisotropy with age; this maturation was observed for all regions used in the OB's segmentation but was most evident for the lobules' centers, in particular for the granular cell layer. The complexity of the OB neuronal connections also increased during maturation, as evidenced by the growth in directionalities arising in the mean diffusivity direction maps.