Hybrid Diffusion Imaging in Mild Traumatic Brain Injury

White Matter Alterations in Military Service Members With Remote Mild Traumatic Brain Injury

Importance

Mild traumatic brain injury (mTBI) is the signature injury experienced by military service members and is associated with poor neuropsychiatric outcomes. Yet, there is a lack of reliable clinical tools for mTBI diagnosis and prognosis.

Objective

To examine the white matter microstructure and neuropsychiatric outcomes of service members with a remote history of mTBI (ie, mTBI that occurred over 2 years ago) using diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI).

Design, Setting, and Participants

This case-control study examined 98 male service members enrolled in a study at the National Intrepid Center of Excellence. Eligible participants were active duty status or able to enroll in the Defense Enrollment Eligibility Reporting system, ages 18 to 60 years, and had a remote history of mTBI; controls were matched by age.

Exposures

Remote history of mTBI.

Main Outcomes and Measures

White matter microstructure was assessed using a region-of-interest approach of skeletonized diffusion images, including DTI (fractional anisotropy, mean diffusivity, radial diffusivity and axial diffusivity) and NODDI (orientation dispersion index [ODI], isotropic volume fraction, intra-cellular volume fraction). Neuropsychiatric outcomes associated with posttraumatic stress disorder (PTSD) and postconcussion syndrome were assessed.

Results

A total of 65 male patients with a remote history of mTBI (mean [SD] age, 40.5 [5.0] years) and 33 age-matched male controls (mean [SD] age, 38.9 [5.6] years) were included in analysis. Compared with the control cohort, the 65 service members with mTBI presented with significantly more severe PTSD-like symptoms (mean [SD] PTSD CheckList-Civilian [PCL-C] version scores: control, 19.0 [3.8] vs mTBI, 41.2 [11.6]; P < .001). DTI and NODDI metrics were altered in the mTBI group compared with the control, including intra-cellular volume fraction of the right cortico-spinal tract (β = -0.029, Cohen d = 0.66; P < .001), ODI of the left posterior thalamic radiation (β = -0.006, Cohen d = 0.55; P < .001), and ODI of the left uncinate fasciculus (β = 0.013, Cohen d = 0.61; P < .001). In service members with mTBI, fractional anisotropy of the left uncinate fasciculus was associated with postconcussion syndrome (β = 5.4 × 10-3; P = .003), isotropic volume fraction of the genu of the corpus callosum with PCL-C (β = 4.3 × 10-4; P = .01), and ODI of the left fornix and stria terminalis with PCL-C avoidance scores (β = 1.2 × 10-3; P = .02).

Conclusions and Relevance

In this case-control study of military-related mTBI, the results suggest that advanced magnetic resonance imaging techniques using NODDI can reveal white matter microstructural alterations associated with neuropsychiatric symptoms in the chronic phase of mTBI. Diffusion trends observed throughout widespread white matter regions-of-interest may reflect mechanisms of neurodegeneration as well as postinjury tissue scarring and reorganization.

Return to Play Following Concussion: Role for Imaging?

This review surveys concussion management, focusing on the use of neuroimaging techniques in return to play (RTP) decisions. Clinical assessments traditionally were the foundation of concussion diagnoses. However, their subjective nature prompted an exploration of neuroimaging modalities to enhance diagnosis and management. Magnetic resonance spectroscopy provides information about metabolic changes and alterations in the absence of structural abnormalities. Diffusion tensor imaging uncovers microstructural changes in white matter. Functional magnetic resonance imaging assesses neuronal activity to reveal changes in cognitive and sensorimotor functions. Positron emission tomography can assess metabolic disturbances using radiotracers, offering insight into the long-term effects of concussions. Vestibulo-ocular dysfunction screening and eye tracking assess vestibular and oculomotor function. Although these neuroimaging techniques demonstrate promise, continued research and standardization are needed before they can be integrated into the clinical setting. This review emphasizes the potential for neuroimaging in enhancing the accuracy of concussion diagnosis and guiding RTP decisions.

Neurite Damage in Patients with Migraine

We examined neurite orientation dispersion and density imaging in patients with migraine. We found that patients with medication overuse headache exhibited lower orientation dispersion than those without. Moreover, orientation dispersion in the body of the corpus callosum was statistically negatively correlated with migraine attack frequencies. These findings indicate that neurite dispersion is damaged in patients with chronic migraine. Our study results indicate the orientation preference of neurite damage in migraine.

Associations of prior concussion severity with brain microstructure using mean apparent propagator magnetic resonance imaging

Magnetic resonance imaging (MRI) diffusion studies have shown chronic microstructural tissue abnormalities in athletes with history of concussion, but with inconsistent findings. Concussions with post-traumatic amnesia (PTA) and/or loss of consciousness (LOC) have been connected to greater physiological injury. The novel mean apparent propagator (MAP) MRI is expected to be more sensitive to such tissue injury than the conventional diffusion tensor imaging. This study examined effects of prior concussion severity on microstructure with MAP-MRI. Collegiate-aged athletes (N = 111, 38 females; ≥6 months since most recent concussion, if present) completed semistructured interviews to determine the presence of prior concussion and associated injury characteristics, including PTA and LOC. MAP-MRI metrics (mean non-Gaussian diffusion [NG Mean], return-to-origin probability [RTOP], and mean square displacement [MSD]) were calculated from multi-shell diffusion data, then evaluated for associations with concussion severity through group comparisons in a primary model (athletes with/without prior concussion) and two secondary models (athletes with/without prior concussion with PTA and/or LOC, and athletes with/without prior concussion with LOC only). Bayesian multilevel modeling estimated models in regions of interest (ROI) in white matter and subcortical gray matter, separately. In gray matter, the primary model showed decreased NG Mean and RTOP in the bilateral pallidum and decreased NG Mean in the left putamen with prior concussion. In white matter, lower NG Mean with prior concussion was present in all ROI across all models and was further decreased with LOC. However, only prior concussion with LOC was associated with decreased RTOP and increased MSD across ROI. Exploratory analyses conducted separately in male and female athletes indicate associations in the primary model may differ by sex. Results suggest microstructural measures in gray matter are associated with a general history of concussion, while a severity-dependent association of prior concussion may exist in white matter.

A cross-comparative analysis of in vivo versus ex vivo MRI indices in a mouse model of concussion

BACKGROUND

We present a cross-sectional, case-matched, and pair-wise comparison of structural magnetic resonance imaging (MRI), diffusion tensor imaging (DTI), and neurite orientation dispersion and density imaging (NODDI) measures in vivo and ex vivo in a mouse model of concussion, thus aiming to establish the concordance of structural and diffusion imaging findings in living brain and after fixation.

METHODS

We allocated 28 male mice aged 3-4 months to sham injury and concussion (CON) groups. CON mice had received a single concussive impact on day 0 and underwent MRI at day 2 (n = 9) or 7 (n = 10) post-impact, and sham control mice likewise underwent imaging at day 2 (n = 5) or 7 (n = 4). Immediately after the final scanning, we collected the perfusion-fixed brains, which were stored for imaging ex vivo 6-12 months later. We then compared the structural imaging, DTI, and NODDI results between different methods.

RESULTS

In vivo to ex vivo structural and DTI/NODDI findings were in notably poor agreement regarding the effects of concussion on structural integrity of the brain.

COMPARISON WITH EXISTING METHODS

ex vivo imaging was frequently done to study the effects of diseases and treatments, but our results showed that ex vivo and in vivo imaging can detect completely opposite and contradictory results. This is also the first study that compares in vivo and ex vivo NODDI.

CONCLUSION

Our findings call for caution in extrapolating translational capabilities obtained ex vivo to physiological measurements in vivo. The divergent findings may reflect fixation artefacts and the contribution of the glymphatic system changes.

The relationship between cognition and white matter tract damage after mild traumatic brain injury in a premorbidly healthy, hospitalised adult cohort during the post-acute period

Introduction

Recent developments in neuroimaging techniques enable increasingly sensitive consideration of the cognitive impact of damage to white matter tract (WMT) microstructural organisation after mild traumatic brain injury (mTBI).

Objective

This study investigated the relationship between WMT microstructural properties and cognitive performance.

Participants setting and design

Using an observational design, a group of 26 premorbidly healthy adults with mTBI and a group of 20 premorbidly healthy trauma control (TC) participants who were well-matched on age, sex, premorbid functioning and a range of physical, psychological and trauma-related variables, were recruited following hospital admission for traumatic injury.

Main measures

All participants underwent comprehensive unblinded neuropsychological examination and structural neuroimaging as outpatients 6-10 weeks after injury. Neuropsychological examination included measures of speed of processing, attention, memory, executive function, affective state, pain, fatigue and self-reported outcome. The WMT microstructural properties were estimated using both diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) modelling techniques. Tract properties were compared between the corpus callosum, inferior longitudinal fasciculus, uncinate fasciculus, anterior corona radiata and three segmented sections of the superior longitudinal fasciculus.

Results

For the TC group, in all investigated tracts, with the exception of the uncinate fasciculus, two DTI metrics (fractional anisotropy and apparent diffusion coefficient) and one NODDI metric (intra-cellular volume fraction) revealed expected predictive linear relationships between extent of WMT microstructural organisation and processing speed, memory and executive function. The mTBI group showed a strikingly different pattern relative to the TC group, with no relationships evident between WMT microstructural organisation and cognition on most tracts.

Conclusion

These findings indicate that the predictive relationship that normally exists in adults between WMT microstructural organisation and cognition, is significantly disrupted 6-10 weeks after mTBI and suggests that WMT microstructural organisation and cognitive function have disparate recovery trajectories.

Machine learning-based classification of chronic traumatic brain injury using hybrid diffusion imaging

Background and purpose

Traumatic brain injury (TBI) can cause progressive neuropathology that leads to chronic impairments, creating a need for biomarkers to detect and monitor this condition to improve outcomes. This study aimed to analyze the ability of data-driven analysis of diffusion tensor imaging (DTI) and neurite orientation dispersion imaging (NODDI) to develop biomarkers to infer symptom severity and determine whether they outperform conventional T1-weighted imaging.

Materials and methods

A machine learning-based model was developed using a dataset of hybrid diffusion imaging of patients with chronic traumatic brain injury. We first extracted the useful features from the hybrid diffusion imaging (HYDI) data and then used supervised learning algorithms to classify the outcome of TBI. We developed three models based on DTI, NODDI, and T1-weighted imaging, and we compared the accuracy results across different models.

Results

Compared with the conventional T1-weighted imaging-based classification with an accuracy of 51.7-56.8%, our machine learning-based models achieved significantly better results with DTI-based models at 58.7-73.0% accuracy and NODDI with an accuracy of 64.0-72.3%.

Conclusion

The machine learning-based feature selection and classification algorithm based on hybrid diffusion features significantly outperform conventional T1-weighted imaging. The results suggest that advanced algorithms can be developed for inferring symptoms of chronic brain injury using feature selection and diffusion-weighted imaging.

Longitudinal Associations Between Blood Biomarkers and White Matter MRI in Sport-Related Concussion: A Study of the NCAA-DoD CARE Consortium

BACKGROUND AND OBJECTIVES

To study longitudinal associations between blood-based neural biomarkers (including total tau, neurofilament light [NfL], glial fibrillary acidic protein [GFAP], and ubiquitin C-terminal hydrolase-L1) and white matter neuroimaging biomarkers in collegiate athletes with sport-related concussion (SRC) from 24 hours postinjury to 1 week after return to play.

METHODS

We analyzed clinical and imaging data of concussed collegiate athletes in the Concussion Assessment, Research, and Education (CARE) Consortium. The CARE participants completed same-day clinical assessments, blood draws, and diffusion tensor imaging (DTI) at 3 time points: 24-48 hours postinjury, point of becoming asymptomatic, and 7 days after return to play. DTI probabilistic tractography was performed for each participant at each time point to render 27 participant-specific major white matter tracts. The microstructural organization of these tracts was characterized by 4 DTI metrics. Mixed-effects models with random intercepts were applied to test whether white matter microstructural abnormalities are associated with the blood-based biomarkers at the same time point. An interaction model was used to test whether the association varies across time points. A lagged model was used to test whether early blood-based biomarkers predict later microstructural changes.

RESULTS

Data from 77 collegiate athletes were included in the following analyses. Among the 4 blood-based biomarkers, total tau had significant associations with the DTI metrics across the 3 time points. In particular, high tau level was associated with high radial diffusivity (RD) in the right corticospinal tract (β = 0.25, SE = 0.07, p FDR-adjusted = 0.016) and superior thalamic radiation (β = 0.21, SE = 0.07, p FDR-adjusted = 0.042). NfL and GFAP had time-dependent associations with the DTI metrics. NfL showed significant associations only at the asymptomatic time point (|β|s > 0.12, SEs <0.09, psFDR-adjusted < 0.05) and GFAP showed a significant association only at 7 days after return to play (βs > 0.14, SEs <0.06, psFDR-adjusted < 0.05). The p values for the associations of early tau and later RD were not significant after multiple comparison adjustment, but were less than 0.1 in 7 white matter tracts.

DISCUSSION

This prospective study using data from the CARE Consortium demonstrated that in the early phase of SRC, white matter microstructural integrity detected by DTI neuroimaging was associated with elevated levels of blood-based biomarkers of traumatic brain injury. Total tau in the blood showed the strongest association with white matter microstructural changes.

Use of Support Vector Machines Approach via ComBat Harmonized Diffusion Tensor Imaging for the Diagnosis and Prognosis of Mild Traumatic Brain Injury: A CENTER-TBI Study

The prediction of functional outcome after mild traumatic brain injury (mTBI) is challenging. Conventional magnetic resonance imaging (MRI) does not do a good job of explaining the variance in outcome, as many patients with incomplete recovery will have normal-appearing clinical neuroimaging. More advanced quantitative techniques such as diffusion MRI (dMRI), can detect microstructural changes not otherwise visible, and so may offer a way to improve outcome prediction. In this study, we explore the potential of linear support vector classifiers (linearSVCs) to identify dMRI biomarkers that can predict recovery after mTBI. Simultaneously, the harmonization of fractional anisotropy (FA) and mean diffusivity (MD) via ComBat was evaluated and compared for the classification performances of the linearSVCs. We included dMRI scans of 179 mTBI patients and 85 controls from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI), a multi-center prospective cohort study, up to 21 days post-injury. Patients were dichotomized according to their Extended Glasgow Outcome Scale (GOSE) scores at 6 months into complete (n = 92; GOSE = 8) and incomplete (n = 87; GOSE <8) recovery. FA and MD maps were registered to a common space and harmonized via the ComBat algorithm. LinearSVCs were applied to distinguish: (1) mTBI patients from controls and (2) mTBI patients with complete from those with incomplete recovery. The linearSVCs were trained on (1) age and sex only, (2) non-harmonized, (3) two-category-harmonized ComBat, and (4) three-category-harmonized ComBat FA and MD images combined with age and sex. White matter FA and MD voxels and regions of interest (ROIs) within the John Hopkins University (JHU) atlas were examined. Recursive feature elimination was used to identify the 10% most discriminative voxels or the 10 most discriminative ROIs for each implementation. mTBI patients displayed significantly higher MD and lower FA values than controls for the discriminative voxels and ROIs. For the analysis between mTBI patients and controls, the three-category-harmonized ComBat FA and MD voxel-wise linearSVC provided significantly higher classification scores (81.4% accuracy, 93.3% sensitivity, 80.3% F1-score, and 0.88 area under the curve [AUC], p < 0.05) compared with the classification based on age and sex only and the ROI approaches (accuracies: 59.8% and 64.8%, respectively). Similar to the analysis between mTBI patients and controls, the three-category-harmonized ComBat FA and MD maps voxelwise approach yields statistically significant prediction scores between mTBI patients with complete and those with incomplete recovery (71.8% specificity, 66.2% F1-score and 0.71 AUC, p < 0.05), which provided a modest increase in the classification score (accuracy: 66.4%) compared with the classification based on age and sex only and ROI-wise approaches (accuracy: 61.4% and 64.7%, respectively). This study showed that ComBat harmonized FA and MD may provide additional information for diagnosis and prognosis of mTBI in a multi-modal machine learning approach. These findings demonstrate that dMRI may assist in the early detection of patients at risk of incomplete recovery from mTBI.

Emotional Regulation and Adolescent Concussion: Overview and Role of Neuroimaging

Emotional dysregulation symptoms following a concussion are associated with an increased risk for emotional dysregulation disorders (e.g., depression and anxiety), especially in adolescents. However, predicting the emergence or worsening of emotional dysregulation symptoms after concussion and the extent to which this predates the onset of subsequent psychiatric morbidity after injury remains challenging. Although advanced neuroimaging techniques, such as functional magnetic resonance imaging and diffusion magnetic resonance imaging, have been used to detect and monitor concussion-related brain abnormalities in research settings, their clinical utility remains limited. In this narrative review, we have performed a comprehensive search of the available literature regarding emotional regulation, adolescent concussion, and advanced neuroimaging techniques in electronic databases (PubMed, Scopus, and Google Scholar). We highlight clinical evidence showing the heightened susceptibility of adolescents to experiencing emotional dysregulation symptoms following a concussion. Furthermore, we describe and provide empirical support for widely used magnetic resonance imaging modalities (i.e., functional and diffusion imaging), which are utilized to detect abnormalities in circuits responsible for emotional regulation. Additionally, we assess how these abnormalities relate to the emotional dysregulation symptoms often reported by adolescents post-injury. Yet, it remains to be determined if a progression of concussion-related abnormalities exists, especially in brain regions that undergo significant developmental changes during adolescence. We conclude that neuroimaging techniques hold potential as clinically useful tools for predicting and, ultimately, monitoring the treatment response to emotional dysregulation in adolescents following a concussion.

Effects of acute alcohol exposure and chronic alcohol use on neurite orientation dispersion and density imaging (NODDI) parameters

RATIONALE

Little is known about how acute and chronic alcohol exposure may alter the in vivo membrane properties of neurons.

OBJECTIVES

We employed neurite orientation dispersion and density imaging (NODDI) to examine acute and chronic effects of alcohol exposure on neurite density.

METHODS

Twenty-one healthy social drinkers (CON) and thirteen nontreatment-seeking individuals with alcohol use disorder (AUD) underwent a baseline multi-shell diffusion magnetic resonance imaging (dMRI) scan. A subset (10 CON, 5 AUD) received dMRI during intravenous infusions of saline and alcohol during dMRI. NODDI parametric images included orientation dispersion (OD), isotropic volume fraction (ISOVF), and corrected intracellular volume fraction (cICVF). Diffusion tensor imaging metrics of fractional anisotropy and mean, axial, and radial diffusivity (FA, MD, AD, RD) were also computed. Average parameter values were extracted from white matter (WM) tracts defined by the Johns Hopkins University atlas.

RESULTS

There were group differences in FA, RD, MD, OD, and cICVF, primarily in the corpus callosum. Both saline and alcohol had effects on AD and cICVF in WM tracts proximal to the striatum, cingulate, and thalamus. This is the first work to indicate that acute fluid infusions may alter WM properties, which are conventionally believed to be insensitive to acute pharmacological challenges. It also suggests that the NODDI approach may be sensitive to transient changes in WM. The next steps should include determining if the effect on neurite density differs with solute or osmolality, or both, and translational studies to assess how alcohol and osmolality affect the efficiency of neurotransmission.

Diffusion-Weighted Imaging in Mild Traumatic Brain Injury: A Systematic Review of the Literature

There is evidence that diffusion-weighted imaging (DWI) is able to detect tissue alterations following mild traumatic brain injury (mTBI) that may not be observed on conventional neuroimaging; however, findings are often inconsistent between studies. This systematic review assesses patterns of differences in DWI metrics between those with and without a history of mTBI. A PubMed literature search was performed using relevant indexing terms for articles published prior to May 14, 2020. Findings were limited to human studies using DWI in mTBI. Articles were excluded if they were not full-length, did not contain original data, if they were case studies, pertained to military populations, had inadequate injury severity classification, or did not report post-injury interval. Findings were reported independently for four subgroups: acute/subacute pediatric mTBI, acute/subacute adult mTBI, chronic adult mTBI, and sport-related concussion, and all DWI acquisition and analysis methods used were included. Patterns of findings between studies were reported, along with strengths and weaknesses of the current state of the literature. Although heterogeneity of sample characteristics and study methods limited the consistency of findings, alterations in DWI metrics were most commonly reported in the corpus callosum, corona radiata, internal capsule, and long association pathways. Many acute/subacute pediatric studies reported higher FA and lower ADC or MD in various regions. In contrast, acute/subacute adult studies most commonly indicate lower FA within the context of higher MD and RD. In the chronic phase of recovery, FA may remain low, possibly indicating overall demyelination or Wallerian degeneration over time. Longitudinal studies, though limited, generally indicate at least a partial normalization of DWI metrics over time, which is often associated with functional improvement. We conclude that DWI is able to detect structural mTBI-related abnormalities that may persist over time, although future DWI research will benefit from larger samples, improved data analysis methods, standardized reporting, and increasing transparency.

HYDI-DSI revisited: Constrained non-parametric EAP imaging without q-space re-gridding

Hybrid Diffusion Imaging (HYDI) was one of the first attempts to use multi-shell samplings of the q-space to infer diffusion properties beyond Diffusion Tensor Imaging (DTI) or High Angular Resolution Diffusion Imaging (HARDI). HYDI was intended as a flexible protocol embedding both DTI (for lower b-values) and HARDI (for higher b-values) processing, as well as Diffusion Spectrum Imaging (DSI) when the entire data set was exploited. In the latter case, the spherical sampling of the q-space is re-gridded by interpolation to a Cartesian lattice whose extent covers the range of acquired b-values, hence being acquisition-dependent. The Discrete Fourier Transform (DFT) is afterwards used to compute the corresponding Cartesian sampling of the Ensemble Average Propagator (EAP) in an entirely non-parametric way. From this lattice, diffusion markers such as the Return To Origin Probability (RTOP) or the Mean Squared Displacement (MSD) can be numerically estimated. We aim at re-formulating this scheme by means of a Fourier Transform encoding matrix that eliminates the need for q-space re-gridding at the same time it preserves the non-parametric nature of HYDI-DSI. The encoding matrix is adaptively designed at each voxel according to the underlying DTI approximation, so that an optimal sampling of the EAP can be pursued without being conditioned by the particular acquisition protocol. The estimation of the EAP is afterwards carried out as a regularized Quadratic Programming (QP) problem, which allows to impose positivity constraints that cannot be trivially embedded within the conventional HYDI-DSI. We demonstrate that the definition of the encoding matrix in the adaptive space allows to analytically (as opposed to numerically) compute several popular descriptors of diffusion with the unique source of error being the cropping of high frequency harmonics in the Fourier analysis of the attenuation signal. They include not only RTOP and MSD, but also Return to Axis/Plane Probabilities (RTAP/RTPP), which are defined in terms of specific spatial directions and are not available with the former HYDI-DSI. We report extensive experiments that suggest the benefits of our proposal in terms of accuracy, robustness and computational efficiency, especially when only standard, non-dedicated q-space samplings are available.

Association of sub-acute changes in plasma amino acid levels with long-term brain pathologies in a rat model of moderate-severe traumatic brain injury

Introduction

Traumatic brain injury (TBI) induces a cascade of cellular alterations that are responsible for evolving secondary brain injuries. Changes in brain structure and function after TBI may occur in concert with dysbiosis and altered amino acid fermentation in the gut. Therefore, we hypothesized that subacute plasma amino acid levels could predict long-term microstructural outcomes as quantified using neurite orientation dispersion and density imaging (NODDI).

Methods

Fourteen 8-10-week-old male rats were randomly assigned either to sham (n = 6) or a single moderate-severe TBI (n = 8) procedure targeting the primary somatosensory cortex. Venous blood samples were collected at days one, three, seven, and 60 post-procedure and NODDI imaging were carried out at day 60. Principal Component Regression analysis was used to identify time dependent plasma amino acid concentrations after in the subacute phase post-injury that predicted NODDI metric outcomes at day 60.

Results

The TBI group had significantly increased plasma levels of glutamine, arginine, alanine, proline, tyrosine, valine, isoleucine, leucine, and phenylalanine at days three-seven post-injury. Higher levels of several neuroprotective amino acids, especially the branched-chain amino acids (valine, isoleucine, leucine) and phenylalanine, as well as serine, arginine, and asparagine at days three-seven post-injury were also associated with lower isotropic diffusion volume fraction measures in the ventricles and thus lesser ventricular dilation at day 60.

Discussion

In the first such study, we examined the relationship between the long-term post-TBI microstructural outcomes across whole brain and the subacute changes in plasma amino acid concentrations. At days three to seven post-injury, we observed that increased plasma levels of several amino acids, particularly the branched-chain amino acids and phenylalanine, were associated with lesser degrees of ventriculomegaly and hydrocephalus TBI neuropathology at day 60 post-injury. The results imply that altered amino acid fermentation in the gut may mediate neuroprotection in the aftermath of TBI.

Effects of White-Matter Tract Length in Sport-Related Concussion: A Tractography Study from the NCAA-DoD CARE Consortium

Sport-related concussion (SRC) is an important public health issue. White-matter alterations after SRC are widely studied by neuroimaging approaches, such as diffusion magnetic resonance imaging (MRI). Although the exact anatomical location of the alterations may differ, significant white-matter alterations are commonly observed in long fiber tracts, but are never proven. In the present study, we performed streamline tractography to characterize the association between tract length and white-matter microstructural alterations after SRC. Sixty-eight collegiate athletes diagnosed with acute concussion (24-48 h post-injury) and 64 matched contact-sport controls were included in this study. The athletes underwent diffusion tensor imaging (DTI) in 3.0 T MRI scanners across three study sites. DTI metrics were used for tract-based spatial statistics to map white-matter regions-of-interest (ROIs) with significant group differences. Whole-brain white-mater streamline tractography was performed to extract "affected" white-matter streamlines (i.e., streamlines passing through the identified ROIs). In the concussed athletes, streamline counts and DTI metrics of the affected white-matter fiber tracts were summarized and compared with unaffected white-matter tracts across tract length in the same participant. The affected white-matter tracts had a high streamline count at length of 80-100 mm and high length-adjusted affected ratio for streamline length longer than 80 mm. DTI mean diffusivity was higher in the affected streamlines longer than 100 mm with significant associations with the Brief Symptom Inventory score. Our findings suggest that long fibers in the brains of collegiate athletes are more vulnerable to acute SRC with higher mean diffusivity and a higher affected ratio compared with the whole distribution.

Transdiagnostic In Vivo Magnetic Resonance Imaging Markers of Neuroinflammation

Accumulating evidence suggests that inflammation is not limited to archetypal inflammatory diseases such as multiple sclerosis, but instead represents an intrinsic feature of many psychiatric and neurological disorders not typically classified as neuroinflammatory. A growing body of research suggests that neuroinflammation can be observed in early and prodromal stages of these disorders and, under certain circumstances, may lead to tissue damage. Traditional methods to assess neuroinflammation include serum or cerebrospinal fluid markers and positron emission tomography. These methods require invasive procedures or radiation exposure and lack the exquisite spatial resolution of magnetic resonance imaging (MRI). There is, therefore, an increasing interest in noninvasive neuroimaging tools to evaluate neuroinflammation reliably and with high specificity. While MRI does not provide information at a cellular level, it facilitates the characterization of several biophysical tissue properties that are closely linked to neuroinflammatory processes. The purpose of this review is to evaluate the potential of MRI as a noninvasive, accessible, and cost-effective technology to image neuroinflammation across neurological and psychiatric disorders. We provide an overview of current and developing MRI methods used to study different aspects of neuroinflammation and weigh their strengths and shortcomings. Novel MRI contrast agents are increasingly able to target inflammatory processes directly, therefore offering a high degree of specificity, particularly if used in conjunction with multitissue, biophysical diffusion MRI compartment models. The capability of these methods to characterize several aspects of the neuroinflammatory milieu will likely push MRI to the forefront of neuroimaging modalities used to characterize neuroinflammation transdiagnostically.

White Matter Abnormalities and Cognitive Deficit After Mild Traumatic Brain Injury: Comparing DTI, DKI, and NODDI

White matter (WM) disruption is an important determinant of cognitive impairment after mild traumatic brain injury (mTBI), but traditional diffusion tensor imaging (DTI) shows some limitations in assessing WM damage. Diffusion kurtosis imaging (DKI) and neurite orientation dispersion and density imaging (NODDI) show advantages over DTI in this respect. Therefore, we used these three diffusion models to investigate complex WM changes in the acute stage after mTBI. From 32 mTBI patients and 31 age-, sex-, and education-matched healthy controls, we calculated eight diffusion metrics based on DTI (fractional anisotropy, axial diffusivity, radial diffusivity, and mean diffusivity), DKI (mean kurtosis), and NODDI (orientation dispersion index, volume fraction of intracellular water (Vic), and volume fraction of the isotropic diffusion compartment). We used tract-based spatial statistics to identify group differences at the voxel level, and we then assessed the correlation between diffusion metrics and cognitive function. We also performed subgroup comparisons based on loss of consciousness. Patients showed WM abnormalities and cognitive deficit. And these two changes showed positive correlation. The correlation between Vic of the splenium of the corpus callosum and Digit Symbol Substitution Test scores showed the smallest p-value (p = 0.000, r = 0.481). We concluded that WM changes, especially in the splenium of the corpus callosum, correlate to cognitive deficit in this study. Furthermore, the high voxel count of NODDI results and the consistency of mean kurtosis and the volume fraction of intracellular water in previous studies and our study showed the functional complementarity of DKI and NODDI to DTI.

Abnormal neurite density and orientation dispersion in frontal lobe link to elevated hyperactive/impulsive behaviors in young adults with traumatic brain injury

Traumatic brain injury is a major public health concern. A significant proportion of individuals experience post-traumatic brain injury behavioural impairments, especially in attention and inhibitory control domains. Traditional diffusion-weighted MRI techniques, such as diffusion tensor imaging, have provided tools to assess white matter structural disruptions reflecting the long-term brain tissue alterations associated with traumatic brain injury. The recently developed neurite orientation dispersion and density imaging is a more advanced diffusion MRI modality, which provides more refined characterization of brain tissue microstructures by assessing the neurite orientation dispersion and neurite density properties. In this study, neurite orientation dispersion and density imaging data from 44 young adults with chronic traumatic brain injury (who had no prior-injury diagnoses of any sub-presentation of attention deficits/hyperactivity disorder or experience of severe inattentive and/or hyperactive behaviours) and 45 group-matched normal controls were investigated, to assess the post-injury morphometrical and microstructural brain alterations and their relationships with the behavioural outcomes. Maps of fractional anisotropy, neurite orientation dispersion index and neurite density index were calculated. Vertex-wise and voxel-wise analyses were conducted for grey matter and white matter, respectively. Post hoc region-of-interest-based analyses were also performed. Compared to the controls, the group of traumatic brain injury showed significantly increased orientation dispersion index and significantly decreased neurite density index in various grey matter regions, as well as significantly decreased orientation dispersion index in several white matter regions. Brain–behavioural association analyses indicated that the reduced neurite density index of the left precentral gyrus and the reduced orientation dispersion index of the left superior longitudinal fasciculus were significantly associated with elevated hyperactive/impulsive symptoms in the patients with traumatic brain injury. These findings suggest that post-injury chronical neurite intracellular volume and angular distribution anomalies in the frontal lobe, practically the precentral area, can significantly contribute to the onset of hyperactive/impulsive behaviours in young adults with traumatic brain injury.

Morphometric changes in the cortex following acute mild traumatic brain injury

Morphometric changes in cortical thickness (CT), cortical surface area (CSA), and cortical volume (CV) can reflect pathological changes after acute mild traumatic brain injury (mTBI). Most previous studies focused on changes in CT, CSA, and CV in subacute or chronic mTBI, and few studies have examined changes in CT, CSA, and CV in acute mTBI. Furthermore, acute mTBI patients typically show transient cognitive impairment, and few studies have reported on the relationship between cerebral morphological changes and cognitive function in patients with mTBI. This prospective cohort study included 30 patients with acute mTBI (15 males, 15 females, mean age 33.7 years) and 27 matched healthy controls (12 males, 15 females, mean age 37.7 years) who were recruited from the Second Xiangya Hospital of Central South University between September and December 2019. High-resolution T1-weighted images were acquired within 7 days after the onset of mTBI. The results of analyses using FreeSurfer software revealed significantly increased CSA and CV in the right lateral occipital gyrus of acute-stage mTBI patients compared with healthy controls, but no significant changes in CT. The acute-stage mTBI patients also showed reduced executive function and processing speed indicated by a lower score in the Digital Symbol Substitution Test, and reduced cognitive ability indicated by a longer time to complete the Trail Making Test-B. Both increased CSA and CV in the right lateral occipital gyrus were negatively correlated with performance in the Trail Making Test part A. These findings suggest that cognitive deficits and cortical alterations in CSA and CV can be detected in the acute stage of mTBI, and that increased CSA and CV in the right lateral occipital gyrus may be a compensatory mechanism for cognitive dysfunction in acute-stage mTBI patients. This study was approved by the Ethics Committee of the Second Xiangya Hospital of Central South University, China (approval No. 086) on February 9, 2019.

Tractography methods and findings in brain tumors and traumatic brain injury

White matter fiber tracking using diffusion magnetic resonance imaging (dMRI) provides a noninvasive approach to map brain connections, but improving anatomical accuracy has been a significant challenge since the birth of tractography methods. Utilizing tractography in brain studies therefore requires understanding of its technical limitations to avoid shortcomings and pitfalls. This review explores tractography limitations and how different white matter pathways pose different challenges to fiber tracking methodologies. We summarize the pros and cons of commonly-used methods, aiming to inform how tractography and its related analysis may lead to questionable results. Extending these experiences, we review the clinical utilization of tractography in patients with brain tumors and traumatic brain injury, starting from tensor-based tractography to more advanced methods. We discuss current limitations and highlight novel approaches in the context of these two conditions to inform future tractography developments.

Tau deposition and structural connectivity demonstrate differential association patterns with neurocognitive tests

Tau neurofibrillary tangles have a central role in the pathogenesis of Alzheimer’s Disease (AD). Mounting evidence indicates that the propagation of tau is assisted by brain connectivity with weakened white-matter integrity along the propagation pathways. Recent advances in tau positron emission tomography tracers and diffusion magnetic resonance imaging allow the visualization of tau pathology and white-matter connectivity of the brain in vivo. The current study aims to investigate how tau deposition and structural connectivity are associated with memory function in prodromal AD. In this study, tau accumulation and structural connectivity data from 83 individuals (57 cognitively normal participants and 26 participants with mild cognitive impairment) were associated with neurocognitive test scores. Statistical analyses were performed in 70 cortical/subcortical brain regions to determine: 1. the level of association between tau and network metrics extracted from structural connectivity and 2. the association patterns of brain memory function with tau accumulation and network metrics. The results showed that tau accumulation and network metrics were correlated in early tau deposition regions. Furthermore, tau accumulation was associated with worse performance in almost all neurocognitive tests performance evaluated in the study. In comparison, decreased network connectivity was associated with declines in the delayed memory recall in Craft Stories and Benson Figure Copy. Interaction analysis indicates that tau deposition and dysconnectivity have a synergistic effect on the delayed Benson Figure Recall. Overall, our findings indicate that both tau deposition and structural dysconnectivity are associated with neurocognitive dysfunction. They also suggest that tau-PET may have better sensitivity to neurocognitive performance than diffusion MRI-derived measures of white-matter connectivity.

Neurite orientation dispersion and density imaging in a rodent model of acute mild traumatic brain injury

BACKGROUND AND PURPOSE

Identification of changesin brain microstructure following mild traumatic brain injury (mTBI) could be instrumental in understanding the underlying pathophysiology. The purpose of this study was to apply neurite orientation dispersion and density imaging (NODDI) to a rodent model of mTBI to determine whether microstructural changes could be detected immediately following injury.

METHODS

Fifteen adult male Wistar rats were scanned on a Bruker 9.4 Tesla small animal MRI using a multi-shell acquisition (30 b = 1000 s/mm² and 60 b = 2000 s/mm² ). Nine animals experienced a single closed head controlled cortical impact followed by NODDI from 1 to 4 h post injury. Region of interest analysis focused on the corpus callosum and hippocampus. A mixed analysis of variance (ANOVA) was used to determine statistically significant interactions in neurite density index (NDI), orientation dispersion index (ODI), fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity. Follow up repeated-measures ANOVAs were used to determine individual changes over time.

RESULTS

NDI showed a significant increase in the hippocampus and corpus callosum following injury, while ODI showed increases in the corpus callosum. No significant changes were observed in the sham control animals. No changes were found in FA, MD, AD, or RD. Histological analysis revealed increased glial fibrillary acidic protein staining relative to controls in both the hippocampus and corpus callosum, with evidence of activated astrocytes in these regions.

CONCLUSIONS

Changes in NODDI metrics were detected as early as 1 h following mTBI. No changes were detected with conventional diffusion tensor imaging (DTI) metrics, suggesting that NODDI provides greater sensitivity to microstructural changes than conventional DTI.

White matter abnormalities in active elite adult rugby players

The recognition, diagnosis and management of mild traumatic brain injuries are difficult and confusing. It is unclear how the severity and number of injuries sustained relate to brain injuries, such as diffuse axonal injury, diffuse vascular injury and progressive neurodegeneration. Advances in neuroimaging techniques enable the investigation of neuropathologies associated with acute and long-term effects of injury. Head injuries are the most commonly reported injury seen during professional rugby. There is increased vigilance for the immediate effects of these injuries in matches, but there has been surprisingly little research investigating the longer-term effects of rugby participation. Here, we present a longitudinal observational study investigating the relationship of exposure to rugby participation and sub-acute head injuries in professional adult male and female rugby union and league players using advanced MRI. Diffusion tensor imaging and susceptibility weighted imaging was used to assess white matter structure and evidence of axonal and diffuse vascular injury. We also studied changes in brain structure over time using Jacobian Determinant statistics extracted from serial volumetric imaging. We tested 41 male and 3 female adult elite rugby players, of whom 21 attended study visits after a head injury, alongside 32 non-sporting controls, 15 non-collision-sport athletic controls and 16 longitudinally assessed controls. Eighteen rugby players participated in the longitudinal arm of the study, with a second visit at least 6 months after their first scan. Neuroimaging evidence of either axonal injury or diffuse vascular injury was present in 23% (10/44) of players. In the non-acutely injured group of rugby players, abnormalities of fractional anisotropy and other diffusion measures were seen. In contrast, non-collision-sport athletic controls were not classified as showing abnormalities. A group level contrast also showed evidence of sub-acute injury using diffusion tensor imaging in rugby players. Examination of longitudinal imaging revealed unexpected reductions in white matter volume in the elite rugby players studied. These changes were not related to self-reported head injury history or neuropsychological test scores and might indicate excess neurodegeneration in white matter tracts affected by injury. Taken together, our findings suggest an association of participation in elite adult rugby with changes in brain structure. Further well-designed large-scale studies are needed to understand the impact of both repeated sports-related head impacts and head injuries on brain structure, and to clarify whether the abnormalities we have observed are related to an increased risk of neurodegenerative disease and impaired neurocognitive function following elite rugby participation.

Investigating White Matter Tract Microstructural Changes at Six-Twelve Weeks following Mild Traumatic Brain Injury: A Combined Diffusion Tensor Imaging and Neurite Orientation Dispersion and Density Imaging Study

Using diffusion-weighted imaging (DWI), research has demonstrated changes suggestive of damage to white matter tracts (WMT) following mild traumatic brain injury (mTBI). Yet due to the predominant use of the diffusion tensor imaging (DTI) model, which has numerous well-established limitations, it has not yet been possible to clearly examine the nature of changes to WMT microstructure following mTBI. This study used a second DWI-based technique, neurite orientation dispersion and density imaging (NODDI), in combination with DTI to measure microstructural changes within the corpus callosum, three long association and one projection WMTs at 6-12 weeks following mTBI, compared with matched trauma controls (TC). Between-groups differences were identified across all WMT for the DTI metric fractional anisotropy (FA), and the NODDI metrics orientation dispersion index (ODI) and isotropic volume fraction (ISO). No statistically significant between-groups differences were found for other DTI and NODDI metrics. Our study revealed that reduced FA was accompanied by increased ODI, suggesting that mTBI results in reduced coherence of axonal fiber bundles within the studied WMTs. These between-groups differences in WMT microstructure were found at 6-12 weeks post-injury, which suggests that structural recovery is not yet complete towards end of the typical 3-month recovery period.

White Matter Alteration Following SWAT Explosive Breaching Training and the Moderating Effect of a Neck Collar Device: A DTI and NODDI Study

INTRODUCTION

Special Weapons and Tactics (SWAT) personnel who practice breaching with blast exposure are at risk for blast-related head trauma. We aimed to investigate the impact of low-level blast exposure on underlying white matter (WM) microstructure based on diffusion tensor imaging (DTI) and neurite orientation and density imaging (NODDI) in SWAT personnel before and after breacher training. Diffusion tensor imaging is an advanced MRI technique sensitive to underlying WM alterations. NODDI is a novel MRI technique emerged recently that acquires diffusion weighted data from multiple shells modeling for different compartments in the microstructural environment in the brain. We also aimed to evaluate the effect of a jugular vein compression collar device in mitigating the alteration of the diffusion properties in the WM as well as its role as a moderator on the association between the diffusion property changes and the blast exposure.

MATERIALS AND METHODS

Twenty-one SWAT personnel (10 non-collar and 11 collar) completed the breacher training and underwent MRI at both baseline and after blast exposure. Diffusion weighted data were acquired with two shells (b = 1,000, 2,000 s/mm2) on 3T Phillips scanners. Diffusion tensor imaging metrices, including fractional anisotropy, mean, axial, and radial diffusivity, and NODDI metrics, including neurite density index (NDI), isotropic volume fraction (fiso), and orientation dispersion index, were calculated. Tract-based spatial statistics was used in the voxel-wise statistical analysis. Post hoc analyses were performed for the quantification of the pre- to post-blast exposure diffusion percentage change in the WM regions with significant group difference and for the assessment of the interaction of the relationship between blast exposure and diffusion alteration.

RESULTS

The non-collar group exhibited significant pre- to post-blast increase in NDI (corrected P < .05) in the WM involving the right internal capsule, the right posterior corona radiation, the right posterior thalamic radiation, and the right sagittal stratum. A subset of these regions showed significantly greater alteration in NDI and fiso in the non-collar group when compared with those in the collar group (corrected P < .05). In addition, collar wearing exhibited a significant moderating effect for the alteration of fiso for its association with average peak pulse pressure.

CONCLUSIONS

Our data provided initial evidence of the impact of blast exposure on WM diffusion alteration based on both DTI and NODDI. The mitigating effect of WM diffusivity changes and the moderating effect of collar wearing suggest that the device may serve as a promising solution to protect WM against blast exposure.

Hybrid diffusion imaging reveals altered white matter tract integrity and associations with symptoms and cognitive dysfunction in chronic traumatic brain injury

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Hybrid Diffusion Imaging (HYDI) detects white matter associations in patients with cTBI.

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The advanced diffusion model NODDI was more sensitive in detecting between-group differences than classic DTI.

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DTI appeared to be just as sensitive as NODDI for detecting white matter correlations with self-reported symptoms.

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This study highlights the advantages of acquiring both DTI and NODDI to fully characterize white matter microstructure in cTBI.

The detection and association of in vivo biomarkers in white matter (WM) pathology after acute and chronic mild traumatic brain injury (mTBI) are needed to improve care and develop therapies. In this study, we used the diffusion MRI method of hybrid diffusion imaging (HYDI) to detect white matter alterations in patients with chronic TBI (cTBI). 40 patients with cTBI presenting symptoms at least three months post injury, and 17 healthy controls underwent magnetic resonance HYDI. cTBI patients were assessed with a battery of neuropsychological tests. A voxel-wise statistical analysis within the white matter skeleton was performed to study between group differences in the diffusion models. In addition, a partial correlation analysis controlling for age, sex, and time after injury was performed within the cTBI cohort, to test for associations between diffusion metrics and clinical outcomes. The advanced diffusion modeling technique of neurite orientation dispersion and density imaging (NODDI) showed large clusters of between-group differences resulting in lower values in the cTBI across the brain, where the single compartment diffusion tensor model failed to show any significant results. However, the diffusion tensor model appeared to be just as sensitive in detecting self-reported symptoms in the cTBI population using a within-group correlation. To the best of our knowledge this study provides the first application of HYDI in evaluation of cTBI using combined DTI and NODDI, significantly enhancing our understanding of the effects of concussion on white matter microstructure and emphasizing the utility of full characterization of complex diffusion to diagnose, monitor, and treat brain injury.

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.

A roadmap of brain recovery in a mouse model of concussion: insights from neuroimaging

Concussion or mild traumatic brain injury is the most common form of traumatic brain injury with potentially long-term consequences. Current objective diagnosis and treatment options are limited to clinical assessment, cognitive rest, and symptom management, which raises the real danger of concussed patients being released back into activities where subsequent and cumulative injuries may cause disproportionate damages. This study conducted a cross-sectional multi-modal examination investigation of the temporal changes in behavioural and brain changes in a mouse model of concussion using magnetic resonance imaging. Sham and concussed mice were assessed at day 2, day 7, and day 14 post-sham or injury procedures following a single concussion event for motor deficits, psychological symptoms with open field assessment, T2-weighted structural imaging, diffusion tensor imaging (DTI), neurite orientation density dispersion imaging (NODDI), stimulus-evoked and resting-state functional magnetic resonance imaging (fMRI). Overall, a mismatch in the temporal onsets and durations of the behavioural symptoms and structural/functional changes in the brain was seen. Deficits in behaviour persisted until day 7 post-concussion but recovered at day 14 post-concussion. DTI and NODDI changes were most extensive at day 7 and persisted in some regions at day 14 post-concussion. A persistent increase in connectivity was seen at day 2 and day 14 on rsfMRI. Stimulus-invoked fMRI detected increased cortical activation at day 7 and 14 post-concussion. Our results demonstrate the capabilities of advanced MRI in detecting the effects of a single concussive impact in the brain, and highlight a mismatch in the onset and temporal evolution of behaviour, structure, and function after a concussion. These results have significant translational impact in developing methods for the detection of human concussion and the time course of brain recovery.

Neuroimaging in Sports-Related Concussion

Mild traumatic brain injuries, or concussions, often result in transient brain abnormalities not readily detected by conventional imaging methods. Several advanced imaging studies have been evaluated in the past couple decades to improve understanding of microstructural and functional abnormalities in the brain in patients suffering concussions. The thought remains a functional or pathophysiologic change rather than a structural one. The mechanism of injury, whether direct, indirect, or rotational, may drive specific clinical and radiological presentations. This remains a dynamic and constantly evolving area of research. This article focuses on the current status of imaging and future directions in concussion-related research.

Tau-related white-matter alterations along spatially selective pathways

Progressive accumulation of tau neurofibrillary tangles in the brain is a defining pathologic feature of Alzheimer’s disease (AD). Tau pathology exhibits a predictable spatiotemporal spreading pattern, but the underlying mechanisms of this spread are poorly understood. Although AD is conventionally considered a disease of the gray matter, it is also associated with pronounced and progressive deterioration of the white matter (WM). A link between abnormal tau and WM degeneration is suggested by findings from both animal and postmortem studies, but few studies demonstrated their interplay in vivo. Recent advances in diffusion magnetic resonance imaging and the availability of tau positron emission tomography (PET) have made it possible to evaluate the association of tau and WM degeneration (tau-WM) in vivo. In this study, we explored the spatial pattern of tau-WM associations across the whole brain to evaluate the hypothesis that tau deposition is associated with WM microstructural alterations not only in isolated tracts, but in continuous structural connections in a stereotypic pattern. Sixty-two participants, including 22 cognitively normal subjects, 22 individuals with subjective cognitive decline, and 18 with mild cognitive impairment were included in the study. WM characteristics were inferred by classic diffusion tensor imaging (DTI) and a complementary diffusion compartment model – neurite orientation dispersion and density imaging (NODDI) that provides a proxy for axonal density. A data-driven iterative searching (DDIS) approach, coupled with whole-brain graph theory analyses, was developed to continuously track tau-WM association patterns. Without applying prior knowledge of the tau spread, we observed a distinct spatial pattern that resembled the typical propagation of tau pathology in AD. Such association pattern was not observed between diffusion and amyloid-β PET signal. Tau-related WM degeneration is characterized by an increase in the mean diffusivity (with a dominant change in the radial direction) and a decrease in the intra-axonal volume fraction. These findings suggest that cortical tau deposition (as measured in tau PET) is associated with a lower axonal packing density and greater diffusion freedom. In conclusion, our in vivo findings using a data-driven method on cross-sectional data underline the important role of WM alterations in the AD pathological cascade with an association pattern similar to the postmortem Braak staging of AD. Future studies will focus on longitudinal analyses to provide in vivo evidence of tau pathology spreads along neuroanatomically connected brain areas.

Two Coarse Spatial Patterns of Altered Brain Microstructure Predict Post-traumatic Amnesia in the Subacute Stage of Severe Traumatic Brain Injury

Introduction: Diffuse traumatic axonal injury (TAI) is one of the key mechanisms leading to impaired consciousness after severe traumatic brain injury (TBI). In addition, preferential regional expression of TAI in the brain may also influence clinical outcome. Aim: We addressed the question whether the regional expression of microstructural changes as revealed by whole-brain diffusion tensor imaging (DTI) in the subacute stage after severe TBI may predict the duration of post-traumatic amnesia (PTA). Method: Fourteen patients underwent whole-brain DTI in the subacute stage after severe TBI. Mean fractional anisotropy (FA) and mean diffusivity (MD) were calculated for five bilateral brain regions: fronto-temporal, parieto-occipital, and midsagittal hemispheric white matter, as well as brainstem and basal ganglia. Region-specific calculation of mean FA and MD only considered voxels that showed no tissue damage, using an exclusive mask with all voxels that belonged to local brain lesions or microbleeds. Mean FA or MD of the five brain regions were entered in separate partial least squares (PLS) regression analyses to identify patterns of regional microstructural changes that account for inter-individual variations in PTA. Results: For FA, PLS analysis revealed two spatial patterns that significantly correlated with individual PTA. The lower the mean FA values in all five brain regions, the longer that PTA lasted. A pattern characterized by lower FA values in the deeper brain regions relative to the FA values in the hemispheric regions also correlated with longer PTA. Similar trends were found for MD, but opposite in sign. The spatial FA changes as revealed by PLS components predicted the duration of PTA. Individual PTA duration, as predicted by a leave-one-out cross-validation analysis, correlated with true PTA values (Spearman r = 0.68, p permutation = 0.008). Conclusion: Two coarse spatial patterns of microstructural damage, indexed as reduction in FA, were relevant to recovery of consciousness after TBI. One pattern expressed was consistent with diffuse microstructural damage across the entire brain. A second pattern was indicative of a preferential damage of deep midline brain structures.

Diffusion Tensor Imaging-Based Studies at the Group-Level Applied to Animal Models of Neurodegenerative Diseases

The understanding of human and non-human microstructural brain alterations in the course of neurodegenerative diseases has substantially improved by the non-invasive magnetic resonance imaging (MRI) technique of diffusion tensor imaging (DTI). Animal models (including disease or knockout models) allow for a variety of experimental manipulations, which are not applicable to humans. Thus, the DTI approach provides a promising tool for cross-species cross-sectional and longitudinal investigations of the neurobiological targets and mechanisms of neurodegeneration. This overview with a systematic review focuses on the principles of DTI analysis as used in studies at the group level in living preclinical models of neurodegeneration. The translational aspect from in-vivo animal models toward (clinical) applications in humans is covered as well as the DTI-based research of the non-human brains' microstructure, the methodological aspects in data processing and analysis, and data interpretation at different abstraction levels. The aim of integrating DTI in multiparametric or multimodal imaging protocols will allow the interrogation of DTI data in terms of directional flow of information and may identify the microstructural underpinnings of neurodegeneration-related patterns.

NODDI in clinical research

Diffusion MRI (dMRI) has proven to be a useful imaging approach for both clinical diagnosis and research investigating the microstructures of nervous tissues, and it has helped us to better understand the neurophysiological mechanisms of many diseases. Though diffusion tensor imaging (DTI) has long been the default tool to analyze dMRI data in clinical research, acquisition with stronger diffusion weightings beyond the DTI regimen is now possible with modern clinical scanners, potentially enabling even more detailed characterization of tissue microstructures. To take advantage of such data, neurite orientation dispersion and density imaging (NODDI) has been proposed as a way to relate the dMRI signal to tissue features via biophysically inspired modeling. The number of reports demonstrating the potential clinical utility of NODDI is rapidly increasing. At the same time, the pitfalls and limitations of NODDI, and general challenges in microstructure modeling, are becoming increasingly recognized by clinicians. dMRI microstructure modeling is a rapidly evolving field with great promise, where people from different scientific backgrounds, such as physics, medicine, biology, neuroscience, and statistics, are collaborating to build novel tools that contribute to improving human healthcare. Here, we review the applications of NODDI in clinical research and discuss future perspectives for investigations toward the implementation of dMRI microstructure imaging in clinical practice.

Ultra-High-Field Diffusion Tensor Imaging Identifies Discrete Patterns of Concussive Injury in the Rodent Brain

Although concussions can result in persistent neurological post-concussion symptoms, they are typically invisible on routine magnetic resonance imaging (MRI) scans. Our study aimed to investigate the use of ultra-high-field diffusion tensor imaging (UHF-DTI) in discerning severity-dependent microstructural changes in the mouse brain following a concussion. Twenty-three C57BL/6 mice were randomly allocated into three groups: the low concussive (LC, n = 9) injury group, the high concussive (HC, n = 6) injury group, and the sham control (SC, n = 7) group. Mice were perfused on day 2 post-injury, and the brains were scanned on a 16.4T MRI scanner with UHF-DTI and neurite orientation dispersion imaging (NODDI). Finite element analysis (FEA) was performed to determine the pattern and extent of the physical impact on the brain tissue. MRI findings were correlated with histopathological analysis in a subset of mice. In the LC group, increased fractional anisotropy (FA) and decreased orientation dispersion index (ODI) but limited neurite density index (NDI) changes were found in the gray matter, and minimal changes to white matter (WM) were observed. The HC group presented increased mean diffusivity (MD), decreased NDI, and decreased ODI in the WM and gray matter (GM); decreased FA was also found in a small area of the WM. WM changes were associated with WM degeneration and neuroinflammation. FEA showed varying region-dependent degrees of stress, in line with the different imaging findings. This study provides evidence that UHF-DTI combined with NODDI can detect concussions of variable intensities. This has significant implications for the diagnosis of concussion in humans.

White Matter Changes Caused by Mild Traumatic Brain Injury in Mice Evaluated Using Neurite Orientation Dispersion and Density Imaging

Mild traumatic brain injury (mTBI) is common and can lead to persistent cognitive and behavioral symptoms. Although diffusion tensor imaging (DTI) has demonstrated some sensitivity to changes in white matter following mTBI, recent studies have suggested that more complex geometric models of diffusion, including the neurite orientation dispersion and density imaging (NODDI) model, may be more sensitive and specific. Here, we evaluate microstructural changes in white matter following mTBI using DTI and NODDI in a mouse model, and compare the time course of these changes to behavioral impairment and recovery. We also assess volumetric changes for a comprehensive picture of the structural alterations in the brain and histological staining to identify cellular changes that may contribute to the differences detected in the imaging data. Increased orientation dispersion index (ODI) was observed in the optic tracts of mTBI mice compared with shams. Changes in fractional anisotropy (FA) were not statistically significant. Volume deficits were detected in the optic tract as well as in several gray matter regions: the lateral geniculate nuclei of the thalamus, the entorhinal cortex, and the superior colliculi. Glial fibrillary acidic protein (GFAP) and ionized calcium binding adaptor molecule 1 (Iba1) staining was increased in the optic tracts of mTBI brains, and this staining correlated with ODI values. A transient impairment in working memory was observed, which resolved by 6 weeks, whereas increased ODI, GFAP, and Iba1 persisted to 18 weeks post-injury. We conclude that the optic tracts are particularly vulnerable to damage from the closed-skull impact model used in this study, and that ODI may be a more sensitive metric to this damage than FA. Differences in ODI and in histological measures of astrogliosis, neuroinflammation, and axonal degeneration persist beyond behavioral impairment in this model.

A deep network for tissue microstructure estimation using modified LSTM units

Diffusion magnetic resonance imaging (dMRI) offers a unique tool for noninvasively assessing tissue microstructure. However, accurate estimation of tissue microstructure described by complicated signal models can be challenging when a reduced number of diffusion gradients are used. Deep learning based microstructure estimation has recently been developed and achieved promising results. In particular, optimization-based learning, where deep network structures are constructed by unfolding the iterative processes performed for solving optimization problems, has demonstrated great potential in accurate microstructure estimation with a reduced number of diffusion gradients. In this work, using the optimization-based learning strategy, we propose a deep network structure that is motivated by the use of historical information in iterative optimization for tissue microstructure estimation, and such incorporation of historical information has not been previously explored in the design of deep networks for microstructure estimation. We assume that (1) diffusion signals can be sparsely represented by a dictionary and its coefficients jointly in the spatial and angular domain, and (2) tissue microstructure can be computed from the sparse representation. Following these assumptions, our network comprises two cascaded stages. The first stage takes image patches as input and computes the spatial-angular sparse representation of the input with learned weights. Specifically, the network structure in the first stage is constructed by unfolding an iterative process for solving sparse reconstruction problems, where historical information is incorporated. The components in this network can be shown to correspond to modified long short-term memory (LSTM) units. In the second stage, fully connected layers are added to compute the mapping from the sparse representation to tissue microstructure. The weights in the two stages are learned jointly by minimizing the mean squared error of microstructure estimation. Experiments were performed on dMRI scans with a reduced number of diffusion gradients. For demonstration, we evaluated the estimation of tissue microstructure described by three signal models: the neurite orientation dispersion and density imaging (NODDI) model, the spherical mean technique (SMT) model, and the ensemble average propagator (EAP) model. The results indicate that the proposed approach outperforms competing methods.

Neurite orientation dispersion and density imaging can detect presymptomatic axonal degeneration in the spinal cord of ALS mice

Neurite orientation dispersion and density imaging (NODDI), a MRI multi-shell diffusion technique, has offered new insights for the study of microstructural changes in neurodegenerative diseases. Mainly, the present study aimed to determine the connection between NODDI-derived parameters and changes in white matter (WM) abnormalities at early stages of amyotrophic lateral sclerosis (ALS). Spinal cords from ALS mice (G93A-SOD1 mice) were scanned in a Bruker Avance III HD 17.6T magnet. Fluorescent axonal-tagged mice (YFP, G93A-SOD1 mice) were used for quantitative histological analysis. NODDI showed a decrease in intra-cellular volume fraction (-24%) and increases in orientation dispersion index (+35%) and isotropic volume fraction (+33%). In addition, histoathological results demonstrated a reductions in axonal area (-11%) and myelin content (-29%). A histological decrease in WM intra-axonal space (-71%) and an increase in the extra-axonal compartment (+22%) were also detected. Our studies demonstrate that NODDI may be a suitable technique for detecting presymptomatic spinal cord WM microstructural degeneration in ALS.