Principles of diffusion tensor imaging and its applications to basic neuroscience research

Longitudinal DTI analysis of microstructural changes in lumbar nerve roots following Interspinous process device placement

Diffusion tensor imaging (DTI) and its parameters such as fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD) are increasingly being used to assess peripheral nerve integrity alongside nerve conduction studies. This pilot study aims to compare DTI values of lumbar spinal nerve roots before (T0) and after (T1) treatment with an interspinous process device (IPD). Seven patients (5 females, 2 males; mean age: 68) suffering from neurogenic claudication and lumbar spinal canal and foraminal stenosis were evaluated. Visual Analog Scale (VAS) for perceived pain, Oswestry Disability Index (ODI), and DTI parameters were assessed between T0 and T1. No significant difference in FA was found in treated roots, while MD (p = 0.0015), RD (p = 0.0032), and AD (p = 0.0221) were significantly altered. At untreated levels, all DTI parameters showed highly significant differences (p < 0.0001) between T0 and T1. In treated roots, FA values significantly increased in the intraforaminal segment(p = 0.0229), while MD(p = 0.0124), AD(p = 0.0128), and RD (p = 0.0143) values decreased in the pre-foraminal segment. In untreated roots, FA significantly increased in pre(p = 0.0039)and intraforaminal(p = 0.0003) segments, and MD, AD, and RD decreased in all segments (p < 0.0001). VAS (p < 0.0001) also decreased between T0 and T1. This pilot study aims to clarify the biomechanical impact of interspinous spacers through microstructural analysis of both treated and adjacent untreated nerve roots. To our knowledge, no studies have examined the short- to medium-term changes in DTI values of lumbar nerve roots before and after IPD placement, or compared changes between treated and untreated roots.

Characterization of neurite and soma organization in the brain and spinal cord with diffusion MRI

The central nervous system (CNS), comprised of both the brain and spinal cord, and is a complex network of white and gray matter responsible for sensory, motor, and cognitive functions. Advanced diffusion MRI (dMRI) techniques offer a promising mechanism to non-invasively characterize CNS architecture, however, most studies focus on the brain or spinal cord in isolation. Here, we implemented a clinically feasible dMRI protocol on a 3T scanner to simultaneously characterize neurite and soma microstructure of both the brain and spinal cord. The protocol enabled the use of Diffusion Tensor Imaging (DTI), Standard Model Imaging (SMI), and Soma and Neurite Density Imaging (SANDI), representing the first time SMI and SANDI have been evaluated in the cord, and in the cord and brain simultaneously. Our results demonstrate high image quality even at high diffusion weightings, reproducibility of SMI and SANDI derived metrics similar to those of DTI with few exceptions, and biologically feasible contrasts between and within white and gray matter regions. Reproducibility and contrasts were decreased in the cord compared to that of the brain, revealing challenges due to partial volume effects and image preprocessing. This study establishes a harmonized approach for brain and cord microstructural imaging, and the opportunity to study CNS pathologies and biomarkers of structural integrity across the neuroaxis.

The Robustness of White Matter Brain Networks Decreases with Aging

BACKGROUND

White matter (WM) is a principal component of the human brain, forming the structural basis for neural transmission between cortico-cortical and subcortical structures. The impairment of WM integrity is closely associated with the aging process, manifesting as the reorganization of brain networks based on graph theoretical analysis of complex networks and increased volume of white matter hyperintensities (WMHs) in imaging studies.

METHODS

This study investigated changes in the robustness of WM brain networks during aging and assessed their correlation with WMHs. We constructed WM brain networks for 159 volunteers from a community sample dataset using diffusion tensor imaging (DTI). We then calculated the robustness of these networks by simulating neurodegeneration based on network attack analysis, and studied the correlations between WM network robustness, age, and the proportion of WMHs.

RESULTS

The analysis revealed a moderate, negative correlation between WM network robustness and age, and a weak and negative correlation between WM network robustness and the proportion of WMHs.

CONCLUSIONS

These findings suggest that WM pathologies are associated with aging and offer new insights into the imaging characteristics of the aging brain.

From diagnosis to treatment: exploring the mechanisms underlying optic neuritis in multiple sclerosis

Multiple sclerosis (MS) is a chronic autoimmune disease affecting the central nervous system, commonly causing sensory disturbances, motor weakness, impaired gait, incoordination and optic neuritis (ON). According to the statistics, up to 50% of MS patients experience vision problems during the disease course, suffering from blurred vision, pain, color vision deficits, and even blindness. Treatments have progressed from corticosteroids to therapies targeted against B/T cells. This review comprehensively and systematically reappraises the diagnostic methods for visual impairment in MS patients. It also summarizes the most recent treatment approaches and effective medications for ON in MS. Finally, we examine the immunoinflammatory mechanisms that underlie lesions in the central nervous system in multiple sclerosis, in order to direct future investigations to confirm these mechanisms in the visual pathway.

Advanced Magnetic Resonance Imaging for Early Diagnosis and Monitoring of Movement Disorders

Advanced magnetic resonance imaging (MRI) techniques are transforming the study of movement disorders by providing valuable insights into disease mechanisms. This narrative review presents a comprehensive overview of their applications in this field, offering an updated perspective on their potential for early diagnosis, disease monitoring, and therapeutic evaluation. Emerging MRI modalities such as neuromelanin-sensitive imaging, diffusion-weighted imaging, magnetization transfer imaging, and relaxometry provide sensitive biomarkers that can detect early microstructural degeneration, iron deposition, and connectivity disruptions in key regions like the substantia nigra. These techniques enable earlier and more accurate differentiation of movement disorders, including Parkinson's disease, progressive supranuclear palsy, multiple system atrophy, corticobasal degeneration, Lewy body and frontotemporal dementia, Huntington's disease, and dystonia. Furthermore, MRI provides objective metrics for tracking disease progression and assessing therapeutic efficacy, making it an indispensable tool in clinical trials. Despite these advances, the absence of standardized protocols limits their integration into routine clinical practice. Addressing this gap and incorporating these techniques more systematically could bring the field closer to leveraging advanced MRI for personalized treatment strategies, ultimately improving outcomes for individuals with movement disorders.

White matter integrity upon progesterone antagonism in individuals with premenstrual dysphoric disorder: A randomized placebo-controlled diffusion tensor imaging study

BACKGROUND

Premenstrual dysphoric disorder (PMDD) is a depressive disorder triggered by fluctuations of progesterone and estradiol during the luteal phase of the menstrual cycle. Selective progesterone receptor modulation (SPRM), while exerting an antagonistic effect on progesterone and maintaining estradiol on moderate levels, has shown beneficial effects on the mental symptoms of PMDD. Progesterone is also known for its neuroprotective effects, while synthetic progestins have been suggested to promote myelination. However, the impact of SPRM treatment on white matter microstructure is unexplored.

METHODS

Diffusion tensor imaging was employed to collect data on white matter integrity in patients with PMDD, before and after treatment with ulipristal acetate (an SPRM) or placebo, as part of a double-blind randomized controlled-trial. Tract based spatial statistics were performed to investigate SPRM treatment vs. placebo longitudinal effects on fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD), on the whole white matter skeleton.

RESULTS

Voxel-wise analyses indicated no change over time in any white matter microstructure metrics in individuals treated with SPRM versus placebo. Improvement in PMDD symptoms did not correlate with changes in white matter microstructure. In secondary, exploratory, cross-sectional comparisons during treatment, the SPRM group displayed lower FA and higher MD, RD, and AD than the placebo group in several tracts.

CONCLUSION

The main findings suggest that SPRM treatment did not impact white matter microstructure compared with placebo. However, secondary exploratory analyses yielded between-group differences after treatment, which call for further investigation on the tracts potentially impacted by progesterone antagonism.

CLINICAL TRIAL REGISTRATION

EUDRA-CT 2016-001719-19; "Selective progesterone receptor modulators for treatment of premenstrual dysphoric disorder. A randomized, double-blind, placebo-controlled study."; https://www.clinicaltrialsregister.eu/ctr-search/trial/2016-001719-19/SE.

Structural MRI of brain similarity networks

Recent advances in structural MRI analytics now allow the network organization of individual brains to be comprehensively mapped through the use of the biologically principled metric of anatomical similarity. In this Review, we offer an overview of the measurement and meaning of structural MRI similarity, especially in relation to two key assumptions that often underlie its interpretation: (i) that MRI similarity can be representative of architectonic similarity between cortical areas and (ii) that similar areas are more likely to be axonally connected, as predicted by the homophily principle. We first introduce the historical roots and technical foundations of MRI similarity analysis and compare it with the distinct MRI techniques of structural covariance and tractography analysis. We contextualize this empirical work with two generative models of homophilic networks: an economic model of cost-constrained connectional homophily and a heterochronic model of ontogenetically phased cortical maturation. We then review (i) studies of the genetic and transcriptional architecture of MRI similarity in population-averaged and disorder-specific contexts and (ii) developmental studies of normative cohorts and clinical studies of neurodevelopmental and neurodegenerative disorders. Finally, we prioritize knowledge gaps that must be addressed to consolidate structural MRI similarity as an accessible, valid marker of the architecture and connectivity of an individual brain network.

Aerobic Exercise Training for the Aging Brain: Effective Dosing and Vascular Mechanism

This article presents evidence supporting the hypothesis that starting aerobic exercise in early adulthood and continuing it throughout life leads to significant neurocognitive benefits compared with starting exercise later in life. Regular aerobic exercise at moderate-to-vigorous intensity during midlife is associated with significant improvement in cardiorespiratory fitness, which may create a favorable brain microenvironment promoting neuroplasticity through enhanced vascular function.

Biomarkers Unveiling the Interplay of Mind, Nervous System, and Immunity

The field of psychoneuroimmunology has significantly expanded in the last few decades and so has our understanding of the bidirectional communications between the immune and central nervous systems (CNS). There is a preponderance of evidence supporting the fact that immunological pathways and neuroinflammation are involved in the pathophysiology of multiple neurological and mental health conditions. In this chapter, we have explored various neuroimmunological biomarkers involved in these pathways, responsible for developing and perpetuating different neuropsychiatric disorders. This chapter will examine inflammatory biomarkers and those associated with intestinal homeostasis, blood-brain barrier (BBB) permeability, glial cells, and neuronal injury. A range of tests has been developed to evaluate these markers, and we will also explore the existing methods currently employed for these techniques. Further studies of these inflammatory and neurological markers are needed to support their utility as biomarkers for diagnosis and prognosis and to inform treatment strategies for various neuropsychiatric disorders.

Spherical Harmonics-Based Deep Learning Achieves Generalized and Accurate Diffusion Tensor Imaging

Diffusion tensor imaging (DTI) is a prevalent magnetic resonance imaging (MRI) technique, widely used in clinical and neuroscience research. However, the reliability of DTI is affected by the low signal-to-noise ratio inherent in diffusion-weighted (DW) images. Deep learning (DL) has shown promise in improving the quality of DTI, but its limited generalization to variable acquisition schemes hinders practical applications. This study aims to develop a generalized, accurate, and efficient DL-based DTI method. By leveraging the representation of voxel-wise diffusion MRI (dMRI) signals on the sphere using spherical harmonics (SH), we propose a novel approach that utilizes SH coefficient maps as input to a network for predicting the diffusion tensor (DT) field, enabling improved generalization. Extensive experiments were conducted on simulated and in-vivo datasets, covering various DTI application scenarios. The results demonstrate that the proposed SH-DTI method achieves advanced performance in both quantitative and qualitative analyses of DTI. Moreover, it exhibits remarkable generalization capabilities across different acquisition schemes, centers, and scanners, ensuring its broad applicability in diverse settings.

A novel approach in MRI signal processing for unveiling the intricacies of brain axonal organization

This article introduces an innovative methodology to unveil the intricacies of white matter fiber pathways in the brain using diffusion MRI. Relying on the rationale that traditional methods observe a significant decrease in signal intensity values in the direction of higher diffusivity, our novel approach strategically selects for diffusion-sensitizing gradient directions (dSGDs, representing the directions along which signals are generated) aligned with reduced signal intensities. By treating these selected directions as maximum diffusivity directions, we generate uniformly distributed gradient directions (GDs) around them, which are subsequently employed in the reconstruction process. This approach addresses the shortcomings of existing methods. It improves upon the uniform gradient directions (UGDs) approach, which suffers from gradient direction redundancy, and the adaptive gradient directions (AGDs) approach, which requires solving the linear system twice per voxel. Proposed method simultaneously addresses both limitations, offering a more efficient and streamlined process. The effectiveness of our proposed methodology is rigorously evaluated through simulations and experiments involving real data, showcasing its superior performance in uncovering the complex white matter fiber pathways in the brain.

Tractography analysis results of the trigeminus nerve, which contains fibers responsible for proprioception sensation and motor control in Adolescent Idiopathic Scoliosis

STUDY DESIGN

Cross-sectional Study.

BACKGROUND

It is not yet clear whether the loss of proprioceptive sensation and muscle weakness seen in adolescent idiopathic scoliosis (AIS) is the result of central nervous system dysfunction or secondary to spinal deformity. In our study, in order to find an answer to this question, we examined the microarchitecture of the nervus trigeminus, which is least affected by spinal deformity and contains both proprioceptive sensory and motor fibers.

METHODS

In this single-center, cross-sectional cohort study, 40 Lenke Type 3 (27 female, 13 male) AIS patients and 40 (25 female, 15 male) healthy individuals between the ages of 10-18 years. Tractography of the nervus trigenimus was performed using the "DSI Studio" program. The volumes of the targeted musculus pterygoideus lateralis and musculus pterygoideus medialis were measured using the Insight Segmentation and Registration Tool Kit (ITK -SNAP) program. The data were evaluated using the Statistical Package for the Social Sciences 22.0 program for Windows.

RESULTS

There was no significant difference between the two groups in terms of baseline characteristics (p˃0.05). Left nervus trigeminus fiber number and fiber ratio were significantly higher in the control group compared to the scoliosis group p < 0.05. Right and left lateral pterygoid muscle showed lower volume and volume percentage in the scoliosis group compared to the control group (p < 0.05).

CONCLUSION

According to the study data, proprioceptive sensory and motor control dysfunction in AIS is predicted to develop independently of spinal deformity.

Cortical microstructural alterations in different stages of Parkinson's disease

To explore the cortical microstructural alterations in Parkinson's disease (PD) at different stages. 149 PD patients and 76 healthy controls were included. PD patients were divided into early stage PD (EPD) (Hoehn-Yahr stage ≤ 2) and moderate-to-late stage PD (MLPD) (Hoehn-Yahr stage ≥ 2.5) according to their Hoehn-Yahr stages. All participants underwent two-shell diffusion MRI and the images were fitted to Neurite Orientation Dispersion and Density Imaging (NODDI) model to obtain the neurite density index (NDI) and orientation dispersion index (ODI) to reflect the cortical microstructure. We used gray matter-based spatial statistics method to compare the voxel-wise cortical NODDI metrics between groups. Partial correlation was used to correlate the NODDI metrics and global composite outcome in PD patients. Compared with healthy controls, EPD patients showed lower ODI in widespread regions, covering bilateral frontal, temporal, parietal and occipital cortices, as well as regional lower NDI in bilateral cingulate and frontal lobes. Compared with healthy controls, MLPD patients showed lower ODI and NDI in more widespread regions. Compared with EPD patients, MLPD patients showed lower ODI in bilateral temporal, parietal and occipital cortices, where the ODI values were negatively correlated with global composite outcome in PD patients. PD patients showed widespread cortical microstructural degeneration, characterized by reduced neurite density and orientation dispersion, and the cortical neuritic microstructure exhibit progressive degeneration during the progression of PD.

tDKI-Net: A Joint q-t Space Learning Network for Diffusion-Time-Dependent Kurtosis Imaging

Time-dependent diffusion magnetic resonance imaging (TDDMRI) is useful for the non-invasive characterization of tissue microstructure. These models require densely sampled q-t space data for microstructural fitting, leading to very time-consuming acquisition protocols. To overcome this problem, we present a joint q-t space model-tDKI-Net to estimate diffusion-time dependent kurtosis and the transmembrane exchange, using downsampled q-t space data. The tDKI-Net is composed of several q-Encoders and a t-Encoder, designed based on the extragradient mechanism, each integrated with their respective mapping networks. In the tDKI-Net, two types of encoders along with their mapping networks are employed sequentially to generate kurtosis at individual diffusion times and to fit the transmembrane exchange time () using the time-dependent kurtosis according to the Kärger's model. Meanwhile, we proposed a three-stage training strategy, including physics-informed self-supervised pretraining, DKI warm-up, and joint training, to match the network structure. Our results demonstrated that the proposed tDKI-Net could effectively accelerate tDKI scans, resulting in lower estimation error compared with other methods. Our proposed three-stage training strategy demonstrated superior results than those training from scratch, e.g., the normalized root mean square error (NRMSE) of decreased by up to 1.4%. We also investigated the training data size effects and found that although we used one-subject training, the network achieved lower NRMSEs for , and (2.50%, 3.04%, 10.86%) than previous work that used three-subject training (3.8%, 9.5%, 12.1%). tDKI-Net can considerably reduce the scan time by 10.5-fold by joint downsampling the q-t space data without compromising the estimation accuracy.

Decoding Glioblastoma Heterogeneity: Neuroimaging Meets Machine Learning

Recent advancements in neuroimaging and machine learning have significantly improved our ability to diagnose and categorize isocitrate dehydrogenase (IDH)-wildtype glioblastoma, a disease characterized by notable tumoral heterogeneity, which is crucial for effective treatment. Neuroimaging techniques, such as diffusion tensor imaging and magnetic resonance radiomics, provide noninvasive insights into tumor infiltration patterns and metabolic profiles, aiding in accurate diagnosis and prognostication. Machine learning algorithms further enhance glioblastoma characterization by identifying distinct imaging patterns and features, facilitating precise diagnoses and treatment planning. Integration of these technologies allows for the development of image-based biomarkers, potentially reducing the need for invasive biopsy procedures and enabling personalized therapy targeting specific pro-tumoral signaling pathways and resistance mechanisms. Although significant progress has been made, ongoing innovation is essential to address remaining challenges and further improve these methodologies. Future directions should focus on refining machine learning models, integrating emerging imaging techniques, and elucidating the complex interplay between imaging features and underlying molecular processes. This review highlights the pivotal role of neuroimaging and machine learning in glioblastoma research, offering invaluable noninvasive tools for diagnosis, prognosis prediction, and treatment planning, ultimately improving patient outcomes. These advances in the field promise to usher in a new era in the understanding and classification of IDH-wildtype glioblastoma.

A review of diffusion MRI in mood disorders: mechanisms and predictors of treatment response

By measuring the molecular diffusion of water molecules in brain tissue, diffusion MRI (dMRI) provides unique insight into the microstructure and structural connections of the brain in living subjects. Since its inception, the application of dMRI in clinical research has expanded our understanding of the possible biological bases of psychiatric disorders and successful responses to different therapeutic interventions. Here, we review the past decade of diffusion imaging-based investigations with a specific focus on studies examining the mechanisms and predictors of therapeutic response in people with mood disorders. We present a brief overview of the general application of dMRI and key methodological developments in the field that afford increasingly detailed information concerning the macro- and micro-structural properties and connectivity patterns of white matter (WM) pathways and their perturbation over time in patients followed prospectively while undergoing treatment. This is followed by a more in-depth summary of particular studies using dMRI approaches to examine mechanisms and predictors of clinical outcomes in patients with unipolar or bipolar depression receiving pharmacological, neurostimulation, or behavioral treatments. Limitations associated with dMRI research in general and with treatment studies in mood disorders specifically are discussed, as are directions for future research. Despite limitations and the associated discrepancies in findings across individual studies, evolving research strongly indicates that the field is on the precipice of identifying and validating dMRI biomarkers that could lead to more successful personalized treatment approaches and could serve as targets for evaluating the neural effects of novel treatments.

A combined DTI-fMRI approach for optimizing the delineation of posteromedial versus anterolateral entorhinal cortex

In the entorhinal cortex (EC), attempts have been made to identify the human homologue regions of the medial (MEC) and lateral (LEC) subregions using either functional magnetic resonance imaging (fMRI) or diffusion tensor imaging (DTI). However, there are still discrepancies between entorhinal subdivisions depending on the choice of connectivity seed regions and the imaging modality used. While DTI can be used to follow the white matter tracts of the brain, fMRI can identify functionally connected brain regions. In this study, we used both DTI and resting-state fMRI in 103 healthy adults to investigate both structural and functional connectivity between the EC and associated cortical brain regions. Differential connectivity with these regions was then used to predict the locations of the human homologues of MEC and LEC. Our results from combining DTI and fMRI support a subdivision into posteromedial (pmEC) and anterolateral (alEC) EC and reveal a confined border between the pmEC and alEC. Furthermore, the EC subregions obtained by either imaging modality showed similar distinct whole-brain connectivity profiles. Optimizing the delineation of the human homologues of MEC and LEC with a combined, cross-validated DTI-fMRI approach allows to define a likely border between the two subdivisions and has implications for both cognitive and translational neuroscience research.

The hemostatic system in chronic brain diseases: A new challenging frontier?

Neurological diseases (ND), including neurodegenerative diseases (NDD) and psychiatric disorders (PD), present a significant public health challenge, ranking third in Europe for disability and premature death, following cardiovascular diseases and cancers. In 2017, approximately 540 million cases of ND were reported among Europe's 925 million people, with strokes, dementia, and headaches being most prevalent. Nowadays, more and more evidence highlight the hemostasis critical role in cerebral homeostasis and vascular events. Indeed, hemostasis, thrombosis, and brain abnormalities contributing to ND form a complex and poorly understood equilibrium. Alterations in vascular biology, particularly involving the blood-brain barrier, are implicated in ND, especially dementia, and PD. While the roles of key coagulation players such as thrombin and fibrinogen are established, the roles of other hemostasis components are less clear. Moreover, the involvement of these elements in psychiatric disease pathogenesis is virtually unstudied, except in specific pathological models such as antiphospholipid syndrome. Advanced imaging techniques, primarily functional magnetic resonance imaging and its derivatives like diffusion tensor imaging, have been developed to study brain areas affected by ND and to improve our understanding of the pathophysiology of these diseases. This literature review aims to clarify the current understanding of the connections between hemostasis, thrombosis, and neurological diseases, as well as explore potential future diagnostic and therapeutic strategies.

White matter correlates of dissociation in a diverse sample of trauma-exposed women

Dissociation is a common response to trauma linked to functional brain disruptions in brain networks subserving emotion regulation and multisensory integration; however, structural neural correlates of dissociation are less known, particularly abnormalities in stress-sensitive white matter (WM) tracts. The present study examined associations between dissociation and WM microstructure, assessed via fractional anisotropy (FA), in a large, diverse sample of women recruited as part of a long-standing trauma study, the Grady Trauma Project (GTP). As part of GTP, 135 trauma-exposed women (18-62 years old, M=34.25, SD=12.96, 84% self-identifying as Black) were recruited, received diffusion tensor imaging, and completed the Multiscale Dissociation Inventory (MDI); FA values were extracted from ten major WM tracts of interest. Partial correlations were conducted to examine associations between dissociation facets (MDI total and subscales) and FA while covarying age and temporal signal-to-noise ratio; false discovery rate corrected p < 0.05 indicated statistical significance. FA in seven tracts showed significant negative associations with overall dissociation (MDI total score; rs<-0.19, pFDR<0.05); the corona radiata, corpus callosum, superior longitudinal fasciculus, thalamic radiation, anterior cingulum, fornix, and uncinate fasciculus. Among facets of dissociation, FA was most consistently associated with dissociative memory disturbance, showing a significant and negative association with all but one of tract of interest, (rs<-0.23, pFDR<0.05). Our findings indicated that dissociation severity was linked to proportionally lesser WM microstructural integrity in tracts involved with sensory integration, emotion regulation, memory, and self-referential processing. Disruptions in these pathways may underlie dissociative phenomena, representing important psychotherapeutic and neuromodulatory targets.

Role of diffusion tensor imaging in the evaluation of white matter integrity in idiopathic intracranial hypertension

OBJECTIVES

To determine whether idiopathic intracranial hypertension (IIH) may affect white matter integrity and optic pathways by using diffusion tensor imaging (DTI) and to correlate the DTI metrics with intracranial pressure (ICP).

METHODS

This study is a retrospective case-control study. A total of 42 patients who underwent lumbar puncture and those with elevated ICP, meeting the diagnostic criteria for IIH, were included in the study. All patients had supportive magnetic resonance imaging findings for the diagnosis of IIH. The headache control group comprised 36 patients who presented to the Neurology Department with infrequent episodic tension-type headache, had a normal neurologic examination, and had clinical and radiological findings suggestive of normal ICP. For each patient with IIH, clinical findings and ophthalmological measurements were recorded. The apparent diffusion coefficient (ADC), fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD) values were calculated using a region of interest-based method in different white matter tracts and optic pathways and compared.

RESULTS

A total of 42 patients diagnosed with IIH (three males, 39 females), with a mean (standard deviation [SD] age of 38.1 (8.9) years), and 36 headache controls (10 males, 26 females, mean [SD] age; 38.1 [9.4] years) were included in the study. The mean (SD) body mass index (BMI) of the patients with IIH was 25.2 (1.9) kg/m2, and the mean (SD) BMI of the headache controls was 23.3 (1.5) kg/m2 (p < 0.001). Decreased FA values and increased RD values in the cingulum were detected in patients with IIH compared to the headache controls (p = 0.003, Cohen's d = 0.681; p = 0.002 Cohen's d = -0.710). Decreased AD values in the left and right superior cerebellar peduncle and increased ADC values in the middle cerebellar peduncle were detected in patients with IIH compared to the headache controls (p < 0.001, Cohen's d = 0.961; p = 0.009, Cohen's d = 0.607; p = 0.015, Cohen's d = -0.564). Increased ADC and RD values and decreased FA values in optic nerve were detected in patients with IIH (p = 0.010, Cohen's d = -0.603; p = 0.004, Cohen's d = -0.676; p = 0.015 Cohen's d = 0.568). A positive correlation was found between the cerebrospinal fluid pressure and ADC values of the left and right superior and left inferior longitudinal fasciculus, genu of the corpus callosum, and right optic radiation (r = 0.43, p = 0.005; r = 0.31, p = 0.044; r = 0.39, p = 0.010; r = 0.35, p = 0.024; r = 0,41, p = 0.007). There was a positive correlation between the retinal nerve fiber layer thickness and the ADC values of the optic nerve (r = 0.32, p = 0.039).

CONCLUSIONS

Intracranial hypertension can be associated with deteriorated DTI values, which might be interpreted as a sign of impaired white matter microstructural integrity in many brain regions beyond the periventricular white matter. Pressure-induced edema and axonal degeneration may be the potential underlying mechanisms of this microstructural damage.

Magnetic Resonance Imaging of Endometriosis: The Role of Advanced Techniques

Endometriosis is a chronic inflammatory disease that affects about 10% of women, and it is characterized by the presence of endometrial tissue outside the uterine cavity. Associated symptoms are dyspareunia, chronic pelvic pain, and infertility. The diagnosis of endometriosis can be challenging due to various clinical and imaging presentations. Laparoscopy is the gold standard for the diagnosis, but it is an invasive procedure. The literature has increasingly promoted a switch to less invasive imaging techniques, such as ultrasound and magnetic resonance imaging (MRI). The latter, also in relation to the latest technological advances, allows a comprehensive and accurate assessment of the pelvis and it can also identify sites of endometriosis that escape laparoscopic evaluation. Furthermore, MRI has been found to be more accurate than other imaging techniques in relation to its improved sensitivity and specificity in identifying disease sites, also due to the role of new emerging sequences. This article aims to review the current role of advanced MRI applications in the assessment of endometriosis.

White Matter Magnetic Resonance Diffusion Measures in Multiple Sclerosis with Overactive Bladder

BACKGROUND

Lower urinary tract (LUT) symptoms are reported in more than 80% of patients with multiple sclerosis (MS), most commonly an overactive bladder (OAB). The relationship between brain white matter (WM) changes in MS and OAB symptoms is poorly understood.

OBJECTIVES

We aim to evaluate (i) microstructural WM differences across MS patients (pwMS) with OAB symptoms, patients without LUT symptoms, and healthy subjects using diffusion tensor imaging (DTI), and (ii) associations between clinical OAB symptom scores and DTI indices.

METHODS

Twenty-nine female pwMS [mean age (SD) 43.3 years (9.4)], including seventeen with OAB [mean age (SD) 46.1 years (8.6)] and nine without LUT symptoms [mean age (SD) 37.5 years (8.9)], and fourteen healthy controls (HCs) [mean age (SD) 48.5 years (20)] were scanned in a 3T MRI with a DTI protocol. Additionally, clinical scans were performed for WM lesion segmentation. Group differences in fractional anisotropy (FA) were evaluated using tract-based spatial statistics. The Urinary Symptom Profile questionnaire assessed OAB severity.

RESULTS

A statistically significant reduction in FA (p = 0.004) was identified in microstructural WM in pwMS, compared with HCs. An inverse correlation was found between FA in frontal and parietal WM lobes and OAB scores (p = 0.021) in pwMS. Areas of lower FA, although this did not reach statistical significance, were found in both frontal lobes and the rest of the non-dominant hemisphere in pwMS with OAB compared with pwMS without LUT symptoms (p = 0.072).

CONCLUSIONS

This study identified that lesions affecting different WM tracts in MS can result in OAB symptoms and demonstrated the role of the WM in the neural control of LUT functions. By using DTI, the association between OAB symptom severity and WM changes were identified, adding knowledge to the current LUT working model. As MS is predominantly a WM disease, these findings suggest that regional WM involvement, including of the anterior corona radiata, anterior thalamic radiation, superior longitudinal fasciculus, and superior frontal-occipital fasciculus and a non-dominant prevalence in WM, can result in OAB symptoms. OAB symptoms in MS correlate with anisotropy changes in different white matter tracts as demonstrated by DTI. Structural impairment in WM tracts plays an important role in LUT symptoms in MS.

Diffusion Tensor Imaging: Techniques and Applications for Peripheral Nerve Injury

ABSTRACT

Peripheral nerve injuries (PNIs) represent a complex clinical challenge, necessitating precise diagnostic approaches for optimal management. Traditional diagnostic methods often fall short in accurately assessing nerve recovery as these methods rely on the completion of nerve reinnervation, which can prolong a patient's treatment. Diffusion tensor imaging (DTI), a noninvasive magnetic resonance imaging (MRI) technique, has emerged as a promising tool in this context. DTI offers unique advantages including the ability to quantify nerve recovery and provide in vivo visualizations of neuronal architecture. Therefore, this review aims to examine and outline DTI techniques and its utility in detecting distal nerve regeneration in both preclinical and clinical settings for peripheral nerve injury.

Comparison of T1-weighted landmark placement and ROI transfer onto diffusion-weighted EPI sequences for targeted tractography tasks in the optic nerve

Diffusion-based tractography in the optic nerve requires sampling strategies assisted by anatomical landmark information (regions of interest [ROIs]). We aimed to investigate the feasibility of expert-placed, high-resolution T1-weighted ROI-data transfer onto lower spatial resolution diffusion-weighted images. Slab volumes from 20 volunteers were acquired and preprocessed including distortion bias correction and artifact reduction. Constrained spherical deconvolution was used to generate a directional diffusion information grid (fibre orientation distribution-model [FOD]). Three neuroradiologists marked landmarks on both diffusion imaging variants and structural datasets. Structural ROI information (volumetric interpolated breath-hold sequence [VIBE]) was respectively registered (linear with 6/12 degrees of freedom [DOF]) onto single-shot EPI (ss-EPI) and readout-segmented EPI (rs-EPI) volumes, respectively. All eight ROI/FOD-combinations were compared in a targeted tractography task of the optic nerve pathway. Inter-rater reliability for placed ROIs among experts was highest in VIBE images (lower confidence interval 0.84 to 0.97, mean 0.91) and lower in both ss-EPI (0.61 to 0.95, mean 0.79) and rs-EPI (0.59 to 0.86, mean 0.70). Tractography success rate based on streamline selection performance was highest in VIBE-drawn ROIs registered (6-DOF) onto rs-EPI FOD (70.0% over 5%-threshold, capped to failed ratio 39/16) followed by both 12-DOF-registered (67.5%; 41/16) and nonregistered VIBE (67.5%; 40/23). On ss-EPI FOD, VIBE-ROI-datasets obtained fewer streamlines overall with each at 55.0% above 5%-threshold and with lower capped to failed ratio (6-DOF: 35/36; 12-DOF: 34/34, nonregistered 33/36). The combination of VIBE-placed ROIs (highest inter-rater reliability) with 6-DOF registration onto rs-EPI targets (best streamline selection performance) is most suitable for white matter template generation required in group studies.

A diffusion tensor imaging white matter atlas of the domestic canine brain

There is increasing reliance on magnetic resonance imaging (MRI) techniques in both research and clinical settings. However, few standardized methods exist to permit comparative studies of brain pathology and function. To help facilitate these studies, we have created a detailed, MRI-based white matter atlas of the canine brain using diffusion tensor imaging. This technique, which relies on the movement properties of water, permits the creation of a three-dimensional diffusivity map of white matter brain regions that can be used to predict major axonal tracts. To generate an atlas of white matter tracts, thirty neurologically and clinically normal dogs underwent MRI imaging under anesthesia. High-resolution, three-dimensional T1-weighted sequences were collected and averaged to create a population average template. Diffusion-weighted imaging sequences were collected and used to generate diffusivity maps, which were then registered to the T1-weighted template. Using these diffusivity maps, individual white matter tracts-including association, projection, commissural, brainstem, olfactory, and cerebellar tracts-were identified with reference to previous canine brain atlas sources. To enable the use of this atlas, we created downloadable overlay files for each white matter tract identified using manual segmentation software. In addition, using diffusion tensor imaging tractography, we created tract files to delineate major projection pathways. This comprehensive white matter atlas serves as a standard reference to aid in the interpretation of quantitative changes in brain structure and function in clinical and research settings.

Mismatch of MRI White Matter Hyperintensities and Gait Function in Patients With Cerebral Small Vessel Disease

BACKGROUND

Cerebral small vessel disease (CSVD) is closely related to gait disorders. Previous studies have found a negative correlation between the severity of MRI white matter hyperintensities (WMH) and gait speed. However, not every individual with WMH experiences a gait disorder.

PURPOSE

To investigate the mechanisms underlying the mismatch between the severity of MRI WMH and gait impairment, in particular in subjects with severe WMH (Fazekas 3, scale 0-3) resulting from vascular disease.

STUDY TYPE

Cohort.

POPULATION

54 subjects with severe WMH and gait disorder (WMH-GD; 29 males) and 114 subjects with severe WMH with no gait disorder (WMH-nGD; 60 males).

FIELD STRENGTH/SEQUENCE

3T/diffusion tensor imaging (DTI), and T1-weighted, T2-weighted, FLAIR, DWI, SWI.

ASSESSMENT

Trace-based spatial statistics analysis (TBSS) approach (fractional anisotropy, FA; mean diffusivity; radial diffusivity; axial diffusivity); Cognitive assessment; Conventional MRI markers of CSVD (WMH, enlarged perivascular spaces, lacunae, and cerebral microbleeds); Gait parameters (gait speed; cadence; stride length; gait cycle duration; step duration; time-up-and-go test, TUG). Gait disorder was defined as a TUG time exceeding 12 sec.

STATISTICAL TESTS

The t-tests, Mann-Whitney U tests, Chi-square tests, and partial correlation analysis (Pearson or Spearman) were used. P < 0.05 with threshold-free cluster enhancement corrected was considered statistically significant for TBSS.

RESULTS

After adjusting for age, sex, height, and other conventional MRI markers of CSVD, the WMH-nGD group showed significantly decreased FA values in the corpus callosum, bilateral superior longitudinal fasciculus, left corona radiata, and left posterior thalamic radiation. There was a significant association between FA values and TUG time, gait speed, and stride length in multiple WM tracts, independent of other conventional CSVD markers.

DATA CONCLUSION

This study provides evidence for microstructural damage of specific fibers in WMH-GD subjects compared to WMH-nGD subjects. This may explain the mismatch between WMH and gait impairment in subjects with severe WMH.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY: Stage 3.

An MRI evaluation of white matter involvement in paradigmatic forms of spastic ataxia: results from the multi-center PROSPAX study

BACKGROUND

Autosomal Recessive Spastic Ataxia of Charlevoix-Saguenay (ARSACS) and Spastic Paraplegia Type 7 (SPG7) are paradigmatic spastic ataxias (SPAX) with suggested white matter (WM) involvement. Aim of this work was to thoroughly disentangle the degree of WM involvement in these conditions, evaluating both macrostructure and microstructure via the analysis of diffusion MRI (dMRI) data.

MATERIAL AND METHODS

In this multi-center prospective study, ARSACS and SPG7 patients and Healthy Controls (HC) were enrolled, all undergoing a standardized dMRI protocol and a clinimetrics evaluation including the Scale for the Assessment and Rating of Ataxia (SARA). Differences in terms of WM volume or global microstructural WM metrics were probed, as well as the possible occurrence of a spatially defined microstructural WM involvement via voxel-wise analyses, and its correlation with patients' clinical status.

RESULTS

Data of 37 ARSACS (M/F = 21/16; 33.4 ± 12.4 years), 37 SPG7 (M/F = 24/13; 55.7 ± 10.7 years), and 29 HC (M/F = 13/16; 42.1 ± 17.2 years) were analyzed. While in SPG7, only a mild mean microstructural damage was found compared to HC, ARSACS patients present a severe WM involvement, with a reduced global volume (p < 0.001), an alteration of all microstructural metrics (all with p < 0.001), without a spatially defined pattern of damage but with a prominent involvement of commissural fibers. Finally, in ARSACS, a correlation between microstructural damage and SARA scores was found (p = 0.004).

CONCLUSION

In ARSACS, but not SPG7 patients, we observed a complex and multi-faced involvement of brain WM, with a clinically meaningful widespread loss of axonal and dendritic integrity, secondary demyelination and, overall, a reduction in cellularity and volume.

Assessing biological self-organization patterns using statistical complexity characteristics: a tool for diffusion tensor imaging analysis

OBJECT

Diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) are well-known and powerful imaging techniques for MRI. Although DTI evaluation has evolved continually in recent years, there are still struggles regarding quantitative measurements that can benefit brain areas that are consistently difficult to measure via diffusion-based methods, e.g., gray matter (GM). The present study proposes a new image processing technique based on diffusion distribution evaluation of López-Ruiz, Mancini and Calbet (LMC) complexity called diffusion complexity (DC).

MATERIALS AND METHODS

The OASIS-3 and TractoInferno open-science databases for healthy individuals were used, and all the codes are provided as open-source materials.

RESULTS

The DC map showed relevant signal characterization in brain tissues and structures, achieving contrast-to-noise ratio (CNR) gains of approximately 39% and 93%, respectively, compared to those of the FA and ADC maps.

DISCUSSION

In the special case of GM tissue, the DC map obtains its maximum signal level, showing the possibility of studying cortical and subcortical structures challenging for classical DTI quantitative formalism. The ability to apply the DC technique, which requires the same imaging acquisition for DTI and its potential to provide complementary information to study the brain's GM structures, can be a rich source of information for further neuroscience research and clinical practice.

The effect of spinal correction surgery on the tractography data of the pain pathway in scoliosis patients: a preliminary report

STUDY DESIGN

Cross-sectional study.

OBJECTIVE

Pain in individuals with opered scoliosis is usually evaluated with a postural analysis or questionnaire. In this study, we evaluated pain in individuals with scoliosis who underwent spinal correction surgery by tractography and compared it with individuals with non-opered scoliosis and healthy individuals.

DESIGN

Fifteen healthy individuals, 15 non-operated scoliosis patients and 15 operated scoliosis patients were included in the study.

METHODS

All female participants in this prospectively planned study used their right hand as the dominant hand. Bilateral tractography analysis of the pain pathways was performed with DSI Studio software using brain magnetic resonance images (MRI) of the participants. Statistical analysis of the study was performed with IBM SPSS 23.0 and p<0.05 values were considered significant.

RESULTS

It was observed that the tractography values of the operated scoliosis group were similar to the control group (p˃0.05). In the non-operated scoliosis group, tractography findings related to nerve conduction velocity such as fiber count, fiber ratio and axial diffusivity (AD) were found to be higher than the other two groups (p<0.05). Fractional anisotropy (FA) values of the unoperated scoliosis group were significantly different between the pain pathways projected from the right/left side of the body (p<0.05).

CONCLUSION

The fact that the pain path tractography values of patients with scoliosis who underwent surgery were similar to those of healthy individuals may be evidence of decreased pain sensation reaching the brain. Surgery may be a good choice in the treatment of pain in patients with scoliosis.

Tractometry of Human Visual White Matter Pathways in Health and Disease

Diffusion-weighted MRI (dMRI) provides a unique non-invasive view of human brain tissue properties. The present review article focuses on tractometry analysis methods that use dMRI to assess the properties of brain tissue within the long-range connections comprising brain networks. We focus specifically on the major white matter tracts that convey visual information. These connections are particularly important because vision provides rich information from the environment that supports a large range of daily life activities. Many of the diseases of the visual system are associated with advanced aging, and tractometry of the visual system is particularly important in the modern aging society. We provide an overview of the tractometry analysis pipeline, which includes a primer on dMRI data acquisition, voxelwise model fitting, tractography, recognition of white matter tracts, and calculation of tract tissue property profiles. We then review dMRI-based methods for analyzing visual white matter tracts: the optic nerve, optic tract, optic radiation, forceps major, and vertical occipital fasciculus. For each tract, we review background anatomical knowledge together with recent findings in tractometry studies on these tracts and their properties in relation to visual function and disease. Overall, we find that measurements of the brain's visual white matter are sensitive to a range of disorders and correlate with perceptual abilities. We highlight new and promising analysis methods, as well as some of the current barriers to progress toward integration of these methods into clinical practice. These barriers, such as variability in measurements between protocols and instruments, are targets for future development.

Transcriptome analysis identifies an ASD-Like phenotype in oligodendrocytes and microglia from C58/J amygdala that is dependent on sex and sociability

BACKGROUND

Autism Spectrum Disorder (ASD) is a group of neurodevelopmental disorders with higher incidence in males and is characterized by atypical verbal/nonverbal communication, restricted interests that can be accompanied by repetitive behavior, and disturbances in social behavior. This study investigated brain mechanisms that contribute to sociability deficits and sex differences in an ASD animal model.

METHODS

Sociability was measured in C58/J and C57BL/6J mice using the 3-chamber social choice test. Bulk RNA-Seq and snRNA-Seq identified transcriptional changes in C58/J and C57BL/6J amygdala within which DMRseq was used to measure differentially methylated regions in amygdala.

RESULTS

C58/J mice displayed divergent social strata in the 3-chamber test. Transcriptional and pathway signatures revealed immune-related biological processes differ between C58/J and C57BL/6J amygdala. Hypermethylated and hypomethylated genes were identified in C58/J versus C57BL/6J amygdala. snRNA-Seq data in C58/J amygdala identified differential transcriptional signatures within oligodendrocytes and microglia characterized by increased ASD risk gene expression and predicted impaired myelination that was dependent on sex and sociability. RNA velocity, gene regulatory network, and cell communication analysis showed diminished oligodendrocyte/microglia differentiation. Findings were verified using Bulk RNA-Seq and demonstrated oxytocin's beneficial effects on myelin gene expression.

LIMITATIONS

Our findings are significant. However, limitations can be noted. The cellular mechanisms linking reduced oligodendrocyte differentiation and reduced myelination to an ASD phenotype in C58/J mice need further investigation. Additional snRNA-Seq and spatial studies would determine if effects in oligodendrocytes/microglia are unique to amygdala or if this occurs in other brain regions. Oxytocin's effects need further examination to understand its' potential as an ASD therapeutic.

CONCLUSIONS

Our work demonstrates the C58/J mouse model's utility in evaluating the influence of sex and sociability on the transcriptome in concomitant brain regions involved in ASD. Our single-nucleus transcriptome analysis elucidates potential pathological roles of oligodendrocytes and microglia in ASD. This investigation provides details regarding regulatory features disrupted in these cell types, including transcriptional gene dysregulation, aberrant cell differentiation, altered gene regulatory networks, and changes to key pathways that promote microglia/oligodendrocyte differentiation. Our studies provide insight into interactions between genetic risk and epigenetic processes associated with divergent affiliative behavior and lack of positive sociability.

Connection Failure: Differences in White Matter Microstructure Are Associated with 5-HTTLPR but Not with Risk Seeking for Losses

S/S carriers of 5-HTTLPR have been found to be more risk seeking for losses compared to L/L carriers. This finding may be the result of reduced top-down control from the frontal cortex due to altered signal pathways involving the amygdala and ventral striatum. The serotonergic system is known to be involved in neurodevelopment and neuroplasticity. Therefore, the aim of this study was to investigate whether structural differences in white matter can explain the differences in risk-seeking behaviour. Lower structural connectivity in S/S compared to L/L carriers and a negative relationship between risk seeking for losses and connectivity were assumed. Diffusion-weighted imaging was used to compute diffusion parameters for the frontostriatal and uncinate tract in 175 genotyped individuals. The results showed no significant relationship between diffusion parameters and risk seeking for losses. Furthermore, we did not find significant differences in diffusion parameters of the S/S vs. L/L group. There were only group differences in the frontostriatal tract showing stronger structural connectivity in the S/L group, which is also reflected in the whole brain approach. Therefore, the data do not support the hypothesis that the association between 5-HTTLPR and risk seeking for losses is related to differences in white matter pathways implicated in decision-making.

The Use of Diffusion Tensor Imaging in the Identification of Acute Rejection and Chronic Allograft Nephropathy After Renal Transplantation

BACKGROUND

Identifying the cause of renal allograft dysfunction is important for the clinical management of kidney transplant recipients.

PURPOSE

To evaluate the diagnostic efficiency of diffusion tensor imaging (DTI) for identifying allografts with acute rejection (AR) and chronic allograft nephropathy (CAN).

STUDY TYPE

Prospective.

SUBJECTS

Seventy-seven renal transplant patients (aged 42.5 ± 9.5 years), including 29 patients with well-functioning stable allografts (Control group), 25 patients diagnosed with acute rejection (AR group), and 23 patients diagnosed with chronic allograft nephropathy (CAN group).

FIELD STRENGTH/SEQUENCE

1.5 T/T2-weighted imaging and DTI.

ASSESSMENT

The serum creatinine, proteinuria, pathologic results, and fractional anisotropy (FA) values were obtained and compared among the three groups.

STATISTICAL TEST

One-way analysis of variance; correlation analysis; independent-sample t-test; intraclass correlation coefficients and receiver operating characteristic curves. Statistical significance was set to a P-value <0.05.

RESULTS

The AR and CAN groups presented with significantly elevated serum creatinine as compared with the Control group (191.8 ± 181.0 and 163.1 ± 115.8 μmol/L vs. 82.3 ± 20.9 μmol/L). FA decreased in AR group (cortical/medullary: 0.13 ± 0.02/0.31 ± 0.07) and CAN group (cortical/medullary: 0.11 ± 0.02/0.27 ± 0.06), compared with the Control group (cortical/medullary: 0.15 ± 0.02/0.35 ± 0.05). Cortical FA in the AR group was higher than in the CAN group. The area under the curve (AUC) for identifying AR from normal allografts was 0.756 and 0.744 by cortical FA and medullary FA, respectively. The AUC of cortical FA and medullary FA for differentiating CAN from normal allografts was 0.907 and 0.830, respectively. The AUC of cortical FA and medullary FA for distinguishing AR and CAN from normal allografts was 0.828 and 0.785, respectively. Cortical FA was able to distinguish between AR and CAN with an AUC of 0.728.

DATA CONCLUSION

DTI was able to detect patients with dysfunctional allografts. Cortical FA can further distinguish between AR and CAN.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 2.

Multi-parametric MRI can detect enhanced myelination in the Gli1 -/- mouse brain

This study investigated the potential of combining multiple MR parameters to enhance the characterization of myelin in the mouse brain. We collected ex vivo multi-parametric MR data at 7 Tesla from control and Gli1 -/- mice; the latter exhibit enhanced myelination at postnatal day 10 (P10) in the corpus callosum and cortex. The MR data included relaxivity, magnetization transfer, and diffusion measurements, each targeting distinct myelin properties. This analysis was followed by and compared to myelin basic protein (MBP) staining of the same samples. Although a majority of the MR parameters included in this study showed significant differences in the corpus callosum between the control and Gli1 -/- mice, only T 2 , T 1 /T 2, and radial diffusivity (RD) demonstrated a significant correlation with MBP values. Based on data from the corpus callosum, partial least square regression suggested that combining T 2 , T 1 /T 2 , and inhomogeneous magnetization transfer ratio could explain approximately 80% of the variance in the MBP values. Myelin predictions based on these three parameters yielded stronger correlations with the MBP values in the P10 mouse brain corpus callosum than any single MR parameter. In the motor cortex, combining T 2 , T 1 /T 2, and radial kurtosis could explain over 90% of the variance in the MBP values at P10. This study demonstrates the utility of multi-parametric MRI in improving the detection of myelin changes in the mouse brain.

Longitudinal Free-Water Changes in Dementia with Lewy Bodies

BACKGROUND

Diffusion-weighted magnetic resonance imaging (dMRI) examines tissue microstructure integrity in vivo. Prior dementia with Lewy bodies (DLB) diffusion tensor imaging studies yielded mixed results.

OBJECTIVE

We employed free-water (FW) imaging to assess DLB progression and correlate with clinical decline in DLB.

METHODS

Baseline and follow-up MRIs were obtained at 12 and/or 24 months for 27 individuals with DLB or mild cognitive impairment with Lewy bodies (MCI-LB). FW was analyzed using the Mayo Clinic Adult Lifespan Template. Primary outcomes were FW differences between baseline and 12 or 24 months. To compare FW change longitudinally, we included 20 cognitively unimpaired individuals from the Alzheimer's Disease Neuroimaging Initiative.

RESULTS

We followed 23 participants to 12 months and 16 participants to 24 months. Both groups had worsening in Montreal Cognitive Assessment (MoCA) and Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) scores. We found significant FW increases at both time points compared to baseline in the insula, amygdala, posterior cingulum, parahippocampal, entorhinal, supramarginal, fusiform, retrosplenial, and Rolandic operculum regions. At 24 months, we found more widespread microstructural changes in regions implicated in visuospatial processing, motor, and cholinergic functions. Between-group analyses (DLB vs. controls) confirmed significant FW changes over 24 months in most of these regions. FW changes were associated with longitudinal worsening of MDS-UPDRS and MoCA scores.

CONCLUSIONS

FW increased in gray and white matter regions in DLB, likely due to neurodegenerative pathology associated with disease progression. FW change was associated with clinical decline. The findings support dMRI as a promising tool to track disease progression in DLB. © 2024 International Parkinson and Movement Disorder Society.

Multiple Sclerosis Part 2: Advanced Imaging and Emerging Techniques

Multiple advanced imaging methods for multiple sclerosis (MS) have been in investigation to identify new imaging biomarkers for early disease detection, predicting disease prognosis, and clinical trial endpoints. Multiple techniques probing different aspects of tissue microstructure (ie, advanced diffusion imaging, magnetization transfer, myelin water imaging, magnetic resonance spectroscopy, glymphatic imaging, and perfusion) support the notion that MS is a global disease with microstructural changes evident in normal-appearing white and gray matter. These global changes are likely better predictors of disability compared with lesion load alone. Emerging techniques in glymphatic and molecular imaging may improve understanding of pathophysiology and emerging treatments.

Characterization of early markers of disease in the mouse model of mucopolysaccharidosis IIIB

BACKGROUND

Mucopolysaccharidosis (MPS) IIIB, also known as Sanfilippo Syndrome B, is a devastating childhood disease. Unfortunately, there are currently no available treatments for MPS IIIB patients. Yet, animal models of lysosomal storage diseases have been valuable tools in identifying promising avenues of treatment. Enzyme replacement therapy, gene therapy, and bone marrow transplant have all shown efficacy in the MPS IIIB model systems. A ubiquitous finding across rodent models of lysosomal storage diseases is that the best treatment outcomes resulted from intervention prior to symptom onset. Therefore, the aim of the current study was to identify early markers of disease in the MPS IIIB mouse model as well as examine clinically-relevant behavioral domains not yet explored in this model.

METHODS

Using the MPS IIIB mouse model, we explored early developmental trajectories of communication and gait, and later social behavior, fear-related startle and conditioning, and visual capabilities. In addition, we examined brain structure and function via magnetic resonance imaging and diffusion tensor imaging.

RESULTS

We observed reduced maternal isolation-induced ultrasonic vocalizations in MPS IIIB mice relative to controls, as well as disruption in a number of the spectrotemporal features. MPS IIIB also exhibited disrupted thermoregulation during the first two postnatal weeks without any differences in body weight. The developmental trajectories of gait were largely normal. In early adulthood, we observed intact visual acuity and sociability yet a more submissive phenotype, increased aggressive behavior, and decreased social sniffing relative to controls. MPS IIIB mice showed greater inhibition of startle in response to a pretone with a decrease in overall startle response and reduced cued fear memory. MPS IIIB also weighed significantly more than controls throughout adulthood and showed larger whole brain volumes and normalized regional volumes with intact tissue integrity as measured with magnetic resonance and diffusion tensor imaging, respectively.

CONCLUSIONS

Together, these results indicate disease markers are present as early as the first two weeks postnatal in this model. Further, this model recapitulates social, sensory and fear-related clinical features. Our study using a mouse model of MPS IIIB provides essential baseline information that will be useful in future evaluations of potential treatments.

Connectome alterations following perinatal deafness in the cat

Following sensory deprivation, areas and networks in the brain may adapt and reorganize to compensate for the loss of input. These adaptations are manifestations of compensatory crossmodal plasticity, which has been documented in both human and animal models of deafness-including the domestic cat. Although there are abundant examples of structural plasticity in deaf felines from retrograde tracer-based studies, there is a lack of diffusion-based knowledge involving this model compared to the current breadth of human research. The purpose of this study was to explore white matter structural adaptations in the perinatally-deafened cat via tractography, increasing the methodological overlap between species. Plasticity was examined by identifying unique group connections and assessing altered connectional strength throughout the entirety of the brain. Results revealed a largely preserved connectome containing a limited number of group-specific or altered connections focused within and between sensory networks, which is generally corroborated by deaf feline anatomical tracer literature. Furthermore, five hubs of cortical plasticity and altered communication following perinatal deafness were observed. The limited differences found in the present study suggest that deafness-induced crossmodal plasticity is largely built upon intrinsic structural connections, with limited remodeling of underlying white matter.

White matter tracts adjacent to the human cingulate sulcus visual area (CSv)

Human cingulate sulcus visual area (CSv) was first identified as an area that responds selectively to visual stimulation indicative of self-motion. It was later shown that the area is also sensitive to vestibular stimulation as well as to bodily motion compatible with locomotion. Understanding the anatomical connections of CSv will shed light on how CSv interacts with other parts of the brain to perform information processing related to self-motion and navigation. A previous neuroimaging study (Smith et al. 2018, Cerebral Cortex, 28, 3685-3596) used diffusion-weighted magnetic resonance imaging (dMRI) to examine the structural connectivity of CSv, and demonstrated connections between CSv and the motor and sensorimotor areas in the anterior and posterior cingulate sulcus. The present study aimed to complement this work by investigating the relationship between CSv and adjacent major white matter tracts, and to map CSv's structural connectivity onto known white matter tracts. By re-analysing the dataset from Smith et al. (2018), we identified bundles of fibres (i.e. streamlines) from the whole-brain tractography that terminate near CSv. We then assessed to which white matter tracts those streamlines may belong based on previously established anatomical prescriptions. We found that a significant number of CSv streamlines can be categorised as part of the dorsalmost branch of the superior longitudinal fasciculus (SLF I) and the cingulum. Given current thinking about the functions of these white matter tracts, our results support the proposition that CSv provides an interface between sensory and motor systems in the context of self-motion.

Discontinuity third harmonic generation microscopy for label-free imaging and quantification of intraepidermal nerve fibers

Label-free imaging methodologies for nerve fibers rely on spatial signal continuity to identify fibers and fail to image free intraepidermal nerve endings (FINEs). Here, we present an imaging methodology-called discontinuity third harmonic generation (THG) microscopy (dTHGM)-that detects three-dimensional discontinuities in THG signals as the contrast. We describe the mechanism and design of dTHGM and apply it to reveal the bead-string characteristics of unmyelinated FINEs. We confirmed the label-free capability of dTHGM through a comparison study with the PGP9.5 immunohistochemical staining slides and a longitudinal spared nerve injury study. An intraepidermal nerve fiber (IENF) index based on a discontinuous-dot-connecting algorithm was developed to facilitate clinical applications of dTHGM. A preliminary clinical study confirmed that the IENF index was highly correlated with skin-biopsy-based IENF density (Pearson's correlation coefficient R = 0.98) and could achieve differential identification of small-fiber neuropathy (p = 0.0102) in patients with diabetic peripheral neuropathy.

Diagnostic efficacy of tract-specific diffusion tensor imaging in cervical spondylotic myelopathy with electrophysiological examination validation

PURPOSE

This study aimed to investigate the effectiveness of tract-specific diffusion tensor imaging (DTI) metrics in identifying the responsible segments for neurological dysfunction in cervical spondylotic myelopathy (CSM).

METHODS

The study encompassed nineteen participants diagnosed with CSM, including 10 males and 9 females. Additionally, a control group consisting of ten healthy caregivers (5 males and 5 females) were recruited with no symptoms and no compressions on magnetic resonance imaging (MRI). All participants underwent a comprehensive physical examination, MRI assessment, and DTI examination conducted by a senior chief physician. Several parameters were collected from the MR images, including the aspect ratio (defined as the anteroposterior diameter / the transverse diameter of the corresponding segment's spinal cord), transverse ratio (defined as the transverse diameter of the corresponding segment's spinal cord / the transverse diameter of the spinal cord at C2/3), and T2 high signal of the spinal cord. Furthermore, quantitative DTI metrics, such as axial diffusivity (AD), mean diffusivity (MD), radial diffusivity (RD), and fractional anisotropy (FA), were calculated using automatic region-of-interest (ROI) analysis for both whole spinal cord column and dorsal column. Receiver operating characteristic (ROC) curves were constructed to evaluate the diagnostic efficacy of the aspect ratio, transverse ratio, and DTI parameters. The area under the curve (AUC), sensitivity, and specificity were calculated. Intraoperative spinal cord electrophysiological examination was performed as the objective measure of spinal cord function during surgery.

RESULTS

As determined by electrophysiological examination, neurological dysfunction was found in 2 patients due to C3/4 compression, in 10 patients due to C4/5 compression, in 6 patients due to C5/6 compression, and in 1 patient due to C6/7 compression. The modified Japanese Orthopedic Association scale (mJOA) was 12.71 ± 1.55 in the CSM group, with 4.87 ± 0.72 for sensory nerve function and 5.05 ± 1.35 for motor nerve function. For the control group, none of the volunteers had neurological dysfunction. T2 high signal was found at the most stenotic segment in 13 patients of the CSM group. Considering all the cervical segments, the aspect ratio (AUC = 0.823, P = 0.001, Sensitivity = 68.42%, Specificity = 82.47%) was more capable of determining the responsible segment than transverse ratio (AUC = 0.661, P = 0.027, Sensitivity = 68.42%, Specificity = 67.01%). AD, MD, and RD were significantly higher while FA was significantly lower in the responsible segment than in the irresponsible segment (P < 0.05). The AUC of DTI-Dorsal column parameters (AD, MD, RD, FA) was larger than the corresponding parameters of the DTI (Whole spinal cord). AD of DTI-Dorsal Column possessed the greatest efficacy (AUC = 0.823, sensitivity = 84.21%, specificity = 77.32%) to determine the responsible segment, larger than AD of DTI-Whole spinal cord (AUC = 0.822, P = 0.001, Sensitivity = 89.47%, Specificity = 77.32%), aspect ratio (AUC = 0.823, P = 0.001, Sensitivity = 68.42%, Specificity = 82.47%) and transverse ratio (AUC = 0.661, P = 0.027, Sensitivity = 68.42%, Specificity = 67.01%). Subgroup analysis revealed that the diagnostic efficacy of DTI and MRI parameters was influenced by cervical spine segment.

CONCLUSIONS

When considering all cervical segments, AD from the DTI-Dorsal Column exhibited the most significant potential in identifying responsible segments. This potential was found to be superior to that of DTI-Whole spinal cord, aspect ratio, the most stenotic segment, T2 high signals, transverse ratio, motor nerve dysfunction, and sensory nerve dysfunction. The diagnostic effectiveness of both DTI and MRI parameters was notably influenced by the specific cervical spine segment.

Combination of fMRI and PET reveals the beneficial effect of three-phase enriched environment on post-stroke memory deficits by enhancing plasticity of brain connectivity between hippocampus and peri-hippocampal cortex

AIM

The three-phase enriched environment (EE) intervention paradigm has been shown to improve learning and memory function after cerebral ischemia, but the neuronal mechanisms are still unclear. This study aimed to investigate the hippocampal-cortical connectivity and the metabolic interactions between neurons and astrocytes to elucidate the underlying mechanisms of EE-induced memory improvement after stroke.

METHODS

Rats were subjected to permanent middle cerebral artery occlusion (pMCAO) or sham surgery and housed in standard environment or EE for 30 days. Memory function was examined by Morris water maze (MWM) test. Magnetic resonance imaging (MRI) was conducted to detect the structural and functional changes. [18 F]-fluorodeoxyglucose (FDG) positron emission tomography (PET) was conducted to detect brain energy metabolism. PET-based brain connectivity and network analysis was performed to study the changes of hippocampal-cortical connectivity. Astrocyte-neuron metabolic coupling, including gap junction protein connexin 43 (Cx43), glucose transporters (GLUTs), and monocarboxylate transporters (MCTs), was detected by histological studies.

RESULTS

Our results showed EE promoted memory function improvement, protected structure integrity, and benefited energy metabolism after stroke. More importantly, EE intervention significantly increased functional connectivity between the hippocampus and peri-hippocampal cortical regions, and specifically regulated the level of Cx43, GLUTs and MCTs in the hippocampus and cortex.

CONCLUSIONS

Our results revealed the three-phase enriched environment paradigm enhanced hippocampal-cortical connectivity plasticity and ameliorated post-stroke memory deficits. These findings might provide some new clues for the development of EE and thus facilitate the clinical transformation of EE.

Model-based parcellation of diffusion MRI of injured spinal cord predicts hand use impairment and recovery in squirrel monkeys

A mathematical model-based parcellation of magnetic resonance diffusion tensor images (DTI) has been developed to quantify progressive changes in three types of tissues - grey (GM), white matter (WM), and damaged spinal cord tissue, along with behavioral assessments over a 6 month period following targeted spinal cord injuries (SCI) in monkeys. Sigmoid Gompertz function based fittings of DTI metrics provide early indicators that correlate with, and predict, recovery of hand grasping behavior. Our three tissue pool model provided unbiased, data-driven segmentation of spinal cord images and identified DTI metrics that can serve as reliable biomarkers of severity of spinal cord injuries and predictors of behavioral outcomes.

Oxytocin-induced birth causes sex-specific behavioral and brain connectivity changes in developing rat offspring

Despite six decades of the use of exogenous oxytocin for management of labor, little is known about its effects on the developing brain. Motivated by controversial reports suggesting a link between oxytocin use during labor and autism spectrum disorders (ASDs), we employed our recently validated rat model for labor induction with oxytocin to address this important concern. Using a combination of molecular biological, behavioral, and neuroimaging assays, we show that induced birth with oxytocin leads to sex-specific disruption of oxytocinergic signaling in the developing brain, decreased communicative ability of pups, reduced empathy-like behaviors especially in male offspring, and widespread sex-dependent changes in functional cortical connectivity. Contrary to our hypothesis, social behavior, typically impaired in ASDs, was largely preserved. Collectively, our foundational studies provide nuanced insights into the neurodevelopmental impact of birth induction with oxytocin and set the stage for mechanistic investigations in animal models and prospective longitudinal clinical studies.

Deep learning-based diffusion tensor image generation model: a proof-of-concept study

This study created an image-to-image translation model that synthesizes diffusion tensor images (DTI) from conventional diffusion weighted images, and validated the similarities between the original and synthetic DTI. Thirty-two healthy volunteers were prospectively recruited. DTI and DWI were obtained with six and three directions of the motion probing gradient (MPG), respectively. The identical imaging plane was paired for the image-to-image translation model that synthesized one direction of the MPG from DWI. This process was repeated six times in the respective MPG directions. Regions of interest (ROIs) in the lentiform nucleus, thalamus, posterior limb of the internal capsule, posterior thalamic radiation, and splenium of the corpus callosum were created and applied to maps derived from the original and synthetic DTI. The mean values and signal-to-noise ratio (SNR) of the original and synthetic maps for each ROI were compared. The Bland-Altman plot between the original and synthetic data was evaluated. Although the test dataset showed a larger standard deviation of all values and lower SNR in the synthetic data than in the original data, the Bland-Altman plots showed each plot localizing in a similar distribution. Synthetic DTI could be generated from conventional DWI with an image-to-image translation model.

Imaging Biomarkers of Peripheral Nerves: Focus on Magnetic Resonance Neurography and Ultrasonography

Peripheral neuropathy is a prevalent and debilitating condition affecting millions of individuals globally. Magnetic resonance neurography (MRN) and ultrasonography (US) are noninvasive methods offering comprehensive visualization of peripheral nerves, using anatomical and functional imaging biomarkers to ensure accurate evaluation. For optimized MRN, superior and high-resolution two-dimensional and three-dimensional imaging protocols are essential. The anatomical MRN and US imaging markers include quantitative measures of nerve and fascicular size and signal, and qualitative markers of course and morphology. Among them, quantitative markers of T2-signal intensity ratio are sensitive to nerve edema-like signal changes, and the T1-mapping technique reveals nerve and muscle tissue fatty and fibrous compositional alterations.The functional markers are derived from physiologic properties of nerves, such as diffusion characteristics or blood flow. They include apparent diffusion coefficient from diffusion-weighted imaging and fractional anisotropy and tractography from diffusion tensor imaging to delve into peripheral nerve microstructure and integrity. Peripheral nerve perfusion using dynamic contrast-enhanced magnetic resonance imaging estimates perfusion parameters, offering insights into nerve health and neuropathies involving edema, inflammation, demyelination, and microvascular alterations in conditions like type 2 diabetes, linking nerve conduction pathophysiology to vascular permeability alterations.Imaging biomarkers thus play a pivotal role in the diagnosis, prognosis, and monitoring of nerve pathologies, thereby ensuring comprehensive assessment and elevating patient care. These biomarkers provide valuable insights into nerve structure, function, and pathophysiology, contributing to the accurate diagnosis and management planning for peripheral neuropathy.

White matter integrity assessment in spinocerebellar ataxia type 2 (SCA2) patients

AIM

To assess the burden of white matter (WM) damage in the cerebrum and cerebellum of spinocerebellar ataxia type 2 (SCA2) patients in an attempt to identify key regions affected by the neurodegenerative processes using diffusion tensor imaging (DTI).

MATERIALS AND METHODS

Nine SCA2 patients and 16 age-matched healthy controls were examined twice (SCA2 patients 3.6 ± 0.7 years and controls 3.3 ± 1.0 years apart) on the same 1.5 T scanner by acquiring T1-weighted and diffusion-weighted (b-value = 1,000 s/mm2) images. Using tract-based spatial statistics, DTI analysis on fractional anisotropy (FA), mean diffusivity (MD), axial (AD)/radial (RD) diffusivity was performed.

RESULTS

At baseline magnetic resonance imaging (MRI), FA was significantly decreased in SCA2 patients in the corticospinal tracts, inferior and superior cerebellar peduncles, middle cerebellar peduncles, cerebral peduncles, right superior and posterior corona radiata. RD was only significantly increased in SCA2 patients in the middle cerebellar peduncles. No significant AD and MD changes were observed. Tract-based spatial statistics (TBSS) analysis between SCA2 patients at baseline and at follow-up showed no significant changes in any of the DTI metrics.

CONCLUSIONS

DTI is a sensitive tool for following the progression of WM neurodegeneration and severity assessment in patients with SCA2. These findings add to a better understanding of the neurological underpinnings of the symptoms experienced by SCA2 patients.

Multi-resolution X-ray phase-contrast and dark-field tomography of human cerebellum with near-field speckles

In this study, we use synchrotron-based multi-modal X-ray tomography to examine human cerebellar tissue in three dimensions at two levels of spatial resolution (2.3 µm and 11.9 µm). We show that speckle-based imaging (SBI) produces results that are comparable to propagation-based imaging (PBI), a well-established phase-sensitive imaging method. The different SBI signals provide complementary information, which improves tissue differentiation. In particular, the dark-field signal aids in distinguishing tissues with similar average electron density but different microstructural variations. The setup's high resolution and the imaging technique's excellent phase sensitivity enabled the identification of different cellular layers and additionally, different cell types within these layers. We also correlated this high-resolution phase-contrast information with measured dark-field signal levels. These findings demonstrate the viability of SBI and the potential benefit of the dark-field modality for virtual histology of brain tissue.

Structural Alterations of the Corpus Callosum in Children With Infantile Hydrocephalus

This study investigates structural alterations of the corpus callosum in children diagnosed with infantile hydrocephalus. We aim to assess both macrostructural (volume) and microstructural (diffusion tensor imaging metrics) facets of the corpus callosum, providing insights into the nature and extent of alterations associated with this condition. Eighteen patients with infantile hydrocephalus (mean age = 9 years) and 18 age- and sex-matched typically developing healthy children participated in the study. Structural magnetic resonance imaging and diffusion tensor imaging were used to assess corpus callosum volume and microstructure, respectively. Our findings reveal significant alterations in corpus callosum volume, particularly in the posterior area, as well as distinct microstructural disparities, notably pronounced in these same segments. These results highlight the intricate interplay between macrostructural and microstructural aspects in understanding the impact of infantile hydrocephalus. Examining these structural alterations provides an understanding into the mechanisms underlying the effects of infantile hydrocephalus on corpus callosum integrity, given its pivotal role in interhemispheric communication. This knowledge offers a more nuanced perspective on neurologic disorders and underscores the significance of investigating the corpus callosum's health in such contexts.

Interaction Between a High-Fat Diet and Tau Pathology in Mice: Implications for Alzheimer's Disease

BACKGROUND

Obesity is a modifiable risk factor for Alzheimer's disease (AD). However, its relation with tau pathology (i.e., aberrant tau protein behavior in tauopathies such as AD) has been inconclusive.

OBJECTIVE

This study investigated the interaction between a high-fat diet (HFD) and tau pathology in adult male mice.

METHODS

Transgenic mice overexpressing human P301S Tau (those with the pathology) and wild-type (WT) littermates were subjected to behavioral tests, functional magnetic resonance imaging (fMRI), diffusion tensor imaging (DTI), and western blotting analysis to investigate the effects of prolonged HFD versus regular diet during adulthood.

RESULTS

HFD increased body weight in both WT and P301S mice but had minimal effect on blood glucose levels. The brain response to HFD was tau genotype-specific. WT mice exhibited decreased recognition memory and enhanced network connectivity in fMRI, while P301S mice exhibited white matter tract disorganization in DTI as the sole significant finding. The reduction of insulin receptor β, insulin downstream signaling, neuronal nuclear protein, CD68-positive phagocytic activity, and myelin basic protein level were confined to the cortex of WT mice. In contrast to P301S mice, WT mice showed significant changes in the tau protein and its phosphorylation levels along with increased soluble neurofilament light levels in the hippocampus.

CONCLUSIONS

HFD-induced brain dysfunction and pathological changes were blunted in mice with the pathology and more profound in healthy mice. Our findings highlight the need to consider this interaction between obesity and tau pathology when tailoring treatment strategies for AD and other tauopathies.