Diffusion Magnetic Resonance Imaging Research Articles

Prognostic value of preoperative diffusion restriction in glioblastoma.

Although glioblastoma (GBM) has a very poor prognosis, overall survival (OS) in treated patients shows great difference varying from few days to several months. Identifying factors explaining this difference would improve management of patient treatment. To determine the relevance of diffusion restriction in newly diagnosed treatment-naïve GBM patients. Preoperative magnetic resonance scans of 33 patients with GBM were reviewed. Regions of interest including all the T2 hyperintense lesion were drawn on diffusion weighted B0 images and transferred to the apparent diffusion coefficient (ADC) map. For each patient, a histogram displaying the ADC values within in the regions of interest was generated. Volumetric parameters including tumor regions with restricted diffusion, parameters derived from histogram and mean ADC value of the tumor were calculated. Their relationship with OS was analyzed. Patients with mean ADC value < 1415x10-6 mm2/s had a significantly shorter OS (p=0.021). Among volumetric parameters, the percentage of volume within T2 lesion with a normalized ADC value <1.5 times that in white matter was significantly associated with OS (p=0.0045). Patients with a percentage>23.92% had a shorter OS. Among parameters derived from histogram, the 50th percentile showed a trend towards significance for OS (p=0.055) with patients living longer when having higher values of 50th percentile. A difference in OS was observed between patients according to ADC peak of histogram but this difference did not reach statistical significance (p=0.0959). Diffusion magnetic resonance imaging may provide useful information for predicting GBM prognosis.

DCP: A pipeline toolbox for diffusion connectome.

The brain structural network derived from diffusion magnetic resonance imaging (dMRI) reflects the white matter connections between brain regions, which can quantitatively describe the anatomical connection pattern of the entire brain. The development of structural brain connectome leads to the emergence of a large number of dMRI processing packages and network analysis toolboxes. However, the fully automated network analysis based on dMRI data remains challenging. In this study, we developed a cross-platform MATLAB toolbox named "Diffusion Connectome Pipeline" (DCP) for automatically constructing brain structural networks and calculating topological attributes of the networks. The toolbox integrates a few developed packages, including FSL, Diffusion Toolkit, SPM, Camino, MRtrix3, and MRIcron. It can process raw dMRI data collected from any number of participants, and it is also compatible with preprocessed files from public datasets such as HCP and UK Biobank. Moreover, a friendly graphical user interface allows users to configure their processing pipeline without any programming. To prove the capacity and validity of the DCP, two tests were conducted with using DCP. The results showed that DCP can reproduce the findings in our previous studies. However, there are some limitations of DCP, such as relying on MATLAB and being unable to fixel-based metrics weighted network. Despite these limitations, overall, the DCP software provides a standardized, fully automated computational workflow for white matter network construction and analysis, which is beneficial for advancing future human brain connectomics application research.

Microstructural integrity of the locus coeruleus and its tracts reflect noradrenergic degeneration in Alzheimer’s disease and Parkinson’s disease

BackgroundDegeneration of the locus coeruleus (LC) noradrenergic system contributes to clinical symptoms in Alzheimer’s disease (AD) and Parkinson’s disease (PD). Diffusion magnetic resonance imaging (MRI) has the potential to evaluate the integrity of the LC noradrenergic system. The aim of the current study was to determine whether the diffusion MRI-measured integrity of the LC and its tracts are sensitive to noradrenergic degeneration in AD and PD.MethodsPost-mortem in situ T1-weighted and multi-shell diffusion MRI was performed for 9 AD, 14 PD, and 8 control brain donors. Fractional anisotropy (FA) and mean diffusivity were derived from the LC, and from tracts between the LC and the anterior cingulate cortex, the dorsolateral prefrontal cortex (DLPFC), the primary motor cortex (M1) or the hippocampus. Brain tissue sections of the LC and cortical regions were obtained and immunostained for dopamine-beta hydroxylase (DBH) to quantify noradrenergic cell density and fiber load. Group comparisons and correlations between outcome measures were performed using linear regression and partial correlations.ResultsThe AD and PD cases showed loss of LC noradrenergic cells and fibers. In the cortex, the AD cases showed increased DBH + immunoreactivity in the DLPFC compared to PD cases and controls, while PD cases showed reduced DBH + immunoreactivity in the M1 compared to controls. Higher FA within the LC was found for AD, which was correlated with loss of noradrenergic cells and fibers in the LC. Increased FA of the LC-DLPFC tract was correlated with LC noradrenergic fiber loss in the combined AD and control group, whereas the increased FA of the LC-M1 tract was correlated with LC noradrenergic neuronal loss in the combined PD and control group. The tract alterations were not correlated with cortical DBH + immunoreactivity.ConclusionsIn AD and PD, the diffusion MRI-detected alterations within the LC and its tracts to the DLPFC and the M1 were associated with local noradrenergic neuronal loss within the LC, rather than noradrenergic changes in the cortex.

Diagnostic value of Video Electroencephalography combined with Magnetic Resonance Imaging-diffusion tensor imaging in epilepsy.

To explore the diagnostic value of video electroencephalography (VEEG) combined with magnetic resonance imaging diffusion tensor imaging (MRI-DTI) in epilepsy. In this retrospective observational study, clinical data of 60 patients who underwent both VEEG and MRI examinations at the Neurosurgery Department of Quzhou People's Hospital from December 2020 to March 2023 were retrospectively reviewed, and a total of 55 patients were finally included. We evaluated the diagnostic value of combining VEEG and MRI to determine seizure type, location of epileptic focus, and structural abnormalities of brain tissue, using surgical and pathological results as the gold standard. The accuracy of the combined approach for determining the seizure type was 98.18%, which was higher than the accuracy of MRI (85.45%, P<0.05) or VEEG (81.82%, P<0.05) alone. The accuracy of joint examination for lesion location was 100.00%, which was higher than those of MRI (85.45%, P<0.05) or VEEG (83.64%, P<0.05) alone. Similar abnormal brain tissue structure detection rates was found for both MRI and VEEG (P>0.05). The application of MRI-DTI combined with VEEG to diagnose patients with epilepsy allows for the identification of abnormal structural changes in brain and the location of lesions. Combining both approaches can improve the diagnostic accuracy of each technique alone and provide a reference for the formulation and adjustment of disease management plans.

Influence of preprocessing, distortion correction and cardiac triggering on the quality of diffusion MR images of spinal cord

Diffusion MRI of the spinal cord (SC) is susceptible to geometric distortion caused by field inhomogeneities, and prone to misalignment across time series and signal dropout caused by biological motion. Several modifications of image acquisition and image processing techniques have been introduced to overcome these artifacts, but their specific benefits are largely unproven and warrant further investigations. We aim to evaluate two specific aspects of image acquisition and processing that address image quality in diffusion studies of the spinal cord: susceptibility corrections to reduce geometric distortions, and cardiac triggering to minimize motion artifacts. First, we evaluate 4 distortion preprocessing strategies on 7 datasets of the cervical and lumbar SC and find that while distortion correction techniques increase geometric similarity to structural images, they are largely driven by the high-contrast cerebrospinal fluid, and do not consistently improve the geometry within the cord nor improve white-to-gray matter contrast. We recommend at a minimum to perform bulk-motion correction in preprocessing and posit that improvements/adaptations are needed for spinal cord distortion preprocessing algorithms, which are currently optimized and designed for brain imaging. Second, we design experiments to evaluate the impact of removing cardiac triggering. We show that when triggering is foregone, images are qualitatively similar to triggered sequences, do not have increased prevalence of artifacts, and result in similar diffusion tensor indices with similar reproducibility to triggered acquisitions. When triggering is removed, much shorter acquisitions are possible, which are also qualitatively and quantitatively similar to triggered sequences. We suggest that removing cardiac triggering for cervical SC diffusion can be a reasonable option to save time with minimal sacrifice to image quality.

Restricted diffusion characteristics in oscillating gradient spin echo with mesoscopic phantom

In diffusion magnetic resonance imaging, oscillating gradient spin echo (OGSE) has an extremely short diffusion time if motion probing gradient (MPG) is applied to the waveform. Further, it can detect microstructural specificity. OGSE changes sensitivity to spin displacement velocity based on the MPG phase. The current study aimed to investigate the restricted diffusion characteristics of each OGSE waveform using the capillary phantom with various b-values, frequencies, and MPG phases. We performed OGSE (b-value = 300, 500, 800, 1200, 1600, and 2000 s/mm2) for the sine and cosine waveforms using the capillary phantom (6, 12, 25, 50, and 100 μm and free water) with a 9.4-T experimental magnetic resonance imaging system and a solenoid coil. We evaluated the axial and radial diffusivity (AD, RD) of each structure size. The output current of the MPG was assessed with an oscilloscope and analyzed with the gradient modulation power spectra by fast Fourier transform.In sine, the sidelobe spectrum was enhanced with increasing frequency, and the central spectrum slightly increased. The difference in RD was detected at 6 and 12 μm; however, it did not depend on the structure scale at 50 or 100 μm and free water. In cosine, the diffusion spectrum was enhanced, whereas the central spectrum decreased with increasing frequency. Both AD and RD in cosine had a frequency dependence, and AD and RD increased with a higher frequency regardless of structure size. AD and RD in either sine or cosine had no evident b-value dependence. We evaluated the OGSE-restricted diffusion characteristics. The measurements obtained diffusion information similar to the pulsed gradient spin echo. Hence, the cosine measurements indicated that a higher frequency could capture faster diffusion within the diffusion phenomena.

Brain asymmetries from mid- to late life and hemispheric brain age

The human brain demonstrates structural and functional asymmetries which have implications for ageing and mental and neurological disease development. We used a set of magnetic resonance imaging (MRI) metrics derived from structural and diffusion MRI data in N=48,040 UK Biobank participants to evaluate age-related differences in brain asymmetry. Most regional grey and white matter metrics presented asymmetry, which were higher later in life. Informed by these results, we conducted hemispheric brain age (HBA) predictions from left/right multimodal MRI metrics. HBA was concordant to conventional brain age predictions, using metrics from both hemispheres, but offers a supplemental general marker of brain asymmetry when setting left/right HBA into relationship with each other. In contrast to WM brain asymmetries, left/right discrepancies in HBA are lower at higher ages. Our findings outline various sex-specific differences, particularly important for brain age estimates, and the value of further investigating the role of brain asymmetries in brain ageing and disease development.

Abstract 109: Towards Individualised Prediction of Neurodevelopmental Outcomes After Neonatal Stroke: A Brain Lesion Network Mapping Study Leveraging Large-Scale Datasets

Introduction: Prediction of adverse neurodevelopmental outcomes after neonatal arterial ischemic stroke (NAIS) is challenging. We identified brain regions functionally connected to stroke lesions (lesion networks), and investigated whether such lesion networks are related to the development of cerebral palsy (CP) after NAIS. Methods: We performed a novel lesion network mapping approach, involving: 1. Creation of a normative connectome using the developing Human Connectome Project (dHCP) dataset. Resting state functional magnetic resonance imaging (MRI) scans of 518 neonates born at term (&gt;36 weeks) from the dHCP were aligned to a template, built from T 2 -weighted scans of the same neonates; 2. Manual segmentation of lesions using diffusion MRI scans of 85 term-born neonates with NAIS, who were identified from Australian and Swiss pediatric stroke registries. Lesion masks were aligned to the template; 3. Construction of lesion network maps, by computing functional correlations between lesion masks and other brain grey matter regions, making use of the normative connectome; 4. Investigation of relationships between lesion networks and CP, diagnosed by clinical examination at least 18 months after NAIS. Lesion network maps were compared between those who did (n=28) and did not (n=57) develop CP after NAIS, with two sample t-tests. Results: In participants who developed CP after NAIS, lesions were more strongly functionally connected to the following regions: frontal (inferior and orbital frontal), temporal (pole, superior, and mesial temporal), insula, basal ganglia, thalamus and cerebellum (Figure 1). Conclusions: Leveraging large-scale datasets and innovative connectomic methods, we uncovered brain networks related to adverse outcomes after NAIS. This provided novel findings compared to past methods such as voxel-based lesion-symptom mapping. Our results point to differences in network vulnerabilities after stroke in neonates compared to adults.

Abstract WP136: Impaired Venous Outflow Impacts Functional Outcomes in Acute Small Subcortical Infarcts: A Single-Center Retrospective Analysis

Introduction: Acute small subcortical infarcts (SSI), colloquially acute lacunar stroke, are a radiographic diagnosis representing a myriad of pathophysiologic processes. One such pathophysiologic subgroup is venous collagenosis which serves as a pathologic indicator that aberrant venous outflow may contribute to SSI development. We aimed to identify whether impaired venous outflow (IVO) impacted functional outcomes in individuals presenting with SSI. Methods: We performed a single-center retrospective study of individuals who presented to the Rhode Island Hospital Comprehensive Stroke Center. Included individuals were ≥ 18 years with the diagnosis of SSI, as defined per consensus criteria, on brain MRI diffusion weighted imaging. The primary exposure is the presence of impaired venous outflow (IVO) defined radiologically in accordance with prior studies, as hyperintensity of the jugular, sigmoid, or transverse sinuses along the skull base on MR angiogram time of flight, Figure. The primary outcome was a favorable function outcome at hospital discharge defined as a modified Rankin Scale (mRS) of ≤ 3. Standard descriptive and regression statistical techniques were used for data interpretation. Results: We identified 39 patients who met criteria with 12 (30.8%) with IVO. Age and vascular risk factors did not significantly differ amongst the cohort. Twenty-six (66.7%) had a favorable hospital discharge outcome favorable functional outcome with IVO being less common [IVO present: 5/26 (19.2%) versus LVO absent: 21/26, (80.8%), p = 0.034]]. After adjusting for age and hypertension, IVO was associated with an odds ratio of 8.33 (95%CI 1.41-49.3, p =0.019). Conclusion: We found that IVO may be an independent contributor to fewer favorable functional outcomes. This data highlights that not only the arterial vessels are of relevance in acute SSI.

Decreased uncinate fasciculus integrity in functional seizures following traumatic brain injury.

The uncinate fasciculus (UF) has been implicated previously in contributing to the pathophysiology of functional (nonepileptic) seizures (FS). FS are frequently preceded by adverse life events (ALEs) and present with comorbid psychiatric symptoms, yet neurobiological correlates of these factors remain unclear. To address this gap, using advanced diffusion magnetic resonance imaging (dMRI), UF tracts in a large cohort of patients with FS and pre-existing traumatic brain injury (TBI + FS) were compared to those in patients with TBI without FS (TBI-only). We hypothesized that dMRI measures in UF structural connectivity would reveal UF differences when controlling for TBI status. Partial correlation tests assessed the potential relationships with psychiatric symptom severity measures. Participants with TBI-only (N = 46) and TBI + FS (N = 55) completed a series of symptom questionnaires and MRI scanning. Deterministic tractography via diffusion spectrum imaging (DSI) was implemented in DSI studio (https://dsi-studio.labsolver.org) with q-space diffeomorphic reconstruction (QSDR), streamline production, and manual segmentation to assess bilateral UF integrity. Fractional anisotropy (FA), radial diffusivity (RD), streamline counts, and their respective asymmetry indices (AIs) served as estimates of white matter integrity. Compared to TBI-only, TBI + FS participants demonstrated decreased left hemisphere FA and RD asymmetry index (AI) for UF tracts (both p < .05, false discovery rate [FDR] corrected). Additionally, TBI + FS reported higher symptom severity in depression, anxiety, and PTSD measures (all p < .01). Correlation tests comparing UF white matter integrity differences to psychiatric symptom severity failed to reach criteria for significance (all p > .05, FDR corrected). In a large, well-characterized sample, participants with FS had decreased white matter health after controlling for the history of TBI. Planned follow-up analysis found no evidence to suggest that UF connectivity measures are a feature of group differences in mood or anxiety comorbidities for FS. These findings suggest that frontolimbic structural connectivity may play a role in FS symptomology, after accounting for prior ALEs and comorbid psychopathology severity.

Fibre orientation atlas guided rapid segmentation of white matter tracts.

Fibre tract delineation from diffusion magnetic resonance imaging (MRI) is a valuable clinical tool for neurosurgical planning and navigation, as well as in research neuroimaging pipelines. Several popular methods are used for this task, each with different strengths and weaknesses making them more or less suited to different contexts. For neurosurgical imaging, priorities include ease of use, computational efficiency, robustness to pathology and ability to generalise to new tracts of interest. Many existing methods use streamline tractography, which may require expert neuroimaging operators for setting parameters and delineating anatomical regions of interest, or suffer from as a lack of generalisability to clinical scans involving deforming tumours and other pathologies. More recently, data-driven approaches including deep-learning segmentation models and streamline clustering methods have improved reproducibility and automation, although they can require large amounts of training data and/or computationally intensive image processing at the point of application. We describe an atlas-based direct tract mapping technique called 'tractfinder', utilising tract-specific location and orientation priors. Our aim was to develop a clinically practical method avoiding streamline tractography at the point of application while utilising prior anatomical knowledge derived from only 10-20 training samples. Requiring few training samples allows emphasis to be placed on producing high quality, neuro-anatomically accurate training data, and enables rapid adaptation to new tracts of interest. Avoiding streamline tractography at the point of application reduces computational time, false positives and vulnerabilities to pathology such as tumour deformations or oedema. Carefully filtered training streamlines and track orientation distribution mapping are used to construct tract specific orientation and spatial probability atlases in standard space. Atlases are then transformed to target subject space using affine registration and compared with the subject's voxel-wise fibre orientation distribution data using a mathematical measure of distribution overlap, resulting in a map of the tract's likely spatial distribution. This work includes extensive performance evaluation and comparison with benchmark techniques, including streamline tractography and the deep-learning method TractSeg, in two publicly available healthy diffusion MRI datasets (from TractoInferno and the Human Connectome Project) in addition to a clinical dataset comprising paediatric and adult brain tumour scans. Tract segmentation results display high agreement with established techniques while requiring less than 3 min on average when applied to a new subject. Results also display higher robustness than compared methods when faced with clinical scans featuring brain tumours and resections. As well as describing and evaluating a novel proposed tract delineation technique, this work continues the discussion on the challenges surrounding the white matter segmentation task, including issues of anatomical definitions and the use of quantitative segmentation comparison metrics.

"Pscore": A Novel Percentile-Based Metric to Accurately Assess Individual Deviations in Non-Gaussian Distributions of Quantitative MRI Metrics.

Quantitative magnetic resonance imaging (MRI) metrics could be used in personalized medicine to assess individuals against normative distributions. Conventional Zscore analysis is inadequate in the presence of non-Gaussian distributions. Therefore, if quantitative MRI metrics deviate from normality, an alternative is needed. To confirm non-Gaussianity of diffusion MRI (dMRI) metrics on a publicly available dataset, and to propose a novel percentile-based method, "Pscore" to address this issue. Retrospective cohort. Nine hundred and sixty-one healthy young adults (age: 22-35 years, females: 53%) from the Human Connectome Project. 3-T, spin-echo diffusion echo-planar imaging, T1-weighted: MPRAGE. The dMRI data were preprocessed using the TORTOISE pipeline. Forty-eight regions of interest (ROIs) from the JHU atlas were redrawn on a study-specific diffusion tensor (DT) template and average values were computed from various DT and mean apparent propagator (MAP) metrics. For each ROI, percentile ranks across participants were computed to generate "Pscores"-which normalized the difference between the median and a participant's value with the corresponding difference between the median and the 5th/95th percentile values. ROI-wise distributions were assessed using log transformations, Zscore, and the "Pscore" methods. The percentages of extreme values above-95th and below-5th percentile boundaries (PEV>95(%), PEV<5(%)) were also assessed in the overall white matter. Bootstrapping was performed to test the reliability of Pscores in small samples (N = 100) using 100 iterations. The dMRI metric distributions were systematically non-Gaussian, including positively skewed (eg, mean and radial diffusivity) and negatively skewed (eg, fractional and propagator anisotropy) metrics. This resulted in unbalanced tails in Zscore distributions (PEV>95 ≠ 5%, PEV<5 ≠ 5%) whereas "Pscore" distributions were symmetric and balanced (PEV>95 = PEV<5 = 5%); even for small bootstrapped samples (average [SD]). The inherent skewness observed for dMRI metrics may preclude the use of conventional Zscore analysis. The proposed "Pscore" method may help estimating individual deviations more accurately in skewed normative data, even from small datasets. 1 TECHNICAL EFFICACY: Stage 1.

Elucidating Multimodal Imaging Patterns in Accelerated Brain Aging: Heterogeneity through a Discriminant Analysis Approach Using the UK Biobank Dataset.

Accelerated brain aging (ABA) intricately links with age-associated neurodegenerative and neuropsychiatric diseases, emphasizing the critical need for a nuanced exploration of heterogeneous ABA patterns. This investigation leveraged data from the UK Biobank (UKB) for a comprehensive analysis, utilizing structural magnetic resonance imaging (sMRI), diffusion magnetic resonance imaging (dMRI), and resting-state functional magnetic resonance imaging (rsfMRI) from 31,621 participants. Pre-processing employed tools from the FMRIB Software Library (FSL, version 5.0.10), FreeSurfer, DTIFIT, and MELODIC, seamlessly integrated into the UKB imaging processing pipeline. The Lasso algorithm was employed for brain-age prediction, utilizing derived phenotypes obtained from brain imaging data. Subpopulations of accelerated brain aging (ABA) and resilient brain aging (RBA) were delineated based on the error between actual age and predicted brain age. The ABA subgroup comprised 1949 subjects (experimental group), while the RBA subgroup comprised 3203 subjects (control group). Semi-supervised heterogeneity through discriminant analysis (HYDRA) refined and characterized the ABA subgroups based on distinctive neuroimaging features. HYDRA systematically stratified ABA subjects into three subtypes: SubGroup 2 exhibited extensive gray-matter atrophy, distinctive white-matter patterns, and unique connectivity features, displaying lower cognitive performance; SubGroup 3 demonstrated minimal atrophy, superior cognitive performance, and higher physical activity; and SubGroup 1 occupied an intermediate position. This investigation underscores pronounced structural and functional heterogeneity in ABA, revealing three subtypes and paving the way for personalized neuroprotective treatments for age-related neurological, neuropsychiatric, and neurodegenerative diseases.

Diagnosis of dysthyroid optic neuropathy: combined value of orbital MRI and intracranial visual pathway diffusion kurtosis imaging.

To evaluate the combined performance of orbital MRI and intracranial visual pathway diffusion kurtosis imaging (DKI) in diagnosing dysthyroid optic neuropathy (DON). We retrospectively enrolled 61 thyroid-associated ophthalmopathy (TAO) patients, including 25 with DON (40 eyes) and 36 without DON (72 eyes). Orbital MRI-based apical muscle index (MI), diameter index (DI) of the optic nerve (ON), area index (AI) of the ON, apparent diffusion coefficient (ADC) and signal intensity ratio (SIR) of the ON, DKI-based kurtosis fractional anisotropy (KFA) and mean kurtosis (MK) of the optic tract (OT), optic radiation (OR), and Brodmann areas (BAs) 17, 18, and 19 were measured and compared between groups. The diagnostic performances of models were evaluated using receiver operating characteristic curve analyses and compared using the DeLong test. TAO patients with DON had significantly higher apical MI, apical AI, and SIR of the ON, but significantly lower ADC of the ON than those without DON (p < 0.05). Meanwhile, the DON group exhibited significantly lower KFA across the OT, OR, BA17, BA18, and BA19 and lower MK at the OT and OR than the non-DON group (p < 0.05). The model integrating orbital MRI and intracranial visual pathway DKI parameters performed the best in diagnosing DON (AUC = 0.926), with optimal diagnostic sensitivity (80%) and specificity (94.4%), followed by orbital MRI combination (AUC = 0.890), and then intracranial visual pathway DKI combination (AUC = 0.832). Orbital MRI and intracranial visual pathway DKI can both assist in diagnosing DON. Combining orbital and intracranial imaging parameters could further optimize diagnostic efficiency. The novel finding could bring novel insights into the precise diagnosis and treatment of dysthyroid optic neuropathy, accordingly, contributing to the improvement of the patients' prognosis and quality of life in the future. • Orbital MRI and intracranial visual pathway diffusion kurtosis imaging can both assist in diagnosing dysthyroid optic neuropathy. • Combining orbital MRI and intracranial visual pathway diffusion kurtosis imaging optimized the diagnostic efficiency of dysthyroid optic neuropathy.

A matched case-control study of early cervical spondylotic myelopathy based on diffusion magnetic resonance imaging

BackgroundEarly cervical spondylotic myelopathy (CSM) is challenging to diagnose and easily missed. Diffusion MRI (dMRI) has the potential to identify early CSM.MethodsUsing diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), and neurite orientation dispersion and density imaging (NODDI), a 1:1 matched case-control study was conducted to evaluate the potential of dMRI in identifying early CSM and assessing uncompressed segments of CSM patients. CSM patients and volunteers were matched by age and spinal location. The differences in dMRI parameters between groups were assessed by the paired t-test, the multicollinearity of the dMRI parameters was evaluated by the variance inflation factor (VIF), and the value of dMRI parameters in distinguishing controls from CSM patients was determined by logistic regression. The univariate t-test was used to analyse differences between CSM patients and volunteers in adjacent uncompressed areas.ResultsIn total, 56 CSM patients and 56 control volunteers were included. Paired t-tests revealed significant differences in nine dMRI parameters between groups. Multicollinearity calculated through VIF and combined with logistic regression showed that the orientation division index (ODI) was significantly positively correlated (r = 2.12, p = 0.035), and the anisotropic water fraction (AWF) was significantly negatively correlated (r = −0.98, p = 0.015). The fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), isotropic volume fraction (ISOVF), ODI, and AWF were significantly different in the upper and lower uncompressed areas at all ages.ConclusiondMRI can noninvasively identify early CSM patients and potentially identify the extent of CSM lesions involving the cervical spinal cord.Critical relevance statementDiffusion MRI (dMRI) can identify early cervical spondylotic myelopathy (CSM) and has the potential to help determine the extent of CSM involvement. The application of dMRI can help screen for early CSM and develop clinical surgical and rehabilitation treatment plans.Key points• Diffusion MRI can differentiate between normal and early-stage cervical spondylotic myelopathy patients.• Diffusion MRI has the ability to identify the extent of spinal cord involvement in cervical spondylotic myelopathy.• Diffusion MRI enables the early screening of cervical spondylotic myelopathy and helps guide clinical treatment.Graphical

Baseline Structural Connectomics Data of Healthy Brain Development Assessed with Multi-Modal Magnetic Resonance Imaging

Diffusion magnetic resonance imaging (MRI) tractography is a powerful tool for non-invasively studying brain architecture and structural integrity by inferring fiber tracts based on water diffusion profiles. This study provided a thorough set of baseline data of structural connectomics biomarkers for 809 healthy participants between the ages of 1 and 35 years. The data provided can help to identify potential biomarkers that may be helpful in characterizing physiological and anatomical neurodevelopmental changes linked with healthy brain maturation and can be used as a baseline for comparing abnormal and pathological development in future studies. Our results demonstrate statistically significant differences between the sexes, representing a potentially important baseline from which to establish healthy growth trajectories. Biomarkers that correlated with age, potentially representing useful methods for assessing brain development, are also presented. This baseline information may facilitate studies that identify abnormal brain development associated with a variety of pathological conditions as departures from healthy sex-specific age-dependent neural development. Our findings are the result of combining the use of mainstream analytic methods with in-house-developed open-source software to help facilitate reproducible analyses, inclusive of many potential biomarkers that cannot be derived from existing software packages. Assessing relationships between our identified regional tract measurements produced by our technology and participant characteristics/phenotypic data in future analyses has tremendous potential for the study of human neurodevelopment.

Microvascular Dysfunction and Whole-Brain White Matter Connectivity: The Maastricht Study.

Microvascular dysfunction is involved in the development of various cerebral disorders. It may contribute to these disorders by disrupting white matter tracts and altering brain connectivity, but evidence is scarce. We investigated the association between multiple biomarkers of microvascular function and whole-brain white matter connectivity. Cross-sectional data from The Maastricht Study, a Dutch population-based cohort (n=4326; age, 59.4±8.6 years; 49.7% women). Measures of microvascular function included urinary albumin excretion, central retinal arteriolar and venular calibers, composite scores of flicker light-induced retinal arteriolar and venular dilation, and plasma biomarkers of endothelial dysfunction (intercellular adhesion molecule-1, vascular cell adhesion molecule-1, E-selectin, and von Willebrand factor). White matter connectivity was calculated from 3T diffusion magnetic resonance imaging to quantify the number (average node degree) and organization (characteristic path length, global efficiency, clustering coefficient, and local efficiency) of white matter connections. A higher plasma biomarkers of endothelial dysfunction composite score was associated with a longer characteristic path length (β per SD, 0.066 [95% CI, 0.017-0.114]) after adjustment for sociodemographic, lifestyle, and cardiovascular factors but not with any of the other white matter connectivity measures. After multiple comparison correction, this association was nonsignificant. None of the other microvascular function measures were associated with any of the connectivity measures. These findings suggest that microvascular dysfunction as measured by indirect markers is not associated with whole-brain white matter connectivity.

Disrupted Maturation of White Matter Microstructure After Concussion Is Associated With Internalizing Behavior Scores in Female Children

BackgroundSome children who experience concussions, particularly females, develop long-lasting emotional and behavioral problems. Establishing the potential contribution of preexisting behavioral problems and disrupted white matter maturation has been challenging due to a lack of preinjury data. MethodsFrom the Adolescent Brain Cognitive Development cohort, 239 (90 female) children age 12.1 ± 0.6 years who experienced a concussion after study entry at 10.0 ± 0.6 years were compared to 6438 (3245 female) children without head injuries who were age 9.9 ± 0.6 years at baseline and 12.0 ± 0.6 years at follow-up. The Child Behavior Checklist was used to assess internalizing and externalizing behavior at study entry and follow-up. In the children with magnetic resonance imaging data available (concussion n = 134, comparison n = 3520), deep and superficial white matter was characterized by neurite density from restriction spectrum image modeling of diffusion magnetic resonance imaging. Longitudinal ComBat harmonization removed scanner effects. Linear regressions modeled 1) behavior problems at follow-up controlling for baseline behavior, 2) impact of concussion on white matter maturation, and 3) contribution of deviations in white matter maturation to postconcussion behavior problems. ResultsOnly female children with concussion had higher internalizing behavior problem scores. The youngest children with concussion showed less change in superficial white matter neurite density over 2 years than children with no concussion. In females with concussion, less change in superficial white matter neurite density was correlated with increased internalizing behavior problem scores. ConclusionsConcussions in female children are associated with emotional problems beyond preinjury levels. Injury to superficial white matter may contribute to persistent internalizing behavior problems in females.

Free-water diffusion magnetic resonance imaging under selegiline treatment in Parkinson's disease

IntroductionMonoamine oxidase type B inhibitors, including selegiline, are established as anti-Parkinsonian Drugs. Inhibition of monoamine oxidase type B enzymes might suppress the inflammation because of inhibition to generate reactive oxygen species. However, its effect on brain microstructure remains unclear. The aim of this study is to elucidate white matter and substantia nigra (SN) microstructural differences between Patients with Parkinson's disease with and without selegiline treatment by two independently recruited cohorts. MethodsDiffusion tensor imaging and free water imaging indices of WM and SN were compared among 22/15 Patients with Parkinson's disease with selegiline (PDselegiline(+)), 33/23 Patients with Parkinson's disease without selegiline (PDselegiline(−)), and 25/20 controls, in the first/second cohorts. Two cohorts were analyzed with different MRI protocols. ResultsDiffusion tensor imaging and free-water indices of major white matter tracts were significantly differed between the PDselegiline(−) and controls in both cohorts, although not between the PDselegiline(+) and controls except for restricted areas. Compared with the PDselegiline(+), free-water was significantly higher in the PDselegiline(−) in the inferior fronto-occipital fasciculus, superior longitudinal fasciculus, and superior and posterior corona radiata (first cohort) and the forceps major and splenium of the corpus callosum (second cohort). There were no significant differences in free-water of anterior or posterior substantia nigra between PDselegiline(+) and PDselegiline(−). ConclusionsSelegiline treatment might reduce the white matter microstructural abnormalities detected by free-water imaging in Parkinson's disease.

The glymphatic system as a potential biomarker and therapeutic target in secondary progressive multiple sclerosis

BackgroundMultiple sclerosis (MS) is a refractory immune-mediated inflammatory disease of the central nervous system, and some cases of the major subtype, relapsing-remitting (RR), transition to secondary progressive (SP). However, the detailed pathogenesis, biomarkers, and effective treatment strategies for secondary progressive multiple sclerosis have not been established. The glymphatic system, which is responsible for waste clearance in the brain, is an intriguing avenue for investigation and is primarily studied through diffusion tensor image analysis along the perivascular space (DTI-ALPS). This study aimed to compare DTI-ALPS indices between patients with RRMS and SPMS to uncover potential differences in their pathologies and evaluate the utility of the glymphatic system as a possible biomarker. MethodsA cohort of 26 patients with MS (13 RRMS and 13 SPMS) who met specific criteria were enrolled in this prospective study. Magnetic resonance imaging (MRI), including diffusion MRI, 3D T1-weighted imaging, and relaxation time quantification, was conducted. The ALPS index, a measure of glymphatic function, was calculated using diffusion-weighted imaging data. Demographic variables, MRI metrics, and ALPS indices were compared between patients with RRMS and those with SPMS. ResultsThe ALPS index was significantly lower in the SPMS group. Patients with SPMS exhibited longer disease duration and higher Expanded Disability Status Scale (EDSS) scores than those with RRMS. Despite these differences, the correlations between the EDSS score, disease duration, and ALPS index were minimal, suggesting that the impact of these clinical variables on ALPS index variations was negligible. DiscussionOur study revealed the potential microstructural and functional differences between RRMS and SPMS related to glymphatic system impairment. Although disease severity and duration vary among subtypes, their influence on ALPS index differences appears to be limited. This highlights the stronger association between SP conversion and changes in the ALPS index. These findings align with those of previous research, indicating the involvement of the glymphatic system in the progression of MS. ConclusionAlthough the causality remains uncertain, our study suggests that a reduced ALPS index, reflecting glymphatic system dysfunction, may contribute to MS progression, particularly in SPMS. This suggests the potential of the ALPS index as a diagnostic biomarker for SPMS and underscores the potential of the glymphatic system as a therapeutic target to mitigate MS progression. Future studies with larger cohorts and pathological validation are necessary to confirm these findings. This study provides new insights into the pathogenesis of SPMS and the potential for innovative therapeutic strategies.