Shape analysis of the human association pathways

Loss of white matter tracts and persistent microglial activation in the chronic phase of ischemic stroke in female rats and the effect of miR-20a-3p treatment

Our previous studies showed that intravenous injections of the small non-coding RNA mir-20a-3p is neuroprotective for stroke in the acute phase and attenuates long-term cognitive impairment in middle-aged female rats. In this study, we evaluated postmortem brain pathology at 100+d after stroke in a set of behaviorally characterized animals. This included Sham (no stroke) controls or stroke animals that received either mir20a-3p at 4h, 24h and 70d iv post stroke (MCAo+mir20a-3p) or a scrambled oligo (MCAo+Scr). Brain volumetric features were analyzed with T2 weighted and Diffusion Tensor magnetic resonance imaging (MRI) followed by histological analysis. Principal component analysis of Fractional Anisotropy (FA)-diffusion tensor MRI measures showed that MCAo+Scr and MCAo+mir20a-3p groups differed significantly in the volume of white matter but not gray matter. Weil myelin-stained sections confirmed decreased volume of the corpus callosum, internal capsule and the anterior commissure in the ischemic hemisphere of MCAo+Scr animals compared to the non-ischemic hemisphere, while sham and MCAo+Mir-20a-3p showed no hemispheric asymmetries. The MCAo+Scr group also exhibited asymmetry in hemisphere and lateral ventricle volumes, with ventricular enlargement in the ischemic hemisphere as compared to the non-ischemic hemisphere. The numbers of microglia were significantly elevated in white matter tracts in the MCAo+Scr group, with a trend towards increased myelin phagocytic microglia in these tracts. Regression analysis indicated that performance on an episodic memory test (novel object recognition test; NORT) was associated with decreased white matter volume and increased microglial numbers. These data support the hypothesis that stroke-induced cognitive impairment is accompanied by white matter attrition and persistent microglial activation and is consistent with reports that cognitive deterioration resulting from vascular diseases, such as stroke, is associated with secondary neurodegeneration in regions distal from the initial infarction.

Differential tractography identifies a distinct pattern of white matter alterations in essential tremor with or without resting tremor

Essential Tremor (ET) is characterized by action tremor often associated with resting tremor (rET). Although previous studies have identified widespread brain white matter (WM) alterations in ET patients, differences between ET and rET have been less explored. In this study we employed differential tractography to investigate WM microstructural alterations in these tremor disorders. We conducted a Diffusion Tensor Imaging (DTI) study on age- and sex-matched cohorts: 25 healthy controls (HC), 30 ET, and 30 rET patients. Differential tractography using DSI Studio was employed to pairwise compare fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) among cohorts. ET and rET patients compared to HC exhibited similar widespread MD increase especially in basal ganglia and brainstem projections. WM changes were more pronounced in the left cerebral hemisphere and cerebellum (crus I and II) in ET, while in rET patients WM alterations were prevalent in right cerebral hemisphere and cerebellum crus I. Small FA decrease was found in rET but not in ET patients. ET patients showed changes in the left non-decussating dentato-rubro-thalamic tract (ndDRTT), whereas rET patients showed changes in both left ndDRTT and right decussating DRTT. In conclusion, our findings confirmed the DRTT involvement in essential tremor and demonstrated that ET and rET exhibited similar microstructural WM changes in the brain, with different hemispheric involvement-greater on the left side in ET and on the right side in rET-suggesting that these tremor disorders may be distinct subtypes of the same disease.

DTI fiber-tracking parameters adjacent to gliomas: the role of tract irregularity value in operative planning, resection, and outcome

PURPOSE

The goal of glioma surgery is maximal tumor resection associated with minimal post-operative morbidity. Diffusion tensor imaging-tractography/fiber tracking (DTI-FT) is a valuable white-matter (WM) visualization tool for diagnosis and surgical planning. Still, it assumes a descriptive role since the main DTI metrics and parameters showed several limitations in clinical use. New applications and quantitative measurements were recently applied to describe WM architecture that surround the tumor area. The brain adjacent tumor area (BAT) is defined as the region adjacent to the gross tumor volume, which contains signal abnormalities on T2-weighted or FLAIR sequences. The DTI-FT analysis of the BAT can be adopted as predictive values and a guide for safe tumor resection.

METHODS

This is an observational prospective study on an extensive series of glioma patients who performed magnetic resonance imaging (MRI) with pre-operative DTI-FT analyzed on the BAT by two different software. We examined DTI parameters of Fractional anisotropy (FA mean, min-max), Mean diffusivity (MD), and the shape-metric "tract irregularity" (TI) grade, comparing it with the surgical series' clinical, radiological, and outcome data.

RESULTS

The population consisted of 118 patients, with a mean age of 60.6 years. 82 patients suffering from high-grade gliomas (69.5%), and 36 from low-grade gliomas (30.5%). A significant inverse relationship exists between the FA mean value and grading (p = 0.001). The relationship appears directly proportional regarding MD values (p = 0.003) and TI values (p = 0.005). FA mean and MD values are susceptible to significant variations with tumor and edema volume (p = 0.05). TI showed an independent relationship with grading regardless of tumor radiological features and dimensions, with a direct relationship with grading, ki67% (p = 0,05), PFS (p < 0.001), and EOR (p < 0.01).

CONCLUSION

FA, MD, and TI are useful predictive measures of the clinical behavior of glioma, and TI could be helpful for tumor grading identification and surgical planning.

Regional differences in three-dimensional fiber organization, smooth muscle cell phenotype, and contractility in the pregnant mouse cervix

The orientation and function of smooth muscle in the cervix may contribute to the important biomechanical properties that change during pregnancy. Thus, this study examined the three-dimensional structure, smooth muscle phenotype, and mechanical and contractile functions of the upper and lower cervix of nongravid (not pregnant) and gravid (pregnant) mice. In gravid cervix, we uncovered region-specific changes in the structure and organization of fiber tracts. We also detected a greater proportion of contractile smooth muscle cells (SMCs), but an equal proportion of synthetic SMCs, in the upper versus lower cervix. Furthermore, we revealed that the lower cervix had infrequent spontaneous contractions, distension had a minimal effect on contractility, and the upper cervix had forceful contractions in response to labor-inducing agents (oxytocin and prostaglandin E2). These findings identify regional differences in cervix contractility related to contractile SMC content and fiber organization, which could be targeted with diagnostic technologies and for therapeutic intervention.

The Relationship between White Matter Architecture and Language Lateralization in the Healthy Brain

Interhemispheric anatomical differences have long been thought to be related to language lateralization. Previous studies have explored whether asymmetries in the diffusion characteristics of white matter language tracts are consistent with language lateralization. These studies, typically with smaller cohorts, yielded mixed results. This study investigated whether connectomic analysis of quantitative anisotropy (QA) and shape features of white matter tracts across the whole brain are associated with language lateralization. We analyzed 1,040 healthy individuals (562 females) from the Human Connectome Project database. Hemispheric language dominance for each participant was quantified using a laterality quotient (LQ) derived from fMRI activation in regions of interest (ROIs) associated with a language comprehension task compared against a math task. A linear regression model was used to examine the relationship between structural asymmetry and functional lateralization. Connectometry revealed a significant negative correlation between LQs and QA of corpus callosum tracts, indicating that higher QA in these regions is associated with bilateral and right hemisphere language representation in frontal and temporal regions. Left language laterality in the temporal lobe was significantly associated with longer right inferior fronto-occipital fasciculus (IFOF) and forceps minor tracts. These results suggest that diffusion measures of microstructural architecture as well as geometrical features of reconstructed white matter tracts play a role in language lateralization. People with increased dependence on the right or both frontal hemispheres for language processing may have more developed commissural fibers, which may support more efficient interhemispheric communication.

Changing the Paradigm for Tractography Segmentation in Neurosurgery: Validation of a Streamline-Based Approach

In glioma surgery, maximizing the extent of resection while preserving cognitive functions requires an understanding of the unique architecture of the white matter (WM) pathways of the single patient and of their spatial relationship with the tumor. Tractography enables the reconstruction of WM pathways, and bundle segmentation allows the identification of critical connections for functional preservation. This study evaluates the effectiveness of a streamline-based approach for bundle segmentation on a clinical dataset as compared to the traditional ROI-based approach. We performed bundle segmentation of the arcuate fasciculus, of its indirect anterior and posterior segments, and of the inferior fronto-occipital fasciculus in the healthy hemisphere of 25 high-grade glioma patients using both ROI- and streamline-based approaches. ROI-based segmentation involved manually delineating ROIs on MR anatomical images in Trackvis (V0.6.2.1). Streamline-based segmentations were performed in Tractome, which integrates clustering algorithms with the visual inspection and manipulation of streamlines. Shape analysis was conducted on each bundle. A paired t-test was performed on the irregularity measurement to compare segmentations achieved with the two approaches. Qualitative differences were evaluated through visual inspection. Streamline-based segmentation consistently yielded significantly lower irregularity scores (p < 0.001) compared to ROI-based segmentation for all the examined bundles, indicating more compact and accurate bundle reconstructions. Qualitative assessment identified common biases in ROI-based segmentations, such as the inclusion of anatomically implausible streamlines or streamlines with undesired trajectories. Streamline-based bundle segmentation with Tractome provides reliable and more accurate reconstructions compared to the ROI-based approach. By directly manipulating streamlines rather than relying on voxel-based ROI delineations, Tractome allows us to discern and discard implausible or undesired streamlines and to identify the course of WM bundles even when the anatomy is distorted by the lesion. These features make Tractome a robust tool for bundle segmentation in clinical contexts.

Gray Matter Reserve Modulates the Association between Glymphatic System Function and Cognition in Patients with Type 2 Diabetes Mellitus

INTRODUCTION

The glymphatic system is regarded as a key factor in the pathogenesis of neurodegenerative diseases. Given the heightened risk of cognitive impairment in patients with type 2 diabetes mellitus (T2DM), the possible alterations in the glymphatic system in T2DM patients remain to be explored. Diffusion tensor imaging (DTI) analysis along the perivascular space (ALPS) index can be utilized to model the glymphatic system in humans. Our aim was to explore the relationship between the ALPS index and cognitive function in patients with T2DM and whether this relationship is modulated by gray matter (GM) integrity anchored by the ALPS index.

METHODS

All participants underwent evaluation using a comprehensive cognitive assessment scale to determine their neurocognitive status. The ALPS index was calculated based on DTI data, and the disparity in ALPS index values between patients with T2DM and healthy controls (HCs) was examined. Furthermore, multiple linear regression analysis was conducted in the T2DM group to identify the GM regions associated with the ALPS index, and the volumes of the GM partitions were extracted. The volume of GM partitions was used as the regulating variable, the ALPS index was used as the independent variable, and cognitive test scores were used as the dependent variable in our analysis.

RESULTS

The ALPS index differed significantly between the two groups, and the ALPS index in patients with T2DM was significantly lower than that in HCs. In addition, our analysis revealed a correlation between the ALPS index and GM volume in the insular region, consistent with the observed GM atrophy in the patient cohort. Moreover, a significant negative correlation was observed between the ALPS index in patients and performance on the Trail-Making Test-A (TMT-A), and this relationship was moderated by GM integrity. In patients with more severe GM atrophy, the ALPS index was more strongly correlated with cognitive function.

CONCLUSIONS

In this study, a decreased ALPS index was found in T2DM patients, indicating impaired glymphatic function in this population. Furthermore, a significant association was detected between the ALPS index and cognitive performance in T2DM patients, and this correlation was influenced by GM integrity. Therefore, the ALPS index has the potential to be used as a biomarker of cognitive impairment in diabetic patients. Further studies are needed to investigate the diagnostic and therapeutic implications of glymphatic dysfunction in T2DM patients with cognitive impairment.

Ultrahigh-resolution 7-Tesla anatomic magnetic resonance imaging and diffusion tensor imaging of ex vivo formalin-fixed human brainstem-cerebellum complex

Introduction

Brain cross-sectional images, tractography, and segmentation are valuable resources for neuroanatomical education and research but are also crucial for neurosurgical planning that may improve outcomes in cerebellar and brainstem interventions. Although ultrahigh-resolution 7-Tesla (7T) magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) reveal such structural brain details in living or fresh unpreserved brain tissue, imaging standard formalin-preserved cadaveric brain specimens often used for neurosurgical anatomic studies has proven difficult. This study sought to develop a practical protocol to provide anatomic information and tractography results of an ex vivo human brainstem-cerebellum specimen.

Materials and methods

A protocol was developed for specimen preparation and 7T MRI with image postprocessing on a combined brainstem-cerebellum specimen obtained from an 85-year-old male cadaver with a postmortem interval of 1 week that was stored in formalin for 6 months. Anatomic image series were acquired for detailed views and diffusion tractography to map neural pathways and segment major anatomic structures within the brainstem and cerebellum.

Results

Complex white matter tracts were visualized with high-precision segmentation of crucial brainstem structures, delineating the brainstem-cerebellum and mesencephalic-dentate connectivity, including the Guillain-Mollaret triangle. Tractography and fractional anisotropy mapping revealed the complexities of white matter fiber pathways, including the superior, middle, and inferior cerebellar peduncles and visible decussating fibers. 3-dimensional (3D) reconstruction and quantitative and qualitative analyses verified the anatomical precision of the imaging relative to a standard brain space.

Discussion

This novel imaging protocol successfully captured the intricate 3D architecture of the brainstem-cerebellum network. The protocol, unique in several respects (including tissue preservation and rehydration times, choice of solutions, preferred sequences, voxel sizes, and diffusion directions) aimed to balance high resolution and practical scan times. This approach provided detailed neuroanatomical imaging while avoiding impractically long scan times. The extended postmortem and fixation intervals did not compromise the diffusion imaging quality. Moreover, the combination of time efficiency and ultrahigh-resolution imaging results makes this protocol a strong candidate for optimal use in detailed neuroanatomical studies, particularly in presurgical trajectory planning.

Global changes in the pattern of connectivity in developmental prosopagnosia

Developmental prosopagnosia is a neurodevelopmental condition characterized by difficulties in recognizing the identity of a person from their face. While current theories of the neural basis of developmental prosopagnosia focus on the face processing network, successful recognition of face identities requires broader integration of neural signals across the whole brain. Here, we asked whether disruptions in global functional and structural connectivity contribute to the face recognition difficulties observed in developmental prosopagnosia. We found that the left temporal pole was less functionally connected to the rest of the brain in developmental prosopagnosia. This was driven by weaker contralateral connections to the middle and inferior temporal gyri, as well as to the medial prefrontal cortex. The pattern of global connectivity in the left temporal pole was also disrupted in developmental prosopagnosia. Critically, these changes in global functional connectivity were only evident when participants viewed faces. Structural connectivity analysis revealed localized reductions in connectivity between the left temporal pole and a number of regions, including the fusiform gyrus, inferior temporal gyrus, and orbitofrontal cortex. Our findings underscore the importance of whole-brain integration in supporting typical face recognition and provide evidence that disruptions in connectivity involving the left temporal pole may underlie the characteristic difficulties of developmental prosopagnosia.

Assessing Postoperative Motor Risk in Insular Low-Grade Gliomas Patients: The Potential Role of Presurgery MRI Corticospinal Tract Shape Measures

BACKGROUND

Insular low-grade gliomas (LGGs) are surgically challenging due to their proximity to critical structures like the corticospinal tract (CST).

PURPOSE

This study aims to determine if preoperative CST shape metrics correlate with postoperative motor complications in insular LGG patients.

STUDY TYPE

Retrospective.

POPULATION

42 patients (mean age 40.26 ± 10.21 years, 25 male) with insular LGGs.

FIELD STRENGTH/SEQUENCE

Imaging was performed using 3.0 Tesla MRI, incorporating T1-weighted magnetization-prepared rapid gradient-echo, T2-weighted space dark-fluid with spin echo (SE), and diffusional kurtosis imaging (DKI) with gradient echo sequences, all integrated with echo planar imaging.

ASSESSMENT

Shape metrics of the CST, including span, irregularity, radius, and irregularity of end regions (RER and IER, respectively), were compared between the affected and healthy hemispheres. Total end region radius (TRER) was determined as the sum of RER 1 and RER 2. The relationships between shape metrics and postoperative short-term (4 weeks) and long-term (>8 weeks) motor disturbances assessing by British Medical Research Council grading system, was analyzed using multivariable regression models.

STATISTICAL TESTING

Paired t-tests compared CST metrics between hemispheres. Logistic regression identified associations between these metrics and motor disturbances. The models were developed using all available data and there was no independent validation dataset. Significance was set at P < 0.05.

RESULTS

Short-term motor disturbance risk was significantly related to TRER (OR = 199.57). Long-term risk significantly correlated with IER 1 (OR = 59.84), confirmed as a significant marker with an AUC of 0.78. Furthermore, the CST on the affected side significantly had the greater irregularity, larger TRER and RER 1, and smaller span compared to the healthy side.

DATA CONCLUSION

Preoperative evaluation of TRER and IER 1 metrics in the CST may serve as a tool for assessing the risk of postoperative motor complications in insular LGG patients.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 2.

Denoising complex-valued diffusion MR images using a two-step non-local principal component analysis approach

Purpose

to propose a two-step non-local principal component analysis (PCA) method and demonstrate its utility for denoising diffusion tensor MRI (DTI) with a few diffusion directions.

Methods

A two-step denoising pipeline was implemented to ensure accurate patch selection even with high noise levels and was coupled with data preprocessing for g-factor normalization and phase stabilization before data denoising with a non-local PCA algorithm. At the heart of our proposed pipeline was the use of a data-driven optimal shrinkage algorithm to manipulate the singular values in a way that would optimally estimate the noise-free signal. Our approach's denoising performances were evaluated using simulation and in-vivo human data experiments. The results were compared to those obtained with existing local-PCA-based methods.

Results

In both simulation and human data experiments, our approach substantially enhanced image quality relative to the noisy counterpart, yielding improved performances for estimation of relevant DTI metrics. It also outperformed existing local-PCA-based methods in reducing noise while preserving anatomic details. It also led to improved whole-brain tractography relative to the noisy counterpart.

Conclusion

The proposed denoising method has the utility for improving image quality for DTI with reduced diffusion directions and is believed to benefit many applications especially those aiming to achieve quality parametric mapping using only a few image volumes.

Fiber Microstructure Quantile (FMQ) Regression: A Novel Statistical Approach for Analyzing White Matter Bundles from Periphery to Core

The structural connections of the brain's white matter are critical for brain function. Diffusion MRI tractography enables the in-vivo reconstruction of white matter fiber bundles and the study of their relationship to covariates of interest, such as neurobehavioral or clinical factors. In this work, we introduce Fiber Microstructure Quantile (FMQ) Regression, a new statistical approach for studying the association between white matter fiber bundles and scalar factors (e.g., cognitive scores). Our approach analyzes tissue microstructure measures based on quantile-specific bundle regions. These regions are defined according to the quantiles of fractional anisotropy (FA) from the periphery to the core of a population fiber bundle, which pools all individuals' bundles. To investigate how fiber bundle tissue microstructure relates to covariates of interest, we employ the statistical technique of quantile regression. Unlike ordinary regression, which only models a conditional mean, quantile regression models the conditional quantiles of a response variable. This enables the proposed analysis, where a quantile regression is fitted for each quantile-specific bundle region. To demonstrate FMQ Regression, we perform an illustrative study in a large healthy young adult tractography dataset derived from the Human Connectome Project-Young Adult (HCP-YA), focusing on particular bundles expected to relate to particular aspects of cognition and motor function. Importantly, our analysis considers sex-specific effects in brain-behavior associations. In comparison with a traditional method, Automated Fiber Quantification (AFQ), which enables FA analysis in regions defined along the trajectory of a bundle, our results suggest that FMQ Regression is much more powerful for detecting brain-behavior associations. Importantly, FMQ Regression finds significant brain-behavior associations in multiple bundles, including findings unique to males or to females. In both males and females, language performance is significantly associated with FA in the left arcuate fasciculus, with stronger associations in the bundle's periphery. In males only, memory performance is significantly associated with FA in the left uncinate fasciculus, particularly in intermediate regions of the bundle. In females only, motor performance is significantly associated with FA in the left and right corticospinal tracts, with a slightly lower relationship at the bundle periphery and a slightly higher relationship toward the bundle core. No significant relationships are found between executive function and cingulum bundle FA. Our study demonstrates that FMQ Regression is a powerful statistical approach that can provide insight into associations from bundle periphery to bundle core. Our results also identify several brain-behavior relationships unique to males or to females, highlighting the importance of considering sex differences in future research.

Optimizing Antidepressant Efficacy: Generalizable Multimodal Neuroimaging Biomarkers for Prediction of Treatment Response

Major depressive disorder (MDD) is a common and often severe condition that profoundly diminishes quality of life for individuals across ages and demographic groups. Unfortunately, current antidepressant and psychotherapeutic treatments exhibit limited efficacy and unsatisfactory response rates in a substantial number of patients. The development of effective therapies for MDD is hindered by the insufficiently understood heterogeneity within the disorder and its elusive underlying mechanisms. To address these challenges, we present a target-oriented multimodal fusion framework that robustly predicts antidepressant response by integrating structural and functional connectivity data (sertraline: R2 = 0.31; placebo: R2 = 0.22). Remarkably, the sertraline response biomarker is further tested on an independent escitalopram-medicated cohort of MDD patients, validating its generalizability (p = 0.01) and suggesting an overlap of psychopharmacological mechanisms across selective serotonin reuptake inhibitors. Through the model, we identify multimodal neuroimaging biomarkers of antidepressant response and observe that sertraline and placebo show distinct predictive patterns. We further decompose the overall predictive patterns into constitutive network constellations with generalizable structural-functional co-variation, which exhibit treatment-specific association with personality traits and behavioral/cognitive task performance. Our innovative and interpretable multimodal framework provides novel and reliable insights into the intricate neuropsychopharmacology of antidepressant treatment, paving the way for advances in precision medicine and development of more targeted antidepressant therapeutics.

Structural network disruption of corticothalamic pathways in cerebral small vessel disease

Generalized fractional anisotropy (GFA) can eliminate the crossing fiber effect, which may be more reflective of brain tissue changes in patients with cerebral small vessel disease (CSVD). This study aimed to explore the alterations of structural networks based on GFA and its relationship with cognitive performance in CSVD patients. We recruited 50 CSVD patients which were divided into two groups: cognitive impairment (CSVD-CI) and normal cognition (CSVD-NC), and 22 healthy controls (HCs). All participants underwent the Montreal Cognitive Assessment (MoCA) and MRI examinations. The structural topological properties were compared among the three groups. The correlation between these structural alterations and MoCA was analyzed. Compared with HCs, significantly decreased nodal efficiency and connectivity were detected in the corticothalamic pathways in both patient groups, of which some were significantly decreased in CSVD-CIs compared with CSVD-NCs. Moreover, both patient groups exhibited global network disruption including decreased global efficiency and increased characteristic path length compared with HCs. Furthermore, the nodal efficiency in the right pallidum positively correlated with MoCA in CSVD-NCs controlling for nuisance variables (r = 0.471, p = 0.031). The alterations in corticothalamic pathways indicated that the brain structural network underwent extensive disruption, providing evidence for the consideration of CSVD as a global brain disease.

Early detection of dopaminergic dysfunction and glymphatic system impairment in Parkinson's disease

PURPOSE

This study aimed to assess the glymphatic function and its correlation with clinical characteristics and the loss of dopaminergic neurons in Parkinson's disease (PD) using hybrid positron emission tomography (PET)-magnetic resonance imaging (MRI) combined with diffusion tensor image analysis along the perivascular space (DTI-ALPS), choroid plexus volume (CPV), and enlarged perivascular space (EPVS) volume.

METHODS

Twenty-five PD patients and thirty matched healthy controls (HC) participated in the study. All participants underwent 18F-fluorodopa (18F-DOPA) PET-MRI scanning. The striatal standardized uptake value ratio (SUVR), DTI-ALPS index, CPV, and EPVS volume were calculated. Furthermore, we also analysed the relationship between the DTI-ALPS index, CPV, EPVS volume and striatal SUVR as well as clinical characteristics of PD patients.

RESULTS

PD patients demonstrated significantly lower values in DTI-ALPS (t = 3.053, p = 0.004) and larger CPV (t = 2.743, p = 0.008) and EPVS volume (t = 2.807, p = 0.008) compared to HC. In PD group, the ALPS-index was negatively correlated with the Unified Parkinson's Disease Rating Scale III (UPDRS-III) scores (r = -0.730, p < 0.001), and positively correlated with the mean putaminal SUVR (r = 0.560, p = 0.007) and mean caudal SUVR (r = 0.459, p = 0.032). Moreover, the mean putaminal SUVR was negatively associated with the UPDRS-III scores (r = -0.544, p = 0.009).

CONCLUSION

DTI-ALPS has the potential to uncover glymphatic dysfunction in patients with PD, with this dysfunction correlating strongly with the severity of disease, together with the mean putaminal and caudal SUVR. PET- MRI can serve as a potential multimodal imaging biomarker for early-stage PD.

Metric comparison of connectome-based lesion-symptom mapping in post-stroke aphasia

Connectome-based lesion-symptom mapping relates behavioural impairments to disruption of structural brain connectivity. Connectome-based lesion-symptom mapping can be based on different approaches (diffusion MRI versus lesion mask), network scales (whole brain versus regions of interest) and measure types (tract-based, parcel-based, or network-based metrics). We evaluated the similarity of different connectome-based lesion-symptom mapping processing choices and identified factors that influence the results using multiverse analysis-the strategy of conducting and displaying the results of all reasonable processing choices. Metrics derived from lesion masks and diffusion-weighted images were tested for association with Boston Naming Test and Token Test performance in a sample of 50 participants with aphasia following left hemispheric stroke. 'Direct' measures were derived from diffusion-weighted images. 'Indirect' measures were derived by overlaying lesion masks on a white matter atlas. Parcel-based connectomes were constructed for the whole brain and regions of interest (14 language-relevant parcels). Numerous tract-based and network-based metrics were calculated. There was a high discrepancy across processing approaches (diffusion-weighted images versus lesion masks), network scales (whole brain versus regions of interest) and metric types. Results indicate weak correlations and different connectome-based lesion-symptom mapping results across the processing choices. Substantial methodological work is needed to validate the various decision points that arise when conducting connectome-based lesion-symptom mapping analyses. Multiverse analysis is a useful strategy for evaluating the similarity across different processing choices in connectome-based lesion-symptom mapping.

Asymmetry of the Frontal Aslant Tract Depends on Handedness

BACKGROUND AND PURPOSE

The human brain displays structural and functional disparities between its hemispheres, with such asymmetry extending to the frontal aslant tract. This plays a role in a variety of cognitive functions, including speech production, language processing, and executive functions. However, the factors influencing the laterality of the frontal aslant tract remain incompletely understood. Handedness is hypothesized to impact frontal aslant tract laterality, given its involvement in both language and motor control. In this study, we aimed to investigate the relationship between handedness and frontal aslant tract lateralization, providing insight into this aspect of brain organization.

MATERIALS AND METHODS

The Automated Tractography Pipeline was used to generate the frontal aslant tract for both right and left hemispheres in a cohort of 720 subjects sourced from the publicly available Human Connectome Project in Aging database. Subsequently, macrostructural and microstructural parameters of the right and left frontal aslant tract were extracted for each individual in the study population. The Edinburgh Handedness Inventory scores were used for the classification of handedness, and a comparative analysis across various handedness groups was performed.

RESULTS

An age-related decline in both macrostructural parameters and microstructural integrity was noted within the studied population. The frontal aslant tract demonstrated a greater volume and larger diameter in male subjects compared with female participants. Additionally, a left-side laterality of the frontal aslant tract was observed within the general population. In the right-handed group, the volume (P < .001), length (P < .001), and diameter (P = .004) of the left frontal aslant tract were found to be higher than those of the right frontal aslant tract. Conversely, in the left-handed group, the volume (P = .040) and diameter (P = .032) of the left frontal aslant tract were lower than those of the right frontal aslant tract. Furthermore, in the right-handed group, the volume and diameter of the frontal aslant tract showed left-sided lateralization, while in the left-handed group, a right-sided lateralization was evident.

CONCLUSIONS

The laterality of the frontal aslant tract appears to differ with handedness. This finding highlights the complex interaction between brain lateralization and handedness, emphasizing the importance of considering handedness as a factor in evaluating brain structure and function.

Connectomic insights into the impact of 1p/19q co-deletion in dominant hemisphere insular glioma patients

Objectives

This study aimed to elucidate the influences of 1p/19q co-deletion on structural connectivity alterations in patients with dominant hemisphere insular diffuse gliomas.

Methods

We incorporated 32 cases of left insular gliomas and 20 healthy controls for this study. Using diffusion MRI, we applied correlational tractography, differential tractography, and graph theoretical analysis to explore the potential connectivity associated with 1p/19q co-deletion.

Results

The study revealed that the quantitative anisotropy (QA) of key deep medial fiber tracts, including the anterior thalamic radiation, superior thalamic radiation, fornix, and cingulum, had significant negative associations with 1p/19q co-deletion (FDR = 4.72 × 10-5). These tracts are crucial in maintaining the integrity of brain networks. Differential analysis further supported these findings (FWER-corrected p < 0.05). The 1p/19q non-co-deletion group exhibited significantly higher clustering coefficients (FDR-corrected p < 0.05) and reduced betweenness centrality (FDR-corrected p < 0.05) in regions around the tumor compared to HC group. Graph theoretical analysis indicated that non-co-deletion patients had increased local clustering and decreased betweenness centrality in peritumoral brain regions compared to co-deletion patients and healthy controls (FDR-corrected p < 0.05). Additionally, despite not being significant through correction, patients with 1p/19q co-deletion exhibited lower trends in weighted average clustering coefficient, transitivity, small worldness, and global efficiency, while showing higher tendencies in weighted path length compared to patients without the co-deletion.

Conclusion

The findings of this study underline the significant role of 1p/19q co-deletion in altering structural connectivity in insular glioma patients. These alterations in brain networks could have profound implications for the neural functionality in patients with dominant hemisphere insular gliomas.

Harnessing the frontal aslant tract's structure to assess its involvement in cognitive functions: new insights from 7-T diffusion imaging

The first therapeutical goal followed by neurooncological surgeons dealing with prefrontal gliomas is attempting supramarginal tumor resection preserving relevant neurological function. Therefore, advanced knowledge of the frontal aslant tract (FAT) functional neuroanatomy in high-order cognitive domains beyond language and speech processing would help refine neurosurgeries, predicting possible relevant cognitive adverse events and maximizing the surgical efficacy. To this aim we performed the recently developed correlational tractography analyses to evaluate the possible relationship between FAT's microstructural properties and cognitive functions in 27 healthy subjects having ultra-high-field (7-Tesla) diffusion MRI. We independently assessed FAT segments innervating the dorsolateral prefrontal cortices (dlPFC-FAT) and the supplementary motor area (SMA-FAT). FAT microstructural robustness, measured by the tract's quantitative anisotropy (QA), was associated with a better performance in episodic memory, visuospatial orientation, cognitive processing speed and fluid intelligence but not sustained selective attention tests. Overall, the percentual tract volume showing an association between QA-index and improved cognitive scores (pQACV) was higher in the SMA-FAT compared to the dlPFC-FAT segment. This effect was right-lateralized for verbal episodic memory and fluid intelligence and bilateralized for visuospatial orientation and cognitive processing speed. Our results provide novel evidence for a functional specialization of the FAT beyond the known in language and speech processing, particularly its involvement in several higher-order cognitive domains. In light of these findings, further research should be encouraged to focus on neurocognitive deficits and their impact on patient outcomes after FAT damage, especially in the context of glioma surgery.

Connectivity of the Piriform Cortex and its Implications in Temporal Lobe Epilepsy

Background

The piriform cortex has been implicated in the initiation, spread and termination of epileptic seizures. This understanding has extended to surgical management of epilepsy, where it has been shown that resection or ablation of the piriform cortex can result in better outcomes. How and why the piriform cortex may play such a crucial role in seizure networks is not well understood. To answer these questions, we investigated the functional and structural connectivity of the piriform cortex in both healthy controls and temporal lobe epilepsy (TLE) patients.

Methods

We studied a retrospective cohort of 55 drug-resistant unilateral TLE patients and 26 healthy controls who received structural and functional neuroimaging. Using seed-to-voxel connectivity we compared the normative whole-brain connectivity of the piriform to that of the hippocampus, a region commonly involved in epilepsy, to understand the differential contribution of the piriform to the epileptogenic network. We subsequently measured the inter-piriform coupling (IPC) to quantify similarities in the inter-hemispheric cortical functional connectivity profile between the two piriform cortices. We related differences in IPC in TLE back to aberrations in normative piriform connectivity, whole brain functional properties, and structural connectivity.

Results

We find that relative to the hippocampus, the piriform is functionally connected to the anterior insula and the rest of the salience ventral attention network (SAN). We also find that low IPC is a sensitive metric of poor surgical outcome (sensitivity: 85.71%, 95% CI: [19.12%, 99.64%]); and differences in IPC within TLE were related to disconnectivity and hyperconnectivity to the anterior insula and the SAN. More globally, we find that low IPC is associated with whole-brain functional and structural segregation, marked by decreased functional small-worldness and fractional anisotropy.

Conclusions

Our study presents novel insights into the functional and structural neural network alterations associated with this structure, laying the foundation for future work to carefully consider its connectivity during the presurgical management of epilepsy.

Diffusion spectrum imaging in patients with idiopathic normal pressure hydrocephalus: correlation with ventricular enlargement

BACKGROUND

To investigate the association between white matter changes and ventricular expansion in idiopathic normal pressure hydrocephalus (iNPH) based on diffusion spectrum imaging (DSI).

METHODS

We included 32 patients with iNPH who underwent DSI using a 3T MRI scanner. The lateral ventricles were manually segmented, and ventricular volumes were measured. Two methods were utilised in the study: manual region-of-interest (ROI) delineation and tract diffusion profile analysis. General fractional anisotropy (GFA) and fractional anisotropy (FA) were extracted in different white matter regions, including the bilateral internal capsule (anterior and posterior limbs) and corpus callosum (body, genu, and splenium) with manual ROI delineation. The 18 main tracts in the brain of each patient were extracted; the diffusion metrics of 100 equidistant nodes on each fibre were calculated, and Spearman's correlation coefficient was used to determine the correlation between diffusion measures and ventricular volume of iNPH patients.

RESULTS

The GFA and FA of all ROI showed no significant correlation with lateral ventricular volume. However, in the tract diffusion profile analysis, lateral ventricular volume was positively correlated with part of the cingulum bundle, left corticospinal tract, and bilateral thalamic radiation posterior, whereas it was negatively correlated with the bilateral cingulum parahippocampal (all p < 0.05).

CONCLUSIONS

The effect of ventricular enlargement in iNPH on some white matter fibre tracts around the ventricles was limited and polarizing, and most white matter fibre tract integrity changes were not associated with ventricular enlargement; this reflects that multiple pathological mechanisms may have been combined to cause white matter alterations in iNPH.

Deep Normative Tractometry for Identifying Joint White Matter Macro- and Micro-structural Abnormalities in Alzheimer's Disease

This study introduces the Deep Normative Tractometry (DNT) framework, that encodes the joint distribution of both macrostructural and microstructural profiles of the brain white matter tracts through a variational autoencoder (VAE). By training on data from healthy controls, DNT learns the normative distribution of tract data, and can delineate along-tract micro- and macro-structural abnormalities. Leveraging a large sample size via generative pre-training, we assess DNT's generalizability using transfer learning on data from an independent cohort acquired in India. Our findings demonstrate DNT's capacity to detect widespread diffusivity abnormalities along tracts in mild cognitive impairment and Alzheimer's disease, aligning closely with results from the Bundle Analytics (BUAN) tractometry pipeline. By incorporating tract geometry information, DNT may be able to distinguish disease-related abnormalities in anisotropy from tract macrostructure, and shows promise in enhancing fine-scale mapping and detection of white matter alterations in neurodegenerative conditions.

Traumatic brain injury alters the effects of class II invariant peptide (CLIP) antagonism on chronic meningeal CLIP + B cells, neuropathology, and neurobehavioral impairment in 5xFAD mice

BACKGROUND

Traumatic brain injury (TBI) is a significant risk factor for Alzheimer's disease (AD), and accumulating evidence supports a role for adaptive immune B and T cells in both TBI and AD pathogenesis. We previously identified B cell and major histocompatibility complex class II (MHCII)-associated invariant chain peptide (CLIP)-positive B cell expansion after TBI. We also showed that antagonizing CLIP binding to the antigen presenting groove of MHCII after TBI acutely reduced CLIP + splenic B cells and was neuroprotective. The current study investigated the chronic effects of antagonizing CLIP in the 5xFAD Alzheimer's mouse model, with and without TBI.

METHODS

12-week-old male wild type (WT) and 5xFAD mice were administered either CLIP antagonist peptide (CAP) or vehicle, once at 30 min after either sham or a lateral fluid percussion injury (FPI). Analyses included flow cytometric analysis of immune cells in dural meninges and spleen, histopathological analysis of the brain, magnetic resonance diffusion tensor imaging, cerebrovascular analysis, and assessment of motor and neurobehavioral function over the ensuing 6 months.

RESULTS

9-month-old 5xFAD mice had significantly more CLIP + B cells in the meninges compared to age-matched WT mice. A one-time treatment with CAP significantly reduced this population in 5xFAD mice. Importantly, CAP also improved some of the immune, histopathological, and neurobehavioral impairments in 5xFAD mice over the ensuing six months. Although FPI did not further elevate meningeal CLIP + B cells, it did negate the ability of CAP to reduce meningeal CLIP + B cells in the 5xFAD mice. FPI at 3 months of age exacerbated some aspects of AD pathology in 5xFAD mice, including further reducing hippocampal neurogenesis, increasing plaque deposition in CA3, altering microgliosis, and disrupting the cerebrovascular structure. CAP treatment after injury ameliorated some but not all of these FPI effects.

Unveiling the axonal connectivity between the precuneus and temporal pole: Structural evidence from the cingulum pathways

Neuroimaging studies have consistently demonstrated concurrent activation of the human precuneus and temporal pole (TP), both during resting-state conditions and various higher-order cognitive functions. However, the precise underlying structural connectivity between these brain regions remains uncertain despite significant advancements in neuroscience research. In this study, we investigated the connectivity of the precuneus and TP by employing parcellation-based fiber micro-dissections in human brains and fiber tractography techniques in a sample of 1065 human subjects and a sample of 41 rhesus macaques. Our results demonstrate the connectivity between the posterior precuneus area POS2 and the areas 35, 36, and TG of the TP via the fifth subcomponent of the cingulum (CB-V) also known as parahippocampal cingulum. This finding contributes to our understanding of the connections within the posteromedial cortices, facilitating a more comprehensive integration of anatomy and function in both normal and pathological brain processes. PRACTITIONER POINTS: Our investigation delves into the intricate architecture and connectivity patterns of subregions within the precuneus and temporal pole, filling a crucial gap in our knowledge. We revealed a direct axonal connection between the posterior precuneus (POS2) and specific areas (35, 35, and TG) of the temporal pole. The direct connections are part of the CB-V pathway and exhibit a significant association with the cingulum, SRF, forceps major, and ILF. Population-based human tractography and rhesus macaque fiber tractography showed consistent results that support micro-dissection outcomes.

A sensorimotor-association axis of thalamocortical connection development

Human cortical development follows a sensorimotor-to-association sequence during childhood and adolescence1-6. The brain's capacity to enact this sequence over decades indicates that it relies on intrinsic mechanisms to regulate inter-regional differences in the timing of cortical maturation, yet regulators of human developmental chronology are not well understood. Given evidence from animal models that thalamic axons modulate windows of cortical plasticity7-12, here we evaluate the overarching hypothesis that structural connections between the thalamus and cortex help to coordinate cortical maturational heterochronicity during youth. We first introduce, cortically annotate, and anatomically validate a new atlas of human thalamocortical connections using diffusion tractography. By applying this atlas to three independent youth datasets (ages 8-23 years; total N = 2,676), we reproducibly demonstrate that thalamocortical connections develop along a maturational gradient that aligns with the cortex's sensorimotor-association axis. Associative cortical regions with thalamic connections that take longest to mature exhibit protracted expression of neurochemical, structural, and functional markers indicative of higher circuit plasticity as well as heightened environmental sensitivity. This work highlights a central role for the thalamus in the orchestration of hierarchically organized and environmentally sensitive windows of cortical developmental malleability.

PhyberSIM: a tool for the generation of ground truth to evaluate brain fiber clustering algorithms

Diffusion Magnetic Resonance Imaging tractography is a non-invasive technique that produces a collection of streamlines representing the main white matter bundle trajectories. Methods, such as fiber clustering algorithms, are important in computational neuroscience and have been the basis of several white matter analysis methods and studies. Nevertheless, these clustering methods face the challenge of the absence of ground truth of white matter fibers, making their evaluation difficult. As an alternative solution, we present an innovative brain fiber bundle simulator that uses spline curves for fiber representation. The methodology uses a tubular model for the bundle simulation based on a bundle centroid and five radii along the bundle. The algorithm was tested by simulating 28 Deep White Matter atlas bundles, leading to low inter-bundle distances and high intersection percentages between the original and simulated bundles. To prove the utility of the simulator, we created three whole-brain datasets containing different numbers of fiber bundles to assess the quality performance of QuickBundles and Fast Fiber Clustering algorithms using five clustering metrics. Our results indicate that QuickBundles tends to split less and Fast Fiber Clustering tends to merge less, which is consistent with their expected behavior. The performance of both algorithms decreases when the number of bundles is increased due to higher bundle crossings. Additionally, the two algorithms exhibit robust behavior with input data permutation. To our knowledge, this is the first whole-brain fiber bundle simulator capable of assessing fiber clustering algorithms with realistic data.

TractGeoNet: A geometric deep learning framework for pointwise analysis of tract microstructure to predict language assessment performance

We propose a geometric deep-learning-based framework, TractGeoNet, for performing regression using diffusion magnetic resonance imaging (dMRI) tractography and associated pointwise tissue microstructure measurements. By employing a point cloud representation, TractGeoNet can directly utilize tissue microstructure and positional information from all points within a fiber tract without the need to average or bin data along the streamline as traditionally required by dMRI tractometry methods. To improve regression performance, we propose a novel loss function, the Paired-Siamese Regression loss, which encourages the model to focus on accurately predicting the relative differences between regression label scores rather than just their absolute values. In addition, to gain insight into the brain regions that contribute most strongly to the prediction results, we propose a Critical Region Localization algorithm. This algorithm identifies highly predictive anatomical regions within the white matter fiber tracts for the regression task. We evaluate the effectiveness of the proposed method by predicting individual performance on two neuropsychological assessments of language using a dataset of 20 association white matter fiber tracts from 806 subjects from the Human Connectome Project Young Adult dataset. The results demonstrate superior prediction performance of TractGeoNet compared to several popular regression models that have been applied to predict individual cognitive performance based on neuroimaging features. Of the twenty tracts studied, we find that the left arcuate fasciculus tract is the most highly predictive of the two studied language performance assessments. Within each tract, we localize critical regions whose microstructure and point information are highly and consistently predictive of language performance across different subjects and across multiple independently trained models. These critical regions are widespread and distributed across both hemispheres and all cerebral lobes, including areas of the brain considered important for language function such as superior and anterior temporal regions, pars opercularis, and precentral gyrus. Overall, TractGeoNet demonstrates the potential of geometric deep learning to enhance the study of the brain's white matter fiber tracts and to relate their structure to human traits such as language performance.

brainlife.io: a decentralized and open-source cloud platform to support neuroscience research

Neuroscience is advancing standardization and tool development to support rigor and transparency. Consequently, data pipeline complexity has increased, hindering FAIR (findable, accessible, interoperable and reusable) access. brainlife.io was developed to democratize neuroimaging research. The platform provides data standardization, management, visualization and processing and automatically tracks the provenance history of thousands of data objects. Here, brainlife.io is described and evaluated for validity, reliability, reproducibility, replicability and scientific utility using four data modalities and 3,200 participants.

Structural changes in corticospinal tract profiling via multishell diffusion models and their relation to overall survival in glioblastoma

PURPOSE

Advanced MR fiber tracking imaging reflects fiber bundle invasion by glioblastoma, particularly of the corticospinal tract (CST), which is more susceptible as the largest downstream fiber tracts. We aimed to investigate whether CST features can predict the overall survival of glioblastoma.

METHODS

In this prospective secondary analysis, 40 participants (mean age, 58 years; 16 male) pathologically diagnosed with glioblastoma were enrolled. Diffusion spectrum MRI was used for CST reconstruction. Fifty morphological and diffusion indicators (DTI, DKI, NODDI, MAP and Q-space) were used to characterize the CST. Optimal parameters capturing fiber bundle damage were obtained through various grouping methods. Eventually, the correlation with overall survival was determined by the hazard ratios (HRs) from various Cox proportional hazard model combinations.

RESULTS

Only intracellular volume fraction (ICVF) and non-Gaussianity (NG) values on the affected tumor level were significant in all four groups or stratified comparisons (all P < .05). During the median follow-up 698 days, only the ICVF on the affected tumor level was independently associated with overall survival, even after adjusting for all classic prognostic factors (HR [95 % CI]: 0.611 [0.403, 0.927], P = .021). Moreover, stratification by the ICVF on the affected tumor level successfully predicted risk (P < .01) and improved the C-index of the multivariate model (from 0.695 to 0.736).

CONCLUSIONS

This study demonstrates a relationship between NODDI-derived CST features, ICVF on the affected tumor level, and overall survival in glioblastoma. Independent of classical prognostic factors for glioblastoma, a lower ICVF on the affected tumor level might predict a lower overall survival.

A Multiscale Closed-Loop Neurotoxicity Model of Alzheimer's Disease Progression Explains Functional Connectivity Alterations

The accumulation of amyloid-β (Aβ) and hyperphosphorylated-tau (hp-tau) are two classical histopathological biomarkers in Alzheimer's disease (AD). However, their detailed interactions with the electrophysiological changes at the meso- and macroscale are not yet fully understood. We developed a mechanistic multiscale model of AD progression, linking proteinopathy to its effects on neural activity and vice-versa. We integrated a heterodimer model of prion-like protein propagation and a brain network model of Jansen-Rit neural masses derived from human neuroimaging data whose parameters varied due to neurotoxicity. Results showed that changes in inhibition guided the electrophysiological alterations found in AD, and these changes were mainly attributed to Aβ effects. Additionally, we found a causal disconnection between cellular hyperactivity and interregional hypersynchrony contrary to previous beliefs. Finally, we demonstrated that early Aβ and hp-tau depositions' location determine the spatiotemporal profile of the proteinopathy. The presented model combines the molecular effects of both Aβ and hp-tau together with a mechanistic protein propagation model and network effects within a closed-loop model. This holds the potential to enlighten the interplay between AD mechanisms on various scales, aiming to develop and test novel hypotheses on the contribution of different AD-related variables to the disease evolution.

A practical evaluation of measures derived from compressed sensing diffusion spectrum imaging

Diffusion Spectrum Imaging (DSI) using dense Cartesian sampling of q-space has been shown to provide important advantages for modeling complex white matter architecture. However, its adoption has been limited by the lengthy acquisition time required. Sparser sampling of q-space combined with compressed sensing (CS) reconstruction techniques has been proposed as a way to reduce the scan time of DSI acquisitions. However prior studies have mainly evaluated CS-DSI in post-mortem or non-human data. At present, the capacity for CS-DSI to provide accurate and reliable measures of white matter anatomy and microstructure in the living human brain remains unclear. We evaluated the accuracy and inter-scan reliability of 6 different CS-DSI schemes that provided up to 80% reductions in scan time compared to a full DSI scheme. We capitalized on a dataset of 26 participants who were scanned over eight independent sessions using a full DSI scheme. From this full DSI scheme, we subsampled images to create a range of CS-DSI images. This allowed us to compare the accuracy and inter-scan reliability of derived measures of white matter structure (bundle segmentation, voxel-wise scalar maps) produced by the CS-DSI and the full DSI schemes. We found that CS-DSI estimates of both bundle segmentations and voxel-wise scalars were nearly as accurate and reliable as those generated by the full DSI scheme. Moreover, we found that the accuracy and reliability of CS-DSI was higher in white matter bundles that were more reliably segmented by the full DSI scheme. As a final step, we replicated the accuracy of CS-DSI in a prospectively acquired dataset (n = 20, scanned once). Together, these results illustrate the utility of CS-DSI for reliably delineating in vivo white matter architecture in a fraction of the scan time, underscoring its promise for both clinical and research applications.

Evaluation of glymphatic system activity by diffusion tensor image analysis along the perivascular space in presbycusis

PURPOSE

Previous studies have suggested that presbycusis (age-related hearing loss) is accompanied with cognitive decline and dementia. However, the neural mechanism underlying the cognitive decline in presbycusis remains unclear. This study aimed to evaluate the glymphatic system function in presbycusis patients compared to healthy controls using diffusion tensor imaging (DTI) with the perivascular space (DTI-ALPS) method.

METHODS

DTI scans were obtained from 30 presbycusis patients with cognitive decline (PCD), 30 presbycusis patients with no cognitive decline (PNCD) and 40 age-, gender-, and education-matched healthy controls (HCs). The DTI-ALPS index was calculated for each group. We evaluated the differences in the DTI-ALPS index among PCD, PNCD and HCs. In addition, we conducted a correlation analysis between the DTI-ALPS index and cognitive performance.

RESULTS

There were significant differences of the DTI-ALPS index among three groups. Post-hoc analysis suggested that the DTI-ALPS index in PCD was significantly lower patients in relative to PNCD and HCs (1.49147 vs. 1.57441 vs. 1.62020, p < 0.001). After correcting for age, gender, and education, the DTI-ALPS index is positively correlated with the MoCA scores (rho = 0.426, p = 0.026).

CONCLUSION

Presbycusis patients with cognitive impairment exhibited decreased glymphatic activity than those without cognitive impairment and HCs. The DTI-ALPS index may provide useful disease progression or treatment biomarkers for patients with presbycusis as an indicator of modulation of glymphatic activity.

Improved reconstruction of crossing fibers in the mouse optic pathways with orientation distribution function fingerprinting

PURPOSE

The accuracy of diffusion MRI tractography reconstruction decreases in the white matter regions with crossing fibers. The optic pathways in rodents provide a challenging structure to test new diffusion tractography approaches because of the small crossing volume within the optic chiasm and the unbalanced 9:1 proportion between the contra- and ipsilateral neural projections from the retina to the lateral geniculate nucleus, respectively.

METHODS

Common approaches based on Orientation Distribution Function (ODF) peak finding or statistical inference were compared qualitatively and quantitatively to ODF Fingerprinting (ODF-FP) for reconstruction of crossing fibers within the optic chiasm using in vivo diffusion MRI (n = 18 $$ n=18 $$ healthy C57BL/6 mice). Manganese-Enhanced MRI (MEMRI) was obtained after intravitreal injection of manganese chloride and used as a reference standard for the optic pathway anatomy.

RESULTS

ODF-FP outperformed by over 100% all the tested methods in terms of the ratios between the contra- and ipsilateral segments of the reconstructed optic pathways as well as the spatial overlap between tractography and MEMRI.

CONCLUSION

In this challenging model system, ODF-Fingerprinting reduced uncertainty of diffusion tractography for complex structural formations of fiber bundles.

DiMANI: diffusion MRI for anatomical nuclei imaging-Application for the direct visualization of thalamic subnuclei

The thalamus is a centrally located and heterogeneous brain structure that plays a critical role in various sensory, motor, and cognitive processes. However, visualizing the individual subnuclei of the thalamus using conventional MRI techniques is challenging. This difficulty has posed obstacles in targeting specific subnuclei for clinical interventions such as deep brain stimulation (DBS). In this paper, we present DiMANI, a novel method for directly visualizing the thalamic subnuclei using diffusion MRI (dMRI). The DiMANI contrast is computed by averaging, voxelwise, diffusion-weighted volumes enabling the direct distinction of thalamic subnuclei in individuals. We evaluated the reproducibility of DiMANI through multiple approaches. First, we utilized a unique dataset comprising 8 scans of a single participant collected over a 3-year period. Secondly, we quantitatively assessed manual segmentations of thalamic subnuclei for both intra-rater and inter-rater reliability. Thirdly, we qualitatively correlated DiMANI imaging data from several patients with Essential Tremor with the localization of implanted DBS electrodes and clinical observations. Lastly, we demonstrated that DiMANI can provide similar features at 3T and 7T MRI, using varying numbers of diffusion directions. Our results establish that DiMANI is a reproducible and clinically relevant method to directly visualize thalamic subnuclei. This has significant implications for the development of new DBS targets and the optimization of DBS therapy.

Probabilistic coverage of the frontal aslant tract in young adults: Insights into individual variability, lateralization, and language functions

The frontal aslant tract (FAT) is a crucial neural pathway of language and speech, but little is known about its connectivity and segmentation differences across populations. In this study, we investigate the probabilistic coverage of the FAT in a large sample of 1065 young adults. Our primary goal was to reveal individual variability and lateralization of FAT and its structure-function correlations in language processing. The study utilized diffusion MRI data from 1065 subjects obtained from the Human Connectome Project. Automated tractography using DSI Studio software was employed to map white matter bundles, and the results were examined to study the population variation of the FAT. Additionally, anatomical dissections were performed to validate the fiber tracking results. The tract-to-region connectome, based on Human Connectome Project-MMP parcellations, was utilized to provide population probability of the tract-to-region connections. Our results showed that the left anterior FAT exhibited the most substantial individual differences, particularly in the superior and middle frontal gyrus, with greater variability in the superior than the inferior region. Furthermore, we found left lateralization in FAT, with a greater difference in coverage in the inferior and posterior portions. Additionally, our analysis revealed a significant positive correlation between the left FAT inferior coverage area and the performance on the oral reading recognition (p = .016) and picture vocabulary (p = .0026) tests. In comparison, fractional anisotropy of the right FAT exhibited marginal significance in its correlation (p = .056) with Picture Vocabulary Test. Our findings, combined with the connectivity patterns of the FAT, allowed us to segment its structure into anterior and posterior segments. We found significant variability in FAT coverage among individuals, with left lateralization observed in both macroscopic shape measures and microscopic diffusion metrics. Our findings also suggested a potential link between the size of the left FAT's inferior coverage area and language function tests. These results enhance our understanding of the FAT's role in brain connectivity and its potential implications for language and executive functions.

Impact of corpus callosum integrity on functional interhemispheric connectivity and cognition in healthy subjects

To examine the corpus callosum's (CC) integrity in terms of fractional anisotropy (FA) and how it affects resting-state hemispheric connectivity (rs-IHC) and cognitive function in healthy individuals. Sixty-eight healthy individuals were recruited for the study. The global FA (gFA) and FA values of each CC tract (forceps minor, body, tapetum, and forceps major) were evaluated using diffusion-weighted imaging (DWI) sequences. The homotopic functional connectivity technique was used to quantify the effects of FA in the CC tracts on bilateral functional connectivity, including the confounding effect of gFA. Brain regions with higher or lower rs-IHC were identified using the threshold-free cluster enhancement family-wise error-corrected p-value of 0.05. The null hypothesis was rejected if the p-value was ≤ 0.05 for the nonparametric partial correlation technique. Several clusters of increased rs-IHC were identified in relation to the FA of individual CC tracts, each with a unique topographic distribution and extension. Only forceps minor FA values correlated with cognitive scores. The integrity of CC influences rs-IHC differently in healthy subjects. Specifically, forceps minor anisotropy impacts rs-IHC and cognition more than other CC tracts do.

Endocannabinoid-mediated rescue of somatosensory cortex activity, plasticity and related behaviors following an early in life concussion

Due to the assumed plasticity of immature brain, early in life brain alterations are thought to lead to better recoveries in comparison to the mature brain. Despite clinical needs, how neuronal networks and associated behaviors are affected by early in life brain stresses, such as pediatric concussions, have been overlooked. Here we provide first evidence in mice that a single early in life concussion durably increases neuronal activity in the somatosensory cortex into adulthood, disrupting neuronal integration while the animal is performing sensory-related tasks. This represents a previously unappreciated clinically relevant mechanism for the impairment of sensory-related behavior performance. Furthermore, we demonstrate that pharmacological modulation of the endocannabinoid system a year post-concussion is well-suited to rescue neuronal activity and plasticity, and to normalize sensory-related behavioral performance, addressing the fundamental question of whether a treatment is still possible once post-concussive symptoms have developed, a time-window compatible with clinical treatment.

Direct interhemispheric cortical communication via thalamic commissures: a new white matter pathway in the primate brain

Cortical neurons of eutherian mammals project to the contralateral hemisphere, crossing the midline primarily via the corpus callosum and the anterior, posterior, and hippocampal commissures. We recently reported and named the thalamic commissures (TCs) as an additional interhemispheric axonal fiber pathway connecting the cortex to the contralateral thalamus in the rodent brain. Here, we demonstrate that TCs also exist in primates and characterize the connectivity of these pathways with high-resolution diffusion-weighted MRI, viral axonal tracing, and fMRI. We present evidence of TCs in both New World (Callithrix jacchus and Cebus apella) and Old World primates (Macaca mulatta). Further, like rodents, we show that the TCs in primates develop during the embryonic period, forming anatomical and functionally active connections of the cortex with the contralateral thalamus. We also searched for TCs in the human brain, showing their presence in humans with brain malformations, although we could not identify TCs in healthy subjects. These results pose the TCs as a vital fiber pathway in the primate brain, allowing for more robust interhemispheric connectivity and synchrony and serving as an alternative commissural route in developmental brain malformations.

Exploring MGMT methylation-driven structural connectivity changes in insular gliomas: a tractography and graph theoretical analysis

OBJECTIVES

This study aims to explore the relationship between the methylation levels of the O-6-methylguanine-DNA methyltransferase (MGMT) promoter and the structural connectivity in insular gliomas across hemispheres.

METHODS

We analyzed 32 left and 29 right insular glioma cases and 50 healthy controls, using differential tractography, correlational tractography, and graph theoretical analysis to investigate the correlation between structural connectivity and the methylation level.

RESULTS

The differential tractography results revealed that in left insular glioma, the volume of affected inferior fronto-occipital fasciculus (IFOF, p = 0.019) significantly correlated with methylation levels. Correlational tractography results showed that the quantitative anisotropy (QA) value of peritumoral fiber tracts also exhibited a significant correlation with methylation levels (FDR < 0.05). On the other hand, in right insular glioma, anterior internal part of the reticular tract, IFOF, and thalamic radiation showed a significant correlation with methylation levels but at a different correlation direction from the left side (FDR < 0.05). The graph theoretical analysis showed that in the left insular gliomas, only the radius of graph was significantly lower in methylated MGMT group than unmethylated group (p = 0.047). No significant correlations between global properties and methylation levels were observed in insular gliomas on both sides.

CONCLUSION

Our findings highlight a significant, hemisphere-specific correlation between MGMT promoter methylation and structural connectivity in insular gliomas. This study provides new insights into the genetic influence on glioma pathology, which could inform targeted therapeutic strategies.

Functional and structural connectivity correlates of semantic verbal fluency deficits in first-episode psychosis

INTRODUCTION

Semantic verbal fluency (SVF) impairments are debilitating and present early in the course of psychotic illness. Deficits within frontal, parietal, and temporal brain regions contribute to this deficit, as long-range communication across this functionally integrated network is critical to SVF. This study sought to isolate disruptions in functional and structural connectivity contributing to SVF deficits during first-episode psychosis in the schizophrenia spectrum (FESz).

METHODS

Thirty-three FESz and 34 matched healthy controls (HC) completed the Animal Naming Task to assess SVF. Magnetoencephalography was recorded during an analogous covert SVF task, and phase-locking value (PLV) used to measure functional connectivity between inferior frontal and temporoparietal structures bilaterally. Diffusion imaging was collected to measure fractional anisotropy (FA) of the arcuate fasciculus, the major tract connecting frontal and temporoparietal language areas.

RESULTS

SVF scores were lower among FESz compared to HC. While PLV and FA did not differ between groups overall, FESz exhibited an absence of the left-lateralized nature of both measures observed in HC. Among FESz, larger right-hemisphere PLV was associated with worse SVF performance (ρ = -0.51) and longer DUP (ρ = -0.50).

DISCUSSION

In addition to worse SVF, FESz exhibited diminished leftward asymmetry of structural and functional connectivity in fronto-temporoparietal SVF network. The relationship between theta-band hyperconnectivity and poorer performance suggests a disorganized executive network and may reflect dysfunction of frontal cognitive control centers. These findings illustrate an aberrant pattern across the distributed SVF network at disease onset and merit further investigation into development of asymmetrical hemispheric connectivity and its failure among high-risk populations.

Associations Between Brain Structural Connectivity and 1‐Year Demoralization in Breast Cancer: A Longitudinal Diffusion Tensor Imaging Study

Purposes: This study aims to explore the association between brain structural connectivity and 1‐year demoralization in patients with newly diagnosed breast cancer.

Methods: Patients were enrolled from a multicenter longitudinal program named as Be Resilient to Breast Cancer (BRBC) between 2017 and 2019. Brain structural connectivity was assessed with diffusion tensor imaging (DTI) at baseline and the demoralization scale II collected self‐report data at baseline and 1 year later. A data‐driven correlational tractography was performed to recognize significant neural pathways associated with the group membership (increased vs. nonincreased demoralization). The incremental prediction values of Quantitative Anisotropy (QA) extracted from the significant white matter tracts against the group membership were evaluated.

Results: 21.2% (N = 31) reported increased 1‐year demoralization. Inferior fronto‐occipital fasciculus (IFOF) was associated with 1‐year demoralization in breast cancer. The incremental prediction values of QAs in net reclassification improvement (NRI) and integrated discrimination improvement (IDI) ranged from 8.11% to 46.89% and 9.12% to 23.95%, respectively, over the conventional tumor‐nodal metatasis (TNM) staging model.

Conclusion: Anisotropy in IFOF is a potential prediction neuromarker to 1‐year demoralization in patients with newly diagnosed breast cancer.

Trial Registration: ClinicalTrials.gov identifier: NCT03026374

Correlation of Cognitive Reappraisal and the Microstructural Properties of the Forceps Minor: A Deductive Exploratory Diffusion Tensor Imaging Study

Cognitive reappraisal (CR) is a mechanism for emotion regulation, and the prefrontal cortex (PFC) plays a central role in the regulation of emotions. We tested the hypothesis of an association between CR function and microstructural properties of forceps minor (a commissural bundle within the PFC) in healthy subjects (HS). We analyzed a population of 65 young HS of a public dataset. The diffusion tensor imaging (DTI) sequence of every subject was analyzed to extract the derived shape (diameter and volume) and DTI metrics in terms of fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) of the forceps minor. The CR subscale of the German version of the Emotion Regulation Questionnaire (ERQ) was used for CR assessment. The Shapiro-Wilk test was applied to test the assumption of normality in all these parameters, adopting a statistical threshold at p < 0.05. Whenever appropriate a non-parametric two-tailed partial correlation analysis was applied to test for correlations between the CR ERQ score and the derived shape and DTI metrics, including age and sex as confounders, adopting a statistical threshold at p < 0.05. The non-parametric two-tailed partial correlation analysis revealed a mildly significant correlation with FA (ρ = 0.303; p = 0.016), a weakly significant negative correlation with MD (ρ = - 0.269; p = 0.033), and a mildly significant negative correlation with RD (ρ = - 0.305; p = 0.015). These findings suggest a correlation between DTI microstructural properties of forceps minor and CR.

ReeBundle: A Method for Topological Modeling of White Matter Pathways Using Diffusion MRI

Tractography can generate millions of complex curvilinear fibers (streamlines) in 3D that exhibit the geometry of white matter pathways in the brain. Common approaches to analyzing white matter connectivity are based on adjacency matrices that quantify connection strength but do not account for any topological information. A critical element in neurological and developmental disorders is the topological deterioration and irregularities in streamlines. In this paper, we propose a novel Reeb graph-based method "ReeBundle" that efficiently encodes the topology and geometry of white matter fibers. Given the trajectories of neuronal fiber pathways (neuroanatomical bundle), we re-bundle the streamlines by modeling their spatial evolution to capture geometrically significant events (akin to a fingerprint). ReeBundle parameters control the granularity of the model and handle the presence of improbable streamlines commonly produced by tractography. Further, we propose a new Reeb graph-based distance metric that quantifies topological differences for automated quality control and bundle comparison. We show the practical usage of our method using two datasets: (1) For International Society for Magnetic Resonance in Medicine (ISMRM) dataset, ReeBundle handles the morphology of the white matter tract configurations due to branching and local ambiguities in complicated bundle tracts like anterior and posterior commissures; (2) For the longitudinal repeated measures in the Cognitive Resilience and Sleep History (CRASH) dataset, repeated scans of a given subject acquired weeks apart lead to provably similar Reeb graphs that differ significantly from other subjects, thus highlighting ReeBundle's potential for clinical fingerprinting of brain regions.

Enhanced white matter fiber tract of the cortical visual system in visual artists: implications for creativity

Introduction

This study aimed to examine the white matter characteristics of visual artists (VAs) in terms of visual creativity and the structural connectivity within the cortical visual system.

Methods

Diffusion spectrum imaging was utilized to examine the changes in white matter within the cortical visual system of a group of VAs (n = 25) in comparison to a group of healthy controls matched for age and education (n = 24). To assess the integrity of white matter and its relationship with visual creativity, we conducted a comprehensive analysis using region-based and track-specific tractographic examinations.

Results

Our study uncovered that VAs demonstrated increased normalized quantitative anisotropy in specific brain regions, including the right inferior temporal gyrus and right lateral occipital gyrus, along with the corresponding white matter fiber tracts connecting these regions. These enhancements within the cortical visual system were also found to be correlated with measures of visual creativity obtained through psychological assessments.

Discussion

The noted enhancement in the white matter within the cortical visual system of VAs, along with its association with visual creativity, is consistent with earlier research demonstrating heightened functional connectivity in the same system among VAs. Our study's findings suggest a link between the visual creativity of VAs and structural alterations within the brain's visual system.

A prospective study of MRI biomarkers in the brain and lower limb muscles for prediction of lower limb motor recovery following stroke

The aim of this prospective observational longitudinal study was to explore and decipher the predictive value of prospective MRI biomarkers in the brain and lower limb muscles for 3-month lower limb motor recovery following stroke. In the brain, we measured the integrity of the corticospinal tract (fractional anisotropy/"FA"). In the muscles, we measured volume, fatty replacement (fat fraction analysis and proton spectroscopy) and oedema. Measurements were taken at two time points: (1) within 4 weeks of stroke (baseline measurement, clinical and imaging) and (2) 3 months following stroke (follow up measurement, clinical only). Clinical measurements consisted of assessments of functional ability and strength (Fugl-Meyer score, motor NIHSS, Functional Ambulation Category/"FAC", and muscle dynamometry). Twenty-three patients completed imaging and clinical assessments at baseline and follow-up; five patients had partial imaging assessment. The results provided some evidence that damage to the corticospinal tract would result in less motor recovery: recovery of the Fugl-Meyer score and dynamometric ankle plantarflexion, ankle dorsiflexion, and knee extension correlated positively and significantly with fractional anisotropy (0.406-0.457; p = 0.034-p = 0.016). However, fractional anisotropy demonstrated a negative correlation with recovery of the Functional Ambulation Category (-0.359, p = 0.046). For the muscle imaging, significant inverse correlation was observed between vastus lateralis fat fraction vs. NIHSS recovery (-0.401, p = 0.04), and a strong positive correlation was observed between ratio of intra- to extra-myocellular lipid concentrations and the recovery of knee flexion (0.709, p = 0.007). This study supports previous literature indicating a positive correlation between the integrity of the corticospinal tract and motor recovery post-stroke, expanding the limited available literature describing this relationship specifically for the lower limb. However, recovery of functional ambulation behaved differently to other clinical recovery markers by demonstrating an inverse relationship with corticospinal tract integrity. The study also introduces some muscle imaging biomarkers as potentially valuable in the prediction of 3-month lower limb motor recovery following stroke.

Structural Fingerprinting of the Frontal Aslant Tract: Predicting Cognitive Control Capacity and Obsessive-Compulsive Symptoms

White matter of the human brain is influenced by common genetic variations and shaped by neural activity-dependent experiences. Variations in microstructure of cerebral white matter across individuals and even across fiber tracts might underlie differences in cognitive capacity and vulnerabilities to mental disorders. The frontoparietal and cingulo-opercular networks of the brain constitute the central system supporting cognitive functions, and functional connectivity of these networks has been used to distinguish individuals known as "functional fingerprinting." The frontal aslant tract (FAT) that passes through the two networks has been implicated in executive functions. However, whether FAT can be used as a "structural fingerprint" to distinguish individuals and predict an individual's cognitive function and dysfunction is unknown. Here we investigated the fingerprinting property of FAT microstructural profiles using three independent diffusion MRI datasets with repeated scans on human participants including both females and males. We found that diffusion and geometric profiles of FAT can be used to distinguish individuals with a high accuracy. Next, we demonstrated that fractional anisotropy in different FAT segments predicted distinct cognitive functions, including working memory, inhibitory control, and relational reasoning. Finally, we assessed the contribution of altered FAT microstructural profiles to cognitive dysfunction in unmedicated patients with obsessive-compulsive disorders. We found that the altered microstructure in FAT was associated with the severity of obsessive-compulsive symptoms. Collectively, our findings suggest that the microstructural profiles of FAT can identify individuals with a high accuracy and may serve as an imaging marker for predicting an individual's cognitive capacity and disease severity.SIGNIFICANCE STATEMENT The frontoparietal network and cingulo-opercular network of the brain constitute a dual-network architecture for human cognitive functions, and functional connectivity of these two networks can be used as a "functional fingerprint" to distinguish individuals. However, the structural underpinnings of these networks subserving individual heterogeneities in their functional connectivity and cognitive ability remain unknown. We show here that the frontal aslant tract (FAT) that passes through the two networks distinguishes individuals with a high accuracy. Further, we demonstrate that the diffusion profiles of FAT predict distinct cognitive functions in healthy subjects and are associated with the clinical symptoms in patients with obsessive-compulsive disorders. Our findings suggest that the FAT may serve as a unique structural fingerprint underlying individual cognitive capability.

A preliminary study on corticospinal tract morphology in incidental and symptomatic insular low-grade glioma: implications for post-surgical motor outcomes

OBJECTIVE

Our study aimed to investigate the shape and diffusion properties of the corticospinal tract (CST) in patients with insular incidental and symptomatic low-grade gliomas (LGGs), especially those in the incidental group, and evaluate their association with post-surgical motor function.

METHODS

We performed automatic fiber tracking on 41 LGG patients, comparing macroscopic shape and microscopic diffusion properties of CST between ipsilateral and contralateral tracts in both incidental and symptomatic groups. A correlation analysis was conducted between properties of CST and post-operative motor strength grades.

RESULTS

In the incidental group, no significant differences in mean diffusion properties were found between bilateral CST. While decreased anisotropy of the CST around the superior limiting sulcus and increased axial diffusivity of the CST near the midbrain level were noted, there was no significant correlation between pre-operative diffusion metrics and post-operative motor strength. In comparison, we found significant correlations between the elongation of the affected CST in the preoperative scans and post-operative motor strength in short-term and long-term follow ups (p = 1.810 × 10-4 and p = 9.560 × 10-4, respectively).

CONCLUSIONS

We found a significant correlation between CST shape measures and post-operative motor function outcomes in patients with incidental insular LGGs. CST morphology shows promise as a potential prognostic factor for identifying functional deficits in this patient population.

Identifying the white matter pathways involved in multiple sclerosis-related tremor using diffusion tensor imaging

Background

Tremor affects up to 45% of patients with Multiple Sclerosis (PwMS). Current understanding is based on insights from other neurological disorders, thus, not fully addressing the distinctive aspects of MS pathology.

Objective

To characterize the brain white matter (WM) correlates of MS-related tremor using diffusion tensor imaging (DTI).

Methods

In a prospective case-control study, PwMS with tremor were assessed for tremor severity and underwent MRI scans including DTI. PwMS without tremor served as matched controls. After tract selection and segmentation, the resulting diffusivity measures were used to calculate group differences and correlations with tremor severity.

Results

This study included 72 PwMS. The tremor group (n = 36) exhibited significant changes in several pathways, notably in the right inferior longitudinal fasciculus (Cohen's d = 1.53, q < 0.001) and left corticospinal tract (d = 1.32, q < 0.001), compared to controls (n = 36). Furthermore, specific tracts showed a significant correlation with tremor severity, notably in the left medial lemniscus (Spearman's coefficient [rsp] = -0.56, p < 0.001), and forceps minor of corpus callosum (rsp = -0.45, p < 0.01).

Conclusion

MS-related tremor is associated with widespread diffusivity changes in WM pathways and its severity correlates with commissural and sensory projection pathways, which suggests a role for proprioception or involvement of the dentato-rubro-olivary circuit.