A comprehensive investigation of the associations between tensor-based morphometry indices and executive functions, memory, language, and visuospatial abilities in patients in the Alzheimer's disease continuum.

OBJECTIVES: Based on the literature, tensor-based morphometry (TBM) parameters were related to neurocognitive functions such as memory, learning, language ability, and executive functions. The present study aims to evaluate the associations between TBM indices with executive functions, memory, language, and visuospatial abilities and the value of TBM in the clinical diagnosis of Alzheimer's disease (AD) among individuals with Alzheimer's disease continuum and mild cognitive impairment (MCI) from Alzheimer's Disease Neuroimaging Initiative (ADNI). METHODS: The authors used ADNI-memory (ADNI-MEM), ADNI-executive functions (ADNI-EF), ADNI-language (ADNI-LAN), and ADNI-visuospatial (ADNI-VS) composite scores. TBM parameters, including measure 1, which represents average within a statistically defined region-of-interest inside the temporal lobes and measure 2 which indicates average within an anatomically defined region-of-interest including bilateral temporal lobes were utilized in the current study. Statistical analysis was performed using IBM SPSS Statistics version 26, and Pearson's correlation, Bonferroni's correction, and multiple linear regression were utilized for data analysis. P <0.05 was considered statistically significant. RESULTS: After screening 800 participants, 270 (151 men, 119 women) were selected for a study with TBM scores and cognition-related assessments at 6, 12, and 24 months. Groups included healthy controls (n=53), MCI (n=158), and Alzheimer's Disease (AD) (n=59). TBM indices correlated with cognitive scores in MCI and AD groups but not healthy controls. Changes in TBM indices and cognitive scores were significantly correlated in MCI and AD groups over 24 months. TBM indices were weak predictors of cognitive decline at all time points. CONCLUSIONS: TBM can help physicians diagnose MCI and AD early. However, TBM could not strongly predict cognitive functions decline at all time points.

Modeling electrical impedance in brain tissue with diffusion tensor imaging for functional neurosurgery applications.

Objective.Decades ago, neurosurgeons used electrical impedance measurements in the brain for coarse intraoperative tissue differentiation. Over time, these techniques were largely replaced by more refined imaging and electrophysiological localization. Today, advanced methods of diffusion tensor imaging (DTI) and finite element method (FEM) modeling may permit non-invasive, high-resolution intracerebral impedance prediction. However, expectations for tissue-impedance relationships and experimentally verified parameters for impedance modeling in human brains are lacking. This study seeks to address this need.Approach.We used FEM to simulate high-resolution single- and dual-electrode impedance measurements along linear electrode trajectories through (1) canonical gray and white matter tissue models, and (2) selected anatomic structures within whole-brain patient DTI-based models. We then compared intraoperative impedance measurements taken at known locations along deep brain stimulation (DBS) surgical trajectories with model predictions to evaluate model accuracy and refine model parameters.Main results.In DTI-FEM models, single- and dual-electrode configurations performed similarly. While only dual-electrode configurations were sensitive to white matter fiber orientation, other influences on impedance, such as white matter density, enabled single-electrode impedance measurements to display significant spatial variation even within purely white matter structures. We compared 308 intraoperative single-electrode impedance measurements in five DBS patients to DTI-FEM predictions at one-to-one corresponding locations. After calibration of model coefficients to these data, predicted impedances reliably estimated intraoperative measurements in all patients (R=0.784±0.116, n=5). Through this study, we derived an updated value for the slope coefficient of the DTI conductance model published by Tuch et al., k=0.0649 S·s/mm3(original k=0.844), for use specifically in humans at physiological frequencies.Significance.This is the first study to compare impedance estimates from imaging-based models of human brain tissue to experimental measurements at the same locations in vivo. Accurate, non-invasive, imaging-based impedance prediction has numerous applications in functional neurosurgery, including tissue mapping, intraoperative electrode localization, and DBS.

Increased extracellular free water is related to white matter hyperintensity burden.

BACKGROUND: Extracellular free water (FW) has important roles in the occurrence and development of white matter hyperintensity (WMH). PURPOSE: To explore the correlations between FW and WMH burden. MATERIAL AND METHODS: A prospective analysis was conducted using magnetic resonance imaging (MRI) data from 126 individuals. WMH burden was determined based on WMH volumes and Fazekas scores from deep and periventricular white matter hyperintensity (DWMH and PWMH, respectively) in fluid-attenuated inversion recovery (FLAIR) images. FW values were taken from diffusion tensor imaging (DTI). RESULTS: Univariate analysis showed that FW values were correlated with WMH burden, including WMH volumes and DWMH and PWMH Fazekas scores (P < 0.05). After multivariate analysis, FW values were correlated with WMH volumes and DWMH and PWMH Fazekas scores when adjusted for age and hypertension (P < 0.05). CONCLUSION: Using MRI, increasing extracellular FW was related to WMH burden.

Pre- and post-skeletal muscle biopsy quantitative magnetic resonance imaging reveals correlations with histopathological findings.

BACKGROUND AND PURPOSE: Quantitative muscle magnetic resonance imaging (MRI) is a promising non-invasive method in the diagnostic workup as well as follow-up of neuromuscular disorders. The aim of this study was to correlate quantitative MRI (qMRI) parameters to histopathological changes in skeletal muscle tissue and thus to verify the data from our pilot study. METHODS: Twenty-six patients (eight females, 46.4 ± 15.1 years) were examined within 72 h before and within 24 h after a skeletal muscle biopsy using quantitative muscle MRI. Post-biopsy MRI was employed to pinpoint the exact localization of the biopsy. qMRI parameters including fat fraction, water T2 relaxation time and diffusion metrics including fractional anisotropy, mean diffusivity, axial diffusivity and radial diffusivity were extracted from the localization of the biopsy and correlated with histopathological findings. Additionally, three different segmentation masks were applied to the qMRI dataset, to evaluate whether the whole muscle represents the exact biopsy location. RESULTS: Fat fraction and water T2 relaxation time in qMRI correlated significantly with the fat fraction in the muscle biopsy and histopathological inflammatory markers. Fractional anisotropy correlated with the quantity of type 2 fibres, whilst mean diffusivity correlated with p62. No differences were found using different segmentation masks in qMRI. CONCLUSIONS: In this follow-up study, the results from our previous study were verified regarding the correlation of qMRI parameters with histopathological features in muscle biopsies, indicating that qMRI serves as a suitable non-invasive method in the follow-up of patients with neuromuscular disorders. If post-biopsy MRI is not available, whole muscle volume can be used for histopathological correlations.

Glymphatic System Impairment in the Advanced Stage of Moyamoya Disease.

Assessing the glymphatic system activity using diffusion tensor imaging analysis along with the perivascular space (DTI-ALPS) may be helpful to understand the pathophysiology of moyamoya disease (MMD). 63 adult patients with MMD and 20 healthy controls (HCs) were included for T1-weighted images, T2-FLAIR, pseudocontinuous arterial spin labeling, and DTI. 60 patients had digital subtraction angiography more than 6 months after combined revascularization. The Suzuki stage, postoperative Matsushima grade, periventricular anastomoses (PA), enlarged perivascular spaces (EPVS), deep and subcortical white matter hyperintensities (DSWMH), DTI-ALPS, cerebral blood flow (CBF), and cognitive scales of MMD patients were assessed. MMD patients were divided into early and advanced stage based on the Suzuki stage. We detected lower DTI-ALPS in patients with advanced stage relative to HCs (p = 0.046) and patients with early stage (p = 0.004), hemorrhagic MMD compared with ischemic MMD (p = 0.048), and PA Grade 2 compared with Grade 0 (p = 0.010). DTI-ALPS was correlated with the EPVS in basal ganglia (r = -0.686, p < 0.001), Suzuki stage (r = -0.465, p < 0.001), DSWMH (r = -0.423, p = 0.001), and global CBF (r = 0.300, p = 0.017) and cognitive scores (r = 0.343, p = 0.018). The DTI-ALPS of patients with good postoperative collateral formation was higher compared to those with poor postoperative collateral formation (p = 0.038). In conclusion, the glymphatic system was impaired in advanced MMD patients and may affected cognitive function and postoperative neoangiogenesis.

The effect of subthalamic nucleus deep brain stimulation on speech performance: a prospective clinical and tractography study.

BACKGROUND: Speech changes significantly impact the quality of life for Parkinson's disease (PD) patients. Deep Brain Stimulation (DBS) of the Subthalamic Nucleus (STN) is a standard treatment for advanced PD, but its effects on speech remain unclear. This study aimed to investigate the relationship between STN-DBS and speech changes in PD patients using comprehensive clinical assessments and tractography. METHODS: Forty-seven PD patients underwent STN-DBS, with preoperative and 3-month postoperative assessments. Speech analyses included acoustic measurements, auditory-perceptual evaluations, and fluency-intelligibility tests. On the other hand, structures within the volume tissue activated (VTA) were identified using MRI and DTI. The clinical and demographic data and structures associated with VTA (Corticospinal tract, Internal capsule, Dentato-rubro-thalamic tract, Medial forebrain bundle, Medial lemniscus, Substantia nigra, Red nucleus) were compared with speech analyses. RESULTS: The majority of patients (36.2-55.4% good, 29.7-53.1% same) exhibited either improved or unchanged speech quality following STN-DBS. Only a small percentage (8.5-14.9%) experienced deterioration. Older patients and those with worsened motor symptoms postoperatively were more likely to experience negative speech changes (p < 0.05). Interestingly, stimulation of the right Substantia Nigra correlated with improved speech quality (p < 0.05). No significant relationship was found between other structures affected by VTA and speech changes. CONCLUSIONS: This study suggests that STN-DBS does not predominantly negatively impact speech in PD patients, with potential benefits observed, especially in younger patients. These findings underscore the importance of individualized treatment approaches and highlight the need for further long-term studies to optimize therapeutic outcomes and better understand the effects of STN-DBS on speech.

Automatic generation of diffusion tensor imaging for the lumbar nerve using convolutional neural networks.

【PURPOSE】: Diffusion Tensor Imaging (DTI) with tractography is useful for the functional diagnosis of degenerative lumbar disorders. However, it is not widely used in clinical settings due to time and health care provider costs, as it is performed manually on hospital workstations. The purpose of this study is to construct a system that extracts the lumbar nerve and generates tractography automatically using deep learning semantic segmentation. 【METHODS】: We acquired 839 axial diffusion weighted images (DWI) from the DTI data of 90 patients with degenerative lumbar disorders, and segmented the lumbar nerve roots using U-Net, a semantic segmentation model. Using five architectural models, the accuracy of the lumbar nerve root segmentation was evaluated using a Dice coefficient. We also created automatic scripts from three commercially available software tools, including MRICronGL for medical image viewing, Diffusion Toolkit for reconstruction of the DWI data, and Trackvis for the creation of the tractography, and compared the time required to create the tractography, and evaluated the quality of the automated tractography was evaluated. 【RESULTS】: Among the five models, the architectural model Resnet34 performed the best with a Dice = 0.780. The creation time for the automatic lumbar nerve tractography was 191 s, which was significantly shorter by 235 s than the manual time of 426 s (p < 0.05). Furthermore, the agreement between manual and automated tractography was 3.67 ± 1.53 (satisfactory). 【CONCLUSIONS】: Using deep learning semantic segmentation, we were able to construct a system that automatically extracted the lumbar nerve and generated lumbar nerve tractography. This technology makes it possible to analyze lumbar nerve DTI and create tractography automatically, and is expected to advance the clinical applications of DTI for the assessment of the lumbar nerve.

Assessment of renal pathophysiological processes and protective effect of quercetin on contrast-induced acute kidney injury in type 1 diabetic mice using diffusion tensor imaging.

Purpose: To investigate the renal pathophysiological processes and protective effect of quercetin on contrast-induced acute kidney injury (CI-AKI) in mice with type 1 diabetic mellitus(DM) using diffusion tensor imaging(DTI).Methods: Mice with DM were divided into two groups. In the diabetic + contrast medium(DCA) group, the changes of the mice kidneys were monitored at 1, 24, 48, and 72 h after the injection of iodixanol(4gI/kg). The mice in the diabetic + contrast medium + quercetin(DCA + QE) group were orally given different concentrations of quercetin for seven days before injection of iodixanol. In vitro experiments, renal tubular epithelial (HK-2) cells exposed to high glucose conditions were treated with various quercetin concentrations before treatment with iodixanol(250 mgI/mL).Results: DTI-derived mean diffusivity(MD) and fractional anisotropy(FA) values can be used to evaluate CI-AKI effectively. Quercetin significantly increased the expression of Sirt 1 and reduced oxidative stress by increasing Nrf 2/HO-1/SOD1. The antiapoptotic effect of quercetin on CI-AKI was revealed by decreasing proteins level and by reducing the number of apoptosis-positive cells. In addition, flow cytometry indicated quercetin-mediated inhibition of M1 macrophage polarization in the CI-AKI.Conclusions: DTI will be an effective noninvasive tool in diagnosing CI-AKI. Quercetin attenuates CI-AKI on the basis of DM through anti-oxidative stress, apoptosis, and inflammation.

High-Precision Determination of NMR Interaction Parameters by Measurement of Single Crystals: A Review of Classical and Advanced Methods.

In this review, the process of extracting precise values for NMR interaction tensors from single crystal samples is systematically explored. Starting with a description of the orientation dependence of the considered interactions, i.e., chemical shift, dipolar, and quadrupole interaction, the techniques for acquiring and analysing single-crystal spectra are outlined. This includes the 'classical' approach, which requires the acquisition of three rotation patterns around three rotation axes that are orthogonal to each other, as well as more recent strategies aimed at reducing the number of required NMR spectra. One such strategy is the 'single-rotation method', which exploits the symmetry relations between tensors in the crystal structure to reduce the necessary amount of orientation-dependent data. This concept may be extended to additionally include the orientation of the goniometer axis itself in the data fit, which may be termed the 'minimal-rotation method'. Other, more exotic schemes, such as the use of specialised probe designs or the investigation of single crystals under magic-angle-spinning, are also briefly discussed. Actual values of NMR interaction tensors as determined from the various single-crystal methods have been collected and are provided in tables for spin I=1/2, I=1, and half-integer spins with I>1/2.

Imaging evaluation focused on microstructural tissue changes using tensor-valued diffusion encoding in breast cancers after neoadjuvant chemotherapy: is it a promising way forward?

Background: Single diffusion encoding is a widely used, noninvasive technique for probing the tissue microstructure in breast tumors. However, it does not provide detailed information about the microenvironmental complexity. This study investigated the clinical utility of tensor-valued diffusion encoding for evaluating microstructural changes in breast cancer after neoadjuvant chemotherapy (NAC). Methods: We retrospectively included patients underwent chemotherapy for histologically proven invasive breast cancer between July 2020 and June 2023 and monitored the tumor response with breast magnetic resonance imaging (MRI), including tensor-valued diffusion encoding. We reviewed pre- and post-NAC MRIs regarding chemotherapy in 23 breast cancers. Q-space trajectory imaging (QTI) parameters were estimated at each time-point, and were compared with histopathological parameters. Results: The mean total mean kurtosis (MKT), anisotropic mean kurtosis (MKA), and microscopic fractional anisotropy (µFA) were significantly decreased on post-NAC MRI compared with pre-NAC MRI, with the large effect size (ES) in MKA and µFA (0.81±0.41 vs. 0.99±0.33, ES: 0.48, P=0.03; 0.48±0.30 vs. 0.73±0.27, ES: 0.88, P<0.001; 0.58±0.14 vs. 0.68±0.11, ES: 0.79, P=0.003; respectively). Regarding prognostic factors, tumors with high Ki-67 expression showed significantly lower pre-NAC mean diffusivity (MD) and higher pre-NAC µFA compared to tumors with low Ki-67 expression (0.98±0.09 vs. 1.25±0.20, P=0.002; and 0.72±0.07 vs. 0.57±0.10, P=0.005; respectively). And negative progesterone receptor (PR) group revealed significantly lower MKT, MKA, and isotropic mean kurtosis than positive PR group on the post-NAC MRI (0.60±0.31 vs. 1.03±0.40, P=0.008; 0.36±0.21 vs. 0.61±0.33, P=0.04; and 0.23±0.17 vs. 0.42±0.25, P=0.046; respectively). Conclusions: QTI parameters reflected the microstructural changes in breast cancer treated with NAC and can be used as noninvasive imaging biomarkers correlated with prognostic factors.

Prenatal tobacco and alcohol exposure, white matter microstructure, and early language skills in toddlers from a South African birth cohort.

Introduction: Tobacco and alcohol are the two most common substances used during pregnancy, and both can disrupt neurodevelopment, resulting in cognitive and behavioral deficits including language difficulties. Previous studies show that children with prenatal substance exposure exhibit microstructural alterations in major white matter pathways, though few studies have investigated the impact of prenatal substance exposure on white matter microstructure and language skills during the toddler years. Methods: In this study, 93 children (34 exposed to alcohol and/or tobacco) aged 23 years from the Drakenstein Child Health Study, South Africa, completed Expressive and Receptive Communication assessments from the Bayley Scales of Infant and Toddler Development, Third Edition (BSID-III) and underwent diffusion MRI scans. Diffusion images were preprocessed, and 11 major white matter tracts were isolated. Fractional anisotropy (FA) and mean diffusivity (MD) were extracted for each white matter tract. Linear regression was used to examine differences between the tobacco/alcohol exposed group and unexposed controls for FA, MD, and language scores, as well as relationships between brain metrics and language. There were no significant group differences in language scores or FA. Results: Children with alcohol or tobacco exposure had lower average MD in the splenium of the corpus callosum compared to unexposed controls. Significant interactions between prenatal substance exposure and language scores were seen in 7 tracts but did not survive multiple comparisons correction. Discussion: Our findings show that prenatal alcohol and/or tobacco exposure appear to alter the relationship between white matter microstructure and early language skills in this population of toddlers, potentially laying the basis of language deficits observed later in older children with prenatal substance exposure, which may have implications for learning and interventions.

Microstructural Changes in the Corpus Callosum in Neurodegenerative Diseases.

The corpus callosum, the largest white matter structure in the brain, plays a crucial role in interhemispheric communication and cognitive function. This review examines the microstructural changes observed in the corpus callosum across various neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, Huntington's disease, and amyotrophic lateral sclerosis (ALS). New neuroimaging studies, mainly those that use diffusion tensor imaging (DTI) and advanced tractography methods, were put together to show how changes have happened in the organization of white matter and the connections between them. Some of the most common ways the corpus callosum breaks down are discussed, including less fractional anisotropy, higher mean diffusivity, and atrophy in certain regions. The relationship between these microstructural changes and cognitive decline, motor dysfunction, and disease progression is explored. Additionally, we consider the potential of corpus callosum imaging as a biomarker for early disease detection and monitoring. Studies show that people with these disorders have lower fractional anisotropy and higher mean diffusivity in the corpus callosum, often in ways that are specific to the disease. These changes often happen before gray matter atrophy and are linked to symptoms, which suggests that the corpus callosum could be used as an early sign of neurodegeneration. The review also highlights the implications of these findings for understanding disease mechanisms and developing therapeutic strategies. Future directions, including the application of advanced imaging techniques and longitudinal studies, are discussed to elucidate the role of corpus callosum degeneration in neurodegenerative processes. This review underscores the importance of the corpus callosum in understanding the pathophysiology of neurodegenerative diseases and its potential as a target for therapeutic interventions.

In vivo cardiac diffusion tensor imaging on an MR system featuring ultrahigh performance gradients with 200 mT/m maximum gradient strength.

PURPOSE: Our aim is to assess the potential of an MR system with ultrahigh performance gradients (200 mT/m maximum gradient strength) to address two interrelated challenges in cardiac DTI: low SNR and sensitivity to bulk motion. METHODS: Imaging was performed in 20 healthy volunteers, two patients, and one swine post-myocardial infarction. The impact of maximum gradient strength was assessed with spin echo cardiac DTI featuring second-order motion compensation and varying maximum system gradient strengths (40, 80, 200 mT/m). Motion compensation requirements at 200 mT/m were assessed with sequences featuring zeroth-, first-, and second-order motion compensation. SNR, mean diffusivity, fractional anisotropy, helix angle transmurality, and secondary eigenvector angle in the left ventricle were compared. RESULTS: Increasing maximum system gradient strength from 40 and 80 mT/m to 200 mT/m increased SNR of b = 500 s/mm2 images by 150% and 40% due to reductions in TE. Observed improvements in DTI metrics included reduction in variance in mean diffusivity and helix angle transmurality across healthy volunteers, improved visualization of myocardial borders and delineation of suspected scar. Whereas second-order motion compensation acquisitions were robust to motion-induced signal dropout, zeroth- and first-order motion compensation acquisitions suffered from severe signal loss and localized signal voids, respectively. CONCLUSION: Ultrahigh performance gradients (200 mT/m) enable high SNR DWIs of the heart and resultant improvements in diffusion tensor metrics. Despite reduced diffusion-encoding duration, second-order motion compensation is required to overcome sensitivity to cardiac motion.

Thalamic-limbic circuit dysfunction and white matter topological alteration in Parkinson's disease are correlated with gait disturbance.

Background: Limbic structures have recently garnered increased attention in Parkinson's disease (PD) research. This study aims to explore changes at the whole-brain level in the structural network, specifically the white matter fibres connecting the thalamus and limbic system, and their correlation with the clinical characteristics of patients with PD. Methods: Between December 2020 and November 2021, we prospectively enrolled 42 patients with PD and healthy controls at the movement disorder centre. All participants underwent diffusion tensor imaging (DTI), 3D T1-weighted imaging (3D-T1WI), and routine brain magnetic resonance imaging on a 3.0 T MR scanner. We employed the tract-based spatial statistical (TBSS) analytic approach, examined structural network properties, and conducted probabilistic fibre tractography to identify alterations in white matter pathways and the topological organisation associated with PD. Results: In patients with PD, significant changes were observed in the fibrous tracts of the prefrontal lobe, corpus callosum, and thalamus. Notably, the fibrous tracts in the prefrontal lobe and corpus callosum showed a moderate negative correlation with the Freezing of Gait Questionnaire (FOG-Q) scores (r = -0.423, p = 0.011). The hippocampus and orbitofrontal gyrus exhibited more fibre bundle parameter changes than other limbic structures. The mean streamline length between the thalamus and the orbitofrontal gyrus demonstrated a moderate negative correlation with Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) III (r = -0.435, p = 0.006). Topological parameters, including characteristic path length (L p), global efficiency (E g), normalised shortest path length (λ) and nodal local efficiency (N le), correlated moderately with the MDS-UPDRS, HAMA, MoCA, PDQ-39, and FOG-Q, respectively. Conclusion: DTI is a valuable tool for detecting changes in water molecule dispersion and the topological structure of the brain in patients with PD. The thalamus may play a significant role in the gait abnormalities observed in PD.

Soft tissue elasticity in total knee arthroplasty: An in vivo quantitative analysis.

BACKGROUND: Soft tissue balance is essential for total knee arthroplasty success. The elastic properties of soft tissues affect knee-joint stability and flexibility. This study proposed a novel methodology for in vivo quantitative analysis of soft tissue elasticity during total knee arthroplasty. In this study, we aimed to (1) establish a mathematical model to depict medial and lateral soft tissue elasticity, (2) report the individual differences and interindividual commonalities in soft tissue elasticity. METHODS: A specifically designed knee tensor was used to evaluate soft tissue elasticity by dynamically applying sequential tensions to medial and lateral compartments while measuring knee joint gaps in both compartments. Measurements were performed on ten knees of six cadavers. Bivariate polynomial regression was used for analysis, and the equivalent elastic coefficient (N/mm) was calculated. FINDINGS: Soft-tissue elasticity showed high individual differences. The equivalent elastic coefficient was larger in the medial compartment than in the lateral compartment, and the equivalent elastic coefficient of the lateral compartment gradually decreased while the medial equivalent elastic coefficient remained constant when the knee was flexed. The lateral gaps increased from 0.1 to 3.9 mm, and the medial gaps increased from 0 to 1.5 mm when the tension increased from 60 to 90 N. The shapes and distributions of the silkworm-like lattices in elasticity and balance evaluations are clinically relevant to knee balance. INTERPRETATION: Soft-tissue balance in total knee arthroplasty is significantly affected by soft-tissue elasticity. An intraoperative quantitative analysis of elasticity helps to tail an individualized balancing target for total knee arthroplasty.

Outcome Prediction by Diffusion Tensor Imaging (DTI) in Patients with Traumatic Injuries of the Median Nerve.

Background/Objectives: The accurate quantification of peripheral nerve axonal regeneration after injury is critically important. Current strategies are limited to detecting early reinnervation. DTI is an MRI modality permitting the assessment of fractional anisotropy, which increases with axonal regeneration. The aim of this pilot study is to evaluate DTI as a potential predictive factor of clinical outcome after median nerve section and microsurgical repair. Methods: We included 10 patients with a complete section of the median nerve, who underwent microsurgical repair up to 7 days after injury. The follow-up period was 1 year, including the current strategy with clinical visits, the Rosén-Lundborg score and electroneuromyography. Additionally, DTI MRI of the injured wrist was planned 1, 3 and 12 months post-operatively and once for the contralateral wrist. Results: The interobserver reliability of DTI measures was almost perfect (ICC 0.802). We report an early statistically significant increase in the fractional anisotropy value after median nerve repair, especially in the region located distal to the suture. Meanwhile, Rosén-Lundborg score gradually increased between the third and sixth month, and continued to increase between the sixth and twelfth month. Conclusions: DTI outcomes three months post-operation could offer greater predictability compared to current strategies. This would enable faster decision-making regarding the need for a potential re-operation in cases of inadequate early reinnervation.

Integrative MR Imaging Interpretation in Cognitive Impairment with Alzheimer's Disease, Small Vessel Disease, and Glymphatic Function-Related MR Parameters.

RATIONALE AND OBJECTIVES: The role of MR imaging in patients with cognitive impairment is to evaluate each component of Alzheimer's disease (AD), small vessel disease (SVD), and glymphatic function. We want to validate the diagnostic performance of the comprehensive interpretation of these parameters to predict the cognitive impairment stage. MATERIALS AND METHODS: This retrospective single-center study included 359 patients with cognitive impairment who had undergone MRI (FLAIR, T2WI, 3D-T1WI, susceptibility-weighted imaging, and diffusion tensor imaging [DTI]) and a neuropsychological screening battery between January 2020 and July 2022. Each AD and SVD-related MR parameter was visually evaluated, and DTI analysis along the perivascular space (ALPS) index was calculated. Volumetry analysis was performed using Neurophet AQUA AI-based software. Using logistic regression analysis, four types of models were developed and compared by adding the components in the following order: (1) clinical factors and AD, (2) SVD, (3) glymphatic function-related MR parameters, and (4) volumetric data. Chi-square automatic interaction detection algorithm was used to develop diagnostic tree analysis (DTA) model to predict late-stage cognitive impairment. RESULTS: APOE4 status, years of education, medial temporal lobe atrophy score, Fazekas scale score, DTI-ALPS index, and white matter hyperintensity were significant predictors of late-stage cognitive impairment. The performance of the prediction model increased from Model 1 to Model 4 (AUC: 0.880, 0.899, 0.914, and 0.945, respectively). The overall accuracy of the DTA model was 87.47%. CONCLUSION: Integrative brain MRI assessments in patients with cognitive impairment, AD, SVD, and glymphatic function-related MR parameters, improve the prediction of late-stage cognitive impairment.

Similarity and characterization of structural and functional neural connections within species under isoflurane anesthesia in the common marmoset.

The common marmoset is an essential model for understanding social cognition and neurodegenerative diseases. This study explored the structural and functional brain connectivity in a marmoset under isoflurane anesthesia, aiming to statistically overcome the effects of high inter-individual variability and noise-related confounds such as physiological noise, ensuring robust and reliable data. Similarities and differences in individual subject data, including assessments of functional and structural brain connectivities derived from resting-state functional MRI and diffusion tensor imaging were meticulously captured. The findings highlighted the high consistency of structural neural connections within the species, indicating a stable neural architecture, while functional connectivity under anesthesia displayed considerable variability. Through independent component and dual regression analyses, several distinct brain connectivities were identified, elucidating their characteristics under anesthesia. Insights into the structural and functional features of the marmoset brain from this study affirm its value as a neuroscience research model, promising advancements in the field through fundamental and translational studies.

Atrophy in the supramarginal gyrus associated with impaired cognitive inhibition in grieving Chinese Shidu parents.

Background: The loss of an only child, known as Shidu in China, is a profoundly distressing experience, often leading to Prolonged Grief Disorder (PGD). Despite its impact, the structural brain alterations associated with PGD, potentially influencing cognitive impairments in Shidu parents, remain understudied.Objective: This study aims to identify brain structural abnormalities related to prolonged grief and their relation with cognitive inhibition in Shidu parents.Methods: The study included 40 Shidu parents and 42 non-bereaved participants. Prolonged grief was evaluated using the Prolonged Grief Questionnaire (PG-13). We employed voxel-based morphometry (VBM) and diffusion tensor imaging (DTI) to assess brain structural alterations and their correlation with cognitive inhibition, as measured by Stroop interference scores.Results: Findings suggest that greater prolonged grief intensity correlates with reduced grey matter volume in the right amygdala and the left supramarginal gyrus (SMG). Additionally, enhanced amygdala-to-whole-brain structural connectivity showed a marginal association with prolonged grief, particularly with emotional-related symptoms. Furthermore, a decrease in SMG volume was found to mediate the relation between prolonged grief and Stroop Time Inference (TI) score, indicating an indirect effect of prolonged grief on cognitive inhibition.Conclusions: The study provides insight into the neural correlates of prolonged grief in Shidu parents, highlighting the SMG's role in cognitive inhibition. These findings emphasise the need for comprehensive grief interventions to address the complex cognitive and emotional challenges faced by this unique bereaved population.

The Shidu parents had a delay in cognitive inhibition when performing the Stroop test, compared to the control group.Prolonged grief intensity was linked to decreased grey matter in the right amygdala and a potential increase in amygdala-to-whole-brain structural connectivity. These volumes were associated with prolonged grief symptoms related to emotions.A higher level of prolonged grief was also associated with reduced grey matter volume in the left supramarginal gyrus, mediating the relationship between prolonged grief and Stroop Time Inference score, which indicates cognitive inhibition.

Analyzing language ability in first-episode psychosis and their unaffected siblings: A diffusion tensor imaging tract-based spatial statistics analysis study.

Schizophrenia (SZ) is a highly heritable mental disorder, and language dysfunctions play a crucial role in diagnosing it. Although language-related symptoms such as disorganized speech were predicted by the polygenic risk for SZ which emphasized the common genetic liability for the disease, few studies investigated possible white matter integrity abnormalities in the language-related tracts in those at familial high-risk for SZ. Also, their results are not consistent. In this current study, we examined possible aberrations in language-related white matter tracts in patients with first-episode psychosis (FEP, N = 20), their siblings (SIB, N = 20), and healthy controls (CON, N = 20) by applying whole-brain Tract-Based Spatial Statistics and region-of-interest analyses. We also assessed language ability by Thought and Language Index (TLI) using Thematic Apperception Test (TAT) pictures and verbal fluency to see whether the scores of these language tests would predict the differences in these tracts. We found significant alterations in language-related tracts such as inferior longitudinal fasciculus (ILF) and uncinate fasciculus (UF) among three groups and between SIB and CON. We also proved partly their relationship with the language test as indicated by the significant correlation detected between TLI Impoverished thought/language sub-scale and ILF. We could not find any difference between FEP and CON. These results showed that the abnormalities, especially in the ILF and UF, could be important pathophysiological vulnerability indexes of schizophrenia. Further studies are required to understand better the role of language as a possible endophenotype in schizophrenia with larger samples.