Diffusion Tensor Research Articles

Anisotropy boosting improves ODF-Fingerprinting tractography in edematous brain.

Peritumoral vasogenic edema of the brain is a major confounding factor for diffusion MRI tractography. Excessive fluids accumulated in edematous white matter decrease anisotropy of water self-diffusion which affects tracking algorithms. We address this hurdle with ODF-Fingerprinting (ODF-FP) - a dictionary-based fiber reconstruction algorithm that accommodates variability of neural tissue. By adding a regularization term to the ODF-FP matching formula, we boost diffusion anisotropy to improve white matter fiber identification in edematous regions.

Diffusion Tensor Imaging Findings in Cerebral Sensorimotor Areas in Patients After Spinal Cord Injury Correlate With Neurophysiological Deficits.

ObjectivesAssessment of sensorimotor cortex and tracts degeneration using novel diffusion tensor imaging (DTI) templates in patients with chronic spinal cord injury (SCI) and its correlation with clinical and neurophysiological findings.MethodsSex and age-matched 29 patients with chronic SCI (paraplegic: p-SCI; tetraplegic: t-SCI) and 29 healthy controls underwent neurophysiological assessment including motor evoked potentials (MEP). DTI was performed on 3 T magnetic resonance imaging scanner and postprocessed using Human Motor Area and Sensorimotor Area Tract Templates. DTI parameters were compared using analysis of covariance with post hoc Scheffé and Bonferroni corrections. Spearman's rank test was used for correlations with P < .05 considered significant.ResultsCompared to controls, all SCI patients showed significantly lower fractional anisotropy (FA) in several tracts (primary motor [M1], somatosensory [S1], pre-supplementary motor area [preSMA], and dorsal premotor [PMd]) and cortices (M1, pre-SMA, and S1). There were no differences in DTI parameters between p-SCI and t-SCI or p-SCI and controls. Compared to controls, t-SCI showed significantly decreased FA within M1 and S1 tracts. In t-SCI higher motor scores were associated with higher FA from ventral premotor area (PMv) tracts and cortex; higher sensory scores were associated with higher FA from S1 tracts. Positive correlations were found between MEP amplitudes from rectus femoris muscles and FA for M1, PMd, PMv, pre-SMA, SMA tracts, and PMv cortex.ConclusionsDTI shows remote degeneration of sensorimotor cortex and supraspinal tracts in SCI correlating with several clinical motor and sensory scores, and MEP parameters. DTI metrics have the potential to become biomarkers of remote degeneration.

Boundary Formation of the Human Caudal Foregut During the Early Fetal Period: Three-Dimensional Analysis Using T1-Weighted and Diffusion Tensor Images.

While caudal foregut development in human fetuses has been outlined in previous research, the formation of its border region remains unclear. This study aimed to visualize the precise timeline of caudal foregut boundary formation. Three-dimensional images of the foregut from T1-weighted scans of 24 fetuses (crown-rump length [CRL]: 34-103 mm) were analyzed to measure the wall thickness and lumen diameter at nine specific sites. The internal structure in the border region was verified using histological sections and diffusion tensor imaging (DTI) tractography. The lower esophageal and pyloric canal walls were thicker in samples with a CRL ≥50 mm. The esophageal wall at the esophageal hiatus, where the lower esophageal sphincter is located, was particularly thick in samples with a CRL ≥88 mm. Increased wall thickness at the esophageal hiatus and pyloric canal resulted in a narrower lumen. The pyloric canal lumen narrowed from its distal to proximal sections. The lumen diameter-to-wall thickness ratio at the esophageal hiatus and proximal pyloric was negatively correlated with CRL. The thickened esophageal wall at the esophageal hiatus had a thick submucosa, and all layers in the pyloric canal thickened with growth. DTI tractography revealed that the lower esophageal wall mainly comprised longitudinal fibers, whereas the pyloric canal wall consisted solely of circular fibers, with fractional anisotropy increasing with growth. This study provides a comprehensive timeline of normal caudal foregut boundary formation during the early human fetal period, thereby improving the understanding of congenital foregut obstruction pathogenesis.

Effective Macroscopic Equations for Biological Fluid and Nutrients' Transport in Vascularized Tumors Growing Via Proliferation and Chemotaxis

ABSTRACTThis paper presents a system of partial differential equations designed to model fluid and nutrient transport within the growing tumor microenvironment. The fluid phase, representing both cells and extracellular fluids flowing within the interstitial space, is assumed to be intrinsically incompressible, so that growth can be modeled as a source, generally defined by volumetric growth terms and nonconvective mass fluxes. Specifically, we consider the volumetric growth term proportional to the nutrient concentration and the nonconvective mass flux driven by the nutrient gradient. By exploiting the scale separation between the microscopic vascular structures and the larger tumor tissue, we employ asymptotic homogenization to derive effective macroscopic equations that integrate detailed microscale characteristics. The resulting model operates as a double porous medium framework, where fluid dynamics are driven by both pressure and concentration gradient, which reduces to a more standard Darcy's law when microscale variations of the convective mass flux are neglected. Nutrient transport is captured through a coupled advection–diffusion–reaction system. Permeability and diffusivity tensors, which encapsulate the influence of microvascular geometry, are computed via cell‐problem analysis to accurately reflect the microscale structure within the macroscopic model. Given that the tissue model includes a fluid phase that continually exchanges with the surrounding vasculature, along with nutrients, the Kedem–Katchalsky formulation is employed to represent fluid and nutrient transport across the capillary walls. This approach provides valuable insights into the interactions between vascular architecture and tumor growth. Although certain limitations remain, such as the static tumor domain and assumptions regarding cell proliferation, the framework offers a foundation for further development. It is adaptable for numerical simulations based on real tumor geometries, with promising potential to inform and improve anticancer treatment strategies through the integration of patient‐specific clinical data.

Exploring the Relationship Between White Matter Tracts and Resting-State Functional Language Lateralization Index

Resting-state functional magnetic resonance imaging (rs-fMRI) enables the evaluation of the language network and is particularly useful for measuring language lateralization with minimal participant effort and methodological biases (e.g., no language task execution or selection). Tractography using diffusion MRI (dMRI) provides complementary information on language-associated white matter bundles. Some structural white matter measures of the left or right hemisphere have been related to the functional language lateralization index (LI) and allow a better understanding of this network. This study utilizes tractography to identify white matter structural predictors of LI from a single hemisphere, employing linear regression and random forest models. Rs-fMRI and dMRI data from 618 healthy subjects of the Human Connectome Project were used to link LI to micro- and macro-structural measures of the arcuate fasciculi, the inferior longitudinal fasciculi, the frontal aslant tracts and sections of the corpus callosum. Results suggest a possible relationship between micro- and macro-structural measures of white matter tracts, and functional language lateralization measured in resting-state. However, the identified predictors are not sufficiently representative to be considered proxies for functional language lateralization. In conclusion, both micro- and macro-structural white matter characteristics as well as both left and right hemispheres are important to consider, but are not sufficient on their own, when investigating the relationship between brain structures and functional language lateralization.

Hand-arm bimanual intensive therapy versus modified constraint-induced movement therapy in children with hemiparetic cerebral palsy: A randomized controlled trial.

Hand-arm bimanual intensive therapy versus modified constraint-induced movement therapy in children with hemiparetic cerebral palsy: A randomized controlled trial.

Brain white matter development in 8-year-old children is associated with maternal mental health during pregnancy.

Maternal mental health during pregnancy can influence fetal brain development, yet its long-term effects remain unclear. This study investigates the association between prenatal maternal depression and anxiety symptoms and white matter microstructure in the limbic system of 8-year-old children. Fifty-one healthy pregnant women and typically developing 8-year-old children dyads were included in this prospective and longitudinal study. Maternal depression and anxiety symptoms were assessed at 12, 24, and 36 weeks of gestation using the Beck Depression Inventory-II (BDI-II) and State-Trait Anxiety Inventory (STAI). Their children underwent a brain MRI examination at age 8 years with multi-shell diffusion imaging analyzed using diffusion tensor imaging (DTI), diffusional kurtosis imaging (DKI), and neurite orientation dispersion and density imaging (NODDI) models for a multi-aspect evaluation of microstructural development. Key diffusion metrics (FA: fractional anisotropy; MD: mean diffusivity; AD: axial diffusivity; RD: radial diffusivity; MK: mean kurtosis; AK: axial kurtosis; RK: radial kurtosis; NDI: neurite density index; ODI: orientation dispersion index; FWF: free water fraction) were extracted from the limbic system white matter structures including cingulum, fornix, and uncinate fasciculus, which are closely associated with emotional and motivational processes. Higher maternal depression symptom scores were associated with lower FA (R = -0.3126, p = 0.0305, in CGH.R; R = -0.3025, p = 0.0366, in FXC.R) and MK (R = -0.3284, p = 0.0227, in CGG.R) and higher MD (R = 0.2879, p = 0.0472, in CGH.R) and RD (R = 0.3451, p = 0.0163, in CGH.R; R = 0.3456, p = 0.0161, in FXC.R) in predominately right-hemisphere limbic tracts. Higher maternal anxiety symptom scores were associated with increased MD (R = 0.2897, p = 0.0458, in FXC.L; R = 0.2859, p = 0.0488, in UF.L) and RD (R = 0.3168, p = 0.0283, in FXC.L), decreased NDI (R = -0.3787, p = 0.0079, in FXC.L; R = -0.3422, p = 0.0173, in UF.R), and increased AK (R = 0.3154, p = 0.029, in UF.L) in predominately left-hemisphere limbic tracts. Our findings suggest that maternal depression and anxiety during pregnancy may have long-lasting impacts on offspring white matter microstructure maturation in the limbic system. This highlights the need for prenatal mental health screening and potential interventions to promote brain development and support optimal neurodevelopmental outcomes in children.

The ReHand-BCI trial: a randomized controlled trial of a brain-computer interface for upper extremity stroke neurorehabilitation.

Brain-computer interfaces (BCI) are a promising complementary therapy for stroke rehabilitation due to the close-loop feedback that can be provided with these systems, but more evidence is needed regarding their clinical and neuroplasticity effects. A randomized controlled trial was performed using the ReHand-BCI system that provides feedback with a robotic hand orthosis. The experimental group (EG) used the ReHand-BCI, while sham-BCI was given to the control group (CG). Both groups performed 30 therapy sessions, with primary outcomes being the Fugl-Meyer Assessment for the Upper Extremity (FMA-UE) and the Action Research Arm Test (ARAT). Secondary outcomes were hemispheric dominance, measured with electroencephalography and functional magnetic resonance imaging, white matter integrity via diffusion tensor imaging, and corticospinal tract integrity and excitability, measured with transcranial magnetic stimulation. At post-treatment, patients in both groups had significantly different FMA-UE scores (EG: baseline = 24.5[20, 36], post-treatment 28[23, 43], CG: baseline = 26[16, 37.5], post-treatment = 34[17.3, 46.5]), while only the EG had significantly different ARAT scores at post-treatment (EG: baseline = 8.5[5, 26], post-treatment = 20[7, 36], CG: baseline = 3[1.8, 30.5], post-treatment = 15[2.5, 40.8]). In addition, across the intervention, the EG showed trends of more pronounced ipsilesional cortical activity and higher ipsilesional corticospinal tract integrity, although these differences were not statistically different compared to the control group, likely due to the study's sample size. To the authors' knowledge, this is the first clinical trial that has assessed such a wide range of physiological effects across a long BCI intervention, implying that a more pronounced ipsilesional hemispheric dominance is associated with upper extremity motor recovery. Therefore, the study brings light into the neuroplasticity effects of a closed-loop BCI-based neurorehabilitation intervention in stroke. https://clinicaltrials.gov/, identifier NCT04724824.

Amino acid patterns predict white matter integrity measures in the brain in patients across the Alzheimer's disease continuum.

Alzheimer's disease (AD), the leading cause of dementia, poses a growing global health challenge due to its rising prevalence and socioeconomic impact. Investigating metabolic alterations associated with white matter integrity (WMI) could provide critical insights into AD pathogenesis and identify potential therapeutic targets. This cross-sectional study explored the associations between amino acid (AA) profiles, assessed via ultra-high-performance liquid chromatography (UHPLC), and WMI metrics derived from diffusion tensor imaging (DTI) in individuals across the AD continuum. A total of 176 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) were included and grouped into cognitively normal (CN) individuals (n = 54), patients with mild cognitive impairment (MCI, n = 88), and AD patients (n = 34). WMI was evaluated using DTI-derived metrics, including fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD). AA profiling was conducted using an appropriate panel. Regression analyses, adjusted for age, gender, and education, was used to identify significant associations between AA levels and WMI. Distinct AA alterations were associated with white matter microstructural integrity across study groups. In CN individuals, higher levels of arginine, glycine, and threonine correlated with decreased FA and increased MD, indicating reduced white matter integrity. Conversely, in AD patients, aspartate, glutamate, and histidine exhibited opposite associations, showing positive correlations with FA and negative correlations with MD, suggesting potential neuroprotective or compensatory mechanisms. These findings underscore the associations between AA patterns and white matter integrity and their potential role as AD progression markers. Further investigations into these AA metabolism pathways may identify novel biomarkers for early diagnosis and targets for therapeutic interventions.

Cerebello-Cerebral Pathways Contribute to Written Word Production

Abstract Written language production is a fundamental aspect of daily communication, yet the neural pathways supporting it are far less studied than those for spoken language production. This study evaluated the contributions of speech-production pathways to written word production, specifically focusing on the central processes of word spelling rather than the motor production processes that support handwriting. Seventy-three English-speaking, neurotypical adults completed a spelling-to-dictation task and underwent diffusion MRI scans. The bilateral cerebello-thalamo-cortical pathways (CTC) and frontal aslant tract (FAT) were identified in individual participants using probabilistic tractography and automated segmentation tools. Fractional anisotropy (FA) values were computed along the trajectory of each tract and entered into correlation analyses with the spelling accuracy scores. A significant correlation was found between spelling accuracy scores and FA in the left CTC, which connects the left cerebellar hemisphere with the right cerebral hemisphere. This effect remained significant after controlling for spoken production measures. A similar trend was observed in the right homologous tract. In contrast, no significant correlations were identified between spelling accuracy scores and FA in the bilateral FAT. These findings demonstrate, for the first time, the involvement of cerebello-cerebral connections in spelling processes, aligning with the growing recognition regarding the role of the cerebellum in higher-order language functions. This effect did not generalize to the FAT, which may be relevant for more peripheral aspects of language production.

Microstructural alterations of the trigeminal ganglion in chronic ocular surface pain patients: A diffusion MRI study.

Microstructural alterations of the trigeminal ganglion in chronic ocular surface pain patients: A diffusion MRI study.

Decreased diffusion tensor image analysis along the perivascular space index is related with clinical classification in essential tremor

The glymphatic dysfunction involved in various neurodegenerative diseases. However, the relationship between glymphatic activity and essential tremor (ET) has not been fully elucidated. Our study explored the impact of glymphatic function on ET and its clinical classification. Participants comprised 37 pure ET, 38 ET-plus and 50 normal controls. Glymphatic function was evaluated via the diffusion tensor image analysis along the perivascular space (DTI-ALPS) index. Statistical comparisons of DTI-ALPS index among patients with pure ET, those with ET-plus and normal controls were conducted using general linear model analysis. Age, gender and disease duration were included as confounding variable. To confirm the relation between the DTI-ALPS index and the clinical characteristics of pure ET and ET-plus, we conducted partial Spearman rank correlation analyses while controlling for age and disease duration. The DTI-ALPS index in ET-plus patients was significantly lower than that in normal controls (P = 0.004) and pure ET patients (P = 0.010). In ET-plus patients, the DTI-ALPS index demonstrated a significant inverse relationship with disease duration (r = −0.330, P = 0.043). No significant correlations were found between the DTI-ALPS index and clinical severity of ET (all P > 0.05). We have identified for the first time that DTI-ALPS index could be used as a potential biomarker for the clinical classification of ET. The DTI-ALPS index was intimately correlated to disease duration in ET-plus patients.

Nonsuicidal self-injury prediction with pain-processing neural circuits using interpretable graph neural network

Background Nonsuicidal self-injury (NSSI) involves the intentional destruction of one’s own body tissues without suicidal intent. Prior research has shown that individuals with NSSI exhibit abnormal pain perception; however, the pain-processing neural circuits underlying NSSI remain poorly understood. This study leverages graph neural networks to predict NSSI risk and examine the learned connectivity of neural underpinnings using multimodal data. Methods Resting-state functional MRI and diffusion tensor imaging were collected from 50 patients with NSSI, 79 healthy controls (HC), and 44 patients with mental disorder who did not engage in NSSI as disease controls (DC). We constructed pain-related brain networks for each participant. An interpretable graph attention networks (GAT) model was developed, considering demographic factors, to predict NSSI risk and highlight NSSI-specific connectivity using learned attention matrices. Results The proposed GAT model based on imaging data achieved an accuracy of 80%, and increased to 88% when self-reported pain scales were incorporated alongside imaging data in distinguishing patients with NSSI from HC. It highlighted amygdala-parahippocampus and inferior frontal gyrus (IFG)-insula connectivity as pivotal in NSSI-related pain processing. After incorporating imaging data of DC, the model’s accuracy reached 74%, underscoring consistent neural connectivity patterns. The GAT model demonstrates high predictive accuracy for NSSI, enhanced by including self-reported pain scales. Conclusions Our proposed GAT model underscores the significance in the functional integration of limbic regions, paralimbic regions and IFG in NSSI pain processing. Our findings suggest altered pain processing as a key mechanism in NSSI, providing insights for potential neural modulation intervention strategies.

DTI Histogram and Texture Features as Early Predictors of Post-Radiotherapy Cognitive Decline

Background: Radiotherapy for brain tumors can induce cognitive decline, yet most studies examine white matter (WM) damage six months post-treatment, overlooking early microstructural changes. This study investigated whether early WM changes, as measured by diffusion tensor imaging (DTI) histogram and texture features, can predict later cognitive deficits. Methods: Nineteen adults with brain metastases underwent DTI before and immediately after radiotherapy. Ten features—eight histogram-based and two texture-based—were extracted from normal-appearing WM of major DTI indices. Changes (Δ) in these features, if any, were analyzed via multiple linear regression, correlating them with cognitive performance at four months after therapy. Results: Out of 40 features, four exhibited significant post-radiotherapy changes. These were the mean (ADmean) and skewness (ADskewness) of axial diffusivity and the kurtosis of mean diffusivity (MDkurtosis) and radial diffusivity (RDkurtosis). Regression identified ΔADmean (β = −3.303 × 104, p = 0.002) as negatively and ΔADskewness (β = 4.642, p = 0.006) and ΔRDkurtosis (β = −1.505, p = 0.027) as positively associated with semantic fluency. Conclusions: Early WM microstructural disruptions—particularly axonal damage and heterogeneous injury—correlate with declines in semantic fluency. DTI histogram and texture features may be promising as early non-invasive biomarkers for cognitive risk following radiotherapy.

Decreased DTI-APLS correlated with cognitive impairment in veterans with post-traumatic stress disorder.

Post-traumatic stress disorder (PTSD) is a risk for cognitive impairment with underlying mechanism unresolved. Our study aimed to evaluate the glymphatic function in veterans with post-traumatic stress disorder (PTSD), and to explore associations between glymphatic function, sleep patterns, cerebrospinal fluid (CSF) biomarkers (Aβ, t-tau, p-tau), and cognitive impairment. In our study, we included 43 Vietnam War veterans with PTSD and 43 controls. Diffusion tensor image analysis along the perivascular space (DTI-ALPS) was calculated to reflect glymphatic function. Multiple linear regressions and mediation analyses were employed to examine the relationships between the clinician-administered PTSD scale (CAPS) scores, Pittsburgh Sleep Quality Index (PSQI), DTI-ALPS and cognitive impairment. Our study revealed that PTSD group exhibited lower DTI-ALPS (p = 0.001), higher CAPS (p < 0.001), higher PSQI (p < 0.001), and poorer cognitive performance in CDR-SoB (p = 0.019) and ADAS-Cog total 13 (p = 0.009). CAPS was significantly associated with DTI-ALPS (β = -0.0018, 95% CI: -0.0029, -0.0006, p = 0.0028). PSQI demonstrated an indirect effect (β = -0.0005, 95% CI: -0.0011, -0.0001) and mediated 21.74% effect for the relationship between CAPS and DTI-ALPS. CAPS was significantly associated with CDR-SoB and ADAS-Cog total 13 (β = 0.0067, 95% CI: 0.00087, 0.0124, p = 0.024; β = 0.058, 95% CI: 0.013, 0.103, p = 0.012). DTI-ALPS had an indirect effect (β = 0.0024, 95% CI: 0.0006, 0.0069) and mediated all effect for the relationship between CAPS and CDR-SoB. In conclusion, glymphatic system was impaired in PTSD veterans revealed by DTI-ALPS, and poor sleep quality partially mediated the relationship between PTSD severity and impaired glymphatic function. DTI-ALPS mediated the relationship between PTSD severity and cognitive impairment.

Impairment of White Matter Microstructure in Alcohol Use Disorders and Its Association With Symptoms.

Alcohol use disorder (AUD) is a global health concern, with alcohol abuse leading to structural damage to white matter (WM) fiber tracts, which are crucial for cognitive and emotional functions. However, existing studies often lack systematic evaluations of these changes and their clinical correlations. Using tract-based spatial statistics (TBSS), we analyzed diffusion tensor imaging (DTI) data from 20 AUD patients and 20 healthy controls. Correlations between fractional anisotropy (FA) values and clinical symptoms, including cognitive dysfunction, depression, and impulsivity, were examined. AUD patients presented significantly decreased FA values in the right corpus callosum, right fornix, left inferior fronto-occipital fasciculus, and left cerebral white matter. The FA peak values of the right fornix and the left cerebral white matter were positively and significantly correlated with cognitive function scores in the AUD group after controlling for smoking status, age, and years of education. Alcohol abuse significantly impairs WM integrity, particularly in regions related to cognitive and emotional regulation. These findings provide structural evidence for the neurobiological mechanisms of AUD and suggest that FA may serve as a potential biomarker for assessing brain damage, guiding therapeutic interventions.

Implications of the glymphatic system in the diagnostic and surgical workup of normal pressure hydrocephalus.

Magnetic Resonance (MRI) Diffusion Tensor Imaging Analysis ALong the Perivascular Space (DTI-ALPS) is a promising technique that assesses the glymphatic system (GS) function in many neurodegenerative diseases. This study aims at evaluating the role of DTI-ALPS in the diagnostic and therapeutic management of normal pressure hydrocephalus (NPH). Twenty-one NPH patients underwent 3 Tesla MRI DTI-ALPS before and after lumbar tap test (TT). Depending on the response to TT, patients were divided into a responsive cohort (15 responders, R) and non-responsive cohort (6 non-responders, NR). R patients underwent ventriculoperitoneal shunt (VPS) surgery, with clinical assessment upon discharge and at a 3-month follow-up (FU) visit; nine patients repeated DTI-ALPS MRI at FU. Besides, 8 matched healthy controls (HC) underwent the same MRI protocol. The pre-TT ALPS-index in NPH patients (R: 1.003 ± 0.108, NR: 0.960 ± 0.079) was significantly lower compared to the HC (1.263 ± 0.161, p < 0.01). The pre-TT ALPS-index in R patients was higher than in NR patients, though not significantly (p = 0.39). Compared to the pre-TT values, the ALPS-index of the R group increased both post TT (1.069 ± 0.122, p = 0.0499) and post VPS (1.120 ± 0.117, p = 0.041), in accordance to the clinical outcome. DTI-ALPS, reflecting the GS function, resulted significantly lower in NPH patients than in healthy controls. Secondly, clinical improvement was associated with DTI-ALPS increase both after a positive response to TT and at long term follow-up following VPS surgery. Therefore, DTI-ALPS index could be a promising, rapid and non-invasive radiological biomarker for the pre-surgical evaluation and prognosis of NPH patients.

Fixel-Based Analysis Reveals Detailed White Matter Changes in Semantic Dementia.

Accurately characterizing white matter (WM) microstructure is critical for understanding neurodegenerative diseases such as semantic dementia (SD). Regionally constrained techniques like tract-based spatial statistics (TBSS) rely on diffusion-tensor imaging (DTI) and assume a single fiber population per voxel, limiting their sensitivity to complex architecture. Fixel-based morphometry (FBM) overcomes this by assessing multiple fiber populations (fixels) within a single voxel. In this study, we compared TBSS and Fixel-based analysis (FBA) for detecting WM alterations in SD variants associated with anterior temporal lobe (ATL) atrophy. Multi-shell diffusion MRI from 16 left-lateralized semantic-variant PPA (svPPA) and 15 right-lateralized semantic-behavioral fronto-temporal dementia (sbvFTD) cases, plus 44 neurologically healthy controls, underwent both TBSS-DTI and whole-brain FBA. Fiber-specific metrics of fiber density and cross-section were contrasted with conventional DTI measures. Both methods confirmed damage to ATL-connected tracts-the uncinate fasciculus, inferior longitudinal fasciculus, inferior fronto-occipital fasciculus, and temporal projections of the arcuate fasciculus. FBA, however, revealed additional involvement of juxtacortical and other previously overlooked pathways, including the tapetum and anterior commissure, projections to the parahippocampal gyrus and amygdala, and longer-range parietal connections. By capturing fiber-specific micro- and macrostructural changes, FBA yields a more comprehensive map of WM degeneration in SD than TBSS. The ability to detect early alterations in commissural and mesial-temporal pathways refines our understanding of disease spread and highlights candidate targets for monitoring and intervention aimed at preserving cognitive function.

ADVANCED NEUROLOGICAL IMAGING ANALYSIS USING DIFFUSION TENSOR TECHNIQUES AND DISTRIBUTED WEB SYSTEMS

Diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) are crucial in modern neurological diagnostics, enabling detailed analysis of brain structures and connectivity. This article presents a comprehensive approach to analysing MRI images using advanced tools such as the FSL software library. The proposed method leverages distributed web systems to enhance the scalability and accessibility of image processing and analysis across multiple medical facilities. Key steps, including noise reduction, artefact removal, and tensor reconstruction, are performed to improve diagnostic accuracy. Additionally, metrics such as fractional anisotropy (FA), mean diffusivity (MD), and axial diffusivity (AD) are evaluated to detect microstructural brain abnormalities. The integration of distributed web technologies facilitates real-time collaboration between specialists, accelerating diagnostic processes and enabling cross-hospital data sharing. This study highlights the potential of combining cutting-edge imaging techniques with scalable digital infrastructures to optimise medical decision-making and improve patient outcomes.

Perivascular space fluid diffusivity predicts clinical deterioration in prodromal and early-stage Parkinson’s disease

The glymphatic system is essential for clearing toxic proteins from the brain, and understanding its dysfunction in the early stages of Parkinson’s disease (PD) may facilitate the development of disease-modifying therapies. This study aimed to evaluate alterations in glymphatic function and its correlation with disease progression in prodromal and early clinical stages of PD. Participants were categorized into three groups: prodromal PD (pPD), de novo PD (dnPD), and healthy controls (HCs), further divided by age. Glymphatic function was assessed using the ALPS index derived from diffusion tensor imaging. Results indicated that the ALPS index was significantly lower in older pPD and dnPD patients, correlating with various clinical symptoms. Longitudinal analysis revealed a decrease in the ALPS index over time in pPD patients who progressed to clinical PD, while it remained stable in non-converters. Additionally, the baseline ALPS index was predictive of the progression of both motor and non-motor symptoms in pPD patients. In dnPD patients, a lower baseline ALPS index predicted the progression of motor symptoms in the older subgroup. Overall, the ALPS index is reduced in the early stages of PD and may serve as a predictor for disease progression.