Search Results (21)

The global prevalence of type 2 diabetes mellitus (T2DM) has increased more than twofold over the last thirty years. T2DM is associated with multiple complications, among which diabetic encephalopathy and accompanying cognitive impairment have drawn considerable interest. This systematic review synthesizes findings from advanced diffusion magnetic resonance imaging (dMRI) studies (published from 2009 to 2025) on T2DM-related brain microstructural abnormalities. The most common technique, diffusion tensor imaging (DTI), consistently reveals reduced white-matter integrity (lower fractional anisotropy, higher diffusivity) associated with cognitive impairment. DTI-based network analysis further identifies disrupted structural network topology, characterized by reduced global and nodal efficiency. To overcome DTI’s limitations, newer techniques provide more specific insights: diffusion kurtosis imaging shows reduced tissue complexity in white matter, gray matter, and crossing-fiber regions via non-Gaussian modeling; neurite orientation dispersion and density imaging quantifies decreased neurite density; intravoxel incoherent motion assesses combined microstructural and microvascular alterations; diffusion spectrum imaging maps complex fiber architecture. These dMRI metrics may provide promising imaging markers for characterizing T2DM-related brain microstructural alterations. However, most available evidence remains cross-sectional, and further longitudinal, multicenter validation is required before these measures can be considered clinically validated biomarkers for prediction, diagnosis, or monitoring. Full article

Background/Objectives: White matter (WM) tract detection is critical in the presurgical planning of tumor resection. However, standard-of-care imaging techniques including T₁-weighted, T₂-weighted, and Diffusion Tensor Imaging (DTI) often fail to identify WM tracts within edematous regions. In T₁/T₂-weighted imaging, edema increases extracellular water and reduces tissue contrast, and in diffusion-weighted imaging, edema elevates isotropic diffusion, reducing sensitivity to anisotropic diffusion along WM tracts. Advanced biophysical diffusion modeling techniques such as Neurite Orientation Dispersion and Density Imaging (NODDI) and the Standard Model (SM) address this limitation by compartmentalizing the diffusion signal into free-water, intra-neurite, and extra-neurite contributions. Here, we test if biophysical multi-compartment models can robustly identify WM tracts and recover tractography streamlines within edematous regions. Methods: In this study, we use multi-shell diffusion-weighted MRI data obtained from patients with meningiomas—a pathology allowing for isolation of the effects of edema without the confounding effects of tumor cell invasion. We compared FA from standard and free-water-corrected DTI, the orientation dispersion index (ODI) from NODDI, and P₂ (a scalar descriptor of fiber orientation coherence) from the SM fODF in edematous and unaffected contralateral WM regions. As a proof of concept, we visually evaluated the tractography performance across models. Results: Our results show that (1 − ODI) and P₂ values in edema remained close to within-subject contralateral measurements, contrasting with substantial reductions in FA and FW-FA. (1 − ODI) showed a small but statistically significant increase in edema (~8%, p = 0.02), while P₂ was unchanged. Conclusions: These results highlight the potential of biophysical diffusion models for preoperative mapping in edema. Full article

Background: Microstructural abnormalities of the corpus callosum (CC) are a consistent finding in schizophrenia, yet conventional diffusion tensor imaging (DTI) metrics provide limited biological specificity. Neurite orientation dispersion and density imaging (NODDI) can disentangle the neurite density index (NDI) and the orientation dispersion index (ODI), providing indirect, model-based markers of white matter microstructure in vivo. Methods: We applied NODDI to diffusion-weighted MRI data in patients with first-episode schizophrenia (FES) and matched healthy controls (HCs). The CC was used as a mask and subdivided into the genu (GCC), body (BCC), and splenium (SCC). Group differences in z-scores of the NDI and ODI were assessed using voxel-wise statistics within the CC and region of interest (ROI) analyses in the GCC, BCC, and SCC, controlling for age and sex. Associations between NODDI metrics and clinical symptoms were examined using the Positive and Negative Syndrome Scale (PANSS). Results: FES patients showed a significantly increased ODI in portions of the GCC, BCC, and SCC, as well as region-specific NDI alterations, with decreased NDI in parts of the SCC and increased NDI in sub-regions of the GCC/BCC (voxel-wise p < 0.05, FWE-corrected). ROI analyses confirmed a significant reduction in NDI z-scores in the SCC in FES patients compared with HCs (p = 0.009), whereas the ODI z-scores in the SCC did not differ significantly between groups (p = 0.124). Despite the absence of group-level ODI differences in the SCC, the SCC ODI was positively correlated with PANSS negative symptom scores in FES patients (r = 0.554, p = 0.002) and was also positively correlated with PANSS total scores in FES (r = 0.457, p = 0.014). This association remained significant in the region of the SCC after regressing out NDI from ODI (residual z_ODI), which was correlated with PANSS negative scores (r = 0.503, p = 0.006) and PANSS total scores (r = 0.474, p = 0.011), and the ODI/NDI ratio in the SCC was also correlated with negative symptom severity (r = 0.457, p = 0.014). Conclusions: Our findings suggest that, in the SCC, negative symptoms in schizophrenia are linked to altered neurite orientation dispersion under conditions of reduced neurite density. The dissociation between group-level NDI and ODI effects and their distinct relationship with psychopathology highlights the value of composite microstructural indices (e.g., residual z_ODI, ODI/NDI) for capturing clinically relevant white matter abnormalities. Full article

Background/Objectives: Autism spectrum disorder (ASD) has been extensively studied through neuroimaging, primarily focusing on grey matter and more in children than in adults. Studies in children and adolescents fail to capture changes that may dampen with age, thus leaving only changes specific to ASD. While grey matter has been the primary focus, white matter (WM) may be more specific in identifying the particular biological signature of the neurodiversity of ASD. Diffusion tensor imaging (DTI) is the more appropriate tool to investigate WM in ASD. Despite being introduced in 1994, its application to ASD research began in 2001. Studies employing DTI identify altered fractional anisotropy (FA), mean diffusivity, and radial diffusivity (RD) in individuals with ASD compared to typically developing (TD) individuals. Methods: We systematically reviewed literature on 21 May 2025 on PubMed using the following strategy: (“autism spectrum”[ti] OR autistic[ti] OR ASD[ti] OR “high-functioning autism” OR Asperger*[ti] OR Rett*[ti]) AND (DTI[ti] OR “diffusion tensor”[ti] OR multimodal[ti] OR “white matter”[ti] OR tractograph*[ti]). Our search yielded 239 results, of which 26 were adult human studies and eligible. Results: Analysing the evidence, we obtained regionally diverse WM alterations in adult ASD, specifically in FA, MD, RD, axial diffusivity and kurtosis, neurite density, and orientation dispersion index, compared to TD individuals, mostly in frontal and interhemispheric tracts, association fibres, and subcortical projection pathways. These alterations were less prominent than those of children and adolescents, indicating that individuals with ASD may improve during brain maturation. Conclusions: Our findings suggest that white matter alterations in adults with ASD are regionally diverse but generally less pronounced than in younger populations. This may indicate a potential improvement or adaptation of brain structure during maturation. Further research is needed to clarify the neurobiological mechanisms underlying these changes and their implications for clinical outcomes. Full article

Background/Objectives: Cerebral palsy (CP), often caused by early brain injury such as perinatal stroke or hemorrhage, is the most common lifelong motor disability. Early identification of at-risk infants and timely access to rehabilitation interventions are essential for improving long-term outcomes. The General Movements Assessment (GMA), performed in the first months of life, has high sensitivity and specificity to predict CP; however, the neurological correlates of general movements remain unclear. This analysis aimed to investigate the relationship between white matter integrity and general movements in infants with perinatal brain injury using advanced neuroimaging techniques. Methods: Diffusion-weighted MRI data were analyzed in 17 infants, 12 with perinatal brain injury and 5 typically developing infants. Tractography was used to identify the corticospinal tract, a key motor pathway often affected by perinatal brain injury, and tract-based spatial statistics (TBSS) were used to examine broader white matter networks. Diffusion parameters from the diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) models were compared between infants with and without typical general movements. Results: Corticospinal tract integrity did not differ between groups when averaged across hemispheres. However, infants with asymmetric general movements exhibited greater corticospinal tract asymmetries. A subset of infants with atypical general movement trajectories at <6 weeks and 3–5 months of age showed reduced corticospinal tract integrity compared to those with typical general movements. TBSS revealed significant differences in white matter integrity between infants with typical and atypical general movements in several white matter pathways, including the corpus callosum, the right posterior corona radiata, bilateral posterior thalamic radiations, the left fornix/stria terminalis, and bilateral tapetum. Conclusions: These findings support and expand upon previous research suggesting that white matter integrity across multiple brain regions plays a role in the formation of general movements. Corticospinal integrity alone was not strongly associated with general movements; interhemispheric and cortical-subcortical connectivity appear critical. These findings underscore the need for further research in larger, diverse populations to refine early biomarkers of neurodevelopmental impairment and guide targeted interventions. Full article

Background and objectives: Type 2 diabetes mellitus (T2DM) affects brain white matter microstructure. While diffusion tensor imaging (DTI) has been used to study white matter abnormalities in T2DM, it lacks specificity for complex white matter tracts. Neurite orientation dispersion and density imaging (NODDI) offers a more specific approach to characterising white matter microstructures. This study aims to explore white matter alterations in T2DM using both DTI and NODDI and assess their association with disease duration and glycaemic control, as indicated by HbA1c levels. Methods and Materials: We analysed white matter microstructure in 48 tracts using data from the UK Biobank, involving 1023 T2DM participants (39% women, mean age 66) and 30,744 non-T2DM controls (53% women, mean age 64). Participants underwent 3.0T multiparametric brain imaging, including T1-weighted and diffusion imaging for DTI and NODDI. We performed region-of-interest analyses on fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), orientation dispersion index (ODI), intracellular volume fraction (ICVF), and isotropic water fraction (IsoVF) to assess white matter abnormalities. Results: We observed reduced FA and ICVF, and increased MD, AD, RD, ODI, and IsoVF in T2DM participants compared to controls (p < 0.05). These changes were associated with longer disease duration and higher HbA1c levels (0 < r ≤ 0.2, p < 0.05). NODDI identified microstructural changes in white matter that were proxies for reduced neurite density and disrupted fibre orientation, correlating with disease progression and poor glucose control. In conclusion, NODDI contributed to DTI in capturing white matter differences in participants with type 2 diabetes, suggesting the feasibility of NODDI in detecting white matter alterations in type 2 diabetes. Type 2 diabetes can cause white matter microstructural abnormalities that have associations with glucose control. Conclusions: The NODDI diffusion model allows the characterisation of white matter neuroaxonal pathology in type 2 diabetes, giving biophysical information for understanding the impact of type 2 diabetes on brain microstructure. Future research should focus on the longitudinal tracking of these microstructural changes to better understand their potential as early biomarkers for cognitive decline in T2DM. Full article

Background/Objectives: The purpose of this study was to evaluate the performance of diffusion kurtosis imaging (DKI), neurite orientation dispersion and density imaging (NODDI), and diffusion microstructure imaging (DMI) in differentiating molecular subtypes of adult-type gliomas. Methods: Standardized MRI was performed and evaluated in 59 patients with adult-type glioma. DKI, NODDI, and DMI parameter values were quantitatively evaluated in ROIs in contrast-enhancing/solid tumor tissue and five concentric shells with peritumoral tissue. DKI, NODDI, and DMI parameters of (i) glioblastomas, Isocitrate dehydrogenase (IDH) wildtype; (ii) astrocytomas, IDH mutant; and (iii) oligodendrogliomas, IDH mutant were compared with analysis of variance (ANOVA). Receiver operating characteristic curve (ROC) curve analysis was conducted to discriminate firstly between IDH mutant and IDH wildtype gliomas and then between IDH mutant astrocytomas and oligodendrogliomas. Results: Significant differences between the three aforementioned subtypes were found for the apparent diffusion coefficient (ADC) and mean kurtosis (MK) and again for the orientation dispersion index (ODI) and intra-axonal volume fraction (v-intra). The diagnostic accuracy depended on the distance to the contrast-enhancing/solid tumor tissue. Some NODDI and DMI parameters significantly predicted the IDH status and significantly discriminated between astrocytomas and oligodendrogliomas; however, ADC and MK showed the best prediction in both ROC analyses (maximum AUC 0.910 (CI 0.824–0.995)). Conclusions: The evaluation of peritumoral tissue can be a valuable procedure, while NODDI and DMI appear to be promising but are currently inferior to DKI in predicting glioma subtypes categorized according to the WHO 2021 classification. Full article

Background/Objectives: White matter (WM) structural changes have been found in patients with chronic spinal pain (CSP). In these patients, pain neuroscience education followed by cognition-targeted exercise therapy (i.e., the Modern Pain Neuroscience Approach (MPNA)) was shown to be more effective than biomedically-focused education followed by symptom-contingent exercise therapy for improving clinical outcomes. The present study examined whether an MPNA, compared to biomedically-focused treatment, can change WM structure in regions of interest and whether potential WM structural changes are associated with clinical improvements in patients with CSP. Methods: Patients with CSP were randomized into an experimental (MPNA) or control (biomedically-focused) treatment group. Diffusion-weighted Magnetic Resonance Images were acquired pre-treatment, post-treatment, and at 1-year follow-up. WM structure was assessed using diffusion tensor imaging in 8 WM regions of interest, and linear mixed models assessed differences between groups in response to treatment. Results: No significant treatment x time interaction effects were found; however, significant main effects of time were found in 7 WM tracts. Significant main effects of time revealed increased fractional anisotropy (FA), decreased mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) in the cingulum hippocampus, and decreased RD and MD in the superior cerebellar peduncle at 1-year follow-up compared to baseline. In contrast, decreased FA and/or increased MD, AD, or RD values were found in other WM tracts (e.g., anterior corona radiata) from pre-treatment to 1-year follow-up. Greater reduction in kinesiophobia was moderately correlated with a smaller decrease in RD in the superior cerebellar peduncle at 1-year follow-up compared to baseline. No other significant associations were found between WM structural changes and clinical improvements. Conclusions: In conclusion, in patients with CSP, regional WM structure changed over time irrespective of prescribed treatment (timespan of 12 months). Further research, including Neurite Orientation Dispersion and Density Imaging and a healthy control group, allowing for a more specific examination of WM microstructural changes in response to multimodal treatment in patients with CSP, is warranted. Full article

Background: Diffusion weighted imaging (DWI) is used for monitoring purposes for lower-grade glioma (LGG). While the apparent diffusion coefficient (ADC) is clinically used, various DWI models have been developed to better understand the micro-environment. However, the validity of these models and how they relate to each other is currently unknown. Therefore, this study assesses the validity and agreement of these models. Methods: Fourteen post-treatment LGG patients and six healthy controls (HC) underwent DWI MRI on a 3T MRI scanner. DWI processing included diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), white matter tract integrity (WMTI), neurite orientation dispersion and density imaging (NODDI), and fixel-based analysis (FBA). Validity was assessed by delineating surgical cavity, peri-surgical cavity, and normal-appearing white matter (NAWM) in LGG patients, and white matter (WM) in HC. Spearman correlation assessed the agreement between DWI parameters. Results: All obtained parameters differed significantly across tissue types. Remarkably, WMTI showed that intra-axonal diffusivity was high in the surgical cavity and low in NAWM and WM. Most DWI parameters correlated well with each other, except for WMTI-derived intra-axonal diffusivity. Conclusion: This study shows that all parameters relevant for tumour monitoring and DWI-derived parameters for axonal fibre-bundle integrity (except WMTI-IAS-D_a) could be used interchangeably, enhancing inter-DWI model interpretability. Full article

Advancements in neuroimaging, particularly diffusion magnetic resonance imaging (MRI) techniques and molecular imaging with positron emission tomography (PET), have significantly enhanced the early detection of biomarkers in neurodegenerative and neuro-ophthalmic disorders. These include Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, neuromyelitis optica, and myelin oligodendrocyte glycoprotein antibody disease. This review highlights the transformative role of advanced diffusion MRI techniques—Neurite Orientation Dispersion and Density Imaging and Diffusion Kurtosis Imaging—in identifying subtle microstructural changes in the brain and visual pathways that precede clinical symptoms. When integrated with artificial intelligence (AI) algorithms, these techniques achieve unprecedented diagnostic precision, facilitating early detection of neurodegeneration and inflammation. Additionally, next-generation PET tracers targeting misfolded proteins, such as tau and alpha-synuclein, along with inflammatory markers, enhance the visualization and quantification of pathological processes in vivo. Deep learning models, including convolutional neural networks and multimodal transformers, further improve diagnostic accuracy by integrating multimodal imaging data and predicting disease progression. Despite challenges such as technical variability, data privacy concerns, and regulatory barriers, the potential of AI-enhanced neuroimaging to revolutionize early diagnosis and personalized treatment in neurodegenerative and neuro-ophthalmic disorders is immense. This review underscores the importance of ongoing efforts to validate, standardize, and implement these technologies to maximize their clinical impact. Full article

The cerebral small vessel disease (cSVD) is one of the main causes of vascular and mixed cognitive impairment (CI), and it is associated, in particular, with brain ageing. An understanding of structural tissue changes in an intact cerebral white matter in cSVD might allow one to develop the sensitive biomarkers for early diagnosis and monitoring of disease progression. Purpose of the study: to evaluate microstructural changes in the corpus callosum (CC) using diffusion MRI (D-MRI) approaches in cSVD patients with different severity of CI and reveal the most sensitive correlations of diffusion metrics with CI. Methods: the study included 166 cSVD patients (51.8% women; 60.4 ± 7.6 years) and 44 healthy volunteers (65.9% women; 59.6 ± 6.8 years). All subjects underwent D-MRI (3T) with signal (diffusion tensor and kurtosis) and biophysical (neurite orientation dispersion and density imaging, NODDI, white matter tract integrity, WMTI, multicompartment spherical mean technique, MC-SMT) modeling in three CC segments as well as a neuropsychological assessment. Results: in cSVD patients, microstructural changes were found in all CC segments already at the subjective CI stage, which was found to worsen into mild CI and dementia. More pronounced changes were observed in the forceps minor. Among the signal models FA, MD, MK, RD, and RK, as well as among the biophysical models, MC-SMT (EMD, ETR) and WMTI (AWF) metrics exhibited the largest area under the curve (>0.85), characterizing the loss of microstructural integrity, the severity of potential demyelination, and the proportion of intra-axonal water, respectively. Conclusion: the study reveals the relevance of advanced D-MRI approaches for the assessment of brain tissue changes in cSVD. The identified diffusion biomarkers could be used for the clarification and observation of CI progression. Full article

Introduction: Despite evidence suggesting deleterious effects of cannabis and nicotine tobacco product (NTP) use on white matter integrity, there have been limited studies examining white matter integrity among users of both cannabis and nicotine. Further, updated white matter methodology provides opportunities to investigate use patterns on neurite orientation dispersion and density (NODDI) indices and subtle tissue changes related to the intra- and extra-neurite compartment. We aimed to investigate how cannabis and NTP use among adolescents and young adults interacts to impact the white matter integrity microstructure. Materials and Methods: A total of 221 participants between the ages of 16 and 22 completed the Customary Drinking and Drug Use Record (CDDR) to measure substance use, and underwent a magnetic resonance imaging (MRI) session. Participants were divided into NTP-control and NTP groupings and cannabis-control and cannabis groupings (≥26 NTP/cannabis uses in past 6 months). Tract-Based Spatial Statistics (TBSS) and two-way between-subjects ANOVA investigated the effects of NTP use group, cannabis use group, and their interaction on fractional anisotropy (FA) and NODDI indices while controlling for age and biological sex. Results: NTP use was associated with decreased FA values and increased orientation dispersion in the left anterior capsule. There were no significant effects of cannabis use or the interaction of NTP and cannabis use on white matter outcomes. Discussion: NTP use was associated with altered white matter integrity in an adolescent and young adult sample. Findings suggest that NTP-associated alterations may be linked to altered fiber tract geometry and dispersed neurite structures versus myelination, as well as differential effects of NTP and cannabis use on white matter structure. Future work is needed to investigate how altered white matter is related to downstream behavioral effects from NTP use. Full article

We examined neurite orientation dispersion and density imaging in patients with migraine. We found that patients with medication overuse headache exhibited lower orientation dispersion than those without. Moreover, orientation dispersion in the body of the corpus callosum was statistically negatively correlated with migraine attack frequencies. These findings indicate that neurite dispersion is damaged in patients with chronic migraine. Our study results indicate the orientation preference of neurite damage in migraine. Full article

Diffusion tensor imaging (DTI) showed its adequacy in evaluating the normal-appearing white matter (NAWM) and lesions in the brain that are difficult to evaluate with routine clinical magnetic resonance imaging (MRI) in multiple sclerosis (MS). Recently, MRI systems have been developed with regard to software and hardware, leading to different proposed diffusion analysis methods such as diffusion tensor imaging, q-space imaging, diffusional kurtosis imaging, neurite orientation dispersion and density imaging, and axonal diameter measurement. These methods have the ability to better detect in vivo microstructural changes in the brain than DTI. These different analysis modalities could provide supplementary inputs for MS disease characterization and help in monitoring the disease’s progression as well as treatment efficacy. This paper reviews some of the recent diffusion MRI methods used for the assessment of MS in vivo. Full article

Patients with degenerative cervical myelopathy (DCM) undergo adaptive supraspinal changes. However, it remains unknown how subcortical white matter changes reflect the gray matter loss. The current study investigated the interrelationship between gray matter and subcortical white matter alterations in DCM patients. Cortical thickness of gray matter, as well as the intra-cellular volume fraction (ICVF) of subcortical whiter matter, were assessed in a cohort of 44 patients and 17 healthy controls (HCs). The results demonstrated that cortical thinning of sensorimotor and pain related regions is associated with more severe DCM symptoms. ICVF values of subcortical white matter underlying the identified regions were significantly lower in study patients than in HCs. The left precentral gyrus (r = 0.5715, p < 0.0001), the left supramarginal gyrus (r = 0.3847, p = 0.0099), the left postcentral gyrus (r = 0.5195, p = 0.0003), the right superior frontal gyrus (r = 0.3266, p = 0.0305), and the right caudal (r = 0.4749, p = 0.0011) and rostral anterior cingulate (r = 0.3927, p = 0.0084) demonstrated positive correlations between ICVF and cortical thickness in study patients, but no significant correlations between ICVF and cortical thickness were observed in HCs. Results from the current study suggest that DCM may cause widespread gray matter alterations and underlying subcortical neurite loss, which may serve as potential imaging biomarkers reflecting the pathology of DCM. Full article