Local white matter abnormalities in Parkinson's disease with mild cognitive impairment: Assessed with neurite orientation dispersion and density imaging.

Mild cognitive impairment is a nonmotor complication in Parkinson's disease (PD) that have a high risk of developing dementia. White matter is associated with cognitive function in PD and the alterations may occur before the symptoms of the disease. Previous diffusion tensor imaging (DTI) studies lacked specificity to characterize the concrete contributions of distinct white matter tissue properties. This may lead to inconsistent conclusions about the alteration of white matter microstructure. Here, we used neurite orientation dispersion and density imaging (NODDI) and white matter fiber clustering method to uncover local white matter microstructures in PD with mild cognitive impairment (PD-MCI). This study included 23 PD-MCI and 20 PD with normal cognition (PD-NC) and 21 healthy controls (HC). To probe specific and fine-grained differences, metrics of NODDI and DTI in white matter fiber clusters were evaluated using along-tract analysis. Our results showed that PD-MCI patients had significantly lower neurite density index (NDI) and orientation dispersion index (ODI) in white matter fiber clusters in the prefrontal region. Correlation analysis and receiver operating characteristic (ROC) analysis revealed that the diagnostic performance of NODDI-derived metrics in cingulum bundle (2 clusters) and thalamo-frontal (2 clusters) were superior to DTI metrics. Our study provides a more specific insight to uncover local white matter abnormalities in PD-MCI, which benefit understanding the underlying mechanism of cognitive decline in PD and predicting the disease in advance.

Microstructural changes along the cingulum in young adolescents with psychotic experiences: An along-tract analysis.

Psychotic experiences (PEs) such as hallucinations and delusions are common among young people without psychiatric diagnoses and are associated with connectivity and white matter abnormalities, particularly in the limbic system. Using diffusion magnetic resonance imaging (MRI) in adolescents with reported PEs and matched controls, we examined the cingulum white matter tract along its length rather than as the usually reported single indivisible structure. Complex regional differences in diffusion metrics were found along the bundle at key loci following Bonferroni significance adjustment (p < .00013) with moderate to large effect sizes (.11-.76) throughout all significant subsegments. In this prospective community-based cohort of school-age children, these findings suggest that white matter alterations in the limbic system may be more common in the general non-clinical adolescent population than previously thought. Such white matter alternations may only be uncovered using a similar more granular along-tract analysis of white matter tracts.

Early-Onset Micromorphological Changes of Neuronal Fiber Bundles During Radiotherapy.

BACKGROUND: Patients receiving cranial radiation face the risk of delayed brain dysfunction. However, an early medical imaging marker is not available until irreversible morphological changes emerge. PURPOSE: To explore the micromorphological white matter changes during the radiotherapy session by utilizing an along-tract analysis framework. STUDY TYPE: Prospective. POPULATION: Eighteen nasopharyngeal carcinoma (two female) patients receiving cranial radiation. FIELD STRENGTH/SEQUENCE: 3.0 T; Diffusion tensor imaging (DTI) and T1- and T2-weighted images (T1W, T2W); computed tomography (CT). ASSESSMENT: Patients received three DTI imaging scans during the radiotherapy (RT), namely the baseline scan (1-2 days before RT began), the middle scan (the middle of the RT session), and the end scan (1-2 days after RT ended). Twelve fibers were segmented after whole-brain tractography. Then, the fractional anisotropy (FA) values and the cumulative radiation dose received for each fiber streamline were resampled and projected into their center fiber. STATISTICAL TESTS: The contrast among the three scans (P1: middle scan-baseline scan; P2: end scan-middle scan; P3: end scan-baseline scan) were compared using the linear mixed model for each of the 12 center fibers. Then, a dose-responsiveness relationship was performed using Pearson correlation. P < 0.05 was considered statistically significant. RESULTS: Six of the 12 center fibers showed significant changes of FA values during the RT but with heterogeneous patterns. The significant changes along a specific center fiber were associated with their cumulative dose received (Genu: P1 r = -0.6182, P2 r = -0.5907; Splenium: P1 r = 0.4055, P = 0.1063, P2 r = 0.6742; right uncinate fasciculus: P1 r = -0.3865, P2 r = -0.4912, P = 0.0533; right corticospinal tract: P1 r = 0.4273, P = 0.1122, P2 r = -0.6885). DATA CONCLUSION: The along-tract analysis might provide sensitive measures on the early-onset micromorphological changes. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 3.

Cognitive and White-Matter Compartment Models Reveal Selective Relations between Corticospinal Tract Microstructure and Simple Reaction Time.

The speed of motor reaction to an external stimulus varies substantially between individuals and is slowed in aging. However, the neuroanatomical origins of interindividual variability in reaction time (RT) remain unclear. Here, we combined a cognitive model of RT and a biophysical compartment model of diffusion-weighted MRI (DWI) to characterize the relationship between RT and microstructure of the corticospinal tract (CST) and the optic radiation (OR), the primary motor output and visual input pathways associated with visual-motor responses. We fitted an accumulator model of RT to 46 female human participants' behavioral performance in a simple reaction time task. The non-decision time parameter (Ter) derived from the model was used to account for the latencies of stimulus encoding and action initiation. From multi-shell DWI data, we quantified tissue microstructure of the CST and OR with the neurite orientation dispersion and density imaging (NODDI) model as well as the conventional diffusion tensor imaging model. Using novel skeletonization and segmentation approaches, we showed that DWI-based microstructure metrics varied substantially along CST and OR. The Ter of individual participants was negatively correlated with the NODDI measure of the neurite density in the bilateral superior CST. Further, we found no significant correlation between the microstructural measures and mean RT. Thus, our findings suggest a link between interindividual differences in sensorimotor speed and selective microstructural properties in white-matter tracts.SIGNIFICANCE STATEMENT How does our brain structure contribute to our speed to react? Here, we provided anatomically specific evidence that interindividual differences in response speed is associated with white-matter microstructure. Using a cognitive model of reaction time (RT), we estimated the non-decision time, as an index of the latencies of stimulus encoding and action initiation, during a simple reaction time task. Using an advanced microstructural model for diffusion MRI, we estimated the tissue properties and their variations along the corticospinal tract and optic radiation. We found significant location-specific correlations between the microstructural measures and the model-derived parameter of non-decision time but not mean RT. These results highlight the neuroanatomical signature of interindividual variability in response speed along the sensorimotor pathways.

Reducing variability in along-tract analysis with diffusion profile realignment.

Diffusion weighted magnetic resonance imaging (dMRI) provides a non invasive virtual reconstruction of the brain's white matter structures through tractography. Analyzing dMRI measures along the trajectory of white matter bundles can provide a more specific investigation than considering a region of interest or tract-averaged measurements. However, performing group analyses with this along-tract strategy requires correspondence between points of tract pathways across subjects. This is usually achieved by creating a new common space where the representative streamlines from every subject are resampled to the same number of points. If the underlying anatomy of some subjects was altered due to, e.g., disease or developmental changes, such information might be lost by resampling to a fixed number of points. In this work, we propose to address the issue of possible misalignment, which might be present even after resampling, by realigning the representative streamline of each subject in this 1D space with a new method, coined diffusion profile realignment (DPR). Experiments on synthetic datasets show that DPR reduces the coefficient of variation for the mean diffusivity, fractional anisotropy and apparent fiber density when compared to the unaligned case. Using 100 in vivo datasets from the human connectome project, we simulated changes in mean diffusivity, fractional anisotropy and apparent fiber density. Independent Student's t-tests between these altered subjects and the original subjects indicate that regional changes are identified after realignment with the DPR algorithm, while preserving differences previously detected in the unaligned case. This new correction strategy contributes to revealing effects of interest which might be hidden by misalignment and has the potential to improve the specificity in longitudinal population studies beyond the traditional region of interest based analysis and along-tract analysis workflows.

Qualitative and Visual Along-Tract Analysis of Diffusion-Based Parameters in Patients with Diffuse Gliomas.

BACKGROUND: Grade 2-3 diffuse gliomas (DGs) show extensive infiltration through white matter (WM) tracts. Along-tract analysis of WM tracts based on diffusion tensor tractography (DTI) can been performed to assess the microstructural integrity of WM tracts. The clinical implication of these DTI-related findings is still under debate, especially in tumor patients. The aim of this study was to analyze and compare diffusion-based parameters along WM tracts and variables specific to WM -tumor interactions in DGs and correlate them with preoperative neuropsychological assessment. METHODS: Fourteen patients with IDH-mutated grade 2-3 DGs were included. Tumor volumes were manually segmented on 3D-FLAIR images after spatial normalisation to MNI space. DTI was acquired using a single-shot echo-planar sequence on a 3T with 48 sampling directions. DTI data were reconstructed within the MNI space using q-space diffeomorphic reconstruction (QSDR) in DSI studio. Five bilateral sets of WM tracts were reconstructed based on the HCP-1065 template. All WM tracts were stretched to the same length of 100 indices, and for each index diffusion-based parameters fractional anisotropy (FA), radial diffusivity (RD), axial diffusivity (AD), mean diffusivity (MD) and quantitative anisotropy (QA) were sampled. Tumor-related parameters (TRP); tumor volume (Tv), maximum tumor presence (MTP) and the number of sequential indices in which a tumor is present (Te) were derived based on the along-tract analysis. Normal data were constructed by calculating the average and standard deviations of contralateral and not-affected WM tracts for each diffusion-based parameter, respectively. Affected WM tracts were individually compared to normal data using a z-test. Preoperative neuropsychological assessment was performed in all subjects and correlated to results from the along-tract analysis using correlation and logistic regression models. RESULTS: Abnormalities in diffusion-based parameters were detected in WM tracts. Topographical and quantitative information were presented within the same graph. AD and MD displayed the highest linear correlation with the TRPs. Abnormal QA showed a linear correlation with Tv per WM tract. Neuropsychological impairment was correlated with all the TRPs and with abnormal FA (p < 0.05) and abnormal QA (p < 0.01). Abnormal QA was the only independent variable able to predict the presence of neuropsychological impairment in the patients based on the linear regression analysis. CONCLUSIONS: Graphical presentation of the along-tract analysis presented in this study shows that it may be a sensitive and robust method to acquire and display topographical and qualitative information regarding WM tracts in close proximity to DGs. Further studies and refinements to the methods presented herein may advance current clinical methods for evaluating displacement and infiltrations and further aid the efforts of pre-planning surgical interventions with the goal to maximise EOR and tailor oncological treatment.