Voxel based versus region of interest analysis in diffusion tensor imaging of neurodevelopment

Diffusion tensor-based analysis of white matter in dogs with idiopathic epilepsy

Introduction

The understanding of epileptic seizure pathogenesis has evolved over time, and it is now generally accepted that not only are cortical and subcortical areas involved but also the connection of these regions in the white matter (WM). Recent human neuroimaging studies confirmed the involvement of the WM in several epilepsy syndromes. Neuroimaging studies investigating WM integrity with diffusion tensor imaging (DTI) in canine idiopathic epilepsy are lacking. This study aimed to test the hypothesis that WM diffusion changes can be found in dogs affected by idiopathic epilepsy.

Method

Twenty-six dogs with idiopathic epilepsy (15 Border Collies and 11 Greater Swiss Mountain dogs) and 24 healthy controls (11 Beagle dogs, 5 Border Collies, and 8 Greater Swiss Mountain dogs) were prospectively enrolled. Most dogs with idiopathic epilepsy (17/26) were enrolled within 3 months after seizure onset. Diffusion tensor imaging of the brain with 32 diffusion directions (low b value = 0 s/mm2; maximal b value = 800 s/mm2) was performed in a 3 Tesla scanner. Tract-based spatial statistics (TBSS), a voxel-based approach, was used to investigate changes in fractional anisotropy (FA) and mean diffusivity (MD) in the idiopathic epilepsy group compared to the healthy control group. Additionally, FA and MD were investigated in the region of corpus callosum and cingulate white matter in both groups.

Results

We observed subtle changes in WM DTI between the idiopathic epilepsy group and the healthy control group limited to cingulate WM, with a significantly lower FA in the idiopathic epilepsy group compared to the healthy control group in the region of interest (ROI) approach (p = 0.027). No significant changes were found between the idiopathic epilepsy group and the healthy control group in the TBSS analysis and in the corpus callosum in the ROI approach.

Conclusion

This study supports the cingulate area as a target structure in canine epilepsy. The subtle changes only might be explained by the short duration of epilepsy, small sample sizes, and the higher variability in canine brain anatomy. Furthermore, all included dogs showed generalized tonic-clonic seizures, possibly affected by generalized epilepsy syndrome, which are also associated with less pronounced DTI changes in humans than focal epilepsy syndromes.

White matter microstructure and executive functions in congenital heart disease from childhood to adulthood: A pooled case-control study

Congenital heart disease (CHD) patients are at risk for alterations in the cerebral white matter microstructure (WMM) throughout development. It is unclear whether the extent of WMM alterations changes with age, especially during adolescence when the WMM undergoes rapid maturation. We investigated differences in WMM between patients with CHD and healthy controls from childhood until early adulthood in a pooled sample of children, adolescents, and young adults. The association between WMM and EF was assessed. Patients with CHD (N=78) and controls (N=137) between 9 and 32 years of age underwent diffusion tensor imaging and an executive function test-battery. Mean fractional anisotropy (FA) was calculated for each white matter tract. Linear regression tested age and group effects (CHD vs control) and their interaction on FA. Relative Variable Importance (RI) estimated the independent contribution of tract FA, presence of CHD, CHD complexity, and parental education to the variability in EF. Mean FA was lower in patients compared to controls in almost all tracts (p between 0.057 and <0.001). WMM alterations in patients were not different depending on age (all interaction effects p>0.074). Predictors of EF were CHD group (RI=43%), parental education (RI=23%), CHD complexity (RI=10%), FA of the hippocampal cingulum (RI=6%) and FA of the corticospinal tract (RI=6%). The lack of group-FA-interactions indicates that the extent of altered FA remains similar across age. Altered FA is associated with EF impairments. CHD is a chronic disease with cerebral and neurocognitive impairments persisting into adulthood and, thus, long-term follow-up programs may improve overall outcome for this population.

Mixed longitudinal and cross-sectional analyses of deep gray matter and white matter using diffusion weighted images in premanifest and manifest Huntington's disease

Changes in the brain of patients with Huntington's disease (HD) begin years before clinical onset, so it remains critical to identify biomarkers to track these early changes. Metrics derived from tensor modeling of diffusion-weighted MRIs (DTI), that indicate the microscopic brain structure, can add important information to regional volumetric measurements. This study uses two large-scale longitudinal, multicenter datasets, PREDICT-HD and IMAGE-HD, to trace changes in DTI of HD participants with a broad range of CAP scores (a product of CAG repeat expansion and age), including those with pre-manifest disease (i.e., prior to clinical onset). Utilizing a fully automated data-driven approach to study the whole brain divided in regions of interest, we traced changes in DTI metrics (diffusivity and fractional anisotropy) versus CAP scores, using sigmoidal and linear regression models. We identified points of inflection in the sigmoidal regression using change-point analysis. The deep gray matter showed more evident and earlier changes in DTI metrics over CAP scores, compared to the deep white matter. In the deep white matter, these changes were more evident and occurred earlier in superior and posterior areas, compared to anterior and inferior areas. The curves of mean diffusivity vs. age of HD participants within a fixed CAP score were different from those of controls, indicating that the disease has an additional effect to age on the microscopic brain structure. These results show the regional and temporal vulnerability of the white matter and deep gray matter in HD, with potential implications for experimental therapeutics.

Structural connectivity of an interoception network in schizophrenia

Interoception refers to the processing, integration, and interpretation of bodily signals by the brain. Interoception is key to not only basic survival, but also motivational and affective functioning. There is emerging evidence suggesting altered interoception in schizophrenia, but few studies have explored potential neural underpinnings. The current study aims to investigate the anatomical connectivity of a previously identified interoception network in individuals with schizophrenia, and the relationship between network structural connectivity and both emotional functioning and clinical symptoms. Thirty-five participants with schizophrenia (SZ) and 36 healthy control participants (HC) underwent diffusion tensor imaging (DTI) and performed tasks measuring emotional functioning. Probabilistic tractography was used to identify white matter tracts connecting key hubs in an interoception network. Microstructural integrity of these tracts was compared across groups and correlated with measures of emotional functioning and symptom severity. Compared with HC, SZ exhibited altered structural connectivity in the interoception network. In HC, the structural connectivity of the network was significantly correlated with emotion recognition, supporting a link between the interoception network and emotional functioning. However, this correlation was much weaker in SZ. These findings suggest that altered interoception may have implications for illness mechanisms of schizophrenia, especially in relation to emotional deficits.

Fixel-based analysis of the diffusion properties of the patients with brain injury and chronic health symptoms

The diffusion properties from diffusion tensor imaging (DTI) are sensitive to white matter (WM) abnormalities and could serve as indicators of diffuse axonal damages incurred during a traumatic brain injury (TBI). Analyses of diffusion metrics in the regions of interest (ROIs) were used to compare the differences in the 18 major fiber tracts in 46 participants, between TBI participants with (n = 17) or without (n = 16) chronic symptoms (CS) and a control group (CG, n = 13). In addition to the widely used diffusion metrics, such as fractional anisotropy (FA), mean (MD), axial (AD) and radial (RD) diffusivities, apparent fiber density (AFD), complexity (CX) and fixel number (FN) derived from Mrtrix3 software package were used to characterize WM tracts and compare between participant groups in the ROIs defined by the fixel numbers. Significant differences were found in FA, AFD, MD, RD and CX in ROIs with different FNs in the corpus callosum forceps minor, left and right inferior longitudinal fasciculus, and left and right uncinate fasciculus for both TBI groups compared to controls. Diffusion properties in ROIs with different FNs can serve as detailed biomarkers of WM abnormalities, especially for individuals with chronic TBI related symptoms.

Automation and standardization of subject-specific region-of-interest segmentation for investigation of diffusion imaging in clinical populations

Diffusion weighted imaging (DWI) is key in clinical neuroimaging studies. In recent years, DWI has undergone rapid evolution and increasing applications. Diffusion magnetic resonance imaging (dMRI) is widely used to analyse group-level differences in white matter (WM), but suffers from limitations that can be particularly impactful in clinical groups where 1) structural abnormalities may increase erroneous inter-subject registration and 2) subtle differences in WM microstructure between individuals can be missed. It also lacks standardization protocols for analyses at the subject level. Region of Interest (ROI) analyses in native diffusion space can help overcome these challenges, with manual segmentation still used as the gold standard. However, robust automated approaches for the analysis of ROI-extracted native diffusion characteristics are limited. Subject-Specific Diffusion Segmentation (SSDS) is an automated pipeline that uses pre-existing imaging analysis methods to carry out WM investigations in native diffusion space, while overcoming the need to interpolate diffusion images and using an intermediate T1 image to limit registration errors and guide segmentation. SSDS is validated in a cohort of healthy subjects scanned three times to derive test-retest reliability measures and compared to other methods, namely manual segmentation and tract-based spatial statistics as an example of group-level method. The performance of the pipeline is further tested in a clinical population of patients with traumatic brain injury and structural abnormalities. Mean FA values obtained from SSDS showed high test-retest and were similar to FA values estimated from the manual segmentation of the same ROIs (p-value > 0.1). The average dice similarity coefficients (DSCs) comparing results from SSDS and manual segmentations was 0.8 ± 0.1. Case studies of TBI patients showed robustness to the presence of significant structural abnormalities, indicating its potential clinical application in the identification and diagnosis of WM abnormalities. Further recommendation is given regarding the tracts used with SSDS.

Relevant Biophysical Parameters Discrimination along Corticospinal Tract in Patients with Stroke Using Convolutional Neural Networks

Stroke remains the leading source of long-term disability. As the only direct descending motor pathway, the corticospinal tract (CST) is the primary pathway to innervate spinal motor neurons and one of the most well studied tracts in human neuroanatomy. Its clinical significance can be demonstrated in many distinguished traumatic situations and diseases such as stroke. Along‐tract statistics analysis enables the extraction of quantitative diffusion metrics along specific white matter fiber tracts. Besides quantitative metrics derived from classical diffusion tensor imaging (DTI), such as fractional anisotropy and diffusivities. In this study, we extracted DTI derived quantitative microstructural diffusion metrics along the CST tract in patients with moderate to severe subacute stroke. Respectively DTI metric of individual patient's fiber tract was then plotted. This approach may be useful for future studies that may compare in two different time (acute and chronic). The contribution of this work presents a totally computerized method of DTI image recognition based on conventional neural network (CNN) in order to supply quantitative appraisal of clinical characteristics. The obtained results have achieved an important classification (Accuracy=94.12%) when applying the CNN. The proposed methodology enables us to assess the classification of the used DTI images database within a reduced processing time. Experimental results prove the success of the proposed rating system for a suitable analysis of microstructural diffusion when compared to previous work.

Hippocampal blood-brain barrier permeability is related to the APOE4 mutation status of elderly individuals without dementia

Blood-brain barrier (BBB) disruption, modulated by APOE4 mutation, is implicated in the pathogenesis of cognitive decline. We determined whether BBB permeability differed according to cognitive functioning and APOE4 status in elderly subjects without dementia. In this prospective study, 33 subjects with mild cognitive impairment (MCI) and 33 age-matched controls (normal cognition [NC]) underwent 3 T brain magnetic resonance imaging. The Patlak model was used to calculate tissue permeability (K_trans). A region-of interest analysis of K_trans was performed to compare relevant brain regions. Effects of K_trans on cognitive functioning were evaluated with linear regression analysis adjusted for confounding factors. NC and MCI groups did not differ in terms of vascular risk factors or hippocampal K_trans, except for hippocampal volume. Hippocampal K_trans was significantly higher in APOE4 carriers than in non-carriers (p = 0.007). Factors which predicted cognitive functioning included hippocampal volume (beta=-0.445, standard error [SE]=0.137, p = 0.003) and hippocampal BBB permeability (beta = 0.142, SE = 0.050, p = 0.008) after correcting for age, education, and APOE4 status. This suggests that hippocampal BBB permeability is associated with APOE4 mutation, and may predict cognitive functioning. BBB permeability imaging represents a distinct imaging biomarker for APOE4 mutations in NC and MCI subjects and for determining the degree of APOE4-related pathology.

Diffusion Tensor Imaging Reveals Whole-Brain Microstructural Changes in the P301L Mouse Model of Tauopathy

INTRODUCTION

Increased expression of hyperphosphorylated tau and the formation of neurofibrillary tangles are associated with neuronal loss and white matter damage. Using high-resolution ex vivo diffusion tensor imaging (DTI), we investigated microstructural changes in the white and grey matter in the P301L mouse model of human tauopathy at 8.5 months of age. For unbiased computational analysis, we implemented a pipeline for voxel-based analysis (VBA) and atlas-based analysis (ABA) of DTI mouse brain data.

METHODS

Hemizygous and homozygous transgenic P301L mice and non-transgenic littermates were used. DTI data were acquired for generation of fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) maps. VBA on the entire brain was performed using SPM8 and the SPM Mouse toolbox. Initially, all DTI maps were coregistered with the Allen mouse brain atlas to bring them to one common coordinate space. In VBA, coregistered DTI maps were normalized and smoothed in order to perform two-sample and unpaired t tests with false discovery rate correction to compare hemizygotes with non-transgenic littermates, homozygotes with non-transgenic littermates, and hemizygotes with homozygotes on each DTI parameter map. In ABA, the average values for selected regions of interests were computed with coregistered DTI maps and labels in Allen mouse brain atlas. Afterwards, a Kruskal-Wallis one-way ANOVA on ranks with a Tukey post hoc test was executed on the estimated average values.

RESULTS

With VBA, we found pronounced and brain-wide spread changes when comparing homozygous, P301L mice with non-transgenic littermates, which were not seen when comparing hemizygous P301L with non-transgenic animals. Statistical comparison of DTI metrics in selected brain regions by ABA corroborated findings from VBA. FA was found to be decreased in most brain regions, while MD, RD, and AD were increased in homozygotes compared to hemizygotes and non-transgenic littermates.

DISCUSSION/CONCLUSION

High-resolution ex vivo DTI demonstrated brain-wide microstructural and gene-dose-dependent changes in the P301L mouse model of human tauopathy. The DTI analysis pipeline may serve for the phenotyping of models of tauopathy and other brain diseases.

Utility of manual fractional anisotropy measurements in the management of patients with Parkinson disease: a feasibility study with a 1.5-T magnetic resonance imaging system

Background

Diffusion tensor imaging has emerged as a promising tool for quantitative analysis of neuronal damage in Parkinson disease, with potential value for diagnostic and prognostic evaluation.

Purpose

The aim of this study was to examine Parkinson disease-associated alterations in specific brain regions revealed by diffusion tensor imaging and how such alterations correlate with clinical variables.

Material and Methods

Diffusion tensor imaging was performed on 42 Parkinson disease patients and 20 healthy controls with a 1.5-T scanner. Manual fractional anisotropy measurements were performed for the ventral, intermediate, and dorsal portions of the substantia nigra, as well as for the cerebral peduncles, putamen, thalamus, and supplementary motor area. The correlation analysis between these measurements and the clinical variables was performed using χ² variance and multiple linear regression.

Results

Compared to healthy controls, Parkinson disease patients had significantly reduced fractional anisotropy values in the substantia nigra (P < .05). Some fractional anisotropy measurements in the substantia nigra correlated inversely with duration of Parkinson disease and Parkinson disease severity scores. Reduced fractional anisotropy values in the substantia nigra were also correlated inversely with age variable. fractional anisotropy values obtained for the right and left putamen varied significantly between males and females in both groups.

Conclusion

Manual fractional anisotropy measurements in the substantia nigra were confirmed to be feasible with a 1.5-T scanner. Diffusion tensor imaging data can be used as a reliable biomarker of Parkinson disease that can be used to support diagnosis, prognosis, and progression/treatment monitoring.

White matter microstructural abnormalities in primary insomnia: A systematic review of diffusion tensor imaging studies

Primary insomnia (PI), the most common sleep disorder, is primarily characterized by difficulties in initiating and maintaining sleep and deficits in daytime functioning. Study of white matter (WM) connections of the brain might provide valuable information regarding the underlying neural mechanism of PI. Diffusion tensor imaging (DTI) provides non-invasive access to the microstructural and network properties of brain WM, and thus, a great opportunity to quantitatively and sensitively study the human brain. The current literature of PI does not provide a consistent explanation of the etiology and pathology of the disorder; thus, we searched PubMed, EMBASE, and SCOPUS for DTI studies that compared WM integrity or network organization between PI patients and healthy controls to integrate all existing literature as an insight for further studies, and, hopefully, effective prevention and management of the disorder. English peer-reviewed full-text publications that investigated the diffusion indices of PI patients or those with insomnia symptoms compared with a group of healthy controls were included. We included 11 studies and extracted the data for qualitative synthesis. Except for one study, all studies were rated as high-quality, based on quality assessment. In aggregation, a total of 541 patients with PI and 679 healthy controls were included in this study. Our review of DTI studies suggests that WM disruptions in PI are better characterized in the context of neural networks. Frontostriatal, frontothalamic, and corticocortiscal networks, as well as the limbic system, seem to be the main neural networks with microstructural and network alterations in patients with PI. To illustrate, different parts of corona radiate and internal capsule within the corticosubcortical networks and superior longitudinal fasciculus within the corticocortical networks showed altered microstructural properties in PI patients. In view of the fact that the findings from individual studies are heterogeneous, it is difficult to derive consistent findings from the results, and the divergence of the findings must not be disregarded. Thus, this study is a starting point for future studies, and its implications for etiology and pathogenesis of insomnia should be regarded cautiously.

Functional coupling of the orbitofrontal cortex and the basolateral amygdala mediates the association between spontaneous reappraisal and emotional response

Emotional regulation is known to be associated with activity in the amygdala. The amygdala is an emotion-generative region that comprises of structurally and functionally distinct nuclei. However, little is known about the contributions of different frontal-amygdala sub-region pathways to emotion regulation. Here, we investigated how functional couplings between frontal regions and amygdala sub-regions are involved in different spontaneous emotion regulation processes by using an individual-difference approach and a generalized psycho-physiological interaction (gPPI) approach. Specifically, 50 healthy participants reported their dispositional use of spontaneous cognitive reappraisal and expressive suppression in daily life and their actual use of these two strategies during the performance of an emotional-picture watching task. Results showed that functional coupling between the orbitofrontal cortex (OFC) and the basolateral amygdala (BLA) was associated with higher scores of both dispositional and actual uses of reappraisal. Similarly, functional coupling between the dorsolateral prefrontal cortex (dlPFC) and the centromedial amygdala (CMA) was associated with higher scores of both dispositional and actual uses of suppression. Mediation analyses indicated that functional coupling of the right OFC-BLA partially mediated the association between reappraisal and emotional response, irrespective of whether reappraisal was measured by dispositional use (indirect effect(SE)=-0.2021 (0.0811), 95%CI_(BC)= [-0.3851, -0.0655]) or actual use (indirect effect(SE)=-0.1951 (0.0796), 95%CI_(BC)= [-0.3654, -0.0518])). These findings suggest that spontaneous reappraisal and suppression involve distinct frontal- amygdala functional couplings, and the modulation of BLA activity from OFC may be necessary for changing emotional response during spontaneous reappraisal.

Longitudinal Reproducibility of Neurite Orientation Dispersion and Density Imaging (NODDI) Derived Metrics in the White Matter

Diffusion-weighted magnetic resonance imaging (DWI) is undergoing constant evolution with the ambitious goal of developing in-vivo histology of the brain. A recent methodological advancement is Neurite Orientation Dispersion and Density Imaging (NODDI), a histologically validated multi-compartment model to yield microstructural features of brain tissue such as geometric complexity and neurite packing density, which are especially useful in imaging the white matter. Since NODDI is increasingly popular in clinical research and fields such as developmental neuroscience and neuroplasticity, it is of vast importance to characterize its reproducibility (or reliability). We acquired multi-shell DWI data in 29 healthy young subjects twice over a rescan interval of 4 weeks to assess the within-subject coefficient of variation (CV_WS), between-subject coefficient of variation (CV_BS) and the intraclass correlation coefficient (ICC), respectively. Using these metrics, we compared regional and voxel-by-voxel reproducibility of the most common image analysis approaches (tract-based spatial statistics [TBSS], voxel-based analysis with different extents of smoothing ["VBM-style"], ROI-based analysis). We observed high test-retest reproducibility for the orientation dispersion index (ODI) and slightly worse results for the neurite density index (NDI). Our findings also suggest that the choice of analysis approach might have significant consequences for the results of a study. Collectively, the voxel-based approach with Gaussian smoothing kernels of ≥4 mm FWHM and ROI-averaging yielded the highest reproducibility across NDI and ODI maps (CV_WS mostly ≤3%, ICC mostly ≥0.8), respectively, whilst smaller kernels and TBSS performed consistently worse. Furthermore, we demonstrate that image quality (signal-to-noise ratio [SNR]) is an important determinant of NODDI metric reproducibility. We discuss the implications of these results for longitudinal and cross-sectional research designs commonly employed in the neuroimaging field.

A Confidence Habitats Methodology in MR Quantitative Diffusion for the Classification of Neuroblastic Tumors

Simple Summary

There is growing interest in applying quantitative diffusion techniques to magnetic resonance imaging for cancer diagnosis and treatment. These measurements are used as a surrogate marker of tumor cellularity and aggressiveness, although there may be factors that introduce some bias to these approaches. Thus, we explored a novel methodology based on confidence habitats and voxel uncertainty to improve the power of the apparent diffusion coefficient to discriminate between benign and malignant neuroblastic tumor profiles in children. We were able to show this offered an improved sensitivity and negative predictive value relative to standard voxel-based methodologies.

Abstract

Background/Aim: In recent years, the apparent diffusion coefficient (ADC) has been used in many oncology applications as a surrogate marker of tumor cellularity and aggressiveness, although several factors may introduce bias when calculating this coefficient. The goal of this study was to develop a novel methodology (Fit-Cluster-Fit) based on confidence habitats that could be applied to quantitative diffusion-weighted magnetic resonance images (DWIs) to enhance the power of ADC values to discriminate between benign and malignant neuroblastic tumor profiles in children. Methods: Histogram analysis and clustering-based algorithms were applied to DWIs from 33 patients to perform tumor voxel discrimination into two classes. Voxel uncertainties were quantified and incorporated to obtain a more reproducible and meaningful estimate of ADC values within a tumor habitat. Computational experiments were performed by smearing the ADC values in order to obtain confidence maps that help identify and remove noise from low-quality voxels within high-signal clustered regions. The proposed Fit-Cluster-Fit methodology was compared with two other methods: conventional voxel-based and a cluster-based strategy. Results: The cluster-based and Fit-Cluster-Fit models successfully differentiated benign and malignant neuroblastic tumor profiles when using values from the lower ADC habitat. In particular, the best sensitivity (91%) and specificity (89%) of all the combinations and methods explored was achieved by removing uncertainties at a 70% confidence threshold, improving standard voxel-based sensitivity and negative predictive values by 4% and 10%, respectively. Conclusions: The Fit-Cluster-Fit method improves the performance of imaging biomarkers in classifying pediatric solid tumor cancers and it can probably be adapted to dynamic signal evaluation for any tumor.

Microstructure of the Corpus Callosum Long after Pediatric Concussion

OBJECTIVE

The long-term effects of pediatric concussion on white matter microstructure are poorly understood. This study investigated long-term changes in white matter diffusion properties of the corpus callosum in youth several years after concussion.

METHODS

Participants were 8-19 years old with a history of concussion (n = 36) or orthopedic injury (OI) (n = 21). Mean time since injury for the sample was 2.6 years (SD = 1.6). Participants underwent diffusion magnetic resonance imaging, completed cognitive testing, and rated their post-concussion symptoms. Measures of diffusivity (fractional anisotropy, mean, axial, and radial diffusivity) were extracted from white matter tracts in the genu, body, and splenium regions of the corpus callosum. The genu and splenium tracts were further subdivided into 21 equally spaced regions along the tract and diffusion values were extracted from each of these smaller regions.

RESULTS

White matter tracts in the genu, body, and splenium did not differ in diffusivity properties between youth with a history of concussion and those with a history of OI. No significant group differences were found in subdivisions of the genu and splenium after correcting for multiple comparisons. Diffusion metrics did not significantly correlate with symptom reports or cognitive performance.

CONCLUSIONS

These findings suggest that at approximately 2.5 years post-injury, youth with prior concussion do not have differences in their corpus callosum microstructure compared to youth with OI. Although these results are promising from the perspective of long-term recovery, further research utilizing longitudinal study designs is needed to confirm the long-term effects of pediatric concussion on white matter microstructure.

Spatial regression analysis of MR diffusion reveals subject-specific white matter changes associated with repetitive head impacts in contact sports

Repetitive head impacts (RHI) are a growing concern due to their possible neurocognitive effects, with research showing a season of RHI produce white matter (WM) changes seen on neuroimaging. We conducted a secondary analysis of diffusion tensor imaging (DTI) data for 28 contact athletes to compare WM changes. We collected pre-season and post-season DTI scans for each subject, approximately 3 months apart. We collected helmet data for the athletes, which we correlated with DTI data. We adapted the SPatial REgression Analysis of DTI (SPREAD) algorithm to conduct subject-specific longitudinal DTI analysis, and developed global inferential tools using functional norms and a novel robust p value combination test. At the individual level, most detected injured regions (93.3%) were associated with decreased FA values. Using meta-analysis techniques to combine injured regions across subjects, we found the combined injured region at the group level occupied the entire WM skeleton, suggesting the WM damage location is subject-specific. Several subject-specific functional summaries of SPREAD-detected WM change, e.g., the [Formula: see text] norm, significantly correlated with helmet impact measures, e.g. cumulative unweighted rotational acceleration (adjusted p = 0.0049), time between hits rotational acceleration (adjusted p value 0.0101), and time until DTI rotational acceleration (adjusted p = 0.0084), suggesting RHIs lead to WM changes.

Abnormalities of effective connectivity and white matter microstructure in the triple network in patients with schizophrenia

Disorganized communication among large-scale brain networks, especially in the salience network, default mode network and central executive network, have been consistently reported in schizophrenia (SZ) patients. However, abnormal patterns of the effective connectivity and abnormalities in the white matter of these networks remains unclear in patients with SZ. Fifty-six SZ patients and fifty-five healthy controls were enrolled in the present study and underwent resting state functional magnetic resonance and diffusion tensor imaging. Twelve main nodes within the triple networks were defined by independent components analysis. Effective connectivity between these main nodes was computed using Granger causality analysis. Voxel-based analysis of the diffusion tensor imaging data was conducted to explore white matter changes. The SZ patients showed abnormal effective connectivity between the anterior cingulate cortex and the dorsolateral prefrontal cortex. The abnormal white matter showed decreased fractional anisotropy localized in the bilateral anterior corona radiate and left superior long fasciculus in patients with SZ. These findings shed light on the importance of the triple network in the pathogenesis of SZ, which may facilitate the understanding of SZ.

Inpainting as a Technique for Estimation of Missing Voxels in Brain Imaging

Issues with model fitting (i.e. suboptimal standard deviation, linewidth/full-width-at-half-maximum, and/or signal-to-noise ratio) in multi-voxel MRI spectroscopy, or chemical shift imaging (CSI) can result in the significant loss of usable voxels. A potential solution to minimize this problem is to estimate the value of unusable voxels by utilizing information from reliable voxels in the same image. We assessed an image restoration method called inpainting as a tool to restore unusable voxels, and compared it with traditional interpolation methods (nearest neighbor, trilinear interpolation and tricubic interpolation). In order to evaluate the performance across varying image contrasts and spatial resolutions, we applied the same techniques to a T1-weighted MRI brain dataset, and N-acetylaspartate (NAA) spectroscopy maps from a CSI dataset. For all image types, inpainting exhibited superior performance (lower normalized root-mean-square errors, NRMSE) compared to all other methods considered (p's < 0.001). Inpainting maintained an average NRMSE of less than 5% even with 50% missing voxels, whereas the other techniques demonstrated up to three times that value, depending on the nature of the image. For CSI maps, inpainting maintained its superiority whether the previously unusable voxels were randomly distributed, or located in regions most commonly affected by voxel loss in real-world data. Inpainting is a promising approach for recovering unusable or missing voxels in voxel-wise analyses, particularly in imaging modalities characterized by low SNR such as CSI. We hypothesize that this technique may also be applicable for datasets from other imaging modalities, such as positron emission tomography, or dynamic susceptibility contrast MRI.

Contralesional White Matter Alterations in Patients After Hemispherotomy

Cerebral lesions may cause degeneration and neuroplastic reorganization in both the ipsi- and the contralesional hemisphere, presumably creating an imbalance of primarily inhibitory interhemispheric influences produced via transcallosal pathways. The two hemispheres are thought to mutually hamper neuroplastic reorganization of the other hemisphere. The results of preceding degeneration and neuroplastic reorganization of white matter may be reflected by Diffusion Tensor Imaging-derived diffusivity parameters such as fractional anisotropy (FA). In this study, we applied Diffusion Tensor Imaging (DTI) to contrast the white matter status of the contralesional hemisphere of young lesioned brains with and without contralateral influences by comparing patients after hemispherotomy to those who had not undergone neurosurgery. DTI was applied to 43 healthy controls (26 females, mean age ± SD: 25.07 ± 11.33 years) and two groups of in total 51 epilepsy patients with comparable juvenile brain lesions (32 females, mean age ± SD: 25.69 ± 12.77 years) either after hemispherotomy (30 of 51 patients) or without neurosurgery (21 of 51 patients), respectively. FA values were compared between these groups using the unbiased tract-based spatial statistics approach. A voxel-wise ANCOVA controlling for age at scan yielded significant group differences in FA. A post hoc t-test between hemispherotomy patients and healthy controls revealed widespread supra-threshold voxels in the contralesional hemisphere of hemispherotomy patients indicating comparatively higher FA values (p < 0.05, FWE-corrected). The non-surgery group, in contrast, showed extensive supra-threshold voxels indicating lower FA values in the contralesional hemisphere as compared to healthy controls (p < 0.05, FWE-corrected). Whereas lower FA values are suggestive of pronounced contralesional degeneration in the non-surgery group, higher FA values in the hemispherotomy group may be interpreted as a result of preceding plastic remodeling. We conclude that, whether juvenile brain lesions are associated with contralesional degeneration or reorganization partly depends on the ipsilesional hemisphere. Contralesional reorganization as observed in hemispherotomy patients was most likely enabled by the complete neurosurgical deafferentation of the ipsilesional hemisphere and, thereby, the disinhibition of the neuroplastic potential of the contralesional hemisphere. The main argument of this study is that hemispherotomy may be seen as a major plastic stimulus and as a prerequisite for contralesional neuroplastic remodeling in patients with juvenile brain lesions.

Denoise magnitude diffusion magnetic resonance images via variance-stabilizing transformation and optimal singular-value manipulation

Although shown to have a great utility for a wide range of neuroscientific and clinical applications, diffusion-weighted magnetic resonance imaging (dMRI) faces a major challenge of low signal-to-noise ratio (SNR), especially when pushing the spatial resolution for improved delineation of brain's fine structure or increasing the diffusion weighting for increased angular contrast or both. Here, we introduce a comprehensive denoising framework for denoising magnitude dMRI. The framework synergistically combines the variance stabilizing transform (VST) with optimal singular value manipulation. The purpose of VST is to transform the Rician data to Gaussian-like data so that an asymptotically optimal singular value manipulation strategy tailored for Gaussian data can be used. The output of the framework is the estimated underlying diffusion signal for each voxel in the image domain. The usefulness of the proposed framework for denoising magnitude dMRI is demonstrated using both simulation and real-data experiments. Our results show that the proposed denoising framework can significantly improve SNR across the entire brain, leading to substantially enhanced performances for estimating diffusion tensor related indices and for resolving crossing fibers when compared to another competing method. More encouragingly, the proposed method when used to denoise a single average of 7 ​Tesla Human Connectome Project-style diffusion acquisition provided comparable performances relative to those achievable with ten averages for resolving multiple fiber populations across the brain. As such, the proposed denoising method is expected to have a great utility for high-quality, high-resolution whole-brain dMRI, desirable for many neuroscientific and clinical applications.

A review of diffusion MRI of typical white matter development from early childhood to young adulthood

Understanding typical, healthy brain development provides a baseline from which to detect and characterize brain anomalies associated with various neurological or psychiatric disorders and diseases. Diffusion MRI is well suited to study white matter development, as it can virtually extract individual tracts and yield parameters that may reflect alterations in the underlying neural micro-structure (e.g. myelination, axon density, fiber coherence), though it is limited by its lack of specificity and other methodological concerns. This review summarizes the last decade of diffusion imaging studies of healthy white matter development spanning childhood to early adulthood (4-35 years). Conclusions about anatomical location, rates, and timing of white matter development with age are discussed, as well as the influence of image acquisition, analysis, age range/sample size, and statistical model. Despite methodological variability between studies, some consistent findings have emerged from the literature. Specifically, diffusion studies of neurodevelopment overwhelmingly demonstrate regionally varying increases of fractional anisotropy and decreases of mean diffusivity during childhood and adolescence, some of which continue into adulthood. While most studies use linear fits to model age-related changes, studies with sufficient sample sizes and age range provide clear evidence that white matter development (as indicated by diffusion) is non-linear. Several studies further suggest that maturation in association tracts with frontal-temporal connections continues later than commissural and projection tracts. The emerging contributions of more advanced diffusion methods are also discussed, as they may reveal new aspects of white matter development. Although non-specific, diffusion changes may reflect increases of myelination, axonal packing, and/or coherence with age that may be associated with changes in cognition.

White Matter Microstructure Breakdown in the Motor Neuron Disease Spectrum: Recent Advances Using Diffusion Magnetic Resonance Imaging

Motor neuron disease (MND) is a fatal progressive neurodegenerative disorder characterized by the breakdown of the motor system. The clinical spectrum of MND encompasses different phenotypes classified according to the relative involvement of the upper or lower motor neurons (LMN) and the presence of genetic or cognitive alterations, with clear prognostic implications. However, the pathophysiological differences of these phenotypes remain largely unknown. Recently, magnetic resonance imaging (MRI) has been recognized as a helpful in-vivo MND biomarker. An increasing number of studies is applying advanced neuroimaging techniques in order to elucidate the pathophysiological processes and to identify quantitative outcomes to be used in clinical trials. Diffusion tensor imaging (DTI) is a non-invasive method to detect white matter alterations involving the upper motor neuron and extra-motor white matter tracts. According to this background, the aim of this review is to highlight the key role of MRI and especially DTI, summarizing cross-sectional and longitudinal results of different approaches applied in MND. Current literature suggests that DTI is a promising tool in order to define anatomical “signatures” of the different phenotypes of MND and to track in vivo the progressive spread of pathological proteins aggregates.

Developmental trajectory of the prefrontal cortex: a systematic review of diffusion tensor imaging studies

Fluctuations in gray and white matter volumes in addition to the fibers' reorganization and refinement of synaptic connectivity apparently happen in a particular temporo-spatial sequence during the dynamic and prolonged process of cerebral maturation. These developmental events are associated with regional modifications of brain tissues and neural circuits, contributing to networks' specialization and enhanced cognitive processing. According to several studies, improvements in cognitive processes are possibly myelin-dependent and associated to white matter maturation. Of particular interest is the developmental pattern of the prefrontal cortex (PFC), more specifically the PFC white matter, due to its role in high-level executive processes such as attention, working memory and inhibitory control. A systematic review of the literature was conducted using the Web of Science, PubMed and Embase databases to analyze the development of PFC white matter using Diffusion Tensor Imaging (DTI), a widely used non-invasive technique to assess white matter maturation. Both the research and reporting of results were based on Cochrane's recommendations and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines. Information extracted from 27 published studies revealed an increased myelination, organization and integrity of frontal white matter with age, as revealed by DTI indexes (fractional anisotropy [FA], mean diffusivity [MD], radial diffusivity [RD] and axial diffusivity [AD]). These patterns highlight the extended developmental course of the frontal structural connectivity, which parallels the improvements in higher-level cognitive functions observed between adolescence and early adulthood.

Structural Thalamofrontal Hypoconnectivity Is Related to Oculomotor Corollary Discharge Dysfunction in Schizophrenia

By predicting sensory consequences of actions, humans can distinguish self-generated sensory inputs from those that are elicited externally. This is one mechanism by which we achieve a subjective sense of agency over our actions. Corollary discharge (CD) signals-"copies" of motor signals sent to sensory areas-permit such predictions, and CD abnormalities are a hypothesized mechanism for the agency disruptions in schizophrenia that characterize a subset of symptoms. Indeed, behavioral evidence of altered CD, including in the oculomotor system, has been observed in schizophrenia patients. A pathway projecting from the superior colliculus to the frontal eye fields (FEFs) via the mediodorsal thalamus (MD) conveys oculomotor CD associated with saccadic eye movements in nonhuman primates. This animal work provides a promising translational framework in which to investigate CD abnormalities in clinical populations. In the current study, we examined whether structural connectivity of this MD-FEF pathway relates to oculomotor CD functioning in schizophrenia. Twenty-two schizophrenia patients and 24 healthy control participants of both sexes underwent diffusion tensor imaging, and a large subset performed a trans-saccadic perceptual task that yields measures of CD. Using probabilistic tractography, we identified anatomical connections between FEF and MD and extracted indices of microstructural integrity. Patients exhibited compromised microstructural integrity in the MD-FEF pathway, which was correlated with greater oculomotor CD abnormalities and more severe psychotic symptoms. These data reinforce the role of the MD-FEF pathway in transmitting oculomotor CD signals and suggest that disturbances in this pathway may relate to psychotic symptom manifestation in patients.SIGNIFICANCE STATEMENT People with schizophrenia sometimes experience abnormalities in a sense of agency, which may stem from abnormal sensory predictions about their own actions. Consistent with this notion, the current study found reduced structural connectivity in patients with schizophrenia in a specific brain pathway found to transmit such sensorimotor prediction signals in nonhuman primates. Reduced structural connectivity was correlated with behavioral evidence for impaired sensorimotor predictions and psychotic symptoms.

Diffusion tensor imaging and disability progression in multiple sclerosis: A 4-year follow-up study

OBJECTIVES

Diffusion tensor imaging (DTI) is sensitive technique to detect widespread changes in water diffusivity in the normal-appearing white matter (NAWM) that appears unaffected in conventional magnetic resonance imaging. We aimed to investigate the prognostic value and stability of DTI indices in the NAWM of the brain in an assessment of disability progression in patients with a relapsing-onset multiple sclerosis (MS).

METHODS

Forty-six MS patients were studied for DTI indices (fractional anisotropy (FA), mean diffusivity (MD), radial (RD), and axial (AD) diffusivity) in the NAWM of the corpus callosum (CC) and the internal capsule at baseline and at 1 year after. DTI analysis for 10 healthy controls was also performed at baseline. Simultaneously, focal brain lesion volume and atrophy measurements were done at baseline for MS patients. Associations between DTI indices, volumetric measurements, and disability progression over 4 years were studied by multivariate logistic regression analysis.

RESULTS

At baseline, most DTI metrics differed significantly between MS patients and healthy controls. There was tendency for associations between baseline DTI indices in the CC and disability progression (p < 0.05). Changes in DTI indices over 1 year were observed only in the CC (p < 0.008), and those changes were not found to predict clinical worsening over 4 years. Clear-cut association with disability progression was not detected for baseline volumetric measurements.

CONCLUSION

Aberrant diffusivity measures in the NAWM of the CC may provide additional information for individual disability progression over 4 years in MS with the relapsing-onset disease. CC may be a good target for DTI measurements in monitoring disease activity in MS, and more studies are needed to assess the related prognostic potential.

Comparison of DTI analysis methods for clinical research: influence of pre-processing and tract selection methods

Background

The primary aim was to compare fractional anisotropy (FA) values derived with different diffusion tensor imaging (DTI) analysis approaches (atlas-based, streamline tractography, and combined). A secondary aim was to compare FA values and number of tracts (NT) with the clinical motor outcome quantified by the functional independence measure for children (WeeFIM).

Methods

Thirty-nine DTI datasets of children with acquired brain injury were analysed. Regions of interest for the ipsilesional corticospinal tract were defined and mean FA and NT were calculated. We evaluated FA values with Spearman correlation, the Friedman and Wilcoxon tests, and Bland-Altman analysis. DTI values were compared to WeeFIM values by non-parametric partial correlation and accuracy was assessed by receiver operating characteristics analysis.

Results

The FA values from all approaches correlated significantly with each other (p < 0.001). However, the FA values from streamline tractography were significantly higher (mean ± standard deviation (SD), 0.52 ± 0.08) than those from the atlas-based (0.42 ± 0.11) or the combined approach (0.41 ± 0.11) (p < 0.001 for both). FA and NT values correlated significantly with WeeFIM values (atlas-based FA, partial correlation coefficient (ρ) = 0.545, p = 0.001; streamline FA, ρ = 0.505, p = 0.002; NT, ρ = 0.434, p = 0.008; combined FA, ρ = 0.611, p < 0.001). FA of the atlas-based approach (sensitivity 90%, specificity 67%, area under the curve 0.82) and the combined approach (87%, 67%, 0.82), provided the highest predictive accuracy for outcome compared to FA (70%, 67%, 0.67) and NT (50%, 100%, 0.79, respectively) of the streamline approach.

Conclusion

FA values from streamline tractography were higher than those from the atlas-based and combined approach. The atlas-based and combined approach offer the best predictive accuracy for motor outcome, although both atlas-based and streamline tractography approaches provide significant predictors of clinical outcome.

Diffusion tensor imaging correlates of early markers of depression in youth at high-familial risk for bipolar disorder

BACKGROUND

Mood disorders are familial psychiatric diseases, in which patients show reduced white matter (WM) integrity. We sought to determine whether WM integrity was affected in young offspring at high-familial risk of mood disorder before they go on to develop major depressive disorder (MDD).

METHODS

The Bipolar Family study is a prospective longitudinal study examining young individuals (age 16-25 years) at familial risk of mood disorder on three occasions 2 years apart. This study used baseline imaging data, categorizing groups according to clinical outcome at follow-up. Diffusion tensor MRI data were acquired for 61 controls and 106 high-risk individuals, the latter divided into 78 high-risk subjects who remained well throughout the study ('high-risk well') and 28 individuals who subsequently developed MDD ('high-risk MDD'). Voxel-wise between-group comparison of fractional anisotropy (FA) based on diagnostic status was performed using tract-based spatial statistics (TBSS).

RESULTS

Compared to controls, both high-risk groups showed widespread decreases in FA (p_corr  < .05) at baseline. Although FA in the high-risk MDD group negatively correlated with subthreshold depressive symptoms at the time of scanning (p_corr  < .05), there were no statistically significant differences at p-corrected levels between the two high-risk groups.

CONCLUSIONS

These results suggest that decreased FA is related to the presence of familial risk for mood disorder along with subdiagnostic symptoms at the time of scanning rather than predictive of subsequent diagnosis. Due to the difficulties performing such longitudinal prospective studies, we note, however, that this latter analysis may be underpowered due to sample size within the high-risk MDD group. Further clinical follow-up may clarify these findings.

Disruption of Inferior Longitudinal Fasciculus Microstructure in Parkinson's Disease: A Systematic Review of Diffusion Tensor Imaging Studies

Parkinson's disease (PD) is a neurodegenerative disorder accompanied by a series of pathological mechanisms which contribute to a variety of motor and non-motor symptoms. Recently, there has been an increasing interest in structural diffusion tensor imaging (DTI) in PD which has shed light on our understanding of structural abnormalities underlying PD symptoms or its associations with pathological mechanisms. One of the white matter tracts shown to be disrupted in PD with a possible contribution to some PD symptoms is the inferior longitudinal fasciculus (ILF). On the whole, lower ILF integrity contributes to thought disorders, impaired visual emotions, cognitive impairments such as semantic fluency deficits, and mood disorders. This review outlines the microstructural changes in ILF associated with systemic inflammation and various PD symptoms like cognitive decline, facial emotion recognition deficit, depression, color discrimination deficit, olfactory dysfunction, and tremor genesis. However, few studies have investigated DTI correlates of each symptom and larger studies with standardized imaging protocols are required to extend these preliminary findings and lead to more promising results.

Isolated focal dystonia phenotypes are associated with distinct patterns of altered microstructure

Objective

Isolated adult-onset focal dystonia is considered a network disorder with disturbances to the motor basal ganglia and cerebellar circuits playing a pathophysiological role, but why specific body regions become affected remains unknown. We aimed to use diffusion tensor imaging to determine if the two most common phenotypes of focal dystonia are associated with distinguishing microstructural changes affecting the motor network.

Methods

Fifteen blepharospasm patients, 20 cervical dystonia patients, and 30 age- and sex-matched healthy controls were recruited. Maps of fractional anisotropy and mean diffusivity were analyzed using a voxel-based approach and an automated region-of-interest technique to evaluate deep gray matter nuclei. Correlations between diffusion measures and dystonia severity were tested, and post hoc discriminant analyses were conducted.

Results

Voxel-based analyses revealed significantly reduced fractional anisotropy in the right cerebellum and increased mean diffusivity in the left caudate of cervical dystonia patients compared to controls, as well as lower fractional anisotropy in the right cerebellum in cervical dystonia patients relative to blepharospasm patients. In addition to reduced fractional anisotropy in the bilateral caudate nucleus of cervical dystonia patients relative to controls and blepharospasm patients, region-of-interest analyses revealed significantly reduced fractional anisotropy in the right globus pallidus internus and left red nucleus of blepharospasm patients compared to both controls and cervical dystonia patients. Diffusivity measures in the red nucleus of blepharospasm patients correlated with disease severity. In a three-group discriminant analysis, participants were correctly classified with only modest reliability (67-75%), but in a two-group discriminant analysis, patients could be distinguished from each other with high reliability (83-100%).

Conclusions

Different focal dystonia phenotypes are associated with distinct patterns of altered microstructure within constituent regions of basal ganglia and cerebellar circuits.

Mapping population-based structural connectomes

Advances in understanding the structural connectomes of human brain require improved approaches for the construction, comparison and integration of high-dimensional whole-brain tractography data from a large number of individuals. This article develops a population-based structural connectome (PSC) mapping framework to address these challenges. PSC simultaneously characterizes a large number of white matter bundles within and across different subjects by registering different subjects' brains based on coarse cortical parcellations, compressing the bundles of each connection, and extracting novel connection weights. A robust tractography algorithm and streamline post-processing techniques, including dilation of gray matter regions, streamline cutting, and outlier streamline removal are applied to improve the robustness of the extracted structural connectomes. The developed PSC framework can be used to reproducibly extract binary networks, weighted networks and streamline-based brain connectomes. We apply the PSC to Human Connectome Project data to illustrate its application in characterizing normal variations and heritability of structural connectomes in healthy subjects.

Current contribution of diffusion tensor imaging in the evaluation of diffuse axonal injury

ABSTRACT Traumatic brain injury (TBI) is the number one cause of death and morbidity among young adults. Moreover, survivors are frequently left with functional disabilities during the most productive years of their lives. One main aspect of TBI pathology is diffuse axonal injury, which is increasingly recognized due to its presence in 40% to 50% of all cases that require hospital admission. Diffuse axonal injury is defined as widespread axonal damage and is characterized by complete axotomy and secondary reactions due to overall axonopathy. These changes can be seen in neuroimaging studies as hemorrhagic focal areas and diffuse edema. However, the diffuse axonal injury findings are frequently under-recognized in conventional neuroimaging studies. In such scenarios, diffuse tensor imaging (DTI) plays an important role because it provides further information on white matter integrity that is not obtained with standard magnetic resonance imaging sequences. Extensive reviews concerning the physics of DTI and its use in the context of TBI patients have been published, but these issues are still hazy for many allied-health professionals. Herein, we aim to review the current contribution of diverse state-of-the-art DTI analytical methods to the understanding of diffuse axonal injury pathophysiology and prognosis, to serve as a quick reference for those interested in planning new studies and who are involved in the care of TBI victims. For this purpose, a comprehensive search in Pubmed was performed using the following keywords: “traumatic brain injury”, “diffuse axonal injury”, and “diffusion tensor imaging”.

Hippocampal Subfields Volume Reduction in High Schoolers with Previous Verbal Abuse Experiences

Objective

Reduced hippocampal volume and alterations in white matter tracts have been frequently reported in adults having the history of emotional maltreatment. We investigated whether these structural change occur in adolescents with previous verbal abuse (VA) experiences.

Methods

Hippocampal subfield volume and white matter structural connectivity measures were assessed in 31 first year male high school students with various degrees of exposure to parental and peer VA.

Results

The high VA group showed significant volume reduction in the left cornu ammonis (CA) 1 and left subiculum compared to the low VA group (p＜0.05). Volumes of left hippocampal subfields CA1 and subiculum were negatively correlated with previous VA experiences (p＜0.05). Increased mean diffusivity (MD) of the splenium of the corpus callosum was related to high VA score across all subjects (p＜0.05). There was an inverse relationship between volume of the CA1 and subiculum and MD of the splenium (p＜0.05).

Conclusion

Exposure to parental and peer VA may affect development of the left hippocampal subfields and the splenium of corpus callosum. These structural alterations can be discernible during adolescence.

Olfactory Impairment in Parkinson's Disease Studied with Diffusion Tensor and Magnetization Transfer Imaging

Background: Olfactory impairment is an early manifestation of Parkinson’s disease (PD). Diffusion Tensor Imaging (DTI) and Magnetization Transfer (MT) are two imaging techniques that allow noninvasive detection of microstructural changes in the cerebral white matter.

Objective: To assess white matter alterations associated with olfactory impairment in PD, using a binary imaging approach with DTI and MT.

Methods: 22 PD patients and 13 healthy controls were examined with DTI, MT and an odor discrimination test. DTI data were first analyzed with tract-based spatial statistics (TBSS) in order to detect differences in fractional anisotropy, mean, radial and axial diffusivity between PD patients and controls. Voxelwise randomized permutation was employed for the MT analysis, after spatial and intensity normalization. Additionally, ROI analysis was performed on both the DTI and MT data, focused on the white matter adjacent to olfactory brain regions.

Results: Whole brain voxelwise analysis revealed decreased axial diffusivity in the left uncinate fasciculus and the white matter adjacent to the left olfactory sulcus of PD patients. ROI analysis demonstrated decreased axial diffusivity in the right orbitofrontal cortex, as well as decreased mean diffusivity and axial diffusivity in the white matter of the left entorhinal cortex of PD patients. There were no significant differences regarding fractional anisotropy, radial diffusivity or MT between patients and controls.

Conclusions: ROI analysis of DTI could detect microstructural changes in the white matter adjacent to olfactory areas in PD patients, whereas MT imaging could not.

Diffusion MRI of white matter microstructure development in childhood and adolescence: Methods, challenges and progress

Diffusion magnetic resonance imaging (dMRI) continues to grow in popularity as a useful neuroimaging method to study brain development, and longitudinal studies that track the same individuals over time are emerging. Over the last decade, seminal work using dMRI has provided new insights into the development of brain white matter (WM) microstructure, connections and networks throughout childhood and adolescence. This review provides an introduction to dMRI, both diffusion tensor imaging (DTI) and other dMRI models, as well as common acquisition and analysis approaches. We highlight the difficulties associated with ascribing these imaging measurements and their changes over time to specific underlying cellular and molecular events. We also discuss selected methodological challenges that are of particular relevance for studies of development, including critical choices related to image acquisition, image analysis, quality control assessment, and the within-subject and longitudinal reliability of dMRI measurements. Next, we review the exciting progress in the characterization and understanding of brain development that has resulted from dMRI studies in childhood and adolescence, including brief overviews and discussions of studies focusing on sex and individual differences. Finally, we outline future directions that will be beneficial to the field.

State-dependent microstructural white matter changes in drug-naïve patients with first-episode psychosis

BACKGROUND

Diffusion tensor imaging (DTI) studies have consistently shown white matter (WM) microstructural abnormalities in schizophrenia. Whether or not such alterations could vary depending on clinical status (i.e. acute psychosis v. remission) remains to be investigated.

METHODS

Twenty-five treatment-naïve first-episode psychosis (FEP) patients and 51 healthy-controls (HC) underwent MRI scanning at baseline. Twenty-one patients were re-scanned as soon as they achieved sustained remission of symptoms; 36 HC were also scanned twice. Rate-of-change maps of longitudinal DTI changes were calculated for in order to examine WM alterations associated with changes in clinical status. We conducted voxelwise analyses of fractional anisotropy (FA) and trace (TR) maps.

RESULTS

At baseline, FEP presented reductions of FA in comparison with HC [p < 0.05, false-discovery rate (FDR)-corrected] affecting fronto-limbic WM and associative, projective and commissural fasciculi. After symptom remission, patients showed FA increase over time (p < 0.001, uncorrected) in some of the above WM tracts, namely the right anterior thalamic radiation, right uncinate fasciculus/inferior fronto-occipital fasciculus, and left inferior fronto-occipital fasciculus/inferior longitudinal fasciculus. We also found significant correlations between reductions in PANSS scores and FA increases over time (p < 0.05, FDR-corrected).

CONCLUSIONS

WM changes affecting brain tracts critical to the integration of perceptual information, cognition and emotions are detectable soon after the onset of FEP and may partially reverse in direct relation to the remission of acute psychotic symptoms. Our findings reinforce the view that WM abnormalities in brain tracts are a key neurobiological feature of acute psychotic disorders, and recovery from such WM pathology can lead to amelioration of symptoms.

The role of diffusion magnetic resonance imaging in Parkinson's disease and in the differential diagnosis with atypical parkinsonism

Parkinson's disease is one of the most common neurodegenerative diseases. Clinically, it is characterized by motor symptoms. Parkinson's disease should be differentiated from atypical parkinsonism conditions. Conventional magnetic resonance imaging is the primary imaging method employed in order to facilitate the differential diagnosis, and its role has grown after the development of advanced techniques such as diffusion-weighted imaging. The purpose of this article was to review the role of magnetic resonance imaging in Parkinson's disease and in the differential diagnosis with atypical parkinsonism, emphasizing the diffusion technique.

Age-related changes of white matter association tracts in normal children throughout adulthood: a diffusion tensor tractography study

PURPOSE

The aim of this study is to study the age, gender and lateral asymmetry-related white matter changes of long association tracts throughout late childhood and adolescence into adulthood using diffusion tensor tractography (DTT).

METHODS

DTT was performed in 44 healthy subjects aged 7-45 years. Fractional anisotropy (FA), radial diffusivity (RD), axial diffusivity (AD), Trace, density and volume were calculated for long association tracts, namely the inferior fronto-occipital fasciculus (IFOF), inferior longitudinal fasciculus (ILF), uncinate fasciculus, superior longitudinal fasciculus (SLF) and its arcuate fibres. FA and diffusivity indices were correlated as function of age using Pearson correlation test. Comparison between males and females, and comparison between both hemispheres among all participants were also performed. A p value less than .01 was considered significant.

RESULTS

The majority of the examined tracts (SLF and IFOF of both hemispheres, and the arcuate fasciculus, uncinate fasciculus, and ILF of the left hemisphere) followed a common pattern of metric changes with age. This pattern was characterized by significant FA increase accompanied by reduction in RD, Trace without significant AD changes. The right arcuate fasciculus showed similar pattern but without significant FA changes. The right uncinate and right ILF fasciculus demonstrated significant reduction in RD, Trace and AD, with and without significant FA increase, respectively. Left hemispheric dominance regarding the FA and diffusivity indices was demonstrated in uncinate fasciculus with no significant gender-related differences.

CONCLUSION

Significant microstructural tract-specific maturation processes continue throughout late childhood into adulthood. These processes may represent stages in a cascade of age-related maturation in white matter microstructure.

A Comparative evaluation of voxel-based spatial mapping in diffusion tensor imaging

This paper presents a comparative evaluation of methods for automated voxel-based spatial mapping in diffusion tensor imaging studies. Such methods are an essential step in computational pipelines and provide anatomically comparable measurements across a population in atlas-based studies. To better understand their strengths and weaknesses, we tested a total of eight methods for voxel-based spatial mapping in two types of diffusion tensor templates. The methods were evaluated with respect to scan-rescan reliability and an application to normal aging. The methods included voxel-based analysis with and without smoothing, two types of region-based analysis, and combinations thereof with skeletonization. The templates included a study-specific template created with DTI-TK and the IIT template serving as a standard template. To control for other factors in the pipeline, the experiments used a common dataset, acquired at 1.5T with a single shell high angular resolution diffusion MR imaging protocol, and tensor-based spatial normalization with DTI-TK. Scan-rescan reliability was assessed using the coefficient of variation (CV) and intraclass correlation (ICC) in eight subjects with three scans each. Sensitivity to normal aging was assessed in a population of 80 subjects aged 25-65 years old, and methods were compared with respect to the anatomical agreement of significant findings and the R2 of the associated models of fractional anisotropy. The results show that reliability depended greatly on the method used for spatial mapping. The largest differences in reliability were found when adding smoothing and comparing voxel-based and region-based analyses. Skeletonization and template type were found to have either a small or negligible effect on reliability. The aging results showed agreement among the methods in nine brain areas, with some methods showing more sensitivity than others. Skeletonization and smoothing were not major factors affecting sensitivity to aging, but the standard template showed higher R2 in several conditions. A structural comparison of the templates showed that large deformations between them may be related to observed differences in patterns of significant voxels. Most areas showed significantly higher R2 with voxel-based analysis, particularly when clusters were smaller than the available regions-of-interest. Looking forward, these results can potentially help to interpret results from existing white matter imaging studies, as well as provide a resource to help in planning future studies to maximize reliability and sensitivity with regard to the scientific goals at hand.

Correlation between white matter damage and gray matter lesions in multiple sclerosis patients

We observed the characteristics of white matter fibers and gray matter in multiple sclerosis patients, to identify changes in diffusion tensor imaging fractional anisotropy values following white matter fiber injury. We analyzed the correlation between fractional anisotropy values and changes in whole-brain gray matter volume. The participants included 20 patients with relapsing-remitting multiple sclerosis and 20 healthy volunteers as controls. All subjects underwent head magnetic resonance imaging and diffusion tensor imaging. Our results revealed that fractional anisotropy values decreased and gray matter volumes were reduced in the genu and splenium of corpus callosum, left anterior thalamic radiation, hippocampus, uncinate fasciculus, right corticospinal tract, bilateral cingulate gyri, and inferior longitudinal fasciculus in multiple sclerosis patients. Gray matter volumes were significantly different between the two groups in the right frontal lobe (superior frontal, middle frontal, precentral, and orbital gyri), right parietal lobe (postcentral and inferior parietal gyri), right temporal lobe (caudate nucleus), right occipital lobe (middle occipital gyrus), right insula, right parahippocampal gyrus, and left cingulate gyrus. The voxel sizes of atrophic gray matter positively correlated with fractional anisotropy values in white matter association fibers in the patient group. These findings suggest that white matter fiber bundles are extensively injured in multiple sclerosis patients. The main areas of gray matter atrophy in multiple sclerosis are the frontal lobe, parietal lobe, caudate nucleus, parahippocampal gyrus, and cingulate gyrus. Gray matter atrophy is strongly associated with white matter injury in multiple sclerosis patients, particularly with injury to association fibers.

Diffusion tensor imaging of white matter and correlates to eye movement control and psychometric testing in children with prenatal alcohol exposure

Prenatal alcohol exposure (PAE) can cause central nervous system dysfunction and widespread structural anomalies as detected by magnetic resonance imaging (MRI). This study focused on diffusion tensor imaging (DTI) of white matter in a large sample of PAE participants that allowed us to examine correlations with behavioral outcomes. Participants were confirmed PAE (n = 69, mean age = 12.5 ± 3.2 years) or typically developing control children (n = 67, mean age = 12.1 ± 3.2 years) who underwent brain MRI, eye movement tasks, and psychometric tests. A semi-automated tractography method extracted fractional anisotropy (FA) and mean diffusivity (MD) values from 15 white matter tracts. The PAE group displayed decreased FA compared with controls in multiple tracts including 3 corpus callosum regions, right corticospinal tract, and 3 left hemisphere tracts connecting to the frontal lobe (cingulum, uncinate fasciculus, and superior longitudinal fasciculus). Significant group by sex interactions were found for the genu, left superior longitudinal fasciculus, and the left uncinate, with females in the PAE group exhibiting lower FA compared with control females. Correlations were found between DTI and eye movement measures in the control group, but these same relationships were absent in the PAE group. In contrast, no correlations were found between DTI and any of the psychometric tests used in this study. These findings support the hypothesis that measures of eye movement control may be valuable functional biomarkers of the brain injury induced by PAE as these tasks reveal group differences that appear to be linked to deficits in white matter integrity in the brain. Hum Brain Mapp 38:444-456, 2017. © 2016 Wiley Periodicals, Inc.

Diffusion tensor imaging reveals changes in the adult rat brain following long-term and passive moderate acoustic exposure

This study investigated neuroanatomical changes following long-term acoustic exposure at moderate sound pressure level (SPL) under passive conditions, without coupled behavioral training. The authors utilized diffusion tensor imaging (DTI) to detect morphological changes in white matter. DTIs from adult rats (n = 8) exposed to continuous acoustic exposure at moderate SPL for 2 months were compared with DTIs from rats (n = 8) reared under standard acoustic conditions. Two distinct forms of DTI analysis were applied in a sequential manner. First, DTI images were analyzed using voxel-based statistics which revealed greater fractional anisotropy (FA) of the pyramidal tract and decreased FA of the tectospinal tract and trigeminothalamic tract of the exposed rats. Region of interest analysis confirmed (p < 0.05) that FA had increased in the pyramidal tract but did not show a statistically significant difference in the FA of the tectospinal or trigeminothalamic tract. The results of the authors show that long-term and passive acoustic exposure at moderate SPL increases the organization of white matter in the pyramidal tract.

Region-of-interest analyses of one-dimensional biomechanical trajectories: bridging 0D and 1D theory, augmenting statistical power

One-dimensional (1D) kinematic, force, and EMG trajectories are often analyzed using zero-dimensional (0D) metrics like local extrema. Recently whole-trajectory 1D methods have emerged in the literature as alternatives. Since 0D and 1D methods can yield qualitatively different results, the two approaches may appear to be theoretically distinct. The purposes of this paper were (a) to clarify that 0D and 1D approaches are actually just special cases of a more general region-of-interest (ROI) analysis framework, and (b) to demonstrate how ROIs can augment statistical power. We first simulated millions of smooth, random 1D datasets to validate theoretical predictions of the 0D, 1D and ROI approaches and to emphasize how ROIs provide a continuous bridge between 0D and 1D results. We then analyzed a variety of public datasets to demonstrate potential effects of ROIs on biomechanical conclusions. Results showed, first, that a priori ROI particulars can qualitatively affect the biomechanical conclusions that emerge from analyses and, second, that ROIs derived from exploratory/pilot analyses can detect smaller biomechanical effects than are detectable using full 1D methods. We recommend regarding ROIs, like data filtering particulars and Type I error rate, as parameters which can affect hypothesis testing results, and thus as sensitivity analysis tools to ensure arbitrary decisions do not influence scientific interpretations. Last, we describe open-source Python and MATLAB implementations of 1D ROI analysis for arbitrary experimental designs ranging from one-sample t tests to MANOVA.

Structural and microstructral imaging of the brain in alcohol use disorders

Magnetic resonance imaging (MRI), by enabling rigorous in vivo study of the longitudinal, dynamic course of alcoholism through periods of drinking, sobriety, and relapse, has enabled characterization of the effects of chronic alcoholism on the brain in the human condition. Importantly, MRI has distinguished alcohol-related brain effects that are permanent versus those that are reversible with abstinence. In support of postmortem neuropathologic studies showing degeneration of white matter, MRI has shown a specific vulnerability of brain white matter to chronic alcohol exposure by demonstrating white-matter volume deficits, yet not leaving selective gray-matter structures unscathed. Diffusion tensor imaging (DTI), by permitting microstructural characterization of white matter, has extended MRI findings in alcoholics. This review focuses on MRI and DTI findings in common concomitants of alcoholism, including Wernicke's encephalopathy, Korsakoff's syndrome, hepatic encephalopathy, central pontine myelinolysis, alcoholic cerebellar degeneration, alcoholic dementia, and Marchiafava-Bignami disease as a framework for findings in so-called "uncomplicated alcoholism," and also covers findings in abstinence and relapse.

Tractography Analysis of 5 White Matter Bundles and Their Clinical and Cognitive Correlates in Early-Course Schizophrenia

PURPOSE

Tractography is the most anatomically accurate method for delineating white matter tracts in the brain, yet few studies have examined multiple tracts using tractography in patients with schizophrenia (SCZ). We analyze 5 white matter connections important in the pathophysiology of SCZ: uncinate fasciculus, cingulum bundle (CB), inferior longitudinal fasciculus (ILF), superior longitudinal fasciculus, and arcuate fasciculus (AF). Additionally, we investigate the relationship between diffusion tensor imaging (DTI) markers and neuropsychological measures.

METHODS

High-resolution DTI data were acquired on a 3 Tesla scanner in 30 patients with early-course SCZ and 30 healthy controls (HC) from the Boston Center for Intervention Development and Applied Research study. After manually guided tracts delineation, fractional anisotropy (FA), trace, radial diffusivity (RD), and axial diffusivity (AD) were calculated and averaged along each tract. The association of DTI measures with the Scales for the Assessment of Negative and Positive Symptoms and neuropsychological measures was evaluated.

RESULTS

Compared to HC, patients exhibited reduced FA and increased trace and RD in the right AF, CB, and ILF. A discriminant analysis showed the possible use of FA of these tracts for better future group membership classifications. FA and RD of the right ILF and AF were associated with positive symptoms while FA and RD of the right CB were associated with memory performance and processing speed.

CONCLUSION

We observed white matter alterations in the right CB, ILF, and AF, possibly caused by myelin disruptions. The structural abnormalities interact with cognitive performance, and are linked to clinical symptoms.

Relationship between age and white matter integrity in children with phenylketonuria

Diffusion tensor imaging (DTI) has shown poorer microstructural white matter integrity in children with phenylketonuria (PKU), specifically decreases in mean diffusivity (MD), in comparison with healthy children. However, little research has been conducted to investigate the relationship between age and white matter integrity in this population. The present study examined group differences in the relationship between age and MD across a range of brain regions in 31 children with early- and continuously-treated PKU and 51 healthy control children. Relationships among MD, age, and group were explored using hierarchical linear regression and Pearson correlation. Results indicated a stronger age-related decrease in MD for children with PKU in comparison with healthy children in 4 of the 10 brain regions examined, suggesting that the trajectory of white matter development is abnormal in children with PKU. Further research using longitudinal methodology is needed to fully elucidate our understanding of white matter development in children with PKU.

"RADIOTRANSCRIPTOMICS": A synergy of imaging and transcriptomics in clinical assessment

Recent advances in quantitative imaging and "omics" technology have generated a wealth of mineable biological "big data". With the push towards a P4 "predictive, preventive, personalized, and participatory" approach to medicine, researchers began integrating complementary tools to further tune existing diagnostic and therapeutic models. The field of radiogenomics has long pioneered such multidisciplinary investigations in neuroscience and oncology, correlating genotypic and phenotypic signatures to study structural and functional changes in relation to altered molecular behavior. Given the innate dynamic nature of complex disorders and the role of environmental and epigenetic factors in pathogenesis, the transcriptome can further elucidate serial modifications undetected at the genome level. We therefore propose "radiotranscriptomics" as a new member of the P4 medicine initiative, combining transcriptome information, including gene expression and isoform variation, and quantitative image annotations.