Tractography in amyotrophic lateral sclerosis using a novel probabilistic tool: a study with tract-based reconstruction compared to voxel-based approach

Dynamic monitoring of radiation-induced white matter microstructure injury in nasopharyngeal carcinoma via high-angular resolution diffusion imaging

PURPOSE

To investigate white matter microstructural abnormalities caused by radiotherapy in nasopharyngeal carcinoma (NPC) patients using MRI high-angular resolution diffusion imaging (HARDI).

METHODS

We included 127 patients with pathologically confirmed NPC: 36 in the pre-radiotherapy group, 29 in the acute response period (post-RT-AP), 23 in the early delayed period (post-RT-ED) group, and 39 in the late-delayed period (post-RT-LD) group. HARDI data were acquired for each patient, and dispersion parameters were calculated to compare the differences in specific fibre bundles among the groups. The Montreal Neurocognitive Assessment (MoCA) was used to evaluate neurocognitive function, and the correlations between dispersion parameters and MoCA were analysed.

RESULTS

In the right cingulum frontal parietal bundles, the fractional anisotropy value decreased to the lowest level post-RT-AP and then reversed and increased post-RT-ED and post-RT-LD. The mean, axial, and radial diffusivity were significantly increased in the post-RT-AP (p < 0.05) and decreased in the post-RT-ED and post-RT-LD groups to varying degrees. MoCA scores were decreased post-radiotherapy than those before radiotherapy (p = 0.005). MoCA and mean diffusivity exhibited a mild correlation in the left cingulum frontal parahippocampal bundle.

CONCLUSIONS

White matter tract changes detected by HARDI are potential biomarkers for monitoring radiotherapy-related brain damage in NPC patients.

Tract-based analyses of white matter in schizophrenia, bipolar disorder, aging, and dementia using high spatial and directional resolution diffusion imaging: a pilot study

Introduction

Structural brain connectivity abnormalities have been associated with several psychiatric disorders. Schizophrenia (SCZ) is a chronic disabling disorder associated with accelerated aging and increased risk of dementia, though brain findings in the disorder have rarely been directly compared to those that occur with aging.

Methods

We used an automated approach to reconstruct key white matter tracts and assessed tract integrity in five participant groups. We acquired one-hour-long high-directional diffusion MRI data from young control (CON, n =28), bipolar disorder (BPD, n =21), and SCZ (n =22) participants aged 18-30, and healthy elderly (ELD, n =15) and dementia (DEM, n =9) participants. Volume, fractional (FA), radial diffusivity (RD) and axial diffusivity (AD) of seven key white matter tracts (anterior thalamic radiation, ATR; dorsal and ventral cingulum bundle, CBD and CBV; corticospinal tract, CST; and the three superior longitudinal fasciculi: SLF-1, SLF-2 and SLF-3) were analyzed with TRACULA. Group comparisons in tract metrics were performed using multivariate and univariate analyses. Clinical relationships of tract metrics with recent and chronic symptoms were assessed in SCZ and BPD participants.

Results

A MANOVA showed group differences in FA (λ=0.5; p=0.0002) and RD (λ=0.35; p<0.0001) across the seven tracts, but no significant differences in tract AD and volume. Post-hoc analyses indicated lower tract FA and higher RD in ELD and DEM groups compared to CON, BPD and SCZ groups. Lower FA and higher RD in SCZ compared to CON did not meet statistical significance. In SCZ participants, a significant negative correlation was found between chronic psychosis severity and FA in the SLF-1 (r= -0.45; p=0.035), SLF-2 (r= -0.49; p=0.02) and SLF-3 (r= -0.44; p=0.042).

Discussion

Our results indicate impaired white matter tract integrity in elderly populations consistent with myelin damage. Impaired tract integrity in SCZ is most prominent in patients with advanced illness.

Automated three-dimensional major white matter bundle segmentation using diffusion magnetic resonance imaging

White matter bundle segmentation using diffusion magnetic resonance imaging fiber tractography enables detailed evaluation of individual white matter tracts three-dimensionally, and plays a crucial role in studying human brain anatomy, function, development, and diseases. Manual extraction of streamlines utilizing a combination of the inclusion and exclusion of regions of interest can be considered the current gold standard for extracting white matter bundles from whole-brain tractograms. However, this is a time-consuming and operator-dependent process with limited reproducibility. Several automated approaches using different strategies to reconstruct the white matter tracts have been proposed to address the issues of time, labor, and reproducibility. In this review, we discuss few of the most well-validated approaches that automate white matter bundle segmentation with an end-to-end pipeline, including TRActs Constrained by UnderLying Anatomy (TRACULA), Automated Fiber Quantification, and TractSeg.

Automated detection of axonal damage along white matter tracts in acute severe traumatic brain injury

New techniques for individualized assessment of white matter integrity are needed to detect traumatic axonal injury (TAI) and predict outcomes in critically ill patients with acute severe traumatic brain injury (TBI). Diffusion MRI tractography has the potential to quantify white matter microstructure in vivo and has been used to characterize tract-specific changes following TBI. However, tractography is not routinely used in the clinical setting to assess the extent of TAI, in part because focal lesions reduce the robustness of automated methods. Here, we propose a pipeline that combines automated tractography reconstructions of 40 white matter tracts with multivariate analysis of along-tract diffusion metrics to assess the presence of TAI in individual patients with acute severe TBI. We used the Mahalanobis distance to identify abnormal white matter tracts in each of 18 patients with acute severe TBI as compared to 33 healthy subjects. In all patients for which a FreeSurfer anatomical segmentation could be obtained (17 of 18 patients), including 13 with focal lesions, the automated pipeline successfully reconstructed a mean of 37.5 ± 2.1 white matter tracts without the need for manual intervention. A mean of 2.5 ± 2.1 tracts resulted in partial or failed reconstructions and needed to be reinitialized upon visual inspection. The pipeline detected at least one abnormal tract in all patients (mean: 9.1 ± 7.9) and accurately discriminated between patients and controls (AUC: 0.91). The number and neuroanatomic location of abnormal tracts varied across patients and levels of consciousness. The premotor, temporal, and parietal sections of the corpus callosum were the most commonly damaged tracts (in 10, 9, and 8 patients, respectively), consistent with prior histopathological studies of TAI. TAI measures were not associated with concurrent behavioral measures of consciousness. In summary, we provide proof-of-principle evidence that an automated tractography pipeline has translational potential to detect and quantify TAI in individual patients with acute severe TBI.

Corticospinal tract abnormalities and ventricular dilatation: A transdiagnostic comparative tractography study

BACKGROUND

Microstructural alterations of corticospinal tract (CST) have been found in idiopathic normal pressure hydrocephalus (iNPH). No study, however, investigated the effect of ventricular dilatation on CST in Progressive Supranuclear Palsy (PSP).

OBJECTIVE

The aim of this study was to investigate CST diffusion profile in a large cohort of PSP patients with and without ventricular dilatation.

METHODS

Twenty-three iNPH patients, 87 PSP patients and 26 controls were enrolled. Evans index (EI) and ventricular volume (VV) were measured in all patients. CST tractography was performed to calculate FA, MD, AxD and RD in six different anatomical regions: medulla oblungata (MO), pons (P), cerebral peduncle (CP), posterior limb of internal capsule (PLIC), corona radiata (CR), subcortical white matter (SWM). ANCOVA was used for comparing CST diffusion profiles between the groups and association between CST microstructural metrics and measures of ventricular dilatation (EI and VV) was assessed.

RESULTS

Thirty-three PSP patients had ventricular dilatation (EI > 0.30, PSP-vd) while 54 PSP patients had normal ventricular system (EI ≤ 0.30, PSP-wvd). iNPH patients had the most marked FA and AxD increase in PLIC and CR of CST followed by PSP-vd, PSP-wvd and controls; RD was altered only in iNPH. A strong correlation was found between CST diffusion metrics and EI or VV.

CONCLUSIONS

Our findings confirm the microstructural changes of CST in iNPH patients and demonstrate for the first time similar alterations in PSP-vd patients, suggesting a crucial role of ventricular dilatation in the mechanical compression of CST.

Evaluation of White Matter Tracts Fractional Anisotropy Using Tract-Based Spatial Statistics and Its correlation with Amyotrophic Lateral Sclerosis Functional Rating Scale Score in Patients with Motor Neuron Disease

Background Motor neuron diseases cause progressive degeneration of upper and lower motor neurons. No Indian studies are available on diffusion tensor imaging (DTI) findings in these patients. Aims This study was done to identify white matter tracts that have reduced fractional anisotropy (FA) in motor neuron disease (MND) patients using tract-based spatial statistics and to correlate FA values with Amyotrophic Lateral Sclerosis Functional Rating Scale (ALSFRS-R) score. Settings and Design A case-control study in a tertiary care hospital. Materials and Methods We did DTI sequence (20 gradient directions, b -value 1,000) in 15 MND patients (10 men and 5 women; mean age: 46.5 ± 16.5 years; 11 amyotrophic lateral sclerosis [ALS], 2 monomelic amyotrophy, 1 progressive muscular atrophy, and 1 bulbar ALS) and 15 age- and sex-matched controls. The data set from each subject was postprocessed using FSL downloaded from the FMRIB Software Library, Oxford, United Kingdom (http://www.fmrib.ox.ac.uk/fsl). Statistical Analysis The statistical permutation tool "randomize" with 5,000 permutations was used to identify voxels that were different between the patient data set and the control data set. Mean FA values of these voxels were obtained separately for each tract as per "JHU white-matter tractography atlas." SPSS was used to look to correlate tract-wise mean FA value with ALSFRS-R score. Results We found clusters of reduced FA values in multiple tracts in the brain of patients with MND. Receiver operating characteristic curves plotted for individual tracts, showed that bilateral corticospinal tract, bilateral anterior thalamic radiation, bilateral uncinate fasciculus, and right superior longitudinal fasciculus were the best discriminators (area under the curve > 0.8, p < 0.01). FA values did not correlate with ALFRS-R severity score. Conclusion In MND patients, not only the motor tracts, but several nonmotor association tracts are additionally affected, reflecting nonmotor pathological processes in ALS.

Multidimensional analysis and detection of informative features in human brain white matter

The white matter contains long-range connections between different brain regions and the organization of these connections holds important implications for brain function in health and disease. Tractometry uses diffusion-weighted magnetic resonance imaging (dMRI) to quantify tissue properties along the trajectories of these connections. Statistical inference from tractometry usually either averages these quantities along the length of each fiber bundle or computes regression models separately for each point along every one of the bundles. These approaches are limited in their sensitivity, in the former case, or in their statistical power, in the latter. We developed a method based on the sparse group lasso (SGL) that takes into account tissue properties along all of the bundles and selects informative features by enforcing both global and bundle-level sparsity. We demonstrate the performance of the method in two settings: i) in a classification setting, patients with amyotrophic lateral sclerosis (ALS) are accurately distinguished from matched controls. Furthermore, SGL identifies the corticospinal tract as important for this classification, correctly finding the parts of the white matter known to be affected by the disease. ii) In a regression setting, SGL accurately predicts "brain age." In this case, the weights are distributed throughout the white matter indicating that many different regions of the white matter change over the lifespan. Thus, SGL leverages the multivariate relationships between diffusion properties in multiple bundles to make accurate phenotypic predictions while simultaneously discovering the most relevant features of the white matter.

Distinguishing persistent post-traumatic headache from migraine: Classification based on clinical symptoms and brain structural MRI data

BACKGROUND

Persistent post-traumatic headache most commonly has symptoms that overlap those of migraine. In some cases, it can be clinically difficult to differentiate persistent post-traumatic headache with a migraine phenotype from migraine. The objective of this study was to develop a classification model based on questionnaire data and structural neuroimaging data that distinguishes individuals with migraine from those with persistent post-traumatic headache.

METHODS

Questionnaires assessing headache characteristics, sensory hypersensitivities, cognitive functioning, and mood, as well as T1-weighted magnetic resonance imaging and diffusion tensor data from 34 patients with migraine and 48 patients with persistent post-traumatic headache attributed to mild traumatic brain injury were included for analysis. The majority of patients with persistent post-traumatic headache had a migraine/probable migraine phenotype (77%). A machine-learning leave-one-out cross-validation algorithm determined the average accuracy for distinguishing individual migraine patients from individual patients with persistent post-traumatic headache.

RESULTS

Based on questionnaire data alone, the average classification accuracy for determining whether an individual person had migraine or persistent post-traumatic headache was 71.9%. Adding imaging data features to the model improved the classification accuracy to 78%, including an average accuracy of 97.1% for identifying individual migraine patients and an average accuracy of 64.6% for identifying individual patients with persistent post-traumatic headache. The most important clinical features that contributed to the classification accuracy included questions related to anxiety and decision making. Cortical brain features and fibertract data from the following regions or tracts most contributed to the classification accuracy: Bilateral superior temporal, inferior parietal and posterior cingulate; right lateral occipital, uncinate, and superior longitudinal fasciculus. A post-hoc analysis showed that compared to incorrectly classified persistent post-traumatic headache patients, those who were correctly classified as having persistent post-traumatic headache had more severe physical, autonomic, anxiety and depression symptoms, were more likely to have post-traumatic stress disorder, and were more likely to have had mild traumatic brain injury attributed to blasts.

DISCUSSION

A classification model that included a combination of questionnaire data and structural imaging parameters classified individual patients as having migraine versus persistent post-traumatic headache with good accuracy. The most important clinical measures that contributed to the classification accuracy included questions on mood. Regional brain structures and fibertracts that play roles in pain processing and pain integration were important brain features that contributed to the classification accuracy. The lower classification accuracy for patients with persistent post-traumatic headache compared to migraine may be related to greater heterogeneity of patients in the persistent post-traumatic headache cohort regarding their traumatic brain injury mechanisms, and physical, emotional, and cognitive symptoms.

Disease aggressiveness signatures of amyotrophic lateral sclerosis in white matter tracts revealed by the D50 disease progression model

Numerous neuroimaging studies in amyotrophic lateral sclerosis (ALS) have reported links between structural changes and clinical data; however phenotypic and disease course heterogeneity have occluded robust associations. The present study used the novel D50 model, which distinguishes between disease accumulation and aggressiveness, to probe correlations with measures of diffusion tensor imaging (DTI). DTI scans of 145 ALS patients and 69 controls were analyzed using tract-based-spatial-statistics of fractional anisotropy (FA), mean- (MD), radial (RD), and axial diffusivity (AD) maps. Intergroup contrasts were calculated between patients and controls, and between ALS subgroups: based on (a) the individual disease covered (Phase I vs. II) or b) patients' disease aggressiveness (D50 value). Regression analyses were used to probe correlations with model-derived parameters. Case-control comparisons revealed widespread ALS-related white matter pathology with decreased FA and increased MD/RD. These affected pathways showed also correlations with the accumulated disease for increased MD/RD, driven by the subgroup of Phase I patients. No significant differences were noted between patients in Phase I and II for any of the contrasts. Patients with high disease aggressiveness (D50 < 30 months) displayed increased AD/MD in bifrontal and biparietal pathways, which was corroborated by significant voxel-wise regressions with D50. Application of the D50 model revealed associations between DTI measures and ALS pathology in Phase I, representing individual disease accumulation early in disease. Patients' overall disease aggressiveness correlated robustly with the extent of DTI changes. We recommend the D50 model for studies developing/validating neuroimaging or other biomarkers for ALS.

Advanced neuroimaging approaches in amyotrophic lateral sclerosis: refining the clinical diagnosis

Introduction: In the last decade, multiparametric magnetic resonance imaging (MRI) has achieved tremendous advances in applications to amyotrophic lateral sclerosis (ALS) to increase the understanding of the associated pathophysiology. The aim of this review is to summarize recent progress in the development of MRI-based techniques aiming to support the clinical diagnosis in ALS.Areas covered: The review of structural and functional MRI applications to ALS and its variants (restricted phenotypes) is focused on the potential of MRI techniques which contribute to the diagnostic work-up of patients with the clinical presentation of a motor neuron disease. The potential of specific MRI methods for patient diagnosis and monitoring is discussed, and the future design of clinical MRI applications to ALS is conceptualized.Expert opinion: Current multiparametric MRI allows for the use as a clinical biological marker and a technical instrument in the clinical diagnosis of patients with ALS and also of patients with ALS variants. Composite neuroimaging indices of specific anatomical areas derived from different MRI techniques might guide in the diagnostic applications to ALS. Such a development of ALS-specific MRI-based composite scores with sufficient discriminative power versus ALS mimics at an individual level requires standardized advanced protocols and comprehensive analysis approaches.

Assessment of the Corticospinal Tract Profile in Pure Lower Motor Neuron Disease: A Diffusion Tensor Imaging Study

AIM

The aim of this study was to evaluate the corticospinal tract (CST) diffusion profile in pure lower motor neuron disease (pLMND) patients who at baseline did not show any clinical or electrophysiological involvement of upper motor neurons (UMN), and in amyotrophic lateral sclerosis (ALS) patients.

MATERIALS AND METHODS

Fifteen ALS patients with delayed central motor conduction time (CMCT) and 14 pLMND patients with normal CMCT were enrolled together with 15 healthy controls. Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) maps were obtained. The tract profile of CST was reconstructed with the automated fiber quantification tool and its diffusion properties were quantified voxel-by-voxel and then compared pairwise between groups. Moreover, a random forest (RF) classifier was trained to evaluate the ability of CST diffusion metrics in distinguishing pairwise the groups from the controls.

RESULTS

ALS patients presented wide microstructural abnormalities in the entire CST as assessed by FA decrease and RD increase while pLMND patients showed focal FA decrease and a larger AD increase in the cerebral peduncle and posterior limb of the internal capsule in comparison with controls. RF revealed that diffusion tensor imaging (DTI) metrics accurately distinguished ALS patients and pLMND patients from controls (96.67 and 95.71% accuracy, respectively).

CONCLUSIONS

Our study demonstrates that the CST was impaired in both ALS and pLMND patients, thus suggesting that DTI metrics are a reliable tool in detecting subtle changes of UMN in pLMND patients, also in the absence of clinical and CMCT abnormalities.

Brain white matter abnormalities and correlation with severity in amyotrophic lateral sclerosis: An atlas-based diffusion tensor imaging study

OBJECTIVES

To assess microstructural alterations in white matter (WM) in amyotrophic lateral sclerosis (ALS) using diffusion tensor imaging (DTI).

METHODS

DTI data were collected from 34 subjects (18 patients with ALS and 16 healthy controls). The atlas-based region of interest (ROI) analysis was conducted to assess WM microstructure in ALS by combining intra-voxel metrics, which included fractional anisotropy (FA) and mean diffusivity (MD), and an inter-voxel metric, i.e., local diffusion homogeneity (LDH). Correlation analysis of diffusion values and clinical factors was also performed.

RESULTS

ALS group showed a significant FA reduction in bilateral corticospinal tract (CST) as well as right uncinate fasciculus (RUF). The areas with higher MD were situated in right corticospinal tract (RCST), left cingulum hippocampus (LCH), RUF, and right superior longitudinal fasciculus (RSLF). Additionally, ALS patients showed decreased LDH in bilateral anterior thalamic radiation (ATR), bilateral CST and left inferior frontal-occipital fasciculus (LIFOF). Significant correlations were observed between ALSFRS-R (revised ALS Functional Rating Scale) scores or progression rate and FA in bilateral CST, as well as between disease duration and LDH in right CST. Receiver operating characteristic (ROC) analysis revealed the feasibility of employing diffusion metrics along the CST to distinguish two groups (AUC = 0.792-0.868, p < .005 for all).

CONCLUSIONS

WM microstructural alteration is a common pathology in ALS, which can be detected by both intra- and inter-voxel diffusion metrics. The extent of abnormalities in several WM tracts such as ATR and LIFOF may be better assessed through the inter-voxel diffusion measurement.

Alterations in white matter microstructure and cortical thickness in individuals at ultra-high risk of psychosis: A multimodal tractography and surface-based morphometry study

There is increasing evidence of white matter (WM) and grey matter pathology in subjects at ultra-high risk of psychosis (UHR), although a limited number of diffusion-weighted magnetic resonance imaging (DW-MRI) and surface-based morphometry (SBM) studies have revealed anatomically inconsistent results. The present multimodal study applies tractography and SBM to analyze WM microstructure, whole-brain cortical anatomy, and potential interconnections between WM and grey matter abnormalities in UHR subjects. Thirty young male UHR patients and 30 healthy controls underwent DW-MRI and T1-weighted MRI. Fractional anisotropy; mean, radial, and axial diffusivity in 18 WM tracts; and vertex-based cortical thickness, area, and volume were analyzed. We found increased radial diffusivity in the left anterior thalamic radiation and reduced bilateral thickness across the frontal, temporal, and parietal cortices. No correlations between WM and grey matter abnormalities were identified. These results provide further evidence that WM microstructure abnormalities and cortical anatomical changes occur in the UHR state. Disruption of structural connectivity in the prefrontal-subcortical circuitry, likely caused by myelin pathology, and cortical thickness reduction affecting the networks presumably involved in processing and coordination of external and internal information streams may underlie the widespread deficits in neurocognitive and social functioning that are consistently reported in UHR subjects.

Differences in fibertract profiles between patients with migraine and those with persistent post-traumatic headache

Objectives

Often, persistent post-traumatic headache and migraine are phenotypically similar. However, the similarities and differences in the neuropathological underpinnings of persistent post-traumatic headache and migraine require further understanding. We used diffusion tensor imaging (DTI) and a novel method for detecting subtle changes in fibertract integrity by measuring node-by-node parameters along each tract to compare fibertract profiles between those with migraine and those with persistent post-traumatic headache, and compared both cohorts to a group of controls.

Methods

Eighteen fibertracts were reconstructed for 131 subjects, including 49 patients with persistent post-traumatic headache attributed to mild traumatic brain injury, 41 with migraine, and 41 controls. Node-by-node diffusion parameters of mean diffusivity and radial diffusivity were calculated along each tract. Mean diffusivity and radial diffusivity measurements were averaged along quartiles of each tract for statistical interpretation and group comparison. Using a post-hoc analysis, correlations between tract quartile measurements and headache frequency were calculated.

Results

There were significant differences between migraine and persistent post-traumatic headache cohorts for quartile measurements of mean diffusivity or radial diffusivity in the bilateral anterior thalamic radiations, cingulum (angular bundles and cingulate gyri), inferior longitudinal fasciculi, and uncinate fasciculi, the left corticospinal tract, and the right superior longitudinal fasciculi-parietal portion. For migraine patients, there was a significant positive correlation between headache frequency and forceps major mean diffusivity, whereas for persistent post-traumatic headache there was a positive correlation between headache frequency and cingulum angular bundle mean diffusivity and radial diffusivity.

Conclusions

Quartile measurements of radial diffusivity and mean diffusivity indicate unique differences in fibertract profiles between those with migraine vs. persistent post-traumatic headache. Although for both migraine and persistent post-traumatic headache there was a positive relationship between fibertract alterations and headache frequency, there were disease-specific differences between headache frequency and fibertract injury patterns. These findings might suggest potential differences in the neuropathological mechanisms underlying migraine and persistent post-traumatic headache.

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.

Gray matter and white matter changes in non-demented amyotrophic lateral sclerosis patients with or without cognitive impairment: A combined voxel-based morphometry and tract-based spatial statistics whole-brain analysis

The phenotypic heterogeneity in amyotrophic lateral sclerosis (ALS) implies that patients show structural changes within but also beyond the motor cortex and corticospinal tract and furthermore outside the frontal lobes, even if frank dementia is not detected. The aim of the present study was to investigate both gray matter (GM) and white matter (WM) changes in non-demented amyotrophic lateral sclerosis (ALS) patients with or without cognitive impairment (ALS-motor and ALS-plus, respectively). Nineteen ALS-motor, 31 ALS-plus and 25 healthy controls (HC) underwent 3D-T1-weighted and 30-directional diffusion-weighted imaging on a 3 T MRI scanner. Voxel-based morphometry and tract-based spatial-statistics analysis were performed to examine GM volume (GMV) changes and WM differences in fractional anisotropy (FA), axial and radial diffusivity (AD, RD, respectively). Compared to HC, ALS-motor patients showed decreased GMV in frontal and cerebellar areas and increased GMV in right supplementary motor area, while ALS-plus patients showed diffuse GMV reduction in primary motor cortex bilaterally, frontotemporal areas, cerebellum and basal ganglia. ALS-motor patients had increased GMV in left precuneus compared to ALS-plus patients. We also found decreased FA and increased RD in the corticospinal tract bilaterally, the corpus callosum and extra-motor tracts in ALS-motor patients, and decreased FA and increased AD and RD in motor and several WM tracts in ALS-plus patients, compared to HC. Multimodal neuroimaging confirms motor and extra-motor GM and WM abnormalities in non-demented cognitively-impaired ALS patients (ALS-plus) and identifies early extra-motor brain pathology in ALS patients without cognitive impairment (ALS-motor).

Clinical and Radiological Markers of Extra-Motor Deficits in Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is now universally recognized as a complex multisystem disorder with considerable extra-motor involvement. The neuropsychological manifestations of frontotemporal, parietal, and basal ganglia involvement in ALS have important implications for compliance with assistive devices, survival, participation in clinical trials, caregiver burden, and the management of individual care needs. Recent advances in neuroimaging have been instrumental in characterizing the biological substrate of heterogeneous cognitive and behavioral deficits in ALS. In this review we discuss the clinical and radiological aspects of cognitive and behavioral impairment in ALS focusing on the recognition, assessment, and monitoring of these symptoms.

Imaging Biomarkers for the Diagnosis and Prognosis of Neurodegenerative Diseases. The Example of Amyotrophic Lateral Sclerosis

The term amyotrophic lateral sclerosis (ALS) comprises a heterogeneous group of fatal neurodegenerative disorders of largely unknown etiology characterized by the upper motor neurons (UMN) and/or lower motor neurons (LMN) degeneration. The development of brain imaging biomarkers is essential to advance in the diagnosis, stratification and monitoring of ALS, both in the clinical practice and clinical trials. In this review, the characteristics of an optimal imaging biomarker and common pitfalls in biomarkers evaluation will be discussed. Moreover, the development and application of the most promising brain magnetic resonance (MR) imaging biomarkers will be reviewed. Finally, the integration of both qualitative and quantitative multimodal brain MR biomarkers in a structured report will be proposed as a support tool for ALS diagnosis and stratification.

Stage-dependent remodeling of projections to motor cortex in ALS mouse model revealed by a new variant retrograde-AAV9

Amyotrophic lateral sclerosis (ALS) is characterized by the progressive degeneration of motoneurons in the primary motor cortex (pMO) and in spinal cord. However, the pathogenic process involves multiple subnetworks in the brain and functional MRI studies demonstrate an increase in functional connectivity in areas connected to pMO despite the ongoing neurodegeneration. The extent and the structural basis of the motor subnetwork remodeling in experimentally tractable models remain unclear. We have developed a new retrograde AAV9 to quantitatively map the projections to pMO in the SOD1(G93A) ALS mouse model. We show an increase in the number of neurons projecting from somatosensory cortex to pMO at presymptomatic stages, followed by an increase in projections from thalamus, auditory cortex and contralateral MO (inputs from 20 other structures remains unchanged) as disease advances. The stage- and structure-dependent remodeling of projection to pMO in ALS may provide insights into the hyperconnectivity observed in ALS patients.

A browser-based tool for visualization and analysis of diffusion MRI data

Human neuroscience research faces several challenges with regards to reproducibility. While scientists are generally aware that data sharing is important, it is not always clear how to share data in a manner that allows other labs to understand and reproduce published findings. Here we report a new open source tool, AFQ-Browser, that builds an interactive website as a companion to a diffusion MRI study. Because AFQ-Browser is portable-it runs in any web-browser-it can facilitate transparency and data sharing. Moreover, by leveraging new web-visualization technologies to create linked views between different dimensions of the dataset (anatomy, diffusion metrics, subject metadata), AFQ-Browser facilitates exploratory data analysis, fueling new discoveries based on previously published datasets. In an era where Big Data is playing an increasingly prominent role in scientific discovery, so will browser-based tools for exploring high-dimensional datasets, communicating scientific discoveries, aggregating data across labs, and publishing data alongside manuscripts.

Longitudinal Diffusion Tensor Imaging-Based Assessment of Tract Alterations: An Application to Amyotrophic Lateral Sclerosis

Objective: The potential of magnetic resonance imaging (MRI) as a technical biomarker for cerebral microstructural alterations in neurodegenerative diseases is under investigation. In this study, a framework for the longitudinal analysis of diffusion tensor imaging (DTI)-based mapping was applied to the assessment of predefined white matter tracts in amyotrophic lateral sclerosis (ALS), as an example for a rapid progressive neurodegenerative disease.

Methods: DTI was performed every 3 months in six patients with ALS (mean (M) = 7.7; range 3 to 15 scans) and in six controls (M = 3; range 2–5 scans) with the identical scanning protocol, resulting in a total of 65 longitudinal DTI datasets. Fractional anisotropy (FA), mean diffusivity (MD), axonal diffusivity (AD), radial diffusivity (RD), and the ratio AD/RD were studied to analyze alterations within the corticospinal tract (CST) which is a prominently affected tract structure in ALS and the tract correlating with Braak’s neuropathological stage 1. A correlation analysis was performed between progression rates based on DTI metrics and the revised ALS functional rating scale (ALS-FRS-R).

Results: Patients with ALS showed an FA and AD/RD decline along the CST, while DTI metrics of controls did not change in longitudinal DTI scans. The FA and AD/RD decrease progression correlated significantly with ALS-FRS-R decrease progression.

Conclusion: On the basis of the longitudinal assessment, DTI-based metrics can be considered as a possible noninvasive follow-up marker for disease progression in neurodegeneration. This finding was demonstrated here for ALS as a fast progressing neurodegenerative disease.

Diffusion tensor imaging identifies presymptomatic axonal degeneration in the spinal cord of ALS mice

Extensive pathological evidence indicates that axonal degeneration represents an early and critical event in amyotrophic lateral sclerosis (ALS). Unfortunately, few MRI studies have focused in the early detection of white matter (WM) alterations in the spinal cord region. To unveil these WM changes, we performed high resolution diffusion tensor imaging (DTI) and correlated the results with histological analysis of adjacent slices taken from the spinal cords of presymptomatic mice. The DTI studies demonstrated a significant reduction in fractional anisotropy (FA) as well as axial diffusivities (AD) and an increase in radial diffusivity (RD), predominantly at lower segments of the spinal cord. Increases in FA and a reduction in AD and RD were observed in spinal cord (SC) gray matter (GM). Diffusion changes are associated with early and progressive alterations in axonal connectivity following a distal to proximal progression. Histological data tagging neuronal, axonal and glial cell markers demonstrated presymptomatic alterations in spinal cord WM and GM. This study demonstrates that DTI methods are optimal preclinical imaging tools to detect structural anomalies in WM and GM spinal cord during early stages of the disease.

Multimodal assessment of white matter tracts in amyotrophic lateral sclerosis

Several quantitative magnetic resonance imaging (MRI) techniques have been proposed to investigate microstructural tissue changes in amyotrophic lateral sclerosis (ALS) including diffusion tensor imaging (DTI), magnetization transfer imaging, and R2* mapping. Here, in this study, we compared these techniques with regard to their capability for detecting ALS related white matter (WM) changes in the brain and their association with clinical findings. We examined 27 ALS patients and 35 age-matched healthy controls. MRI was performed at 3T, after which we analyzed the diffusion properties, the magnetization transfer ratio (MTR), and the effective transversal relaxation rate R2* in 18 WM tracts that were obtained by a fully automated segmentation technique. ALS patients, especially with a bulbar onset, showed a bilateral increase in radial and mean diffusivity, as well as a reduction in fractional anisotropy of the corticospinal tract (CST), and diffusion changes in the parietal and temporal superior longitudinal fasciculus. A reduction of the MTR was found in both CSTs and an R2* reduction was seen only in the left CST. Tract-specific diffusion properties were not related to clinical status in a cross-sectional manner but demonstrated some association with disease progression over three subsequent months. DTI reveals more widespread WM tissue changes than MTR and R2*. These changes are not restricted to the CST, but affect also other WM tracts (especially in patients with bulbar onset), and are associated with the short term course of the disease.

Disruption of white matter structural integrity and connectivity in posttraumatic stress disorder: A TBSS and tractography study

BACKGROUND

Most studies of brain white matter (WM) in posttraumatic stress disorder (PTSD) have focused on combat trauma, and often were confounded by neurological and substance dependence comorbidity. This study used tract-based spatial statistics (TBSS) and probabilistic tractography to characterize WM microstructure in a mixed-sex community sample of PTSD patients exposed to diverse and multiple traumas, and in trauma-exposed normal comparison (TENC) subjects.

METHODS

TBSS compared diffusion measures between 20 adults with DSM-IV PTSD and 17 TENC, using a whole-brain voxel-wise approach. Probabilistic tractography using Freesurfer's TRACULA was employed to measure diffusion tensor imaging (DTI) metrics within anatomically defined pathways. DTI metrics were compared between groups and correlated with PTSD symptom severity and trauma load.

RESULTS

Controlling for age, sex, and motion, PTSD subjects had significantly reduced fractional anisotropy (FA) in a left frontal lobe cluster compared with TENC, at p < .05, family-wise error corrected. Tractography identified significant group differences in the inferior longitudinal fasciculus (ILF), including lower FA and higher radial diffusivity in PTSD compared with TENC. Within the PTSD group, FA values were not correlated with symptom severity or trauma load. Results remained significant after removing participants using psychotropic medication or those with comorbid major depression.

CONCLUSIONS

PTSD patients had reduced WM integrity in left hemisphere frontal WM and temporal-occipital WM tracts, compared to trauma-exposed controls. Reduced frontal FA is consistent with compromised top-down attentional control and emotion regulation in PTSD, while reduced ILF FA may be related to sensory processing and gating abnormalities in this disorder.

The corticospinal tract profile in amyotrophic lateral sclerosis

This work evaluates the potential in diagnostic application of a new advanced neuroimaging method, which delineates the profile of tissue properties along the corticospinal tract (CST) in amyotrophic lateral sclerosis (ALS), by means of diffusion tensor imaging (DTI). Twenty-four ALS patients and twenty-four demographically matched healthy subjects were enrolled in this study. The Automated Fiber Quantification (AFQ), a tool for the automatic reconstruction of white matter tract profiles, based on a deterministic tractography algorithm to automatically identify the CST and quantify its diffusion properties, was used. At a group level, the highest non-overlapping DTI-related differences were detected in the cerebral peduncle, posterior limb of the internal capsule, and primary motor cortex. Fractional anisotropy (FA) decrease and mean diffusivity (MD) and radial diffusivity (RD) increases were detected when comparing ALS patients to controls. The machine learning approach used to assess the clinical utility of this DTI tool revealed that, by combining all DTI metrics measured along tract between the cerebral peduncle and the corona radiata, a mean 5-fold cross validation accuracy of 80% was reached in discriminating ALS from controls. Our study provides a useful new neuroimaging tool to characterize ALS-related neurodegenerative processes by means of CST profile. We demonstrated that specific microstructural changes in the upper part of the brainstem might be considered as a valid biomarker. With further validations this method has the potential to be considered a promising step toward the diagnostic utility of DTI measures in ALS. Hum Brain Mapp 38:727-739, 2017. © 2016 Wiley Periodicals, Inc.

The value of magnetic resonance imaging as a biomarker for amyotrophic lateral sclerosis: a systematic review

BACKGROUND

Amyotrophic lateral sclerosis (ALS) is a fatal, rapidly progressive neurodegenerative disease that mainly affects the motor system. A number of potentially neuroprotective and neurorestorative disease-modifying drugs are currently in clinical development. At present, the evaluation of a drug's clinical efficacy in ALS is based on the ALS Functional Rating Scale Revised, motor tests and survival. However, these endpoints are general, variable and late-stage measures of the ALS disease process and thus require the long-term assessment of large cohorts. Hence, there is a need for more sensitive radiological biomarkers. Various sequences for magnetic resonance imaging (MRI) of the brain and spinal cord have may have value as surrogate biomarkers for use in future clinical trials. Here, we review the MRI findings in ALS, their clinical correlations, and their limitations and potential role as biomarkers.

METHODS

The PubMed database was screened to identify studies using MRI in ALS. We included general MRI studies with a control group and an ALS group and longitudinal studies even if a control group was lacking.

RESULTS

A total of 116 studies were analysed with MRI data and clinical correlations. The most disease-sensitive MRI patterns are in motor regions but the brain is more broadly affected.

CONCLUSION

Despite the existing MRI biomarkers, there is a need for large cohorts with long term MRI and clinical follow-up. MRI assessment could be improved by standardized MRI protocols with multicentre studies.

Migraine affects white-matter tract integrity: A diffusion-tensor imaging study

BACKGROUND

Specific white-matter tract alterations in migraine remain to be elucidated. Using diffusion tensor imaging (DTI), this study investigated whether the integrity of white-matter tracts that underlie regions of the "pain matrix" is altered in migraine and interrogated whether the number of years lived with migraine modifies fibertract structure.

METHODS

Global probabilistic tractography was used to assess the anterior thalamic radiations, the corticospinal tracts and the inferior longitudinal fasciculi in 23 adults with migraine and 18 healthy controls.

RESULTS

Migraine patients show greater mean diffusivity (MD) in the left and right anterior thalamic radiations, the left corticospinal tract, and the right inferior longitudinal fasciculus tract. Migraine patients also show greater radial diffusivity (RD) in the left anterior thalamic radiations, the left corticospinal tract as well as the left and right inferior longitudinal fasciculus tracts. No group fractional anisotropy (FA) differences were identified for any tracts. Migraineurs showed a positive correlation between years lived with migraine and MD in the right anterior thalamic radiations (r = 0.517; p = 0.012) and the left corticospinal tract (r = 0.468; p = 0.024).

CONCLUSION

Results indicate that white-matter integrity is altered in migraine and that longer migraine history is positively correlated with greater alterations in tract integrity.