Effectiveness of regional diffusion MRI measures in distinguishing multiple sclerosis abnormalities within the cervical spinal cord

INTRODUCTION

Multiple sclerosis (MS) is an inflammatory disorder of the central nervous system. Although conventional magnetic resonance imaging (MRI) is widely used for MS diagnosis and clinical follow-up, quantitative MRI has the potential to provide valuable intrinsic values of tissue properties that can enhance accuracy. In this study, we investigate the efficacy of diffusion MRI in distinguishing MS lesions within the cervical spinal cord, using a combination of metrics extracted from diffusion tensor imaging and Ball-and-Stick models.

METHODS

We analyzed spinal cord data acquired from multiple hospitals and extracted average diffusion MRI metrics per vertebral level using a collection of image processing methods and an atlas-based approach. We then performed a statistical analysis to evaluate the feasibility of these metrics for detecting lesions, exploring the usefulness of combining different metrics to improve accuracy.

RESULTS

Our study demonstrates the sensitivity of each metric to underlying microstructure changes in MS patients. We show that selecting a specific subset of metrics, which provide complementary information, significantly improves the prediction score of lesion presence in the cervical spinal cord. Furthermore, the Ball-and-Stick model has the potential to provide novel information about the microstructure of damaged tissue.

CONCLUSION

Our results suggest that diffusion measures, particularly combined measures, are sensitive in discriminating abnormal from healthy cervical vertebral levels in patients. This information could aid in improving MS diagnosis and clinical follow-up. Our study highlights the potential of the Ball-and-Stick model in providing additional insights into the microstructure of the damaged tissue.

Apathy in depression: An arterial spin labeling perfusion MRI study

INTRODUCTION

Apathy, as defined as a deficit in goal-directed behaviors, is a critical clinical dimension in depression associated with chronic impairment. Little is known about its cerebral perfusion specificities in depression. To explore neurovascular mechanisms underpinning apathy in depression by pseudo-continuous arterial spin labeling (pCASL) magnetic resonance imaging (MRI).

METHODS

Perfusion imaging analysis was performed on 90 depressed patients included in a prospective study between November 2014 and February 2017. Imaging data included anatomical 3D T1-weighted and perfusion pCASL sequences. A multiple regression analysis relating the quantified cerebral blood flow (CBF) in different regions of interest defined from the FreeSurfer atlas, to the Apathy Evaluation Scale (AES) total score was conducted.

RESULTS

After confound adjustment (demographics, disease and clinical characteristics) and correction for multiple comparisons, we observed a strong negative relationship between the CBF in the left anterior cingulate cortex (ACC) and the AES score (standardized beta = -0.74, corrected p value = 0.0008).

CONCLUSION

Our results emphasized the left ACC as a key region involved in apathy severity in a population of depressed participants. Perfusion correlates of apathy in depression evidenced in this study may contribute to characterize different phenotypes of depression.

An Iterative Centroid Approach for Diffeomorphic Online Atlasing

Online atlasing, i.e., incrementing an atlas with new images as they are acquired, is key when performing studies on very large, or still being gathered, databases. Regular approaches to atlasing however do not focus on this aspect and impose a complete reconstruction of the atlas when adding images. We propose instead a diffeomorphic online atlasing method that allows gradual updates to an atlas. In this iterative centroid approach, we integrate new subjects in the atlas in an iterative manner, gradually moving the centroid of the images towards its final position. This leads to a computationally cheap approach since it only necessitates one additional registration per new subject added. We validate our approach on several experiments with three main goals: 1- to evaluate atlas image quality of the obtained atlases with sharpness and overlap measures, 2- to assess the deviation in terms of transformations with respect to a conventional atlasing method and 3- to compare its computational time with regular approaches of the literature. We demonstrate that the transformations divergence with respect to a state-of-the-art atlas construction method is small and reaches a plateau, that the two construction methods have the same ability to map subject homologous regions onto a common space and produce images of equivalent quality. The computational time of our approach is also drastically reduced for regular updates. Finally, we also present a direct extension of our method to update spatio-temporal atlases, especially useful for developmental studies.

Visual feedback improves movement illusions induced by tendon vibration after chronic stroke

BACKGROUND

Illusion of movement induced by tendon vibration is commonly used in rehabilitation and seems valuable for motor rehabilitation after stroke, by playing a role in cerebral plasticity. The aim was to study if congruent visual cues using Virtual Reality (VR) could enhance the illusion of movement induced by tendon vibration of the wrist among participants with stroke.

METHODS

We included 20 chronic stroke participants. They experienced tendon vibration of their wrist (100 Hz, 30 times) inducing illusion of movement. Three VR visual conditions were added to the vibration: a congruent moving virtual hand (Moving condition); a static virtual hand (Static condition); or no virtual hand at all (Hidden condition). The participants evaluated for each visual condition the intensity of the illusory movement using a Likert scale, the sensation of wrist's movement using a degree scale and they answered a questionnaire about their preferred condition.

RESULTS

The Moving condition was significantly superior to the Hidden condition and to the Static condition in terms of illusion of movement (p < 0.001) and the wrist's extension (p < 0.001). There was no significant difference between the Hidden and the Static condition for these 2 criteria. The Moving condition was considered the best one to increase the illusion of movement (in 70% of the participants). Two participants did not feel any illusion of movement.

CONCLUSIONS

This study showed the interest of using congruent cues in VR in order to enhance the consistency of the illusion of movement induced by tendon vibration among participants after stroke, regardless of their clinical severity. By stimulating the brain motor areas, this visuo-proprioceptive feedback could be an interesting tool in motor rehabilitation. Record number in Clinical Trials: NCT04130711, registered on October 17th 2019 ( https://clinicaltrials.gov/ct2/show/NCT04130711?id=NCT04130711&draw=2&rank=1 ).

Building memories on prior knowledge: behavioral and fMRI evidence of impairment in early Alzheimer's disease

Impaired memory is a hallmark of prodromal Alzheimer's disease (AD). Prior knowledge associated with the memoranda improves memory in healthy individuals, but we ignore whether the same occurs in early AD. We used functional MRI to investigate whether prior knowledge enhances memory encoding in early AD, and whether the nature of this prior knowledge matters. Patients with early AD and Controls underwent a task-based fMRI experiment where they learned face-scene associations. Famous faces carried pre-experimental knowledge (PEK), while unknown faces with which participants were familiarized prior to learning carried experimental knowledge (EK). Surprisingly, PEK strongly enhanced subsequent memory in healthy controls, but importantly not in patients. Partly nonoverlapping brain networks supported PEK vs. EK associative encoding in healthy controls. No such networks were identified in patients. In addition, patients displayed impaired activation in a right sub hippocampal region where activity predicted successful associative memory formation for PEK stimuli. Despite the limited sample sizes of this study, these findings suggest that the role prior knowledge in new learning might have been so far overlooked and underestimated in AD patients. Prior knowledge may drive critical differences in the way healthy elderly and early AD patients learn novel associations.

The impact of neurofeedback on effective connectivity networks in chronic stroke patients: an exploratory study

Objective.In this study, we assessed the impact of electroencephalography-functional magnetic resonance imaging (EEG-fMRI) neurofeedback (NF) on connectivity strength and direction in bilateral motor cortices in chronic stroke patients. Most of the studies using NF or brain computer interfaces for stroke rehabilitation have assessed treatment effects focusing on successful activation of targeted cortical regions. However, given the crucial role of brain network reorganization for stroke recovery, our broader aim was to assess connectivity changes after an NF training protocol targeting localized motor areas.Approach.We considered changes in fMRI connectivity after a multisession EEG-fMRI NF training targeting ipsilesional motor areas in nine stroke patients. We applied the dynamic causal modeling and parametric empirical Bayes frameworks for the estimation of effective connectivity changes. We considered a motor network including both ipsilesional and contralesional premotor, supplementary and primary motor areas.Main results.Our results indicate that NF upregulation of targeted areas (ipsilesional supplementary and primary motor areas) not only modulated activation patterns, but also had a more widespread impact on fMRI bilateral motor networks. In particular, inter-hemispheric connectivity between premotor and primary motor regions decreased, and ipsilesional self-inhibitory connections were reduced in strength, indicating an increase in activation during the NF motor task.Significance.To the best of our knowledge, this is the first work that investigates fMRI connectivity changes elicited by training of localized motor targets in stroke. Our results open new perspectives in the understanding of large-scale effects of NF training and the design of more effective NF strategies, based on the pathophysiology underlying stroke-induced deficits.

Influence of the visuo-proprioceptive illusion of movement and motor imagery of the wrist on EEG cortical excitability among healthy participants

INTRODUCTION

Motor Imagery (MI) is a powerful tool to stimulate sensorimotor brain areas and is currently used in motor rehabilitation after a stroke. The aim of our study was to evaluate whether an illusion of movement induced by visuo-proprioceptive immersion (VPI) including tendon vibration (TV) and Virtual moving hand (VR) combined with MI tasks could be more efficient than VPI alone or MI alone on cortical excitability assessed using Electroencephalography (EEG).

METHODS

We recorded EEG signals in 20 healthy participants in 3 different conditions: MI tasks involving their non-dominant wrist (MI condition); VPI condition; and VPI with MI tasks (combined condition). Each condition lasted 3 minutes, and was repeated 3 times in randomized order. Our main judgment criterion was the Event-Related De-synchronization (ERD) threshold in sensori-motor areas in each condition in the brain motor area.

RESULTS

The combined condition induced a greater change in the ERD percentage than the MI condition alone, but no significant difference was found between the combined and the VPI condition (p = 0.07) and between the VPI and MI condition (p = 0.20).

CONCLUSION

This study demonstrated the interest of using a visuo-proprioceptive immersion with MI rather than MI alone in order to increase excitability in motor areas of the brain. Further studies could test this hypothesis among patients with stroke to provide new perspectives for motor rehabilitation in this population.

WITHDRAWN: Alternative bimodal unimodal neurofeedback training to induce cerebral reorganization after chronic stroke: A proof-of-concept case report

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Multiparametric Analysis of Cerebral Development in Preterm Infants Using Magnetic Resonance Imaging

Objectives

The severity of neurocognitive impairment increases with prematurity. However, its mechanisms remain poorly understood. Our aim was firstly to identify multiparametric magnetic resonance imaging (MRI) markers that differ according to the degree of prematurity, and secondly to evaluate the impact of clinical complications on these markers.

Materials and Methods

We prospectively enrolled preterm infants who were divided into two groups according to their degree of prematurity: extremely preterm (<28 weeks' gestational age) and very preterm (28-32 weeks' gestational age). They underwent a multiparametric brain MRI scan at term-equivalent age including morphological, diffusion tensor and arterial spin labeling (ASL) perfusion sequences. We quantified overall and regional volumes, diffusion parameters, and cerebral blood flow (CBF). We then compared the parameters for the two groups. We also assessed the effects of clinical data and potential MRI morphological abnormalities on those parameters.

Results

Thirty-four preterm infants were included. Extremely preterm infants (n = 13) had significantly higher frontal relative volumes (p = 0.04), frontal GM relative volumes (p = 0.03), and regional CBF than very preterm infants, but they had lower brainstem and insular relative volumes (respectively p = 0.008 and 0.04). Preterm infants with WM lesions on MRI had significantly lower overall GM CBF (13.3 ± 2 ml/100 g/min versus 17.7 ± 2.5, < ml/100 g/min p = 0.03).

Conclusion

Magnetic resonance imaging brain scans performed at term-equivalent age in preterm infants provide quantitative imaging parameters that differ with respect to the degree of prematurity, related to brain maturation.

Interpolation and Averaging of Diffusion MRI Multi-Compartment Models

Multi-compartment models (MCM) are increasingly used to characterize the brain white matter microstructure from diffusion-weighted imaging (DWI). Their use in clinical studies is however limited by the inability to resample an MCM image towards a common reference frame, or to construct atlases from such brain microstructure models. We propose to solve this problem by first identifying that these two tasks amount to the same problem. We propose to tackle it by viewing it as a simplification problem, solved thanks to spectral clustering and the definition of semi-metrics between several usual compartments encountered in the MCM literature. This generic framework is evaluated for two models: the multi-tensor model where individual fibers are modeled as individual tensors and the diffusion direction imaging (DDI) model that differentiates intra- and extra-axonal components of each fiber. Results on simulated data, simulated transformations and real data show the ability of our method to well interpolate MCM images of these types. We finally present as an application an MCM template of normal controls constructed using our approach.

Structural abnormalities associated with poor outcome of a major depressive episode: The role of thalamus

An identification of precise biomarkers contributing to poor outcome of a major depressive episode (MDE) has the potential to improve therapeutic strategies by reducing time to symptomatic relief. In a cross-sectional volumetric study with a 6 month clinical follow-up, we performed baseline brain grey matter volume analysis between 2 groups based on illness improvement: 27 MDD patients in the "responder" (R) group (Clinical Global Impression- Improvement (CGI-I) score ≤ 2) and 30 in the "non-responder" (NR) group (CGI-I > 2), using a Voxel Based-Morphometry analysis. NR had significantly smaller Grey Matter (GM) volume in the bilateral thalami, in precentral gyrus, middle temporal gyrus, precuneus and middle cingulum compared to R at baseline. Additionally, they exhibited significant greater GM volume increase in the left anterior lobe of cerebellum and posterior cingulate cortex. The latter result was not significant when participants with bipolar disorder were excluded from the analysis. NR group had higher baseline anxiety scores. Our study has pointed out the role of thalamus in prognosis of MDE. These findings highlight the involvement of emotion regulation in the outcome of MDE. The present study provides a step towards the understanding of neurobiological processes of treatment resistant depression.

Influence of virtual reality visual feedback on the illusion of movement induced by tendon vibration of wrist in healthy participants

Introduction

Illusion of movement induced by tendon vibration is an effective approach for motor and sensory rehabilitation in case of neurological impairments. The aim of our study was to investigate which modality of visual feedback in Virtual Reality (VR) associated with tendon vibration of the wrist could induce the best illusion of movement.

Methods

We included 30 healthy participants in the experiment. Tendon vibration inducing illusion of movement (wrist extension, 100Hz) was applied on their wrist during 3 VR visual conditions (10 times each): a moving virtual hand corresponding to the movement that the participants could feel during the tendon vibration (Moving condition), a static virtual hand (Static condition), or no virtual hand at all (Hidden condition). After each trial, the participants had to quantify the intensity of the illusory movement on a Likert scale, the subjective degree of extension of their wrist and afterwards they answered a questionnaire.

Results

There was a significant difference between the 3 visual feedback conditions concerning the Likert scale ranking and the degree of wrist’s extension (p<0.001). The Moving condition induced a higher intensity of illusion of movement and a higher sensation of wrist’s extension than the Hidden condition (p<0.001 and p<0.001 respectively) than that of the Static condition (p<0.001 and p<0.001 respectively). The Hidden condition also induced a higher intensity of illusion of movement and a higher sensation of wrist’s extension than the Static condition (p<0.01 and p<0.01 respectively). The preferred condition to facilitate movement’s illusion was the Moving condition (63.3%).

Conclusions

This study demonstrated the importance of carefully selecting a visual feedback to improve the illusion of movement induced by tendon vibration, and the increase of illusion by adding VR visual cues congruent to the illusion of movement. Further work will consist in testing the same hypothesis with stroke patients.

Exposure of pregnant women to organophosphate insecticides and child motor inhibition at the age of 10-12 years evaluated by fMRI

BACKGROUND

Organophosphate pesticides (OP) are widely used for both agricultural and domestic purposes. Epidemiological studies suggest neurotoxicity in children after exposure to organophosphates pesticides (OP) at low levels but possible mechanism is still unclear.

OBJECTIVES

We aimed at investigating the effects of prenatal exposure to OPs on inhibitory control of 10-12 year-old-children assessed by a motor inhibition task during functional magnetic resonance imaging (fMRI).

METHODS

Ninety-five children from the PELAGIE cohort (Brittany-France, from 2002) underwent a fMRI examination during which inhibition was assessed by a Go/No-Go task. Task performance was assessed by average response latency, commission rate and composite performance score (PS). Whole brain activation was estimated by modeling the hemodynamic response related to inhibition demand and successful inhibition. OP exposure was assessed by measuring six dialkylphosphate (DAP) metabolites in the urine of women in early pregnancy (<19 WG). Concentrations were summed to obtain overall levels of diethylphosphate (DE), dimethylphosphate (DM) and total non-specific metabolites (DAP), standardized to homogenize sampling conditions and categorized into levels of exposure: low (reference), moderate or high. Regression models were adjusted for potential cofounders considered by restriction and statistical criteria.

RESULTS

Moderate levels of DAP were associated with a decreased commission rate (β = -6.65%, p = 0.04), indicating improved performance. Increasing levels of DM and DE were associated with decreased brain activity in the left inferior and bilateral superior frontal regions during successful inhibition. We did not observe any differential activation related to inhibitory demands.

DISCUSSION

These results suggest that prenatal OPs may be associated with altered pattern of brain activity in regions related to inhibition among children and need to be confirmed by additional studies.

Acquisition Duration in Resting-State Arterial Spin Labeling. How Long Is Enough?

Resting-state Arterial Spin Labeling (rs-ASL) is a rather confidential method compared to resting-state BOLD. As ASL allows to quantify the cerebral blood flow, unlike BOLD, rs-ASL can lead to significant clinical subject-scaled applications. Despite directly impacting clinical practicability and functional networks estimation, there is no standard for rs-ASL regarding the acquisition duration. Our work here focuses on assessing the feasibility of ASL as an rs-fMRI method and on studying the effect of the acquisition duration on the estimation of functional networks. To this end, we acquired a long 24 min 30 s rs-ASL sequence and investigated how estimations of six typical functional brain networks evolved with respect to the acquisition duration. Our results show that, after a certain acquisition duration, the estimations of all functional networks reach their best and are stabilized. Since, for clinical application, the acquisition duration should be the shortest possible, we suggest an acquisition duration of 14 min, i.e., 240 volumes with our sequence parameters, as it covers the functional networks estimation stabilization.

A Survey on the Use of Haptic Feedback for Brain-Computer Interfaces and Neurofeedback

Neurofeedback (NF) and brain-computer interface (BCI) applications rely on the registration and real-time feedback of individual patterns of brain activity with the aim of achieving self-regulation of specific neural substrates or control of external devices. These approaches have historically employed visual stimuli. However, in some cases vision is unsuitable or inadequately engaging. Other sensory modalities, such as auditory or haptic feedback have been explored, and multisensory stimulation is expected to improve the quality of the interaction loop. Moreover, for motor imagery tasks, closing the sensorimotor loop through haptic feedback may be relevant for motor rehabilitation applications, as it can promote plasticity mechanisms. This survey reviews the various haptic technologies and describes their application to BCIs and NF. We identify major trends in the use of haptic interfaces for BCI and NF systems and discuss crucial aspects that could motivate further studies.

Small Animal Shanoir (SAS) A Cloud-Based Solution for Managing Preclinical MR Brain Imaging Studies

Clinical multicenter imaging studies are frequent and rely on a wide range of existing tools for sharing data and processing pipelines. This is not the case for preclinical (small animal) studies. Animal population imaging is still in infancy, especially because a complete standardization and control of initial conditions in animal models across labs is still difficult and few studies aim at standardization of acquisition and post-processing techniques. Clearly, there is a need of appropriate tools for the management and sharing of data, post-processing and analysis methods dedicated to small animal imaging. Solutions developed for Human imaging studies cannot be directly applied to this specific domain. In this paper, we present the Small Animal Shanoir (SAS) solution for supporting animal population imaging using tools compatible with open data. The integration of automated workflow tools ensures accessibility and reproducibility of research outputs. By sharing data and imaging processing tools, hosted by SAS, we promote data preparation and tools for reproducibility and reuse, and participation in multicenter or replication "open science" studies contributing to the improvement of quality science in preclinical domain. SAS is a first step for promoting open science for small animal imaging and a contribution to the valorization of data and pipelines of reference.

Unsupervised Domain Adaptation With Optimal Transport in Multi-Site Segmentation of Multiple Sclerosis Lesions From MRI Data

Automatic segmentation of Multiple Sclerosis (MS) lesions from Magnetic Resonance Imaging (MRI) images is essential for clinical assessment and treatment planning of MS. Recent years have seen an increasing use of Convolutional Neural Networks (CNNs) for this task. Although these methods provide accurate segmentation, their applicability in clinical settings remains limited due to a reproducibility issue across different image domains. MS images can have highly variable characteristics across patients, MRI scanners and imaging protocols; retraining a supervised model with data from each new domain is not a feasible solution because it requires manual annotation from expert radiologists. In this work, we explore an unsupervised solution to the problem of domain shift. We present a framework, Seg-JDOT, which adapts a deep model so that samples from a source domain and samples from a target domain sharing similar representations will be similarly segmented. We evaluated the framework on a multi-site dataset, MICCAI 2016, and showed that the adaptation toward a target site can bring remarkable improvements in a model performance over standard training.

Regional brain development analysis through registration using anisotropic similarity, a constrained affine transformation

We propose a novel method to quantify brain growth in 3 arbitrary orthogonal directions of the brain or its sub-regions through linear registration. This is achieved by introducing a 9 degrees of freedom (dof) transformation called anisotropic similarity which is an affine transformation with constrained scaling directions along arbitrarily chosen orthogonal vectors. This gives the opportunity to extract scaling factors describing brain growth along those directions by registering a database of subjects onto a common reference. This information about directional growth brings insights that are not usually available in longitudinal volumetric analysis. The interest of this method is illustrated by studying the anisotropic regional and global brain development of 308 healthy subjects betwen 0 and 19 years old. A gender comparison of those scaling factors is also performed for four age-intervals. We demonstrate through these applications the stability of the method to the chosen reference and its ability to highlight growth differences accros regions and gender.

A Multi-Target Motor Imagery Training Using Bimodal EEG-fMRI Neurofeedback: A Pilot Study in Chronic Stroke Patients

Traditional rehabilitation techniques present limitations and the majority of patients show poor 1-year post-stroke recovery. Thus, Neurofeedback (NF) or Brain-Computer-Interface applications for stroke rehabilitation purposes are gaining increased attention. Indeed, NF has the potential to enhance volitional control of targeted cortical areas and thus impact on motor function recovery. However, current implementations are limited by temporal, spatial or practical constraints of the specific imaging modality used. In this pilot work and for the first time in literature, we applied bimodal EEG-fMRI NF for upper limb stroke recovery on four stroke-patients with different stroke characteristics and motor impairment severity. We also propose a novel, multi-target training approach that guides the training towards the activation of the ipsilesional primary motor cortex. In addition to fMRI and EEG outcomes, we assess the integrity of the corticospinal tract (CST) with tractography. Preliminary results suggest the feasibility of our approach and show its potential to induce an augmented activation of ipsilesional motor areas, depending on the severity of the stroke deficit. Only the two patients with a preserved CST and subcortical lesions succeeded in upregulating the ipsilesional primary motor cortex and exhibited a functional improvement of upper limb motricity. These findings highlight the importance of taking into account the variability of the stroke patients' population and enabled to identify inclusion criteria for the design of future clinical studies.

A Sparse EEG-Informed fMRI Model for Hybrid EEG-fMRI Neurofeedback Prediction

Measures of brain activity through functional magnetic resonance imaging (fMRI) or electroencephalography (EEG), two complementary modalities, are ground solutions in the context of neurofeedback (NF) mechanisms for brain rehabilitation protocols. While NF-EEG (in which real-time neurofeedback scores are computed from EEG signals) has been explored for a very long time, NF-fMRI (in which real-time neurofeedback scores are computed from fMRI signals) appeared more recently and provides more robust results and more specific brain training. Using fMRI and EEG simultaneously for bi-modal neurofeedback sessions (NF-EEG-fMRI, in which real-time neurofeedback scores are computed from fMRI and EEG) is very promising for the design of brain rehabilitation protocols. However, fMRI is cumbersome and more exhausting for patients. The original contribution of this paper concerns the prediction of bi-modal NF scores from EEG recordings only, using a training phase where EEG signals as well as the NF-EEG and NF-fMRI scores are available. We propose a sparse regression model able to exploit EEG only to predict NF-fMRI or NF-EEG-fMRI in motor imagery tasks. We compared different NF-predictors stemming from the proposed model. We showed that predicting NF-fMRI scores from EEG signals adds information to NF-EEG scores and significantly improves the correlation with bi-modal NF sessions compared to classical NF-EEG scores.

Prenatal exposure to glycol ethers and motor inhibition function evaluated by functional MRI at the age of 10 to 12 years in the PELAGIE mother-child cohort

BACKGROUND

Pregnant women are ubiquitously exposed to organic solvents, such as glycol ethers. Several studies suggest potential developmental neurotoxicity following exposure to glycol ethers with a lack of clarity of possible brain mechanisms.

OBJECTIVES

We investigated the association between urinary levels of glycol ethers of women during early pregnancy and motor inhibition function of their 10- to 12-year-old children by behavioral assessment and brain imaging.

METHODS

Exposure to glycol ethers was assessed by measuring six metabolites in urine (<19 weeks of gestation) of 73 pregnant women of the PELAGIE mother-child cohort (France). Maternal urinary levels were classified as low, medium, or high. Children underwent functional magnetic resonance imaging (fMRI) examinations during which motor inhibition function was assessed with a Go/No-Go task. Analyses were performed using linear regression for task performance and generalized linear mixed-effect models for brain activation, FWER-corrected for multiple testing at the spatial cluster level. Confounders were considered by restriction and a priori adjustment.

RESULTS

Higher maternal butoxyacetic acid (BAA) urinary concentrations were associated with poorer child performance (β = -1.1; 95% CI: -1.9, -0.2 for high vs low). There was also a trend for ethoxyacetic acid (EAA) towards poorer performance (β = -0.3; 95% CI: -0.7, 0.01). Considering inhibition demand, there were increased activity in occipital regions in association with moderate EAA (left cuneus) and moderate methoxyacetic acid (MAA) (right precuneus). When children succeeded to inhibit, high ethoxyethoxyacetic acid (EEAA) and moderate phenoxyacetic acid (PhAA) levels were associated with differential activity in frontal cortex, involved in inhibition network.

DISCUSSION

Prenatal urinary levels of two glycol ether metabolites were associated with poorer Go/No-Go task performance. Differential activations were observed in the brain motor inhibition network in relation with successful inhibition, but not with cognitive demand. Nevertheless, there is no consistence between performance indicators and cerebral activity results. Other studies are highly necessary given the ubiquity of glycol ether exposure.

Changes in brain perfusion in successive arterial spin labeling MRI scans in neonates with hypoxic-ischemic encephalopathy

The primary objective of this study was to evaluate changes in cerebral blood flow (CBF) using arterial spin labeling MRI between day 4 of life (DOL4) and day 11 of life (DOL11) in neonates with hypoxic-ischemic encephalopathy (HIE) treated with hypothermia. The secondary objectives were to compare CBF values between the different regions of interest (ROIs) and between infants with ischemic lesions on MRI and infants with normal MRI findings.

We prospectively included all consecutive neonates with HIE admitted to the neonatal intensive care unit of our institution who were eligible for therapeutic hypothermia. Each neonate systematically underwent two MRI examinations as close as possible to day 4 (early MRI) and day 11 (late MRI) of life. A custom processing pipeline of morphological and perfusion imaging data adapted to neonates was developed to perform automated ROI analysis.

Twenty-eight neonates were included in the study between April 2015 and December 2017. There were 16 boys and 12 girls. Statistical analysis was finally performed on 37 MRIs, 17 early MRIs and 20 late MRIs. Eleven neonates had both early and late MRIs of good quality available. Eight out of 17 neonates (47%) had an abnormal on late MRI as performed and 7/20 neonates (35%) had an abnormal late MRI. CBF values in the basal ganglia and thalami (BGT) and temporal lobes were significantly higher on DOL4 than on DOL11. There were no significant differences between DOL4 and DOL11 for the other ROIs. CBF values were significantly higher in the BGT vs. the cortical GM, on both DOL4 and DOL11. On DOL4, the CBF was significantly higher in the cortical GM, the BGT, and the frontal and parietal lobes in subjects with an abnormal MRI compared to those with a normal MRI. On DOL11, CBF values in each ROI were not significantly different between the normal MRI group and the abnormal MRI group, except for the temporal lobes.

This article proposes an innovative processing pipeline for morphological and ASL data suited to neonates that enable automated segmentation to obtain CBF values over ROIs. We evaluate CBF on two successive scans within the first 15 days of life in the same subjects. ASL imaging in asphyxiated neonates seems more relevant when used relatively early, in the first days of life. The correlation of intra-subject changes in cerebral perfusion between early and late MRI with neurodevelopmental outcome warrants investigation in a larger cohort, to determine whether the CBF pattern change can provide prognostic information beyond that provided by visible structural abnormalities on conventional MRI.

•

A processing pipeline suited to neonates was developed for automated ROI analysis.

•

Basal ganglia and thalamic CBF values were significantly higher on DOL4 vs. DOL11.

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Neonates with abnormal morphological MRI had hyperperfusion in grey matter on DOL4.

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No perfusion differences were found on DOL11 between normal and abnormal MRIs.

Joint assessment of brain and spinal cord motor tract damage in patients with early RRMS: predominant impact of spinal cord lesions on motor function

BACKGROUND

In patients with MS, the effect of structural damage to the corticospinal tract (CST) has been separately evaluated in the brain and spinal cord (SC), even though a cumulative impact is suspected.

OBJECTIVE

To evaluate CST damages on both the cortex and cervical SC, and examine their relative associations with motor function, measured both clinically and by electrophysiology.

METHODS

We included 43 patients with early relapsing-remitting MS. Lesions were manually segmented on SC (axial T2*) and brain (3D FLAIR) scans. The CST was automatically segmented using an atlas (SC) or tractography (brain). Lesion volume fractions and diffusion parameters were calculated for SC, brain and CST. Central motor conduction time (CMCT) and triple stimulation technique amplitude ratio were measured for 42 upper limbs, from 22 patients.

RESULTS

Mean lesion volume fractions were 5.2% in the SC portion of the CST and 0.9% in the brain portion. We did not find a significant correlation between brain and SC lesion volume fraction (r = 0.06, p = 0.68). The pyramidal EDSS score and CMCT were both significantly correlated with the lesion fraction in the SC CST (r = 0.39, p = 0.01 and r = 0.33, p = 0.03), but not in the brain CST.

CONCLUSION

Our results highlight the major contribution of SC lesions to CST damage and motor function abnormalities.

Superior explicit memory despite severe developmental amnesia: In-depth case study and neural correlates

The acquisition of new semantic memories is sometimes preserved in patients with hippocampal amnesia. Robust evidence for this comes from case reports of developmental amnesia suggesting that low-to-normal levels of semantic knowledge can be achieved despite compromised episodic learning. However, it is unclear whether this relative preservation of semantic memory results from normal acquisition and retrieval or from residual episodic memory, combined with effortful repetition. Furthermore, lesion studies have mainly focused on the hippocampus itself, and have seldom reported the state of structures in the extended hippocampal system. Preserved components of this system may therefore mediate residual episodic abilities, contributing to the apparent semantic preservation. We report an in-depth study of Patient KA, a 27-year-old man who had severe hypoxia at birth, in which we carefully explored his residual episodic learning abilities. We used novel speeded recognition paradigms to assess whether KA could explicitly acquire and retrieve new context-free memories. Despite a pattern of very severe amnesia, with a 44-point discrepancy between his intelligence and memory quotients, KA exhibited normal-to-superior levels of knowledge, even under strict time constraints. He also exhibited normal-to-superior recognition memory for new material, again under strict time constraints. Multimodal neuroimaging revealed an unusual pattern of selective atrophy within each component of the extended hippocampal system, contrasting with the preservation of anterior subhippocampal cortices. A cortical thickness analysis yielded a pattern of thinner but also thicker regional cortices, pointing toward specific temporal lobe reorganization following early injury. We thus report the first case of superior explicit learning and memory in a severe case of amnesia, raising important questions about how such knowledge can be acquired.

Measurement of magnetization transfer ratio (MTR) from cervical spinal cord: Multicenter reproducibility and variability

BACKGROUND

Assessing the multicenter variability of magnetization transfer ratio (MTR) measurements in the spinal cord of healthy controls is the first step toward investigating its clinical use as a biomarker.

PURPOSE

To analyze the between-session, between-participant, and between-scanner variability of MTR measurements in automatically extracted regions of interest in the cervical cord of healthy controls.

STUDY TYPE

Control study.

POPULATION

Forty-four participants, distributed across five MRI scanners (all from the same manufacturer). Ten participants were scanned twice in the same scanner, and 10 others were scanned twice in two different scanners.

FIELD STRENGTH/SEQUENCE

3D-gradient echo images, centered on C5, without and with magnetization transfer prepulse at 3T.

ASSESSMENT

We calculated the mean MTR for different vertebral levels in the whole cord (WC), as well as in the white matter and gray matter, and determined the between-session, between-participant, and between-scanner variabilities.

STATISTICAL TESTS

Coefficients of variation and intraclass correlations (ICCs) for the different variabilities and their associated confidence intervals.

RESULTS

The MTR measurements for Levels C4-C6 (near the slab center) exhibited a mean value in WC of 34.6 pu and a pooled standard deviation of 0.9 pu. The between-session coefficient of variation was estimated as 2.3% (ICC = 0.63), the between-participant coefficient as 1.6% (ICC = 0.32), and the between-scanner coefficient as 0.7% (ICC = 0.05). The resulting aggregate coefficient of variation was 2.9%, which was sufficiently low to detect an MTR reduction of 1 pu between groups of about 45 participants (Type-I error rate: 0.05; Type-II error rate: 0.10).

DATA CONCLUSION

The good between-scanner reproducibility and low overall variability in cervical spinal cord MTR measurements in a control population might pave the way for multicenter analyses in various neurological diseases with moderate cohort sizes.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:1777-1785.

Objective Evaluation of Multiple Sclerosis Lesion Segmentation using a Data Management and Processing Infrastructure

We present a study of multiple sclerosis segmentation algorithms conducted at the international MICCAI 2016 challenge. This challenge was operated using a new open-science computing infrastructure. This allowed for the automatic and independent evaluation of a large range of algorithms in a fair and completely automatic manner. This computing infrastructure was used to evaluate thirteen methods of MS lesions segmentation, exploring a broad range of state-of-theart algorithms, against a high-quality database of 53 MS cases coming from four centers following a common definition of the acquisition protocol. Each case was annotated manually by an unprecedented number of seven different experts. Results of the challenge highlighted that automatic algorithms, including the recent machine learning methods (random forests, deep learning, …), are still trailing human expertise on both detection and delineation criteria. In addition, we demonstrate that computing a statistically robust consensus of the algorithms performs closer to human expertise on one score (segmentation) although still trailing on detection scores.

Focal and diffuse cervical spinal cord damage in patients with early relapsing-remitting MS: A multicentre magnetisation transfer ratio study

BACKGROUND

Studies including patients with well-established multiple sclerosis (MS) have shown a significant and disability-related reduction in the cervical spinal cord (SC) magnetisation transfer ratio (MTR).

OBJECTIVES

The objectives are to (1) assess whether MTR reduction is already measurable in the SC of patients with early relapsing-remitting multiple sclerosis (RRMS) and (2) describe its spatial distribution.

METHODS

We included 60 patients with RRMS <12  months and 34 age-matched controls at five centres. Axial T2*w, sagittal T2w, sagittal phase-sensitive inversion recovery (PSIR), 3DT1w, and axial magnetisation transfer (MT) images were acquired from C1 to C7. Lesions were manually labelled and mean MTR values computed both for the whole SC and for normal-appearing SC in different regions of interest.

RESULTS

Mean whole SC MTR was significantly lower in patients than controls (33.7 vs 34.9  pu, p  =  0.00005), even after excluding lesions (33.9  pu, p  =  0.0003). We observed a greater mean reduction in MTR for vertebral levels displaying the highest lesion loads (C2-C4). In the axial plane, we observed a greater mean MTR reduction at the SC periphery and barycentre.

CONCLUSION

Cervical SC tissue damage measured using MTR is not restricted to macroscopic lesions in patients with early RRMS and is not homogeneously distributed.

USPIO-positive MS lesions are associated with greater tissue damage than gadolinium-positive-only lesions during 3-year follow-up

Background:

Identifying in vivo the processes that determine lesion severity in multiple sclerosis (MS) remains a challenge.

Objectives:

To describe the dynamics of ultrasmall superparamagnetic iron oxide (USPIO) enhancement in MS lesions and the relationship between USPIO enhancement and microstructural changes over 3 years.

Methods:

Lesion development was assessed at baseline, Months 3, 6, and 9, using magnetic resonance imaging (MRI) with gadolinium and USPIO. Microstructural changes were assessed at baseline, Months 3, 6, 9, 12, 18, 24, and 36, using relaxometry, magnetization transfer, and diffusion-weighted imaging.

Results:

We included 15 patients with clinically isolated syndrome. In the 52 MRI scans acquired with USPIO, 22 lesions were USPIO and gadolinium positive, and 44 were USPIO negative but gadolinium positive. Lesions no longer exhibited sustained USPIO enhancement 3 months later. At baseline, lesions that were both USPIO and gadolinium positive had lower magnetization transfer ratio values (common language effect size = 0.84, p = 0.0005) and lower fractional anisotropy values (0.83, p = 0.001) than gadolinium-positive-only lesions. USPIO-positive lesions remained associated with greater damage than gadolinium-positive-only lesions throughout the 3-year follow-up.

Conclusion:

USPIO enhancement, mainly reflecting monocyte infiltration, is transient and is associated with persistent tissue damage after 3 years.

Block-Matching Distortion Correction of Echo-Planar Images With Opposite Phase Encoding Directions

By shortening the acquisition time of MRI, Echo Planar Imaging (EPI) enables the acquisition of a large number of images in a short time, compatible with clinical constraints as required for diffusion or functional MRI. However such images are subject to large, local distortions disrupting their correspondence with the underlying anatomy. The correction of those distortions is an open problem, especially in regions where large deformations occur. We propose a new block-matching registration method to perform EPI distortion correction based on the acquisition of two EPI with opposite phase encoding directions (PED). It relies on new transformations between blocks adapted to the EPI distortion model, and on an adapted optimization scheme to ensure an opposite symmetric transformation. We present qualitative and quantitative results of the block-matching correction using different metrics on a phantom dataset and on in-vivo data. We show the ability of the block-matching to robustly correct EPI distortion even in strongly affected areas.

Unimodal Versus Bimodal EEG-fMRI Neurofeedback of a Motor Imagery Task

Neurofeedback is a promising tool for brain rehabilitation and peak performance training. Neurofeedback approaches usually rely on a single brain imaging modality such as EEG or fMRI. Combining these modalities for neurofeedback training could allow to provide richer information to the subject and could thus enable him/her to achieve faster and more specific self-regulation. Yet unimodal and multimodal neurofeedback have never been compared before. In the present work, we introduce a simultaneous EEG-fMRI experimental protocol in which participants performed a motor-imagery task in unimodal and bimodal NF conditions. With this protocol we were able to compare for the first time the effects of unimodal EEG-neurofeedback and fMRI-neurofeedback versus bimodal EEG-fMRI-neurofeedback by looking both at EEG and fMRI activations. We also propose a new feedback metaphor for bimodal EEG-fMRI-neurofeedback that integrates both EEG and fMRI signal in a single bi-dimensional feedback (a ball moving in 2D). Such a feedback is intended to relieve the cognitive load of the subject by presenting the bimodal neurofeedback task as a single regulation task instead of two. Additionally, this integrated feedback metaphor gives flexibility on defining a bimodal neurofeedback target. Participants were able to regulate activity in their motor regions in all NF conditions. Moreover, motor activations as revealed by offline fMRI analysis were stronger during EEG-fMRI-neurofeedback than during EEG-neurofeedback. This result suggests that EEG-fMRI-neurofeedback could be more specific or more engaging than EEG-neurofeedback. Our results also suggest that during EEG-fMRI-neurofeedback, participants tended to regulate more the modality that was harder to control. Taken together our results shed first light on the specific mechanisms of bimodal EEG-fMRI-neurofeedback and on its added-value as compared to unimodal EEG-neurofeedback and fMRI-neurofeedback.

How to Build a Hybrid Neurofeedback Platform Combining EEG and fMRI

Multimodal neurofeedback estimates brain activity using information acquired with more than one neurosignal measurement technology. In this paper we describe how to set up and use a hybrid platform based on simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), then we illustrate how to use it for conducting bimodal neurofeedback experiments. The paper is intended for those willing to build a multimodal neurofeedback system, to guide them through the different steps of the design, setup, and experimental applications, and help them choose a suitable hardware and software configuration. Furthermore, it reports practical information from bimodal neurofeedback experiments conducted in our lab. The platform presented here has a modular parallel processing architecture that promotes real-time signal processing performance and simple future addition and/or replacement of processing modules. Various unimodal and bimodal neurofeedback experiments conducted in our lab showed high performance and accuracy. Currently, the platform is able to provide neurofeedback based on electroencephalography and functional magnetic resonance imaging, but the architecture and the working principles described here are valid for any other combination of two or more real-time brain activity measurement technologies.

Longitudinal multiple sclerosis lesion segmentation: Resource and challenge

In conjunction with the ISBI 2015 conference, we organized a longitudinal lesion segmentation challenge providing training and test data to registered participants. The training data consisted of five subjects with a mean of 4.4 time-points, and test data of fourteen subjects with a mean of 4.4 time-points. All 82 data sets had the white matter lesions associated with multiple sclerosis delineated by two human expert raters. Eleven teams submitted results using state-of-the-art lesion segmentation algorithms to the challenge, with ten teams presenting their results at the conference. We present a quantitative evaluation comparing the consistency of the two raters as well as exploring the performance of the eleven submitted results in addition to three other lesion segmentation algorithms. The challenge presented three unique opportunities: (1) the sharing of a rich data set; (2) collaboration and comparison of the various avenues of research being pursued in the community; and (3) a review and refinement of the evaluation metrics currently in use. We report on the performance of the challenge participants, as well as the construction and evaluation of a consensus delineation. The image data and manual delineations will continue to be available for download, through an evaluation website2 as a resource for future researchers in the area. This data resource provides a platform to compare existing methods in a fair and consistent manner to each other and multiple manual raters.

Imaging biomarkers in multiple Sclerosis: From image analysis to population imaging

The production of imaging data in medicine increases more rapidly than the capacity of computing models to extract information from it. The grand challenges of better understanding the brain, offering better care for neurological disorders, and stimulating new drug design will not be achieved without significant advances in computational neuroscience. The road to success is to develop a new, generic, computational methodology and to confront and validate this methodology on relevant diseases with adapted computational infrastructures. This new concept sustains the need to build new research paradigms to better understand the natural history of the pathology at the early phase; to better aggregate data that will provide the most complete representation of the pathology in order to better correlate imaging with other relevant features such as clinical, biological or genetic data. In this context, one of the major challenges of neuroimaging in clinical neurosciences is to detect quantitative signs of pathological evolution as early as possible to prevent disease progression, evaluate therapeutic protocols or even better understand and model the natural history of a given neurological pathology. Many diseases encompass brain alterations often not visible on conventional MRI sequences, especially in normal appearing brain tissues (NABT). MRI has often a low specificity for differentiating between possible pathological changes which could help in discriminating between the different pathological stages or grades. The objective of medical image analysis procedures is to define new quantitative neuroimaging biomarkers to track the evolution of the pathology at different levels. This paper illustrates this issue in one acute neuro-inflammatory pathology: Multiple Sclerosis (MS). It exhibits the current medical image analysis approaches and explains how this field of research will evolve in the next decade to integrate larger scale of information at the temporal, cellular, structural and morphological levels.

An a contrario approach for the detection of patient-specific brain perfusion abnormalities with arterial spin labelling

In this paper, we introduce a new locally multivariate procedure to quantitatively extract voxel-wise patterns of abnormal perfusion in individual patients. This a contrario approach uses a multivariate metric from the computer vision community that is suitable to detect abnormalities even in the presence of closeby hypo- and hyper-perfusions. This method takes into account local information without applying Gaussian smoothing to the data. Furthermore, to improve on the standard a contrario approach, which assumes white noise, we introduce an updated a contrario approach that takes into account the spatial coherency of the noise in the probability estimation. Validation is undertaken on a dataset of 25 patients diagnosed with brain tumours and 61 healthy volunteers. We show how the a contrario approach outperforms the massively univariate general linear model usually employed for this type of analysis.

Ultra-small superparamagnetic iron oxide enhancement is associated with higher loss of brain tissue structure in clinically isolated syndrome

BACKGROUND

Macrophages are important components of inflammatory processes in multiple sclerosis, closely linked to axonal loss, and can now be observed in vivo using ultra-small superparamagnetic iron oxide (USPIO). In the present 1-year longitudinal study, we aimed to determine the prevalence and the impact on tissue injury of macrophage infiltration in patients after the first clinical event of multiple sclerosis.

METHODS

Thirty-five patients, 32 years mean age, were imaged in a mean of 66 days after their first event using conventional magnetic resonance imaging, gadolinium (Gd) to probe blood-brain barrier integrity, USPIO to study macrophage infiltration and magnetization transfer ratio (MTR) to assess tissue structure integrity. Statistics were performed using two-group repeated-measures ANOVA. Any patient received treatment at baseline.

RESULTS

At baseline, patients showed 17 USPIO-positive lesions reflecting infiltration of macrophages present from the onset. This infiltration was associated with local higher loss of tissue structure as emphasized by significant lower MTRnorm values (p<0.03) in USPIO(+)/Gd(+) lesions (n=16; MTRnormUSPIO(+)/Gd(+)=0.78 at baseline, MTRnormUSPIO(+)/Gd(+)=0.81 at M12) relative to USPIO(-)/Gd(+) lesions (n=67; MTRnormUSPIO(-)/Gd(+)=0.82 at baseline, MTRnormUSPIO(-)/Gd(+)=0.85 at M12). No interaction in MTR values was observed during the 12 months follow-up (lesion type × time).

CONCLUSION

Infiltration of activated macrophages evidenced by USPIO enhancement, is present at the onset of multiple sclerosis and is associated with higher and persistent local loss of tissue structure. Macrophage infiltration affects more tissue structure while tissue recovery during the following year has a similar pattern for USPIO and Gd-enhanced lesions, leading to relative higher persistent local loss of tissue structure in lesions showing USPIO enhancement at baseline.

Diffusion MRI abnormalities detection with orientation distribution functions: a multiple sclerosis longitudinal study

We propose a new algorithm for the voxelwise analysis of orientation distribution functions between one image and a group of reference images. It relies on a generic framework for the comparison of diffusion probabilities on the sphere, sampled from the underlying models. We demonstrate that this method, combined to dimensionality reduction through a principal component analysis, allows for more robust detection of lesions on simulated data when compared to classical tensor-based analysis. We then demonstrate the efficiency of this pipeline on the longitudinal comparison of multiple sclerosis patients at an early stage of the disease: right after their first clinically isolated syndrome (CIS) and three months later. We demonstrate the predictive value of ODF-based scores for the early detection of lesions that will appear or heal.

Predictive value of imaging markers at multiple sclerosis disease onset based on gadolinium- and USPIO-enhanced MRI and machine learning

OBJECTIVES

A novel characterization of Clinically Isolated Syndrome (CIS) patients according to lesion patterns is proposed. More specifically, patients are classified according to the nature of inflammatory lesions patterns. It is expected that this characterization can infer new prospective figures from the earliest imaging signs of Multiple Sclerosis (MS), since it can provide a classification of different types of lesions across patients.

METHODS

The method is based on a two-tiered classification. Initially, the spatio-temporal lesion patterns are classified. The discovered lesion patterns are then used to characterize groups of patients. The patient groups are validated using statistical measures and by correlations at 24-month follow-up with hypointense lesion loads.

RESULTS

The methodology identified 3 statistically significantly different clusters of lesion patterns showing p-values smaller than 0.01. Moreover, these patterns defined at baseline correlated with chronic hypointense lesion volumes by follow-up with an R(2) score of 0.90.

CONCLUSIONS

The proposed methodology is capable of identifying three major different lesion patterns that are heterogeneously present in patients, allowing a patient classification using only two MRI scans. This finding may lead to more accurate prognosis and thus to more suitable treatments at early stage of MS.