Browsing Multiple Subjects When the Atlas Adaptation Cannot Be Achieved via a Warping Strategy.

Brain mapping studies often need to identify brain structures or functional circuits into a set of individual brains. To this end, multiple atlases have been published to represent such structures based on different modalities, subject sets, and techniques. The mainstream approach to exploit these atlases consists in spatially deforming each individual data onto a given atlas using dense deformation fields, which supposes the existence of a continuous mapping between atlases and individuals. However, this continuity is not always verified, and this "iconic" approach has limits. We present in this study an alternative, complementary, "structural" approach, which consists in extracting structures from the individual data, and comparing them without deformation. A "structural atlas" is thus a collection of annotated individual data with a common structure nomenclature. It may be used to characterize structure shape variability across individuals or species, or to train machine learning systems. This study exhibits Anatomist, a powerful structural 3D visualization software dedicated to building, exploring, and editing structural atlases involving a large number of subjects. It has been developed primarily to decipher the cortical folding variability; cortical sulci vary enormously in both size and shape, and some may be missing or have various topologies, which makes iconic approaches inefficient to study them. We, therefore, had to build structural atlases for cortical sulci, and use them to train sulci identification algorithms. Anatomist can display multiple subject data in multiple views, supports all kinds of neuroimaging data, including compound structural object graphs, handles arbitrary coordinate transformation chains between data, and has multiple display features. It is designed as a programming library in both C++ and Python languages, and may be extended or used to build dedicated custom applications. Its generic design makes all the display and structural aspects used to explore the variability of the cortical folding pattern work in other applications, for instance, to browse axonal fiber bundles, deep nuclei, functional activations, or other kinds of cortical parcellations. Multimodal, multi-individual, or inter-species display is supported, and adaptations to large scale screen walls have been developed. These very original features make it a unique viewer for structural atlas browsing.

Neocortical morphometry in Huntington's disease: Indication of the coexistence of abnormal neurodevelopmental and neurodegenerative processes.

Huntington's disease (HD) is an inherited, autosomal dominant disorder that is characteristically thought of as a degenerative disorder. Despite cellular and molecular grounds suggesting HD could also impact normal development, there has been scarce systems-level data obtained from in vivo human studies supporting this hypothesis. Sulcus-specific morphometry analysis may help disentangle the contribution of coexisting neurodegenerative and neurodevelopmental processes, but such an approach has never been used in HD. Here, we investigated cortical sulcal depth, related to degenerative process, as well as cortical sulcal length, related to developmental process, in early-stage HD and age-matched healthy controls. This morphometric analysis revealed significant differences in the HD participants compared with the healthy controls bilaterally in the central and intra-parietal sulcus, but also in the left intermediate frontal sulcus and calcarine fissure. As the primary visual cortex is not connected to the striatum, the latter result adds to the increasing in vivo evidence for primary cortical degeneration in HD. Those sulcal measures that differed between HD and healthy populations were mainly atrophy-related, showing shallower sulci in HD. Conversely, the sulcal morphometry also revealed a crucial difference in the imprint of the Sylvian fissure that could not be related to loss of grey matter volume: an absence of asymmetry in the length of this fissure in HD. Strong asymmetry in that cortical region is typically observed in healthy development. As the formation of the Sylvian fissure appears early in utero, and marked asymmetry is specifically found in this area of the neocortex in newborns, this novel finding likely indicates the foetal timing of a disease-specific, genetic interplay with neurodevelopment.

Prospective cohort study of early biosignatures of response to lithium in bipolar-I-disorders: overview of the H2020-funded R-LiNK initiative.

BACKGROUND: Lithium is recommended as a first line treatment for bipolar disorders. However, only 30% of patients show an optimal outcome and variability in lithium response and tolerability is poorly understood. It remains difficult for clinicians to reliably predict which patients will benefit without recourse to a lengthy treatment trial. Greater precision in the early identification of individuals who are likely to respond to lithium is a significant unmet clinical need. STRUCTURE: The H2020-funded Response to Lithium Network (R-LiNK; http://www.r-link.eu.com/ ) will undertake a prospective cohort study of over 300 individuals with bipolar-I-disorder who have agreed to commence a trial of lithium treatment following a recommendation by their treating clinician. The study aims to examine the early prediction of lithium response, non-response and tolerability by combining systematic clinical syndrome subtyping with examination of multi-modal biomarkers (or biosignatures), including omics, neuroimaging, and actigraphy, etc. Individuals will be followed up for 24 months and an independent panel will assess and classify each participants' response to lithium according to predefined criteria that consider evidence of relapse, recurrence, remission, changes in illness activity or treatment failure (e.g. stopping lithium; new prescriptions of other mood stabilizers) and exposure to lithium. Novel elements of this study include the recruitment of a large, multinational, clinically representative sample specifically for the purpose of studying candidate biomarkers and biosignatures; the application of lithium-7 magnetic resonance imaging to explore the distribution of lithium in the brain; development of a digital phenotype (using actigraphy and ecological momentary assessment) to monitor daily variability in symptoms; and economic modelling of the cost-effectiveness of introducing biomarker tests for the customisation of lithium treatment into clinical practice. Also, study participants with sub-optimal medication adherence will be offered brief interventions (which can be delivered via a clinician or smartphone app) to enhance treatment engagement and to minimize confounding of lithium non-response with non-adherence. CONCLUSIONS: The paper outlines the rationale, design and methodology of the first study being undertaken by the newly established R-LiNK collaboration and describes how the project may help to refine the clinical response phenotype and could translate into the personalization of lithium treatment.

IntrAnat Electrodes: A Free Database and Visualization Software for Intracranial Electroencephalographic Data Processed for Case and Group Studies.

In some cases of pharmaco-resistant and focal epilepsies, intracranial recordings performed epidurally (electrocorticography, ECoG) and/or in depth (stereoelectroencephalography, SEEG) can be required to locate the seizure onset zone and the eloquent cortex before surgical resection. In SEEG, each electrode contact records brain's electrical activity in a spherical volume of 3 mm diameter approximately. The spatial coverage is around 1% of the brain and differs between patients because the implantation of electrodes is tailored for each case. Group studies thus need a large number of patients to reach a large spatial sampling, which can be achieved more easily using a multicentric approach such as implemented in our F-TRACT project (f-tract.eu). To facilitate group studies, we developed a software-IntrAnat Electrodes-that allows to perform virtual electrode implantation in patients' neuroanatomy and to overlay results of epileptic and functional mapping, as well as resection masks from the surgery. IntrAnat Electrodes is based on a patient database providing multiple search criteria to highlight various group features. For each patient, the anatomical processing is based on a series of software publicly available. Imaging modalities (Positron Emission Tomography (PET), anatomical MRI pre-implantation, post-implantation and post-resection, functional MRI, diffusion MRI, Computed Tomography (CT) with electrodes) are coregistered. The 3D T1 pre-implantation MRI gray/white matter is segmented and spatially normalized to obtain a series of cortical parcels using different neuroanatomical atlases. On post-implantation images, the user can position 3D models of electrodes defined by their geometry. Each electrode contact is then labeled according to its position in the anatomical atlases, to the class of tissue (gray or white matter, cerebro-spinal fluid) and to its presence inside or outside the resection mask. Users can add more functionally informed labels on contact, such as clinical responses after electrical stimulation, cortico-cortical evoked potentials, gamma band activity during cognitive tasks or epileptogenicity. IntrAnat Electrodes software thus provides a means to visualize multimodal data. The contact labels allow to search for patients in the database according to multiple criteria representing almost all available data, which is to our knowledge unique in current SEEG software. IntrAnat Electrodes will be available in the forthcoming release of BrainVisa software and tutorials can be found on the F-TRACT webpage.

CATI: A Large Distributed Infrastructure for the Neuroimaging of Cohorts.

This paper provides an overview of CATI, a platform dedicated to multicenter neuroimaging. Initiated by the French Alzheimer's plan (2008-2012), CATI is a research project called on to provide service to other projects like an industrial partner. Its core mission is to support the neuroimaging of large populations, providing concrete solutions to the increasing complexity involved in such projects by bringing together a service infrastructure, the know-how of its expert academic teams and a large-scale, harmonized network of imaging facilities. CATI aims to make data sharing across studies easier and promotes sharing as much as possible. In the last 4 years, CATI has assisted the clinical community by taking charge of 35 projects so far and has emerged as a recognized actor at the national and international levels.

Inference of a HARDI fiber bundle atlas using a two-level clustering strategy.

This paper presents a method inferring a model of the brain white matter organisation from HARDI tractography results computed for a group of subjects. This model is made up of a set of generic fiber bundles that can be detected in most of the population. Our approach is based on a two-level clustering strategy. The first level is a multiresolution intra-subject clustering of the million tracts that are computed for each brain. This analysis reduces the complexity of the data to a few thousands fiber bundles for each subject. The second level is an intersubject clustering over fiber bundle centroids from all the subjects using a pairwise distance computed after spatial normalization. The resulting model includes the large bundles of anatomical literature and about 20 U-fiber bundles in each hemisphere.

In vivo evidence for the selective subcortical degeneration in Huntington's disease.

Although Huntington's disease is largely considered to be a subcortical disease, there is no clear consensus on whether all deep grey matter loss is a direct downstream consequence of the massive degeneration of the medium-size spiny neurons in the striatum. Our aim was to characterise in vivo such preferential degeneration by analysing various distinct diffusion imaging measures including mean diffusivity, anisotropy, fibre orientation (using the information of the principal diffusion direction) and white matter tractography. All results converged to demonstrate the selective degeneration of connections in subcortical grey and white matter, degeneration which was likely to originate with the death of the striatal medium-size spiny neurons. Indeed, we found a significant increase of MD and FA in all the subcortical grey matter structures involved in the cortico-striato-thalamo-cortical loops. The atypical striatal and pallidal increase of FA was concurrent to a decrease of the dispersion of the fibre orientation, unambiguously characterising a preferential loss of connections along specific radiating directions from these structures while some others are comparatively spared. Analysis of striatal and pallidal white matter tracts revealed that striato-pallidal projections were the most affected. The ability of DTI to uncover the impact of such neurodegenerative disease on some specific neuronal/axonal populations is a further step towards the future definition of a surrogate marker of this disease. Beyond Huntington's disease, we prove here that diffusion imaging technique, associated to adequate methodological analyses, can provide insight into any neurodegenerative disorder for which some neuronal populations or connections are selectively targeted over others.

Diffusion tensor tractography in mesencephalic bundles: relation to mental flexibility in detoxified alcohol-dependent subjects.

Components of the corticocerebellar circuit and the midbrain individually play a central role in addictive processes and have been associated with altered volumes and impairment of cognitive flexibility in alcohol-dependent subjects. The microstructure of white matter bundles composing the corticocerebellar network and passing through the midbrain was studied using diffusion tensor imaging in a group of detoxified alcohol-dependent men (n=20) and a group of healthy men (n=24). The relationship between properties of these white matter bundles and cognitive flexibility performance was investigated in alcohol-dependent subjects. Bundles connecting two regions of interest were analyzed using a fiber-tracking quantitative approach, which provided estimates of the fractional anisotropy and the apparent diffusion coefficient, as well as the number of tracked fibers normalized by the volume of regions of interest. Within the bundles running between the midbrain and pons, a mean of 18% fewer fibers per unit volume were tracked in alcohol-dependent men than in healthy controls. In addition, the normalized number of these fibers correlated with the performance in the Trail-Making Test part-B. Even though the alcohol-dependent subjects were detoxified and apparently neurologically intact, their earlier excessive use of alcohol seems to be associated with altered neural microstructure of mesencephalic white matter bundles, which may contribute to their cognitive flexibility impairment.

A triangulation-based magnetic resonance image-guided method for transcranial magnetic stimulation coil positioning.

Transcranial magnetic stimulation (TMS) is currently used for cognitive studies and investigated as a treatment for psychiatric disorders. Because of the cortex variability, the coil positioning stage is difficult and should be improved by using individual neuroimaging data. Sophisticated and expensive neuronavigation systems have been developed to guide the coil to selected regions on the patient's magnetic resonance images (MRI). Our objective was to develop a triangulation-based MRI-guided method to position manually the TMS coil over the subject's head, using a cortical target derived from individual MR data. We evaluated both the spatial accuracy and the reproducibility of the method using functional MR activations of two different targets in the motor and parietal cortices. The accuracy of the MRI-guided method, assessed from the Euclidean distance (D(m)) between the thumb motor target and the coil position eliciting reproducible thumb motor-evoked potentials with TMS, was D(m) = 10 +/- 3 mm. The reproducibility of the method, evaluated across two different operators, was D(m) = 6.7 +/- 1.4 mm for the repositioning in the motor cortex and D(m) = 6.0 +/- 3.2 mm in the parietal cortex. This novel method could be used clinically to assist positioning of the TMS coil.

Mean q-ball strings obtained by constrained procrustes analysis with point sliding.

The idea underpinning the work we present herein is to design robust and objective tools for brain white matter (WM) morphometry. We focus on WM tracts, and propose to represent them by their mean lines, to which we associate the attributes derived from high-angular resolution diffusion imaging (HARDI). The definition of the tract mean line derives directly from the geometry of the tract fibres. We determine the fibre point correspondences and impact factors of individual fibres, upon which we estimate average HARDI models along the tract mean lines. This way we obtain a compact tract representation that exploits all the available information, and is at the same time free of the outlier influence and undesired tract edge effects.

Connectivity-based parcellation of the cortical mantle using q-ball diffusion imaging.

This paper exploits the idea that each individual brain region has a specific connection profile to create parcellations of the cortical mantle using MR diffusion imaging. The parcellation is performed in two steps. First, the cortical mantle is split at a macroscopic level into 36 large gyri using a sulcus recognition system. Then, for each voxel of the cortex, a connection profile is computed using a probabilistic tractography framework. The tractography is performed from q fields using regularized particle trajectories. Fiber ODF are inferred from the q-balls using a sharpening process focusing the weight around the q-ball local maxima. A sophisticated mask of propagation computed from a T1-weighted image perfectly aligned with the diffusion data prevents the particles from crossing the cortical folds. During propagation, the particles father child particles in order to improve the sampling of the long fascicles. For each voxel, intersection of the particle trajectories with the gyri lead to a connectivity profile made up of only 36 connection strengths. These profiles are clustered on a gyrus by gyrus basis using a K-means approach including spatial regularization. The reproducibility of the results is studied for three subjects using spatial normalization.

Microstructural correlates of infant functional development: example of the visual pathways.

The development of cognitive functions during childhood relies on several neuroanatomical maturation processes. Among these processes is myelination of the white matter pathways, which speeds up electrical conduction. Quantitative indices of such structural processes can be obtained in vivo with diffusion tensor imaging (DTI), but their physiological significance remains uncertain. Here, we investigated the microstructural correlates of early functional development by combining DTI and visual event-related potentials (VEPs) in 15 one- to 4-month-old healthy infants. Interindividual variations of the apparent conduction speed, computed from the latency of the first positive VEP wave (P1), were significantly correlated with the infants' age and DTI indices measured in the optic radiations. This demonstrates that fractional anisotropy and transverse diffusivity are structural markers of functionally efficient myelination. Moreover, these indices computed along the optic radiations showed an early wave of maturation in the anterior region, with the posterior region catching up later in development, which suggests two asynchronous fronts of myelination in both the geniculocortical and corticogeniculate fibers. Thus, in addition to microstructural information, DTI provides noninvasive exquisite information on the functional development of the brain in human infants.

Asynchrony of the early maturation of white matter bundles in healthy infants: quantitative landmarks revealed noninvasively by diffusion tensor imaging.

Normal cognitive development in infants follows a well-known temporal sequence, which is assumed to be correlated with the structural maturation of underlying functional networks. Postmortem studies and, more recently, structural MR imaging studies have described qualitatively the heterogeneous spatiotemporal progression of white matter myelination. However, in vivo quantification of the maturation phases of fiber bundles is still lacking. We used noninvasive diffusion tensor MR imaging and tractography in twenty-three 1-4-month-old healthy infants to quantify the early maturation of the main cerebral fascicles. A specific maturation model, based on the respective roles of different maturational processes on the diffusion phenomena, was designed to highlight asynchronous maturation across bundles by evaluating the time-course of mean diffusivity and anisotropy changes over the considered developmental period. Using an original approach, a progression of maturation in four relative stages was determined in each tract by estimating the maturation state and speed, from the diffusion indices over the infants group compared with an adults group on one hand, and in each tract compared with the average over bundles on the other hand. Results were coherent with, and extended previous findings in 8 of 11 bundles, showing the anterior limb of the internal capsule and cingulum as the most immature, followed by the optic radiations, arcuate and inferior longitudinal fascicles, then the spinothalamic tract and fornix, and finally the corticospinal tract as the most mature bundle. Thus, this approach provides new quantitative landmarks for further noninvasive research on brain-behavior relationships during normal and abnormal development.

Validation of a standardized normalization template for statistical parametric mapping analysis of 123I-FP-CIT images.

UNLABELLED: (123)I-FP-CIT ((123)I-N-omega-fluoropropyl-2beta-carbomethoxy-3beta-(4-iodophenyl)nortropane) is a SPECT dopamine transporter (DAT) tracer that probes dopaminergic cell loss in Parkinson's disease (PD). Quantification of (123)I-FP-CIT images is performed at equilibrium using a ratio (BR) of specific (striatal) to nonspecific (occipital) uptake with values obtained from regions of interest drawn manually over these structures. Statistical parametric mapping (SPM) is a fully automated voxel-based statistical approach that has great potential in the context of DAT imaging. However, the accuracy of the spatial normalization provided by SPM has not been validated for (123)I-FP-CIT images. Our first aim was to create an (123)I-FP-CIT template that does not require the acquisition of patient-specific MRI and to validate the spatial normalization procedure. Next, we hypothesized that this customized template could be used by different SPECT centers without affecting the outcomes of imaging analyses. METHODS: The spatial normalization to the customized template created with SPM (template A1) was validated using (123)I-FP-CIT images obtained from 6 subjects with essential tremor (ET) with normal DAT status and 6 PD patients. Variability in BR values due to the normalization was evaluated using striatal volume of interest (VOI). To determine whether different SPECT centers could use a unique (123)I-FP-CIT template, we generated 3 other (123)I-FP-CIT templates using different subjects and image-processing schemes. The interchangeability of these templates was assessed using (a) putamen BR values analyzed with the intraclass correlation coefficient (ICC) and the Bland-Altman graphical analysis, and (b) SPM analysis comparing the results of group comparisons-that is, ET versus PD, obtained after normalization to each of the 4 templates. RESULTS: There was no significant difference between pre- and post-normalization striatal BR values in our study. The mean variability calculated with putamen VOI values after normalization to each template was <10%, with the lowest ICC of 98%. Intergroup analyses performed with VOI and SPM approaches provided similar results independently of the template used. CONCLUSION: SPM normalization was accurate even in subjects with low striatal (123)I-FP-CIT uptake, making it a promising approach for automatic analysis of (123)I-FP-CIT images using a single customized template at different centers.

Classification based on cortical folding patterns.

We describe here a classification system based on automatically identified cortical sulci. Multivariate recognition methods are required for the detection of complex brain patterns with a spatial distribution. However, such methods may face the well-known issue of the curse of dimensionality-the risk of overfitting the training dataset in high-dimensional space. We overcame this problem, using a classifier pipeline with one- or two-stage of descriptor selection based on machine-learning methods, followed by a support vector machine classifier or linear discriminant analysis. We compared alternative designs of the pipeline on two different datasets built from the same database corresponding to 151 brains. The first dataset dealt with cortex asymmetry and the second dealt with the effect of the subject's sex. Our system successfully (98%) distinguished between the left and right hemispheres on the basis of sulcal shape (size, depth, etc.). The sex of the subject could be determined with a success rate of 85%. These results highlight the attractiveness of multivariate recognition models combined with appropriate descriptor selection. The sulci selected by the pipeline are consistent with previous whole-brain studies on sex effects and hemispheric asymmetries.

Age-related morphology trends of cortical sulci.

The age-related trends of the width and the depth of major cortical sulci were studied in normal adults. Ninety healthy subjects (47 males, 43 females) age 20-82 years were evaluated. Measurements of average sulcal width and depth in 14 prominent sulcal structures per hemisphere were performed with high-resolution anatomical MRI. The average sulcal width increased at a rate of about 0.7 mm/decade, while the average sulcal depth decreased at a rate of about 0.4 mm/decade. Sulcal age-related trends were found to be highly influenced by gender in the superior temporal, collateral, and cingulate sulci (P < 0.05), with males showing more pronounced age-related change in sulcal width than females. Sulcal structures located in multimodal cortical areas showed more profound age-related changes than sulcal structures in unimodal cortical areas (P < 0.05).

Diffusion tensor imaging of the human optic nerve using a non-CPMG fast spin echo sequence.

PURPOSE: To investigate the diffusion tensor properties of the human optic nerve in vivo using a non-Carr-Purcell-Meiboom-Gill (CPMG) fast spin echo (FSE) sequence. MATERIALS AND METHODS: This non-CPMG FSE sequence, which is based on a quadratic phase modulation of the refocusing pulses, allows diffusion measures to be acquired with full signal and without artifacts from geometric distortions due to magnetic field inhomogeneities, which are among the main problems encountered in the orbital area. RESULTS: Good-quality images were obtained at a resolution of 0.94 x 0.94 x 3 mm. The mean diffusivity (MD) and fractional anisotropy (FA) were respectively 1.1 +/- 0.2 x 10(-3) mm(2)/second and 0.49 +/- 0.06, reflecting the optic nerve anisotropy. CONCLUSION: This non-CPMG-FSE sequence provides reliable diffusion-weighted images of the human optic nerve. This approach could potentially improve the diagnosis and management of optic nerve diseases or compression, such as optic neuritis, orbit tumors, and muscle hypertrophy.