Félix Renard

Hubs of brain functional networks are radically reorganized in comatose patients.

Human brain networks have topological properties in common with many other complex systems, prompting the following question: what aspects of brain network organization are critical for distinctive functional properties of the brain, such as consciousness? To address this question, we used graph theoretical methods to explore brain network topology in resting state functional MRI data acquired from 17 patients with severely impaired consciousness and 20 healthy volunteers. We found that many global network properties were conserved in comatose patients. Specifically, there was no significant abnormality of global efficiency, clustering, small-worldness, modularity, or degree distribution in the patient group. However, in every patient, we found evidence for a radical reorganization of high degree or highly efficient “hub” nodes. Cortical regions that were hubs of healthy brain networks had typically become nonhubs of comatose brain networks and vice versa. These results indicate that global topological properties of complex brain networks may be homeostatically conserved under extremely different clinical conditions and that consciousness likely depends on the anatomical location of hub nodes in human brain networks.

White Matter Atrophy and Cognitive Dysfunctions in Neuromyelitis Optica

Neuromyelitis optica (NMO) is an inflammatory disease of central nervous system characterized by optic neuritis and longitudinally extensive acute transverse myelitis. NMO patients have cognitive dysfunctions but other clinical symptoms of brain origin are rare. In the present study, we aimed to investigate cognitive functions and brain volume in NMO. The study population consisted of 28 patients with NMO and 28 healthy control subjects matched for age, sex and educational level. We applied a French translation of the Brief Repeatable Battery (BRB-N) to the NMO patients. Using SIENAx for global brain volume (Grey Matter, GM; White Matter, WM; and whole brain) and VBM for focal brain volume (GM and WM), NMO patients and controls were compared. Voxel-level correlations between diminished brain concentration and cognitive performance for each tests were performed. Focal and global brain volume of NMO patients with and without cognitive impairment were also compared. Fifteen NMO patients (54%) had cognitive impairment with memory, executive function, attention and speed of information processing deficits. Global and focal brain atrophy of WM but not Grey Matter (GM) was found in the NMO patients group. The focal WM atrophy included the optic chiasm, pons, cerebellum, the corpus callosum and parts of the frontal, temporal and parietal lobes, including superior longitudinal fascicle. Visual memory, verbal memory, speed of information processing, short-term memory and executive functions were correlated to focal WM volumes. The comparison of patients with, to patients without cognitive impairment showed a clear decrease of global and focal WM, including brainstem, corticospinal tracts, corpus callosum but also superior and inferior longitudinal fascicles. Cognitive impairment in NMO patients is correlated to the decreased of global and focal WM volume of the brain. Further studies are needed to better understand the precise origin of cognitive impairment in NMO patients, particularly in the WM.

Use of Advanced Magnetic Resonance Imaging Techniques in Neuromyelitis Optica Spectrum Disorder.

Brain parenchymal lesions are frequently observed on conventional magnetic resonance imaging (MRI) scans of patients with neuromyelitis optica (NMO) spectrum disorder, but the specific morphological and temporal patterns distinguishing them unequivocally from lesions caused by other disorders have not been identified. This literature review summarizes the literature on advanced quantitative imaging measures reported for patients with NMO spectrum disorder, including proton MR spectroscopy, diffusion tensor imaging, magnetization transfer imaging, quantitative MR volumetry, and ultrahigh-field strength MRI. It was undertaken to consider the advanced MRI techniques used for patients with NMO by different specialists in the field. Although quantitative measures such as proton MR spectroscopy or magnetization transfer imaging have not reproducibly revealed diffuse brain injury, preliminary data from diffusion-weighted imaging and brain tissue volumetry indicate greater white matter than gray matter degradation. These findings could be confirmed by ultrahigh-field MRI. The use of nonconventional MRI techniques may further our understanding of the pathogenic processes in NMO spectrum disorders and may help us identify the distinct radiographic features corresponding to specific phenotypic manifestations of this disease.

MRI-based volumetry correlates of autobiographical memory in Alzheimer's disease.

The aim of the present volumetric study was to explore the neuro-anatomical correlates of autobiographical memory loss in Alzheimers patients and healthy elderly, in terms of the delay of retention, with a particular interest in the medial temporal lobe structures. Fifteen patients in early stages of the disease and 11 matched control subjects were included in the study. To assess autobiographical memory and the effect of the retention delay, a modified version of the Crovitz test was used according to five periods of life. Autobiographical memory deficits were correlated to local atrophy via structural MRI using Voxel Based Morphometry. We used a ‘lateralized index’ to compare the relative contribution of hippocampal sub-regions (anterior vs posterior, left vs right) according to the different periods of life. Our results confirm the involvement of the hippocampus proper in autobiographical memory retrieval for both recent and very remote encoding periods, with larger aspect for the very remote period on the left side. Contrary to the prominent left-sided involvement for the young adulthood period, the implication of the right hippocampus prevails for the more recent periods and decreases with the remotness of the memories, which might be associated with the visuo-spatial processing of the memories. Finally, we suggest the existence of a rostrocaudal gradient depending on the retention duration, with left anterior aspects specifically related to retrieval deficits of remote memories from the young adulthood period, whereas posterior aspects would result of simultaneous encoding and/or consolidation and retrieval deficit of more recent memories.

Image analysis for detection of coronary artery soft plaques in MDCT images

In this paper we aim to develop a computationally- efficient image-segmentation procedure for detection and quantification of soft plaques in coronary arteries from multidetector CT images. The proposed method consists of three steps: extraction of the arterial lumen centerline, segmentation of the lumen and arterial wall separately with locally adaptive region growing, and detection of soft plaques based on effective cross- section areas of the lumen and of the wall. Preliminary results using clinical acquisitions are presented to demonstrate the effectiveness of the proposed method.

Diffusion tensor imaging in human global cerebral anoxia: Correlation with histology in a case with autopsy

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Diffusion tensor imaging in human global cerebral anoxia: correlation with histology in a case with autopsy. Stéphane Kremer, Felix Renard, Vincent Noblet, Roxana Mialin, Renée Wolfram-Gabel, Chantal Delon-Martin, Sophie Achard, Maleka Schenck, Michel Mohr, Jean-Louis Dietemann, et al.

Statistical Detection of Longitudinal Changes between Apparent Diffusion Coefficient Images: Application to Multiple Sclerosis

The automatic analysis of longitudinal changes between Diffusion Tensor Imaging (DTI) acquisitions is a promising tool for monitoring disease evolution. However, few works address this issue and existing methods are generally limited to the detection of changes between scalar images characterizing diffusion properties, such as Fractional Anisotropy or Mean Diffusivity, while richer information can be exploited from the whole set of Apparent Diffusion Coefficient (ADC) images that can be derived from a DTI acquisition. In this paper, we present a general framework for detecting changes between two sets of ADC images and we investigate the performance of four statistical tests. Results are presented on both simulated and real data in the context of the follow-up of multiple sclerosis lesion evolution.

Coronary artery extraction and analysis for detection of soft plaques in MDCT images

In this paper we aim to develop a computationally-efficient image-segmentation procedure for detection and quantification of soft plaques in coronary arteries from multidetector CT images. The proposed method consists of three steps: extraction of the arterial lumen centerline, segmentation of the lumen and arterial wall based on a locally-adaptive mixture-model using the expectation- maximization algorithm, and detection of soft plaques based on effective cross-sectional areas of the lumen and of the wall. Preliminary results using clinical acquisitions are presented to demonstrate the effectiveness of the proposed method.

Parietal operculum and motor cortex activities predict motor recovery in moderate to severe stroke

While motor recovery following mild stroke has been extensively studied with neuroimaging, mechanisms of recovery after moderate to severe strokes of the types that are often the focus for novel restorative therapies remain obscure. We used fMRI to: 1) characterize reorganization occurring after moderate to severe subacute stroke, 2) identify brain regions associated with motor recovery and 3) to test whether brain activity associated with passive movement measured in the subacute period could predict motor outcome six months later. Because many patients with large strokes involving sensorimotor regions cannot engage in voluntary movement, we used passive flexion-extension of the paretic wrist to compare 21 patients with subacute ischemic stroke to 24 healthy controls one month after stroke. Clinical motor outcome was assessed with Fugl-Meyer motor scores (motor-FMS) six months later. Multiple regression, with predictors including baseline (one-month) motor-FMS and sensorimotor network regional activity (ROI) measures, was used to determine optimal variable selection for motor outcome prediction. Sensorimotor network ROIs were derived from a meta-analysis of arm voluntary movement tasks. Bootstrapping with 1000 replications was used for internal model validation. During passive movement, both control and patient groups exhibited activity increases in multiple bilateral sensorimotor network regions, including the primary motor (MI), premotor and supplementary motor areas (SMA), cerebellar cortex, putamen, thalamus, insula, Brodmann area (BA) 44 and parietal operculum (OP1-OP4). Compared to controls, patients showed: 1) lower task-related activity in ipsilesional MI, SMA and contralesional cerebellum (lobules V-VI) and 2) higher activity in contralesional MI, superior temporal gyrus and OP1-OP4. Using multiple regression, we found that the combination of baseline motor-FMS, activity in ipsilesional MI (BA4a), putamen and ipsilesional OP1 predicted motor outcome measured 6 months later (adjusted-R2 = 0.85; bootstrap p < 0.001). Baseline motor-FMS alone predicted only 54% of the variance. When baseline motor-FMS was removed, the combination of increased activity in ipsilesional MI-BA4a, ipsilesional thalamus, contralesional mid-cingulum, contralesional OP4 and decreased activity in ipsilesional OP1, predicted better motor outcome (djusted-R2 = 0.96; bootstrap p < 0.001). In subacute stroke, fMRI brain activity related to passive movement measured in a sensorimotor network defined by activity during voluntary movement predicted motor recovery better than baseline motor-FMS alone. Furthermore, fMRI sensorimotor network activity measures considered alone allowed excellent clinical recovery prediction and may provide reliable biomarkers for assessing new therapies in clinical trial contexts. Our findings suggest that neural reorganization related to motor recovery from moderate to severe stroke results from balanced changes in ipsilesional MI (BA4a) and a set of phylogenetically more archaic sensorimotor regions in the ventral sensorimotor trend, in which OP1 and OP4 processes may complement the ipsilesional dorsal motor cortex in achieving compensatory sensorimotor recovery.

Change detection in diffusion MRI using multivariate statistical testing on tensors

This paper presents a longitudinal change detection framework for detecting relevant modifications in diffusion MRI, with application to Multiple Sclerosis (MS). The proposed method is based on multivariate statistical testings which were initially introduced for tensor population comparison. We use these methods in the context of longitudinal change detection by considering several strategies to build sets of tensors characterizing the variability of each voxel. These testing tools have been considered either for the comparison of tensor eigenvalues or eigenvectors, thus enabling to differentiate orientation and diffusivity changes. Results on simulated MS lesion evolutions and on real data are presented. Interestingly, experiments on an MS patient highlight the ability of the proposed approach to detect changes in non evolving lesions (according to conventional MRI) and around lesions (in the normal appearing white matter), which might open promising perspectives for the follow-up of the MS pathology.