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Thomas TOURDIAS




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Cursus:
MD: Radiology, Bordeaux (2008)
PhD: Neurosciences, Bordeaux (2011)
Post doc: Stanford University, CA, USA (2013)
Professeur des Universit├ęs - Praticien Hospitalier; PU PH (2016)






62 publication(s) since Décembre 2006:


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27/11/2018 | Mult Scler   IF 5.3
Longitudinal study of functional brain network reorganization in clinically isolated syndrome.
Koubiyr I, Deloire M, Besson P, Coupe P, Dulau C, Pelletier J, Tourdias T, Audoin B, Brochet B, Ranjeva JP, Ruet A

Abstract:
BACKGROUND:: There is a lack of longitudinal studies exploring the topological organization of functional brain networks at the early stages of multiple sclerosis (MS). OBJECTIVE:: This study aims to assess potential brain functional reorganization at rest in patients with CIS (PwCIS) after 1 year of evolution and to characterize the dynamics of functional brain networks at the early stage of the disease. METHODS:: We prospectively included 41 PwCIS and 19 matched healthy controls (HCs). They were scanned at baseline and after 1 year. Using graph theory, topological metrics were calculated for each region. Hub disruption index was computed for each metric. RESULTS:: Hub disruption indexes of degree and betweenness centrality were negative at baseline in patients ( p < 0.05), suggesting brain reorganization. After 1 year, hub disruption indexes for degree and betweenness centrality were still negative ( p < 0.00001), but such reorganization appeared more pronounced than at baseline. Different brain regions were driving these alterations. No global efficiency differences were observed between PwCIS and HCs either at baseline or at 1 year. CONCLUSION:: Dynamic changes in functional brain networks appear at the early stages of MS and are associated with the maintenance of normal global efficiency in the brain, suggesting a compensatory effect.




12/09/2018 | Sci Rep   IF 4.1
Objective Evaluation of Multiple Sclerosis Lesion Segmentation using a Data Management and Processing Infrastructure.
Commowick O, Istace A, Kain M, Laurent B, Leray F, Simon M, Pop SC, Girard P, Ameli R, Ferre JC, Kerbrat A, Tourdias T, Cervenansky F, Glatard T, Beaumont J, Doyle S, Forbes F, Knight J, Khademi A, Mahbod A, Wang C, McKinley R, Wagner F, Muschelli J, Sweeney E, Roura E, Llado X, Santos MM, Santos WP, Silva-Filho AG, Tomas-Fernandez X, Urien H, Bloch I, Valverde S, Cabezas M, Vera-Olmos FJ, Malpica N, Guttmann C, Vukusic S, Edan G, Dojat M, Styner M, Warfield SK, Cotton F, Barillot C

Abstract:
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.




27/02/2018 | Lancet Neurol   IF 27.1
Use of brain diffusion tensor imaging for the prediction of long-term neurological outcomes in patients after cardiac arrest: a multicentre, international, prospective, observational, cohort study.
Velly L, Perlbarg V, Boulier T, Adam N, Delphine S, Luyt CE, Battisti V, Torkomian G, Arbelot C, Chabanne R, Jean B, Di Perri C, Laureys S, Citerio G, Vargiolu A, Rohaut B, Bruder N, Girard N, Silva S, Cottenceau V, Tourdias T, Coulon O, Riou B, Naccache L, Gupta R, Benali H, Galanaud D, Puybasset L

Abstract:
BACKGROUND: Prediction of neurological outcome after cardiac arrest is a major challenge. The aim of this study was to assess whether quantitative whole-brain white matter fractional anisotropy (WWM-FA) measured by diffusion tensor imaging between day 7 and day 28 after cardiac arrest can predict long-term neurological outcome. METHODS: This prospective, observational, cohort study (part of the MRI-COMA study) was done in 14 centres in France, Italy, and Belgium. We enrolled patients aged 18 years or older who had been unconscious for at least 7 days after cardiac arrest into the derivation cohort. The following year, we recruited the validation cohort on the same basis. We also recruited a minimum of five healthy volunteers at each centre for the normalisation procedure. WWM-FA values were compared with standard criteria for unfavourable outcome, conventional MRI sequences (fluid-attenuated inversion recovery and diffusion-weighted imaging), and proton magnetic resonance spectroscopy. The primary outcome was the best achieved Glasgow-Pittsburgh Cerebral Performance Categories (CPC) at 6 months, dichotomised as favourable (CPC 1-2) and unfavourable outcome (CPC 3-5). Prognostication performance was assessed by the area under the receiver operating characteristic (ROC) curves and compared between groups. This study was registered with ClinicalTrials.gov, number NCT00577954. FINDINGS: Between Oct 1, 2006, and June 30, 2014, 185 patients were enrolled in the derivation cohort, of whom 150 had an interpretable multimodal MRI and were included in the analysis. 33 (22%) patients had a favourable neurological outcome at 6 months. Prognostic accuracy, as quantified by the area under the ROC curve, was significantly higher with the normalised WWM-FA value (area under the ROC curve 0.95, 95% CI 0.91-0.98) than with the standard criteria for unfavourable outcome or other MRI sequences. In a subsequent validation cohort of 50 patients (enrolled between April 1, 2015, and March 31, 2016), a normalised WWM-FA value lower than 0.91, set from the derivation cohort, had a negative predictive value of 71.4% (95% CI 41.9-91.6) and a positive predictive value of 100% (90.0-100), with 89.7% sensitivity (75.8-97.1) and 100% specificity (69.1-100) for the prediction of unfavourable outcome. INTERPRETATION: In patients who are unconscious 7 days after cardiac arrest, the normalised WWM-FA value, measured by diffusion tensor imaging, could be used to accurately predict neurological outcome at 6 months. This evidence requires confirmation from future large-scale trials with a strict protocol of withdrawal or limitation-of-care decisions and time window for MRI. FUNDING: French Ministry of Health, French National Agency for Research, Italian Ministry of Health, and Regione Lombardia.




15/02/2018 | J Neurol Sci   IF 2.4
Preliminary evidence of the cerebellar role on cognitive performances in clinically isolated syndrome.
Moroso A, Ruet A, Lamargue-Hamel D, Munsch F, Deloire M, Ouallet JC, Cubizolle S, Charre-Morin J, Saubusse A, Tourdias T, Dousset V, Brochet B

Abstract:
BACKGROUND: Cerebellar and cognitive dysfunction can occur early in clinically isolated syndrome (CIS). Eye tracking is a reliable tool for the evaluation of both subtle cerebellar symptoms and cognitive impairment. OBJECTIVES: To investigate the early cognitive profile using neuropsychological and ocular motor (OM) testing in CIS with and without cerebellar dysfunction with OM testing compared to healthy subjects (HS). METHODS: Twenty-eight patients and 12 HC underwent OM and neuropsychological testing. Cerebellar impairment was defined by the registration of saccadic intrusions and/or at least 10% of dysmetria during ocular motor recording. Visually guided saccade (VGS), memory-guided saccade (MGS) and antisaccade (AS) paradigms were compared to neuropsychological assessments. RESULTS: The group of patients with cerebellar dysfunction (n=16) performed worse on MGS latencies and error rates, and had worse working memory, executive function and information processing speed (IPS) z scores than patients without cerebellar dysfunction. IPS was correlated with the AS error rate in all patients and with the VGS error rate and the MGS final eye position ratio in cerebellar patients. CONCLUSION: Eye tracking is a sensitive tool to assess cognitive and cerebellar dysfunctions in CIS. In CIS patients, cerebellar impairment is associated with working memory, executive functions and IPS slowness.




02/2018 | Muscle Nerve   IF 2.5
Chronic inflammatory demyelinating polyradiculoneuropathy-causing myelopathy.
Mathis S, Duval F, Sole G, Tourdias T, Le Masson G

Abstract:





30/01/2018 | Neuroimage   IF 5.4
Deciphering the microstructure of hippocampal subfields with in vivo DTI and NODDI: Applications to experimental multiple sclerosis.
Crombe A, Planche V, Raffard G, Bourel J, Dubourdieu N, Panatier A, Fukutomi H, Dousset V, Oliet S, Hiba B, Tourdias T

Abstract:
The hippocampus contains distinct populations of neurons organized into separate anatomical subfields and layers with differential vulnerability to pathological mechanisms. The ability of in vivo neuroimaging to pinpoint regional vulnerability is especially important for better understanding of hippocampal pathology at the early stage of neurodegenerative disorders and for monitoring future therapeutic strategies. This is the case for instance in multiple sclerosis whose neurodegenerative component can affect the hippocampus from the early stage. We challenged the capacity of two models, i.e. the classical diffusion tensor imaging (DTI) model and the neurite orientation dispersion and density imaging (NODDI) model, to compute quantitative diffusion MRI that could capture microstructural alterations in the individual hippocampal layers of experimental-autoimmune encephalomyelitis (EAE) mice, the animal model of multiple sclerosis. To achieve this, the hippocampal anatomy of a healthy mouse brain was first explored ex vivo with high resolution DTI and NODDI. Then, 18 EAE mice and 18 control mice were explored 20 days after immunization with in vivo diffusion MRI prior to sacrifice for the histological quantification of neurites and glial markers in each hippocampal layer. Fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD) and mean diffusivity (MD) maps were computed from the DTI model while the orientation dispersion index (ODI), the neurite density index (NDI) and the volume fraction of isotropic diffusivity (isoVF) maps were computed from the NODDI model. We first showed in control mice that color-coded FA and ODI maps can delineate three main hippocampal layers. The quantification of FA, AD, RD, MD, ODI, NDI and isoVF presented differences within these 3 layers, especially within the molecular layer of the dentate gyrus which displayed a specific signature based on a combination of AD (or MD), ODI and NDI. Then, the comparison between EAE and control mice showed a decrease of AD (p=0.036) and of MD (p=0.033) selectively within the molecular layer of EAE mice while NODDI indices did not present any difference between EAE and control mice in any layer. Histological analyses confirmed the differential vulnerability of the molecular layer of EAE mice that exhibited decreased dendritic length and decreased dendritic complexity together with activated microglia. Dendritic length and intersections within the molecular layer were independent contributors to the observed decrease of AD (R(2)=0.37 and R(2)=0.40, p<0.0001) and MD (R(2)=0.41 and R(2)=0.42, p<0.0001). We therefore identified that NODDI maps can help to highlight the internal microanatomy of the hippocampus but NODDI still presents limitations in grey matter as it failed to capture selective dendritic alterations occurring at early stages of a neurodegenerative disease such as multiple sclerosis, whereas DTI maps were significantly altered.




13/01/2018 | Hum Brain Mapp   IF 4.9
Regional hippocampal vulnerability in early multiple sclerosis: Dynamic pathological spreading from dentate gyrus to CA1.
Planche V, Koubiyr I, Romero JE, Manjon JV, Coupe P, Deloire M, Dousset V, Brochet B, Ruet A, Tourdias T

Abstract:
BACKGROUND: Whether hippocampal subfields are differentially vulnerable at the earliest stages of multiple sclerosis (MS) and how this impacts memory performance is a current topic of debate. METHOD: We prospectively included 56 persons with clinically isolated syndrome (CIS) suggestive of MS in a 1-year longitudinal study, together with 55 matched healthy controls at baseline. Participants were tested for memory performance and scanned with 3 T MRI to assess the volume of 5 distinct hippocampal subfields using automatic segmentation techniques. RESULTS: At baseline, CA4/dentate gyrus was the only hippocampal subfield with a volume significantly smaller than controls (p < .01). After one year, CA4/dentate gyrus atrophy worsened (-6.4%, p < .0001) and significant CA1 atrophy appeared (both in the stratum-pyramidale and the stratum radiatum-lacunosum-moleculare, -5.6%, p < .001 and -6.2%, p < .01, respectively). CA4/dentate gyrus volume at baseline predicted CA1 volume one year after CIS (R(2) = 0.44 to 0.47, p < .001, with age, T2 lesion-load, and global brain atrophy as covariates). The volume of CA4/dentate gyrus at baseline was associated with MS diagnosis during follow-up, independently of T2-lesion load and demographic variables (p < .05). Whereas CA4/dentate gyrus volume was not correlated with memory scores at baseline, CA1 atrophy was an independent correlate of episodic verbal memory performance one year after CIS (ss = 0.87, p < .05). CONCLUSION: The hippocampal degenerative process spread from dentate gyrus to CA1 at the earliest stage of MS. This dynamic vulnerability is associated with MS diagnosis after CIS and will ultimately impact hippocampal-dependent memory performance.




2018 | front neurol
Impact of Lesion Load Thresholds on Alberta Stroke Program Early Computed Tomographic Score in Diffusion-Weighted Imaging.
Schroder J, Cheng B, Malherbe C, Ebinger M, Kohrmann M, Wu O, Kang DW, Liebeskind DS, Tourdias T, Singer OC, Campbell B, Luby M, Warach S, Fiehler J, Kemmling A, Fiebach JB, Gerloff C, Thomalla G

Abstract:
Background and aims: Assessment of ischemic lesions on computed tomography or MRI diffusion-weighted imaging (DWI) using the Alberta Stroke Program Early Computed Tomography Score (ASPECTS) is widely used to guide acute stroke treatment. However, it has never been defined how many voxels need to be affected to label a DWI-ASPECTS region ischemic. We aimed to assess the effect of various lesion load thresholds on DWI-ASPECTS and compare this automated analysis with visual rating. Materials and methods: We analyzed overlap of individual DWI lesions of 315 patients from the previously published predictive value of fluid-attenuated inversion recovery study with a probabilistic ASPECTS template derived from 221 CT images. We applied multiple lesion load thresholds per DWI-ASPECTS region (>0, >1, >10, and >20% in each DWI-ASPECTS region) to compute DWI-ASPECTS for each patient and compared the results to visual reading by an experienced stroke neurologist. Results: By visual rating, median ASPECTS was 9, 84 patients had a DWI-ASPECTS score 0, >1-, >10-, and >20%-thresholds, median DWI-ASPECTS was 1, 5, 8, and 10; 97.1% (306), 72.7% (229), 41% (129), and 25.7% (81) had DWI-ASPECTS 0%: kappaw = 0.020 1%: kappaw = 0.151; 10%: kappaw = 0.386; 20% kappaw = 0.381). Agreement for dichotomized DWI-ASPECTS ranged from fair to substantial (10% kappa = 0.48; >20% kappa = 0.45; 10% kappa = 0.528; and >20% kappa = 0.695). Conclusion: Overall agreement between automated and the standard used visual scoring is low regardless of the lesion load threshold used. However, dichotomized scoring achieved more comparable results. Varying lesion load thresholds had a critical impact on patient selection by ASPECTS. Of note, the relatively low lesion volume and lack of patients with large artery occlusion in our cohort may limit generalizability of these findings.




2018 | front neurol
Differential Gray Matter Vulnerability in the 1 Year Following a Clinically Isolated Syndrome.
Koubiyr I, Deloire M, Coupe P, Dulau C, Besson P, Moroso A, Planche V, Tourdias T, Brochet B, Ruet A

Abstract:
Background and purpose: Whether some gray matter (GM) regions are differentially vulnerable at the early stages of MS is still unknown. The objective of this study is to investigate whether deep and cortical GM are differentially vulnerable after a clinically isolated syndrome (CIS) suggestive of multiple sclerosis (MS). Methods: Fifty-six patients with CIS (PwCIS) and 38 healthy controls (HC) had conventional and diffusion tensor imaging (DTI) at baseline and 46 PwCIS and 20 HC were rescanned after 1 year. Deep GM (DGM) volumes, cortical thickness (CTh), and DTI metrics (FA: fractional anisotropy; MD: mean diffusivity) within these structures were calculated for each participant at each time-point and compared between PwCIS and HC. Linear regression models were used to investigate whether baseline DTI parameters could predict GM volume loss over time. Results: At baseline, GM volumes did not differ between PwCIS and HC, but hippocampal MD was higher in PwCIS than HC (p < 0.01). Over 1 year, GM alterations became more widespread with putamen and hippocampus volumes decreasing in PwCIS (p < 0.01), and cortical thinning in different parts of the cortex along with a significant increase of MD. Hippocampus MD at baseline could predict its volume loss (R (2) = 0.159; p < 0.05) and cortical thinning was associated to microstructural damage (Spearman's rho ranging from -0.424 to -0.603 with p < 0.003). Conclusion: Along with MS being a diffuse inflammatory disease, GM showed a differential vulnerability at the early stage spreading from hippocampus to the cortex. Hippocampus volume loss could be predicted by its MD at baseline.




10/2017 | J Neurol   IF 3.8
Optic neuritis in patients with anti-MOG antibodies spectrum disorder: MRI and clinical features from a large multicentric cohort in France.
Biotti D, Bonneville F, Tournaire E, Ayrignac X, Dalliere CC, Mahieu L, Vignal C, Dulau C, Brochet B, Ruet A, Ouallet JC, Gout O, Heran F, Menjot de Champfleur N, Tourdias T, Deneve M, Labauge P, Deschamps R

Abstract: