Publications by authors named "Isabelle Corouge"

11 Publications

  • Page 1 of 1

Multimodal brain imaging connectivity analyses of emotional and motivational deficits in depression among women.

J Psychiatry Neurosci 2021 Apr 12;46(2):E303-E312. Epub 2021 Apr 12.

From the EA 4712 Comportement et noyaux gris centraux, Université de Rennes 1, France (Robert, Batail, Drapier); the Psychiatry Department, Centre Hospitalier Guillaume Régnier, 108 Boulevard Général Leclerc, 35000, Rennes, France (Robert, Domain, Batail, Drapier); the Radiology Department, CHU Rennes, 2 Rue Henri le Guilloux, 35000 Rennes, France (Bannier, Ferre); the University of Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, Empenn-ERL U 1228, 35000 Rennes, France (Bannier, Corouge, Ferre, Barillot); the Institut de Neurosciences de la Timone, Campus Santé Timone, 27, Bd Jean Moulin 13005 Marseille, France (Comte); the University of Lille & CHU Lille, Inserm, U1171, Degenerative and Vascular Cognitive Disorders, 59000, Lille, France (Dondaine); and the Psychiatry Department, CHU Saint-Etienne, Team PsyR2-Centre de Recherche en Neuroscience de Lyon, (CRNL) CNRS UMR 5292-Inserm U1028, University of Lyon and Saint Etienne, France (Fakra).

Background: Major depressive disorder (MDD) is characterized by impaired cortical-subcortical functional connectivity. Apathy adds to functional impairment, but its cerebral basis in MDD remains unknown. Our objective was to describe impairments in functional connectivity during emotional processing in MDD (with varying levels of congruency and attention), and to determine their correlation with apathy.

Methods: We used the Variable Attention Affective Task during functional MRI, followed by diffusion-weighted MRI, to assess 55 right-handed women (30 with MDD and 25 healthy controls) between September 2012 and February 2015. We estimated functional connectivity using generalized psychophysiologic interaction and anatomic connectivity with tract-based spatial statistics. We measured apathy using the Apathy Evaluation Scale.

Results: We found decreased functional connectivity between the left amygdala and the left anterior cingulate cortex (ACC) during negative stimuli in participants with MDD (t54 = 4.2; p = 0.035, family-wise error [FWE]-corrected). During high-attention stimuli, participants with MDD showed reduced functional connectivity between the right dorsolateral prefrontal cortex (dlPFC) and the right ACC (t54 = 4.06, pFWE = 0.02), but greater functional connectivity between the right dlPFC and the right amygdala (t54 = 3.35, p = 0.048). Apathy was associated with increased functional connectivity between the right dlPFC and the right ACC during high-attention stimuli (t28 = 5.2, p = 0.01) and increased fractional anisotropy in the right posterior cerebellum, the anterior and posterior cingulum and the bilateral internal capsule (all pFWE < 0.05).

Limitations: Limitations included a moderate sample size, concomitant antidepressant therapy and no directed connectivity.

Conclusion: We found that MDD was associated with impairments in cortical-subcortical functional connectivity during negative stimuli that might alter the recruitment of networks engaged in attention. Apathy-related features suggested networks similar to those observed in degenerative disorders, but possible different mechanisms.
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http://dx.doi.org/10.1503/jpn.200074DOI Listing
April 2021

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

Front Neurosci 2020 30;14:598. Epub 2020 Jul 30.

Université de Rennes, Inria, CNRS, Inserm, IRISA UMR 6074, Empenn ERL U-1228, Rennes, France.

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.
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http://dx.doi.org/10.3389/fnins.2020.00598DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7406917PMC
July 2020

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

Neuroimage Clin 2019 16;24:101939. Epub 2019 Jul 16.

Univ Rennes, Inria, CNRS, INSERM, IRISA, Empenn ERL U-1228, F-35000 Rennes, France; CHU Rennes, Radiology Department, F-35033 Rennes, France.

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.
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http://dx.doi.org/10.1016/j.nicl.2019.101939DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6664197PMC
September 2020

White matter abnormalities in depression: A categorical and phenotypic diffusion MRI study.

Neuroimage Clin 2019 4;22:101710. Epub 2019 Feb 4.

Centre Hospitalier Guillaume Régnier, Academic Psychiatry Department, 35703 Rennes, France; Univ of Rennes, "Behavior and Basal Ganglia" research unit (EA 4712), Rennes, France.

Mood depressive disorder is one of the most disabling chronic diseases with a high rate of everyday life disability that affects 350 million people around the world. Recent advances in neuroimaging have reported widespread structural abnormalities, suggesting a dysfunctional frontal-limbic circuit involved in the pathophysiological mechanisms of depression. However, a variety of different white matter regions has been implicated and is sought to suffer from lack of reproducibility of such categorical-based biomarkers. These inconsistent results might be attributed to various factors: actual categorical definition of depression as well as clinical phenotype variability. In this study, we 1/ examined WM changes in a large cohort (114 patients) compared to a healthy control group and 2/ sought to identify specific WM alterations in relation to specific depressive phenotypes such as anhedonia (i.e. lack of pleasure), anxiety and psychomotor retardation -three core symptoms involved in depression. Consistent with previous studies, reduced white matter was observed in the genu of the corpus callosum extending to the inferior fasciculus and posterior thalamic radiation, confirming a frontal-limbic circuit abnormality. Our analysis also reported other patterns of increased fractional anisotropy and axial diffusivity as well as decreased apparent diffusion coefficient and radial diffusivity in the splenium of the corpus callosum and posterior limb of the internal capsule. Moreover, a positive correlation between FA and anhedonia was found in the superior longitudinal fasciculus as well as a negative correlation in the cingulum. Then, the analysis of the anxiety and diffusion metric revealed that increased anxiety was associated with greater FA values in genu and splenium of corpus callosum, anterior corona radiata and posterior thalamic radiation. Finally, the motor retardation analysis showed a correlation between increased Widlöcher depressive retardation scale scores and reduced FA in the body and genu of the corpus callosum, fornix, and superior striatum. Through this twofold approach (categorical and phenotypic), this study has underlined the need to move forward to a symptom-based research area of biomarkers, which help to understand the pathophysiology of mood depressive disorders and to stratify precise phenotypes of depression with targeted therapeutic strategies.
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http://dx.doi.org/10.1016/j.nicl.2019.101710DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6406626PMC
December 2019

Measurement of pediatric regional cerebral blood flow from 6 months to 15 years of age in a clinical population.

Eur J Radiol 2018 Apr 6;101:38-44. Epub 2018 Feb 6.

Univ Rennes1, Faculté de Médecine, F-35043 Rennes, France; INSERM, U 1228, ERL VISAGES, F-35042 Rennes, France; CNRS, IRISA, UMR 6074, F-35042 Rennes, France; INRIA, VISAGES Project-Team, F-35042 Rennes, France; CHU Rennes, Département de Radiologie, F-35033 Rennes, France. Electronic address:

Objectives: To investigate changes in cerebral blood flow (CBF) in gray matter (GM) between 6 months and 15 years of age and to provide CBF values for the brain, GM, white matter (WM), hemispheres and lobes.

Methods: Between 2013 and 2016, we retrospectively included all clinical MRI examinations with arterial spin labeling (ASL). We excluded subjects with a condition potentially affecting brain perfusion. For each subject, mean values of CBF in the brain, GM, WM, hemispheres and lobes were calculated. GM CBF was fitted using linear, quadratic and cubic polynomial regression against age. Regression models were compared with Akaike's information criterion (AIC), and Likelihood Ratio tests.

Results: 84 children were included (44 females/40 males). Mean CBF values were 64.2 ± 13.8 mL/100 g/min in GM, and 29.3 ± 10.0 mL/100 g/min in WM. The best-fit model of brain perfusion was the cubic polynomial function (AIC = 672.7, versus respectively AIC = 673.9 and AIC = 674.1 with the linear negative function and the quadratic polynomial function). A statistically significant difference between the tested models demonstrating the superiority of the quadratic (p = 0.18) or cubic polynomial model (p = 0.06), over the negative linear regression model was not found. No effect of general anesthesia (p = 0.34) or of gender (p = 0.16) was found.

Conclusion: we provided values for ASL CBF in the brain, GM, WM, hemispheres, and lobes over a wide pediatric age range, approximately showing inverted U-shaped changes in GM perfusion over the course of childhood.
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http://dx.doi.org/10.1016/j.ejrad.2018.02.003DOI Listing
April 2018

What semantic dementia teaches us about the functional organization of the left posterior fusiform gyrus.

Neuropsychologia 2017 Nov 23;106:159-168. Epub 2017 Sep 23.

Service de neurologie, CMRR, CHU Pontchaillou, Rennes, France; Normandie Univ, UNICAEN, PSL Research University, EPHE, INSERM, U1077, CHU de Caen, Neuropsychologie et Imagerie de la Mémoire Humaine, 14000 Caen, France.

After demonstrating the relative preservation of fruit and vegetable knowledge in patients with semantic dementia (SD), we sought to identify the neural substrate of this unusual category effect. Nineteen patients with SD performed a semantic sorting task and underwent a morphometric 3T MRI scan. The grey-matter volumes of five regions within the temporal lobe were bilaterally computed, as well as those of two recently described areas (FG1 and FG2) within the posterior fusiform gyrus. In contrast to the other semantic categories we tested, fruit and vegetable scores were only predicted by left FG1 volume. We therefore found a specific relationship between the volume of a subregion within the left posterior fusiform gyrus and performance on fruits and vegetables in SD. We argue that the left FG1 is a convergence zone for the features that might be critical to successfully sort fruits and vegetables. We also discuss evidence for a functional specialization of the fusiform gyrus along two axes (lateral medial and longitudinal), depending on the nature of the concepts and on the level of processing complexity required by the ongoing task.
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http://dx.doi.org/10.1016/j.neuropsychologia.2017.09.023DOI Listing
November 2017

Magnetic resonance imaging in children presenting migraine with aura: Association of hypoperfusion detected by arterial spin labelling and vasospasm on MR angiography findings.

Cephalalgia 2018 04 24;38(5):949-958. Epub 2017 Jul 24.

1 CHU Rennes, Department of Radiology, Pediatric Imaging, Rennes, France.

Objective A child presenting with a first attack of migraine with aura usually undergoes magnetic resonance imaging (MRI) to rule out stroke. The purpose of this study was to report vascular and brain perfusion findings in children suffering from migraine with aura on time-of-flight MR angiography (TOF-MRA) and MR perfusion imaging using arterial spin labelling (ASL). Methods We retrospectively included all children who had undergone an emergency MRI examination with ASL and TOF-MRA sequences for acute neurological deficit and were given a final diagnosis of migraine with aura. The ASL perfusion maps and TOF-MRA images were independently assessed by reviewers blinded to clinical data. A mean cerebral blood flow (CBF) value was obtained for each cerebral lobe after automatic data post-processing. Results Seventeen children were finally included. Hypoperfusion was identified in one or more cerebral lobes on ASL perfusion maps by visual assessment in 16/17 (94%) children. Vasospasm was noted within the intracranial vasculature on the TOF-MRA images in 12/17 (71%) children. All (100%) of the abnormal TOF-MRA images were associated with homolateral hypoperfusion. Mean CBF values were significantly lower ( P < 0.05) in visually hypoperfused lobes than in normally perfused lobes. Conclusion ASL and TOF-MRA are two totally non-invasive, easy-to-use MRI sequences for children in emergency settings. Hypoperfusion associated with homolateral vasospasm may suggest a diagnosis of migraine with aura.
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http://dx.doi.org/10.1177/0333102417723570DOI Listing
April 2018

Analysis of brain white matter via fiber tract modeling.

Conf Proc IEEE Eng Med Biol Soc 2004;2004:4421-4

Department of Computer Science, University of North Carolina, Chapel Hill, NC 27599, USA.

White matter fiber bundles of the human brain form a spatial pattern defined by the anatomical and functional architecture. Tractography applied to the tensor field in diffusion tensor imaging (DTI) results in sets of streamlines which can be associated with major fiber tracts. Comparison of fiber tract properties across subjects needs comparison at corresponding anatomical locations. Moreover, clinical analysis studying fiber tract disruption and integrity requires analysis along tracts and within cross-sections, which is hard to accomplish by conventional region of interest and voxel-based analysis. We propose a new framework for MR DTI analysis that includes tractography, fiber clustering, alignment via local shape parametrization and diffusion analysis across and along tracts. Feasibility is shown with the uncinate fasciculus and the cortico-spinal tracts. The extended set of features including fiber tract geometry and diffusion properties might lead to an improved understanding of diffusion properties and its association to normal/abnormal brain development.
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http://dx.doi.org/10.1109/IEMBS.2004.1404229DOI Listing
September 2007

Fiber tract-oriented statistics for quantitative diffusion tensor MRI analysis.

Med Image Anal 2006 Oct 22;10(5):786-98. Epub 2006 Aug 22.

Department of Computer Science, University of North Carolina, Chapel Hill, USA.

Quantitative diffusion tensor imaging (DTI) has become the major imaging modality to study properties of white matter and the geometry of fiber tracts of the human brain. Clinical studies mostly focus on regional statistics of fractional anisotropy (FA) and mean diffusivity (MD) derived from tensors. Existing analysis techniques do not sufficiently take into account that the measurements are tensors, and thus require proper interpolation and statistics of tensors, and that regions of interest are fiber tracts with complex spatial geometry. We propose a new framework for quantitative tract-oriented DTI analysis that systematically includes tensor interpolation and averaging, using nonlinear Riemannian symmetric space. A new measure of tensor anisotropy, called geodesic anisotropy (GA) is applied and compared with FA. As a result, tracts of interest are represented by the geometry of the medial spine attributed with tensor statistics (average and variance) calculated within cross-sections. Feasibility of our approach is demonstrated on various fiber tracts of a single data set. A validation study, based on six repeated scans of the same subject, assesses the reproducibility of this new DTI data analysis framework.
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http://dx.doi.org/10.1016/j.media.2006.07.003DOI Listing
October 2006

Fiber tract-oriented statistics for quantitative diffusion tensor MRI analysis.

Med Image Comput Comput Assist Interv 2005 ;8(Pt 1):131-9

Department of Computer Science, University of North Carolina, Chapel Hill, USA.

Diffusion tensor imaging (DTI) has become the major modality to study properties of white matter and the geometry of fiber tracts of the human brain. Clinical studies mostly focus on regional statistics of fractional anisotropy (FA) and mean diffusivity (MD) derived from tensors. Existing analysis techniques do not sufficiently take into account that the measurements are tensors, and thus require proper interpolation and statistics based on tensors, and that regions of interest are fiber tracts with complex spatial geometry. We propose a new framework for quantitative tract-oriented DTI analysis that includes tensor interpolation and averaging, using nonlinear Riemannian symmetric space. As a result, tracts of interest are represented by the geometry of the medial spine attributed with tensor statistics calculated within cross-sections. Examples from a clinical neuroimaging study of the early developing brain illustrate the potential of this new method to assess white matter fiber maturation and integrity.
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http://dx.doi.org/10.1007/11566465_17DOI Listing
June 2006

Statistical shape modeling of low level visual area borders.

Med Image Anal 2004 Sep;8(3):353-60

Visages Team, IRISA/INRIA-CNRS, Campus de Beaulieu, 35 042 Rennes Cedex, France.

This paper proposes a statistical modeling of functional landmarks delimiting low level visual areas which are highly variable across individuals. Low level visual areas are first precisely delineated by fMRI retinotopic mapping which provides detailed information about the correspondence between the visual field and its cortical representation. The model is then built by learning the variability within a given training set. It relies on an appropriate data representation and on the definition of an intrinsic coordinate system common to all visual maps. This allows to build a consistent training set on which a principal component analysis is eventually applied. Our approach constitutes a first step toward a functional landmark-based probabilistic atlas of low level visual areas.
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http://dx.doi.org/10.1016/j.media.2004.06.023DOI Listing
September 2004