Structural Magnetic Resonance Imaging in Eating Disorders: A Systematic Review of Voxel-Based Morphometry Studies

King's College London, Institute of Psychiatry, Department of Psychological Medicine, Section of Eating Disorders, London, UK.
European Eating Disorders Review (Impact Factor: 2.46). 03/2012; 20(2):94-105. DOI: 10.1002/erv.1163
Source: PubMed


This systematic review summarises and critically appraises the literature on structural magnetic resonance imaging in people with a current or past eating disorder. Studies using voxel-based morphometry image analysis were included. Ten studies reported on a total of 236 people with a current or past eating disorder and 257 healthy controls. Sample heterogeneity prohibited a meta-analytic approach. The findings do not unequivocally indicate grey or white matter volume abnormalities in people with an eating disorder. Nevertheless, these preliminary data suggest that, compared with healthy controls, people with anorexia nervosa have decreased grey matter in a range of brain regions and that those with bulimia nervosa have increased grey matter volumes in frontal and ventral striatal areas. Research in the recovery phase and longitudinal studies suggest that potential brain tissue abnormalities may recover with clinical improvement. Overall, as the available data are inconclusive, further efforts in this field are warranted.

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Available from: Marcelo Berlim, Mar 07, 2014
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    • "Brain imaging studies bave shown structural and functional alterations in areas that contribute to reward processing that may predispose subjects to thè onset and continuance of EDs, as well as relapse (Frank, 2013). For example, people with AN have decreased gray matter in a range of brain regions, including those involved in reward processing, whereas people with BN have increased gray matter volumes in frontal and ventral striatal areas (Van den Eynde et al., 2012; Titova et al., 2013). Both BN and BED patients were characterized by greater volumes of thè mediai orbitofrontal cortex (OFC) compared to healthy controls (Schàfer et al., 2010). "

    Cannabinoids in Neurologic and Mental Disease, 12/2015: pages 389-413; , ISBN: 9780124170414
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    • "Whereas the vast majority of these studies reported in AN patients global reductions of total gray and white matter (Seitz et al., 2014), as well as cortical thickness (King et al., 2014) a number of recent studies have emphasized regional group differences. What has been proposed was that AN patients are characterized by widespread brain abnormalities involving: (a) the mesolimbic regions (striatum, hippocampus, amygdala and cerebellum), (b) the dorsolateral prefrontal cortex, (c) the visual cortex and (d) the cerebellum (Van den Eynde et al., 2012). Otherwise, neuroimaging literature about BN summarizes the presence of a specific involvement of the reward neural system (ventral striatum, nucleus caudate, anterior cingulate cortex (ACC), orbitofrontal cortex (OFC)), hypothesizing that during binge eating a person must consume greater quantities of food to achieve the feeling of satisfaction, like an addict (Amianto et al., 2013; Marsh et al., 2015; Brooks et al., 2012). "
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    ABSTRACT: Presently there are no valid biomarkers to identify individuals with eating disorders (ED). The aim of this work was to assess the feasibility of a machine learning method for extracting reliable neuroimaging features allowing individual categorization of patients with ED. Support vector machine (SVM) technique, combined with a pattern recognition method, was employed utilizing structural magnetic resonance images. Seventeen females with ED (six with diagnosis of anorexia nervosa and 11 with bulimia nervosa) were compared against 17 body mass index-matched healthy controls (HC). Machine learning allowed individual diagnosis of ED versus HC with an accuracy ≥ 0.80. Voxel-based pattern recognition analysis demonstrated that voxels influencing the classification accuracy involved the occipital cortex, the posterior cerebellar lobule, precuneus, sensorimotor/premotor cortices and the medial prefrontal cortex, all critical regions known to be strongly involved in the pathophysiological mechanisms of ED. Although these findings should be considered preliminary given the small size investigated, SVM analysis highlights the role of well-known brain regions as possible biomarkers to distinguish ED from HC at an individual level, thus encouraging the translational implementation of this new multivariate approach in the clinical practice.
    Behavioural neurology 09/2015; DOI:10.1155/2015/924814 · 1.45 Impact Factor
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    • "Neuroimaging research has identified a variety of neuroanatomical substrates of ED pathophysiology. For example, on structural imaging, ED patients show reductions in gray matter volume in regions involved in reward, impulse control, and emotion regulation: the caudate nucleus, ventral striatum (VS), anterior cingulate (ACC) and orbitofrontal cortex (OFC) (Friederich et al., 2012; Schäfer et al., 2010; Titova et al., 2013; Van den Eynde et al., 2012). Likewise, functional magnetic resonance imaging (fMRI) studies in ED reveal abnormal patterns of resting-state connectivity in the default-mode network (Cowdrey et al., 2014) and other intrinsic brain networks incorporating the ACC and insula (Amianto et al., 2013). "
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    ABSTRACT: Background: Conventional treatments for eating disorders are associated with poor response rates and frequent relapse. Novel treatments are needed, in combination with markers to characterize and predict treatment response. Here, resting-state functional magnetic resonance imaging (rs-fMRI) was used to identify predictors and correlates of response to repetitive transcranial magnetic stimulation (rTMS) of the dorsomedial prefrontal cortex (dmPFC) at 10 Hz for eating disorders with refractory binge/purge symptomatology. Methods: 28 subjects with anorexia nervosa, binge-purge subtype or bulimia nervosa underwent 20-30 sessions of 10 Hz dmPFC rTMS. rs-fMRI data were collected before and after rTMS. Subjects were stratified into responder and nonresponder groups using a criterion of ≥50% reduction in weekly binge/purge frequency. Neural predictors and correlates of response were identified using seed-based functional connectivity (FC), using the dmPFC and adjacent dorsal anterior cingulate cortex (dACC) as regions of interest. Results: 16 of 28 subjects met response criteria. Treatment responders had lower baseline FC from dmPFC to lateral orbitofrontal cortex and right posterior insula, and from dACC to right posterior insula and hippocampus. Responders had low baseline FC from the dACC to the ventral striatum and anterior insula; this connectivity increased over treatment. However, in nonresponders, frontostriatal FC was high at baseline, and dmPFC-rTMS suppressed FC in association with symptomatic worsening. Conclusions: Enhanced frontostriatal connectivity was associated with responders to dmPFC-rTMS for binge/purge behavior. rTMS caused paradoxical suppression of frontostriatal connectivity in nonresponders. rs-fMRI could prove critical for optimizing stimulation parameters in a future sham-controlled trial of rTMS in disordered eating.
    Clinical neuroimaging 07/2015; 8:611-618. DOI:10.1016/j.nicl.2015.06.008 · 2.53 Impact Factor
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