Study of Morphological and Perfusion Imaging Predictors of Pejorative Outcome in Major Depressive Disorder

Depression is a debilitating illness with a risk of developing a treatment resistant form. Currently, diagnosis is purely clinical with little features available to identify potentially adverse developments. Clinical features such as early onset age, prolonged episodes, anxiety, somatic symptoms and apathy are all arguments raising fears the onset of resistance to conventional treatments. According to neuroimaging knowledge about the pathophysiological mechanisms, involving front-limbic functional networks supporting the functions of emotional regulation and reward system, recent work has focused on the identification of neuroimaging biomarkers predicting therapeutic response. Among the regions of interest identified, the anterior cingulate cortex, amygdala, hippocampus, and regions participating in the Default Mode Network Training (Medial prefrontal cortex, posterior cingulate cortex, inferior parietal lobe) are most frequently areas associated with the prediction of therapeutic response. Limitations most reported in these studies are the heterogeneity of experimental paradigms (resting state, cognitive or emotional functional tasks), imaging (PET scan, MRI) the heterogeneity of clinical resistance criteria forms studied, different techniques (as that we consider remission (threshold score) or response (50% decrease from baseline score), and the sample size. Knowing that MRI into daily clinical practice in the SHU of Adult Psychiatry, as the balance sheet of the disease, monitoring its evolution, as in assumption rTMS (repetitive Transcranial Magnetic Stimulation) (pretreatment assessment and neuro), the identification of neuroimaging biomarkers in a population of patients with clinical criteria of Mood Depressive Episode, with an acquisition of identical and reproducible image daily routine methodology appears to be a reliable way to correct the heterogeneity of conventionally published studies on the topic. This study aim to identify, in routine care, predictive