Few studies addressed the evolution of brain activity before and after brain tumor resection. Using a fMRI naming task, we evaluated possible underlying plasticity phenomena. Thirty-two patients with left low-grade gliomas (16 women; age = 38.6 ± 8.31 years) and 19 healthy controls (7 women; age = 42.4 ± 12.1) were included in the study. An overt picture-naming task (DO80) was performed pre and post (3 months) surgery, as well as within the MRI in a covert manner. Exams included an injected 3DT1, a T2FLAIR, a DTI and a GE-EPI (task) sequence. Activations maps were compared with picture naming score, FA and MD maps were estimated, a VLSM analysis was performed on tumor masks, and disconnectome maps were reconstructed. Pre-surgery, the left parahippocampal gyrus (LPH) was inversely associated with task performance. Increased pre-post surgery left lingual gyrus (LLG) activity was found related to decreased picture naming performance. The evolution of left lingual gyrus (LLG) activity was negatively associated with the evolution of picture naming performance. In controls, the LPH was functionally connected to the right precentral gyrus (RPCG) and slightly to the LLG. This was not clearly retrieved in the patient group. Preoperatively, the LLG was connected to the left planum temporale and to the right lingual gyrus. The same result was found for controls. Postoperatively, the LLG was only connected to the RPCG. No association was found between evolution of FA/MD and evolution of picture naming performance. There is not one unique pattern of pre- and postoperative plasticity concerning picture-naming performance in DLGG patients.

Diffuse low-grade gliomas (DLGG) are brain tumors of young adults. They affect the quality of life of the inflicted patients and, if untreated, they evolve into higher grade tumors where the patient's life is at risk. Therapeutic management of DLGGs includes chemotherapy, and tumor diameter is particularly important for the follow-up of DLGG evolution. In fact, the main clinical basis for deciding whether to continue chemotherapy is tumor diameter growth rate. In order to reliably assist the doctors in selecting the most appropriate time to stop treatment, we propose a novel clinical decision support system. Based on two mathematical models, one linear and one exponential, we are able to predict the evolution of tumor diameter under Temozolomide chemotherapy as a first treatment and thus offer a prognosis on when to end it. We present the results of an implementation of these models on a database of 42 patients from Nancy and Montpellier University Hospitals. In this database, 38 patients followed the linear model and four patients followed the exponential model. From a training data set of a minimal size of five, we are able to predict the next tumor diameter with high accuracy. Thanks to the corresponding prediction interval, it is possible to check if the new observation corresponds to the predicted diameter. If the observed diameter is within the prediction interval, the clinician is notified that the trend is within a normal range. Otherwise, the practitioner is alerted of a significant change in tumor diameter.

Background: Major depressive disorder (MDD) is a serious public health problem with high lifetime prevalence (4.4-20%) in the general population. The monoamine hypothesis is the most widespread etiological theory of MDD. Also, recent scientific data has emphasized the importance of immuno-inflammatory pathways in the pathophysiology of MDD. The lack of data on the magnitude of brain neuroinflammation in MDD is the main limitation of this inflammatory hypothesis. Our team has previously demonstrated the relevance of [18F] DPA-714 as a neuroinflammation biomarker in humans. We formulated the following hypotheses for the current study: (i) Neuroinflammation in MDD can be measured by [18F] DPA-714; (ii) its levels are associated with clinical severity; (iii) it is accompanied by anatomical and functional alterations within the frontal-subcortical circuits; (iv) it is a marker of treatment resistance. Methods: Depressed patients will be recruited throughout 4 centers (Bordeaux, Montpellier, Tours, and Toulouse) of the French network from 13 expert centers for resistant depression. The patient population will be divided into 3 groups: (i) experimental group-patients with current MDD (n = 20), (ii) remitted depressed group-patients in remission but still being treated (n = 20); and, (iii) control group without any history of MDD (n = 20). The primary objective will be to compare PET data (i.e., distribution pattern of neuroinflammation) between the currently depressed group and the control group. Secondary objectives will be to: (i) compare neuroinflammation across groups (currently depressed group vs. remitted depressed group vs. control group); (ii) correlate neuroinflammation with clinical severity across groups; (iii) correlate neuroinflammation with MRI parameters for structural and functional integrity across groups; (iv) correlate neuroinflammation and peripheral markers of inflammation across groups. Discussion: This study will assess the effects of antidepressants on neuroinflammation as well as its role in the treatment response. It will contribute to clarify the putative relationships between neuroinflammation quantified by brain neuroimaging techniques and peripheral markers of inflammation. Lastly, it is expected to open innovative and promising therapeutic perspectives based on anti-inflammatory strategies for the management of treatment-resistant forms of MDD commonly seen in clinical practice. Clinical trial registration (reference: NCT03314155) https://www.clinicaltrials.gov/ct2/show/NCT03314155?term=neuroinflammation&cond=depression&cntry=FR&rank=1.