Evaluation of a nnU-Net type automated clinical volumetric tumor segmentation tool for diffuse low-grade glioma follow-up.

BACKGROUND AND PURPOSE: Diffuse low-grade gliomas (DLGG) are characterized by a slow and continuous growth and always evolve towards an aggressive grade. Accurate prediction of the malignant transformation is essential as it requires immediate therapeutic intervention. One of its most precise predictors is the velocity of diameter expansion (VDE). Currently, the VDE is estimated either by linear measurements or by manual delineation of the DLGG on T2 FLAIR acquisitions. However, because of the DLGG's infiltrative nature and its blurred contours, manual measures are challenging and variable, even for experts. Therefore we propose an automated segmentation algorithm using a 2D nnU-Net, to 1) gain time and 2) standardize VDE assessment. MATERIALS AND METHODS: The 2D nnU-Net was trained on 318 acquisitions (T2 FLAIR & 3DT1 longitudinal follow-up of 30 patients, including pre- & post-surgery acquisitions, different scanners, vendors, imaging parameters…). Automated vs. manual segmentation performance was evaluated on 167 acquisitions, and its clinical interest was validated by quantifying the amount of manual correction required after automated segmentation of 98 novel acquisitions. RESULTS: Automated segmentation showed a good performance with a mean Dice Similarity Coefficient (DSC) of 0.82±0.13 with manual segmentation and a substantial concordance between VDE calculations. Major manual corrections (i.e., DSC<0.7) were necessary only in 3/98 cases and 81% of the cases had a DSC>0.9. CONCLUSION: The proposed automated segmentation algorithm can successfully segment DLGG on highly variable MRI data. Although manual corrections are sometimes necessary, it provides a reliable, standardized and time-winning support for VDE extraction to asses DLGG growth.

Precuneal gliomas promote behaviorally relevant remodeling of the functional connectome.

OBJECTIVE: The precuneus hosts one of the most complex patterns of functional connectivity in the human brain. However, due to the extreme rarity of neurological lesions specifically targeting this structure, it remains unknown how focal damage to the precuneus may impact resting-state functional connectivity (rsFC) at the brainwide level. The aim of this study was to investigate glioma-induced rsFC modulations and to identify patterns of rsFC remodeling that accounted for the maintenance of cognitive performance after awake-guided surgical excision. METHODS: In a unique series of patients with IDH1-mutated low-grade gliomas (LGGs) infiltrating the precuneus who were treated at a single neurosurgical center (Montpellier University Medical Center, 2014-2021), the authors gauged the dynamic modulations induced by tumors on rsFC in comparison with healthy participants. All patients received a preoperative resting-state functional MRI and underwent operation guided by awake cognitive mapping. Connectome multivariate pattern analysis (MVPA), seed-network analysis, and graph theoretical analysis were conducted and correlated to executive neurocognitive scores (i.e., phonological and semantic fluencies, Trail-Making Test [TMT] parts A and B) obtained 3 months after surgery. RESULTS: Seventeen patients with focal precuneal infiltration were selected (mean age 38.1 ± 11.2 years) and matched to 17 healthy participants (mean age 40.5 ± 10.4 years) for rsFC analyses. All patients underwent awake cognitive mapping, allowing total resection (n = 3) or subtotal resection (n = 14), with a mean extent of resection of 90.6% ± 7.3%. Using MVPA (cluster threshold: p-false discovery rate corrected < 0.05, voxel threshold: p-uncorrected < 0.001), remote hotspots with significant rsFC changes were identified, including both insulas, the anterior cingulate cortex, superior sensorimotor cortices, and both frontal eye fields. Further seed-network analyses captured 2 patterns of between-network redistribution especially involving hyperconnectivity between the salience, visual, and dorsal attentional networks. Finally, the global efficiency of the salience-visual-dorsal attentional networks was strongly and positively correlated to 3-month postsurgical scores (n = 15) for phonological fluency (r15 = 0.74, p = 0.0027); TMT-A (r15 = 0.65, p = 0.012); TMT-B (r15 = 0.70, p = 0.005); and TMT-B-A (r15 = 0.62, p = 0.018). CONCLUSIONS: In patients with LGGs infiltrating the precuneus, remote and distributed functional connectivity modulations in the preoperative setting are associated with better maintenance of cognitive performance after surgery. These findings provide a new vision of the mechanistic principles underlying neural plasticity and cognitive compensation in patients with LGGs.

Sulcal morphology as cognitive decline predictor in older adults with memory complaints.

To determine whether sulcal morphology can predict changes in cognition, we investigated the relationship between width of 20 cerebral sulci and cognitive decline. Sulcal width was measured in T1-weighted MRI images at baseline in 433 adults aged ≥70 years with memory complaints from the MRI-Multidomain Alzheimer Preventive Trial study. Cognition was evaluated at baseline, 6, 12, 24, and 36 months of follow-up with a composite Z score. The composite score variations over time relative to the baseline sulcal width were assessed using linear mixed regression models. We observed a positive association between a greater decline in cognitive composite score and the width of the superior and the anterior inferior temporal sulci, and the cingulate anterior sulcus of the left hemisphere. Sulcal widening in the lateral temporal and the cingulate anterior areas might predict cognitive decline in individuals with memory complaints.

Prefrontal activity during experimental ostracism and daily psychache in suicide attempters.

BACKGROUND: Suicidal behaviors can result from a complex interaction between social stressors and individual vulnerability. Evidence suggests a specific neural processing of social cues in suicide attempters without knowledge of how it relates to real-world experiences. OBJECTIVE: To investigate the association between brain activity during experimental social exclusion (measured by functional MRI) and psychological pain in daily life (assessed by Ecological Momentary Assessment) in patients with a lifetime history of suicide attempt. METHODS: Thirty-three euthymic females with a history of a major depressive episode were recruited: 13 suicide attempters and 20 affective controls (no history of suicide attempt). Functional MRI scans were acquired while participants played the Cyberball game, a validated social exclusion paradigm. After fMRI, participants completed EMA for a one-week period. Five times per day, they were asked to rate their psychological pain, hopelessness and the negativity of daily events. EMA indices (psychological pain, hopelessness and their interaction with negative events) were correlated with cerebral activations using a ROI approach (orbitofrontal, dorsal and ventrolateral prefrontal cortices, anterior cingulate cortex and insula) in each group. RESULTS: We found a negative correlation between daily ratings of psychological pain and orbitofrontal activation for exclusion versus inclusion during the Cyberball game in suicide attempters but not in affective controls. We did not find correlations between cerebral activation and daily hopelessness ratings. LIMITATIONS: Small sample size CONCLUSION: Scanner-based orbitofrontal activity during social exclusion relates to psychological pain in daily life which participates in suicide risk among vulnerable individuals.

Assessment of Translocator Protein Density, as Marker of Neuroinflammation, in Major Depressive Disorder: A Pilot, Multicenter, Comparative, Controlled, Brain PET Study (INFLADEP Study).

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.