Improved segmentation of deep brain grey matter structures using magnetization transfer (MT) parameter maps.

Basal ganglia and brain stem nuclei are involved in the pathophysiology of various neurological and neuropsychiatric disorders. Currently available structural T1-weighted (T1w) magnetic resonance images do not provide sufficient contrast for reliable automated segmentation of various subcortical grey matter structures. We use a novel, semi-quantitative magnetization transfer (MT) imaging protocol that overcomes limitations in T1w images, which are mainly due to their sensitivity to the high iron content in subcortical grey matter. We demonstrate improved automated segmentation of putamen, pallidum, pulvinar and substantia nigra using MT images. A comparison with segmentation of high-quality T1w images was performed in 49 healthy subjects. Our results show that MT maps are highly suitable for automated segmentation, and so for multi-subject morphometric studies with a focus on subcortical structures.

The Beck Cognitive Insight Scale in outpatients with psychotic disorders: further evidence from a French-speaking sample.

OBJECTIVE: The Beck Cognitive Insight Scale (BCIS) evaluates patients' self-report of their ability to detect and correct misinterpretation. Our study aims to confirm the factor structure and the convergent validity of the original scale in a French-speaking environment. METHOD: Outpatients (n = 158) suffering from schizophrenia or schizoaffective disorders fulfilled the BCIS. The 51 patients in Montpellier were equally assessed with the Positive and Negative Syndrome Scale (PANSS) by a psychiatrist who was blind of the BCIS scores. RESULTS: The fit indices of the confirmatory factor analysis validated the 2-factor solution reported by the developers of the scale with inpatients, and in another study with middle-aged and older outpatients. The BCIS composite index was significantly negatively correlated with the clinical insight item of the PANSS. CONCLUSIONS: The French translation of the BCIS appears to have acceptable psychometric properties and gives additional support to the scale, as well as cross-cultural validity for its use with outpatients suffering from schizophrenia or schizoaffective disorders. The correlation between clinical and composite index of cognitive insight underlines the multidimensional nature of clinical insight. Cognitive insight does not recover clinical insight but is a potential target for developing psychological treatments that will improve clinical insight.

An evaluation of volume-based morphometry for prediction of mild cognitive impairment and Alzheimer's disease.

Voxel-based morphometry from conventional T1-weighted images has proved effective to quantify Alzheimer's disease (AD) related brain atrophy and to enable fairly accurate automated classification of AD patients, mild cognitive impaired patients (MCI) and elderly controls. Little is known, however, about the classification power of volume-based morphometry, where features of interest consist of a few brain structure volumes (e.g. hippocampi, lobes, ventricles) as opposed to hundreds of thousands of voxel-wise gray matter concentrations. In this work, we experimentally evaluate two distinct volume-based morphometry algorithms (FreeSurfer and an in-house algorithm called MorphoBox) for automatic disease classification on a standardized data set from the Alzheimer's Disease Neuroimaging Initiative. Results indicate that both algorithms achieve classification accuracy comparable to the conventional whole-brain voxel-based morphometry pipeline using SPM for AD vs elderly controls and MCI vs controls, and higher accuracy for classification of AD vs MCI and early vs late AD converters, thereby demonstrating the potential of volume-based morphometry to assist diagnosis of mild cognitive impairment and Alzheimer's disease.

Individual prediction of cognitive decline in mild cognitive impairment using support vector machine-based analysis of diffusion tensor imaging data.

Although cross-sectional diffusion tensor imaging (DTI) studies revealed significant white matter changes in mild cognitive impairment (MCI), the utility of this technique in predicting further cognitive decline is debated. Thirty-five healthy controls (HC) and 67 MCI subjects with DTI baseline data were neuropsychologically assessed at one year. Among them, there were 40 stable (sMCI; 9 single domain amnestic, 7 single domain frontal, 24 multiple domain) and 27 were progressive (pMCI; 7 single domain amnestic, 4 single domain frontal, 16 multiple domain). Fractional anisotropy (FA) and longitudinal, radial, and mean diffusivity were measured using Tract-Based Spatial Statistics. Statistics included group comparisons and individual classification of MCI cases using support vector machines (SVM). FA was significantly higher in HC compared to MCI in a distributed network including the ventral part of the corpus callosum, right temporal and frontal pathways. There were no significant group-level differences between sMCI versus pMCI or between MCI subtypes after correction for multiple comparisons. However, SVM analysis allowed for an individual classification with accuracies up to 91.4% (HC versus MCI) and 98.4% (sMCI versus pMCI). When considering the MCI subgroups separately, the minimum SVM classification accuracy for stable versus progressive cognitive decline was 97.5% in the multiple domain MCI group. SVM analysis of DTI data provided highly accurate individual classification of stable versus progressive MCI regardless of MCI subtype, indicating that this method may become an easily applicable tool for early individual detection of MCI subjects evolving to dementia.

Cognitive behavioural therapy for obesity and binge eating associated to antipsychotic drugs

Background and Aims: Overweight, obesity and binge eating disorder are commonly reported in persons with severe mental disorders. Particularly, antipsychotic drugs (AP) induce weight gain in up to half of the patients. The aim of the present study is to confirm a previous study results on a larger sample of patients, to assess the impact of the interventions on other relevant dimensions of eating and weight related cognitions as well as to assess potential clinical indicators of outcomes such as AP drug, concomitant treatment with lithium or carbamazepine, psychiatric diagnostic, binge eating and severity of cognitive distortions. Method: A controlled study (12-week CBT vs. B N E) was carried out on 99 patients treated with an AP and who have gained weight following this treatment. Binge eating symptomatology, eating and weight-related cognitions, as well as weight and body mass index were assessed before treatment, at 12 weeks and at 24 weeks. Results: The findings confirms usefulness and effectiveness of the proposed CBT program on the treatment of binge symptomatology, cognitive distortions and obesity in patients treated with AP. Reduction of binge symptoms and maladapted cognitions appeared early, whereas the effect on weight appeared later during the follow up observation. No differences on outcomes were found across pharmacotherapy characteristics, diagnostic categories, binge eating nor severity of cognitive distortions. Conclusion: The proposed CBT treatment is useful for patients suffering from weight gain associated with AP treatments indeed when a concomitant treatment with lithium or valproate was given.

The relationship between cognitive errors and interpersonal patterns in depressed women.

Individuals with depression process information in an overly negative or biased way (e.g., Henriques & Leitenberg, 2002) and demonstrate significant interpersonal dysfunction (e.g., Zlotnick, Kohn, Keitner, & Della Grotta, 2000). This study examined the relationship between cognitive errors (CEs) and interpersonal interactions in early psychotherapy sessions of 25 female patients with major depression. Transcripts were rated for CEs using the Cognitive Error Rating Scale (Drapeau, Perry, & Dunkley, 2008). Interpersonal patterns were assessed using the Structural Analysis of Social Behavior (Benjamin, 1974). Significant associations were found between CEs and markers of interpersonal functioning in selected contexts. The implications of these findings in bridging the gap between research and practice, enhancing treatment outcome, and improving therapist training are discussed. (PsycINFO Database Record (c) 2012 APA, all rights reserved).