Morphometric hemispheric asymmetry of orbitofrontal cortex in women with borderline personality disorder: a multi-parameter approach.

Functional imaging studies have implicated the orbitofrontal cortex (OFC) in the pathophysiology of borderline personality disorder (BPD). To date, however, volume-based magnetic resonance imaging (MRI) studies have yielded mixed results. We used a surface-based processing approach that allowed us to measure five morphometric cortical features of the OFC, including volumetric (cortical thickness and surface area) and geometric (mean curvature, depth of sulcus, and metric distortion - three indicators of cortical folding) parameters. Participants comprised 25 female BPD patients with no other current psychiatric comorbidity and 25 age- and gender-matched healthy controls who received structural MRI scans. Images were processed using the Freesurfer package. All BPD patients had a history of comorbid psychiatric disorder(s) and were currently on medications. Compared with controls, the BPD group showed reduced cortical thickness, surface area, mean curvature, depth of sulcus, and metric distortion in the right medial OFC. In the left medial OFC, the BPD group had reduced cortical thickness and mean curvature, but increased metric distortion. This study confirmed the utility of surface-based analysis in the study of BPD cortical structures. In addition, we observed extensive structural abnormalities in the medial OFC of female subjects with BPD, findings that were most pronounced in the right OFC, with preliminary data suggesting hemispheric asymmetry.

Can neuroimaging be used as a support to diagnosis of borderline personality disorder? An approach based on computational neuroanatomy and machine learning.

Several recent studies in literature have identified brain morphological alterations associated to Borderline Personality Disorder (BPD) patients. These findings are reported by studies based on voxel-based-morphometry analysis of structural MRI data, comparing mean gray-matter concentration between groups of BPD patients and healthy controls. On the other hand, mean differences between groups are not informative about the discriminative value of neuroimaging data to predict the group of individual subjects. In this paper, we go beyond mean differences analyses, and explore to what extent individual BPD patients can be differentiated from controls (25 subjects in each group), using a combination of automated-morphometric tools for regional cortical thickness/volumetric estimation and Support Vector Machine classifier. The approach included a feature selection step in order to identify the regions containing most discriminative information. The accuracy of this classifier was evaluated using the leave-one-subject-out procedure. The brain regions indicated as containing relevant information to discriminate groups were the orbitofrontal, rostral anterior cingulate, posterior cingulate, middle temporal cortices, among others. These areas, which are distinctively involved in emotional and affect regulation of BPD patients, were the most informative regions to achieve both sensitivity and specificity values of 80% in SVM classification. The findings suggest that this new methodology can add clinical and potential diagnostic value to neuroimaging of psychiatric disorders.