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Structural Covariance Networks in Anorexia Nervosa (AN): A Multimodal Graph Theoretical Analysis

Published online by Cambridge University Press:  23 March 2020

E. Collantoni ,
P. Meneguzzo ,
E. Tenconi ,
R. Manara ,
P. Santonastaso  and
A. Favaro
E. Collantoni
Affiliation:
University of Padua, Department of Neurosciences, Santa Maria Si Sala, Italy
P. Meneguzzo
Affiliation:
University of Padua, Department of Neurosciences, Padua, Italy
E. Tenconi
Affiliation:
University of Padua, Department of Neurosciences, Padua, Italy
R. Manara
Affiliation:
University of Padua, Department of Neurosciences, Padua, Italy
P. Santonastaso
Affiliation:
University of Padua, Department of Neurosciences, Padua, Italy
A. Favaro
Affiliation:
University of Padua, Department of Neurosciences, Padua, Italy

Abstract

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Introduction

The possibility of evaluating cortical morphological and structural features on the basis of their covariance patterns is becoming increasingly important in clinical neuroscience, because their organizational principles reveal an inter-regional structural dependence which derive from a complex mixture of developmental, genetic and environmental factors.

Objectives

In this study, we describe cortical network organization in anorexia nervosa using a MRI morpho-structural covariance analysis based on cortical thickness, gyrification and fractal dimension.

Aim

Aim of the research is to evaluate any alterations in structural network properties measured with graph theory from multi-modal imaging data in AN.

Methods

Thirty-eight patients with acute AN, 38 healthy controls and 20 patients in full remission from AN underwent MRI scanning. Surface extraction was completed using FreeSurfer package. Graph analysis was performed using graph analysis toolbox.

Results

In acute patients, the covariance analysis among cortical thickness values showed a more segregated pattern and a reduction of global integration indexes. In the recovered patients group, we noticed a similar global trend without statistically significant differences for any single parameter. According to gyrification indexes, the covariance network showed a trend towards high segregation both in acute and recovered patients. We did not observe any significant difference in the covariance networks in the analysis of fractal dimension.

Conclusions

The presence of increased segregation properties in cortical covariance networks in AN may be determined by a retardation of neurodevelopmental trajectories or by an energy saving adaptive response. The differences between the analyzed parameters likely depend on their different morpho-functional meanings.

Disclosure of interest

The authors have not supplied their declaration of competing interest.

Type
e-Poster Walk: Sexual medicine and mental health/sleep disorders and stress/eating disorders
Information
European Psychiatry , Volume 41 , Issue S1: Abstract of the 25th European Congress of Psychiatry , April 2017 , pp. S282
Copyright
Copyright © European Psychiatric Association 2017
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