Multivariate pattern analysis of brain structure: A diagnostic tool for Neurofibromatosis type 1

• Type: Article in International Conference Proceedings Book
• Date: 2011

Authors

Duarte, J (Author) Other; Ribeiro, M (Author) Other; Violante, I (Author) Other; Cunha, G (Author) Other; Al Rawi, M (Author) Other; Cunha, JPS (Author) FEUP; Castelo Branco, M (Author) Other

Conference proceedings International

Title: 1st Portuguese Meeting in Biomedical Engineering, ENBENG 2011

2011 1st Portuguese Meeting in Bioengineering: The Challenge of the XXI Century, ENBENG 2011

Lisbon, 1 March 2011 through 4 March 2011

Indexing

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Other information

Authenticus ID: P-008-0PA

DOI: 10.1109/enbeng.2011.6026061

Abstract (EN): Neurofibromatosis type 1 (NF1) is a genetic disorder characterized by increased predisposition for tumor development and cognitive deficits. In this work, we used maps of grey matter density obtained from Magnetic Resonance (MR) brain structural scans to distinguish between NF1 patients and healthy controls with a multivariate pattern analysis technique, Support Vector Machines. Up to 83% of all participants were correctly classified (mean sensitivity of 82%; mean specificity of 84%; significance level p< 0.01). This high level of classification accuracy of NF1 patients suggests this technique as a potential diagnostic tool. In addition, we determined the brain regions that the algorithm used to distinguish between NF1 patients and healthy controls. These regions were not identified as abnormal using univariate voxel-by-voxel comparison indicating that multivariate techniques are a useful powerful tool with which to identify potential structural defects in the NF1 brain. © 2011 IEEE.

Language: English

Type (Professor's evaluation): Scientific