Identifying motor functional neurological disorder using resting-state functional connectivity.

Wegrzyk, Jennifer; Kebets, Valeria; Richiardi, Jonas; Galli, Silvio; de Ville, Dimitri Van; Aybek, Selma (2018). Identifying motor functional neurological disorder using resting-state functional connectivity. NeuroImage: Clinical, 17, pp. 163-168. Elsevier 10.1016/j.nicl.2017.10.012

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BACKGROUND Motor functional neurological disorder (mFND) is a clinical diagnosis with reliable features; however, patients are reluctant to accept the diagnosis and physicians themselves bear doubts on potential misdiagnoses. The identification of a positive biomarker could help limiting unnecessary costs of multiple referrals and investigations, thus promoting early diagnosis and allowing early engagement in appropriate therapy. OBJECTIVES To test whether resting-state (RS) functional magnetic resonance imaging could discriminate patients suffering from mFND from healthy controls. METHODS We classified 23 mFND patients and 25 age- and gender-matched healthy controls based on whole-brain RS functional connectivity (FC) data, using a support vector machine classifier and the standard Automated Anatomic Labeling (AAL) atlas, as well as two additional atlases for validation. RESULTS Accuracy, specificity and sensitivity were over 68% (p = 0.004) to discriminate between mFND patients and controls, with consistent findings between the three tested atlases. The most discriminative connections comprised the right caudate, amygdala, prefrontal and sensorimotor regions. Post-hoc seed connectivity analyses showed that these regions were hyperconnected in patients compared to controls. CONCLUSIONS The good accuracy to discriminate patients from controls suggests that RS FC could be used as a biomarker with high diagnostic value in future clinical practice to identify mFND patients at the individual level.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Department of Head Organs and Neurology (DKNS) > Clinic of Neurology

UniBE Contributor:

Aybek, Selma

Subjects:

600 Technology > 610 Medicine & health

ISSN:

2213-1582

Publisher:

Elsevier

Language:

English

Submitter:

Stefanie Hetzenecker

Date Deposited:

05 Apr 2018 13:11

Last Modified:

24 Oct 2019 05:59

Publisher DOI:

10.1016/j.nicl.2017.10.012

PubMed ID:

29071210

Uncontrolled Keywords:

Biomarker Classification Functional connectivity Functional neurological disorder Resting state functional magnetic resonance imaging

BORIS DOI:

10.7892/boris.107075

URI:

https://boris.unibe.ch/id/eprint/107075

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