Functional Neurological Symptom Disorder: A Diagnostic Algorithm

Functional neurological symptom disorder (FNSD) is a neuropsychiatric disorder characterized by the presence of neurological symptoms in the absence of any neurological abnormality that can be linked to a known pathology. Few studies have taken interest in this subject probably because of the hetero...

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Main Authors: Eugénie Girouard, Isabelle Savoie, Ludivine Chamard Witkowski
Format: Article
Language:English
Published: Wiley 2019-01-01
Series:Behavioural Neurology
Online Access:http://dx.doi.org/10.1155/2019/3154849
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author Eugénie Girouard
Isabelle Savoie
Ludivine Chamard Witkowski
author_facet Eugénie Girouard
Isabelle Savoie
Ludivine Chamard Witkowski
author_sort Eugénie Girouard
collection DOAJ
description Functional neurological symptom disorder (FNSD) is a neuropsychiatric disorder characterized by the presence of neurological symptoms in the absence of any neurological abnormality that can be linked to a known pathology. Few studies have taken interest in this subject probably because of the heterogeneity of results. It is most often a diagnosis of exclusion which often means that patients undergo many tests and find themselves erring for a diagnosis with very little satisfaction of the outcomes. A reliable imagery pattern would therefore provide some relief and confirmation for both patients and clinicians. It could also facilitate acceptation of the diagnosis and reduce the societal cost associated with FNSD for the patient. The aim of this present study was to describe a clinicoradiological correspondence algorithm of FNSD using the PET scan and SPECT scan (PoSPs) and grant the clinician with a reliable tool to facilitate the diagnosis of FNSD. A systematic review according to the 2009 PRISMA criteria statement was used to guide the review. Our study included 3 of our own consenting patients who met the Diagnostic and Statistical Manual of Mental Disorders 5th edition criteria as well as 25 other patients from 7 different studies. Our results showed a hypoactivation with poor clinicoradiological correspondence and poor stability in time. This hypoactivation was mostly in the frontal lobe, which could explain some behavioral alterations. These findings oppose the ones found in organic pathologies and therefore should orient towards FNSD. In the light of these findings, we recommend the clinicians to perform two PoSPs, searching for clinicoradiological lack of correspondence and time stability using our algorithm.
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spelling doaj-art-914024ef91c64b9c945c1815833e13a22025-08-20T03:37:06ZengWileyBehavioural Neurology0953-41801875-85842019-01-01201910.1155/2019/31548493154849Functional Neurological Symptom Disorder: A Diagnostic AlgorithmEugénie Girouard0Isabelle Savoie1Ludivine Chamard Witkowski2Neurology, Dr. Georges-L.-Dumont University Hospital Centre, Centre de Formation Médicale du Nouveau-Brunswick, Moncton, NB, CanadaNuclear Medicine, Dr. Georges-L.-Dumont University Hospital Centre, Moncton, NB, CanadaNeurology, Dr. Georges-L.-Dumont University Hospital Centre, Centre de Formation Médicale du Nouveau-Brunswick, Moncton, NB, CanadaFunctional neurological symptom disorder (FNSD) is a neuropsychiatric disorder characterized by the presence of neurological symptoms in the absence of any neurological abnormality that can be linked to a known pathology. Few studies have taken interest in this subject probably because of the heterogeneity of results. It is most often a diagnosis of exclusion which often means that patients undergo many tests and find themselves erring for a diagnosis with very little satisfaction of the outcomes. A reliable imagery pattern would therefore provide some relief and confirmation for both patients and clinicians. It could also facilitate acceptation of the diagnosis and reduce the societal cost associated with FNSD for the patient. The aim of this present study was to describe a clinicoradiological correspondence algorithm of FNSD using the PET scan and SPECT scan (PoSPs) and grant the clinician with a reliable tool to facilitate the diagnosis of FNSD. A systematic review according to the 2009 PRISMA criteria statement was used to guide the review. Our study included 3 of our own consenting patients who met the Diagnostic and Statistical Manual of Mental Disorders 5th edition criteria as well as 25 other patients from 7 different studies. Our results showed a hypoactivation with poor clinicoradiological correspondence and poor stability in time. This hypoactivation was mostly in the frontal lobe, which could explain some behavioral alterations. These findings oppose the ones found in organic pathologies and therefore should orient towards FNSD. In the light of these findings, we recommend the clinicians to perform two PoSPs, searching for clinicoradiological lack of correspondence and time stability using our algorithm.http://dx.doi.org/10.1155/2019/3154849
spellingShingle Eugénie Girouard
Isabelle Savoie
Ludivine Chamard Witkowski
Functional Neurological Symptom Disorder: A Diagnostic Algorithm
Behavioural Neurology
title Functional Neurological Symptom Disorder: A Diagnostic Algorithm
title_full Functional Neurological Symptom Disorder: A Diagnostic Algorithm
title_fullStr Functional Neurological Symptom Disorder: A Diagnostic Algorithm
title_full_unstemmed Functional Neurological Symptom Disorder: A Diagnostic Algorithm
title_short Functional Neurological Symptom Disorder: A Diagnostic Algorithm
title_sort functional neurological symptom disorder a diagnostic algorithm
url http://dx.doi.org/10.1155/2019/3154849
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