Aiding the diagnosis of dissociative identity disorder: pattern recognition study of brain biomarkers

A diagnosis of dissociative identity disorder (DID) is controversial and prone to under- and misdiagnosis. From the moment of seeking treatment for symptoms to the time of an accurate diagnosis of DID individuals received an average of four prior other diagnoses and spent 7 years, with reports of up...

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Veröffentlicht in:British journal of psychiatry 2019-09, Vol.215 (3), p.536-544
Hauptverfasser: Reinders, Antje A. T. S., Marquand, Andre F., Schlumpf, Yolanda R., Chalavi, Sima, Vissia, Eline M., Nijenhuis, Ellert R. S., Dazzan, Paola, Jäncke, Lutz, Veltman, Dick J.
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container_start_page 536
container_title British journal of psychiatry
container_volume 215
creator Reinders, Antje A. T. S.
Marquand, Andre F.
Schlumpf, Yolanda R.
Chalavi, Sima
Vissia, Eline M.
Nijenhuis, Ellert R. S.
Dazzan, Paola
Jäncke, Lutz
Veltman, Dick J.
description A diagnosis of dissociative identity disorder (DID) is controversial and prone to under- and misdiagnosis. From the moment of seeking treatment for symptoms to the time of an accurate diagnosis of DID individuals received an average of four prior other diagnoses and spent 7 years, with reports of up to 12 years, in mental health services. To investigate whether data-driven pattern recognition methodologies applied to structural brain images can provide biomarkers to aid DID diagnosis. Structural brain images of 75 participants were included: 32 female individuals with DID and 43 matched healthy controls. Individuals with DID were recruited from psychiatry and psychotherapy out-patient clinics. Probabilistic pattern classifiers were trained to discriminate cohorts based on measures of brain morphology. The pattern classifiers were able to accurately discriminate between individuals with DID and healthy controls with high sensitivity (72%) and specificity (74%) on the basis of brain structure. These findings provide evidence for a biological basis for distinguishing between DID-affected and healthy individuals. We propose a pattern of neuroimaging biomarkers that could be used to inform the identification of individuals with DID from healthy controls at the individual level. This is important and clinically relevant because the DID diagnosis is controversial and individuals with DID are often misdiagnosed. Ultimately, the application of pattern recognition methodologies could prevent unnecessary suffering of individuals with DID because of an earlier accurate diagnosis, which will facilitate faster and targeted interventions. The authors declare no competing financial interests.
doi_str_mv 10.1192/bjp.2018.255
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T. S. ; Marquand, Andre F. ; Schlumpf, Yolanda R. ; Chalavi, Sima ; Vissia, Eline M. ; Nijenhuis, Ellert R. S. ; Dazzan, Paola ; Jäncke, Lutz ; Veltman, Dick J.</creator><creatorcontrib>Reinders, Antje A. T. S. ; Marquand, Andre F. ; Schlumpf, Yolanda R. ; Chalavi, Sima ; Vissia, Eline M. ; Nijenhuis, Ellert R. S. ; Dazzan, Paola ; Jäncke, Lutz ; Veltman, Dick J.</creatorcontrib><description>A diagnosis of dissociative identity disorder (DID) is controversial and prone to under- and misdiagnosis. From the moment of seeking treatment for symptoms to the time of an accurate diagnosis of DID individuals received an average of four prior other diagnoses and spent 7 years, with reports of up to 12 years, in mental health services. To investigate whether data-driven pattern recognition methodologies applied to structural brain images can provide biomarkers to aid DID diagnosis. Structural brain images of 75 participants were included: 32 female individuals with DID and 43 matched healthy controls. Individuals with DID were recruited from psychiatry and psychotherapy out-patient clinics. Probabilistic pattern classifiers were trained to discriminate cohorts based on measures of brain morphology. The pattern classifiers were able to accurately discriminate between individuals with DID and healthy controls with high sensitivity (72%) and specificity (74%) on the basis of brain structure. These findings provide evidence for a biological basis for distinguishing between DID-affected and healthy individuals. We propose a pattern of neuroimaging biomarkers that could be used to inform the identification of individuals with DID from healthy controls at the individual level. This is important and clinically relevant because the DID diagnosis is controversial and individuals with DID are often misdiagnosed. Ultimately, the application of pattern recognition methodologies could prevent unnecessary suffering of individuals with DID because of an earlier accurate diagnosis, which will facilitate faster and targeted interventions. 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To investigate whether data-driven pattern recognition methodologies applied to structural brain images can provide biomarkers to aid DID diagnosis. Structural brain images of 75 participants were included: 32 female individuals with DID and 43 matched healthy controls. Individuals with DID were recruited from psychiatry and psychotherapy out-patient clinics. Probabilistic pattern classifiers were trained to discriminate cohorts based on measures of brain morphology. The pattern classifiers were able to accurately discriminate between individuals with DID and healthy controls with high sensitivity (72%) and specificity (74%) on the basis of brain structure. These findings provide evidence for a biological basis for distinguishing between DID-affected and healthy individuals. We propose a pattern of neuroimaging biomarkers that could be used to inform the identification of individuals with DID from healthy controls at the individual level. This is important and clinically relevant because the DID diagnosis is controversial and individuals with DID are often misdiagnosed. Ultimately, the application of pattern recognition methodologies could prevent unnecessary suffering of individuals with DID because of an earlier accurate diagnosis, which will facilitate faster and targeted interventions. 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T. S.</au><au>Marquand, Andre F.</au><au>Schlumpf, Yolanda R.</au><au>Chalavi, Sima</au><au>Vissia, Eline M.</au><au>Nijenhuis, Ellert R. S.</au><au>Dazzan, Paola</au><au>Jäncke, Lutz</au><au>Veltman, Dick J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Aiding the diagnosis of dissociative identity disorder: pattern recognition study of brain biomarkers</atitle><jtitle>British journal of psychiatry</jtitle><addtitle>Br J Psychiatry</addtitle><date>2019-09-01</date><risdate>2019</risdate><volume>215</volume><issue>3</issue><spage>536</spage><epage>544</epage><pages>536-544</pages><issn>0007-1250</issn><eissn>1472-1465</eissn><abstract>A diagnosis of dissociative identity disorder (DID) is controversial and prone to under- and misdiagnosis. From the moment of seeking treatment for symptoms to the time of an accurate diagnosis of DID individuals received an average of four prior other diagnoses and spent 7 years, with reports of up to 12 years, in mental health services. To investigate whether data-driven pattern recognition methodologies applied to structural brain images can provide biomarkers to aid DID diagnosis. Structural brain images of 75 participants were included: 32 female individuals with DID and 43 matched healthy controls. Individuals with DID were recruited from psychiatry and psychotherapy out-patient clinics. Probabilistic pattern classifiers were trained to discriminate cohorts based on measures of brain morphology. The pattern classifiers were able to accurately discriminate between individuals with DID and healthy controls with high sensitivity (72%) and specificity (74%) on the basis of brain structure. 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subjects Acknowledgment
Adult
Adverse Childhood Experiences
Biological markers
Biomarkers
Brain
Brain Mapping - methods
Brain structure
Case-Control Studies
Classification
Comorbidity
Diagnosis
Diagnosis, Differential
Dissociative disorders
Dissociative identity disorder
Dissociative Identity Disorder - diagnosis
Dissociative Identity Disorder - pathology
Female
Gray Matter - pathology
Health services utilization
Help seeking behavior
Humans
Identity
Magnetic Resonance Imaging
Male
Medical diagnosis
Medical imaging
Mental disorders
Mental health services
Misdiagnosis
Morphology
Neuroimaging
NMR
Nuclear magnetic resonance
Pattern recognition
Personality disorders
Post traumatic stress disorder
Prone
Psychiatry
Psychotherapy
Sensitivity and Specificity
Stress Disorders, Post-Traumatic - diagnosis
Stress Disorders, Post-Traumatic - pathology
Suffering
White Matter - pathology
title Aiding the diagnosis of dissociative identity disorder: pattern recognition study of brain biomarkers
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