Aiding the diagnosis of dissociative identity disorder: pattern recognition study of brain biomarkers
Aiding the diagnosis of dissociative identity disorder: pattern recognition study of brain biomarkers
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DOI：
10.1192/bjp.2018.255
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发表时间：
2019-09-01
影响因子：
10.5
通讯作者：
Veltman, Dick J.
中科院分区：
文献类型：
--
作者：
Reinders, Antje A. T. S.;Marquand, Andre F.;Veltman, Dick J.
背景分离性身份识别障碍（DID）的诊断是有争议的，容易误诊和漏诊。从寻求症状治疗的那一刻到准确诊断DID的时间，个人平均接受了4次其他诊断，并在精神卫生服务中度过了7年，报告长达12年。目的探讨数据驱动模式识别方法应用于脑结构图像是否可以提供生物标志物，以帮助DID诊断。方法对32例女性DID患者和43例正常对照者的脑结构图像进行分析。从精神病学和心理治疗门诊招募DID患者。训练概率模式分类器以基于脑形态的测量来区分群组。结果基于脑结构的模式分类器能够准确区分DID患者和健康对照者，具有高灵敏度（72%）和特异性（74%）。这些发现为区分DID患者和健康个体的生物学基础提供了证据。结论：我们提出了一种神经影像学生物标志物模式，可用于在个体水平上从健康对照中识别DID个体。这是重要的和临床相关的，因为DID的诊断是有争议的，患有DID的个体经常被误诊。最终，模式识别方法的应用可以防止DID患者因早期准确诊断而遭受不必要的痛苦，这将有助于更快和有针对性的干预。提交人声明没有竞争性的经济利益。
Background 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. Aim To investigate whether data-driven pattern recognition methodologies applied to structural brain images can provide biomarkers to aid DID diagnosis. Method 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. Results 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. Conclusions 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. Declaration of interest The authors declare no competing financial interests.