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女性大脑磁共振成像在精神分裂症与重性抑郁障碍鉴别诊断中的应用

Discrimination between schizophrenia and major depressive disorder by magnetic resonance imaging of the female brain.

机构信息

Department of Mental Disorder Research, National Institute of Neuroscience, National Center of Neurology and Psychiatry, 4-1-1, Ogawa-Higashi, Kodaira, Tokyo 187-8502, Japan.

出版信息

J Psychiatr Res. 2013 Oct;47(10):1383-8. doi: 10.1016/j.jpsychires.2013.06.010. Epub 2013 Jul 3.

Abstract

BACKGROUND

Although schizophrenia and major depressive disorder (MDD) differ on a variety of neuroanatomical measures, a diagnostic tool to discriminate these disorders has not yet been established. We tried to identify structural changes of the brain that best discriminate between schizophrenia and MDD on the basis of gray matter volume, ventricle volume, and diffusion tensor imaging (DTI).

METHOD

The first exploration sample consisted of 25 female patients with schizophrenia and 25 females with MDD. Regional brain volumes and fractional anisotropy (FA) values were entered into a discriminant analysis. The second validation sample consisted of 18 female schizophrenia and 16 female MDD patients.

RESULTS

The stepwise discriminant analysis resulted in correct classification rates of 0.80 in the schizophrenic group and 0.76 in MDD. In the second validation sample, the obtained model yielded correct classification rates of 0.72 in the schizophrenia group and 0.88 in the MDD group.

CONCLUSION

Our results suggest that schizophrenia and MDD have differential structural changes in the examined brain regions and that the obtained discriminant score may be useful to discriminate the two disorders.

摘要

背景

尽管精神分裂症和重度抑郁症(MDD)在各种神经解剖学测量上存在差异,但尚未建立一种用于区分这些疾病的诊断工具。我们试图根据灰质体积、脑室体积和弥散张量成像(DTI)来确定能够最好地区分精神分裂症和 MDD 的大脑结构变化。

方法

第一个探索性样本包括 25 名女性精神分裂症患者和 25 名女性 MDD 患者。将区域性脑容量和各向异性分数(FA)值输入到判别分析中。第二个验证性样本包括 18 名女性精神分裂症患者和 16 名女性 MDD 患者。

结果

逐步判别分析在精神分裂症组中的正确分类率为 0.80,在 MDD 组中的正确分类率为 0.76。在第二个验证性样本中,所获得的模型在精神分裂症组中的正确分类率为 0.72,在 MDD 组中的正确分类率为 0.88。

结论

我们的结果表明,精神分裂症和 MDD 在受检脑区存在不同的结构变化,并且所获得的判别评分可能有助于区分这两种疾病。

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