Classification of schizophrenic patients and healthy controls using [18F] fluorodopa PET imaging
Classification of schizophrenic patients and healthy controls using [18F] fluorodopa PET imaging
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DOI：
10.1016/j.schres.2008.09.011
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发表时间：
2008-12-01
影响因子：
4.5
通讯作者：
Grasby, Paul M.
中科院分区：
文献类型：
--
作者：
Bose, Subrata K.;Turkheimer, Federico E.;Grasby, Paul M.
基于体内神经影像学研究，纹状体多巴胺能过度活跃与精神分裂症的病理生理学有关。特别是，使用放射性示踪剂6 - [18F]氟 - L - 多巴（[18F]多巴）和正电子发射断层扫描（PET），在精神分裂症中反复证明纹状体多巴胺合成和储存增加。常规分析的[18F]多巴PET成像缺乏用于诊断的敏感性或特异性。本研究的目的是确定应用人工神经网络（ANN）是否会改善图像分类，并提高[18F]多巴作为精神分裂症潜在诊断测试的敏感性和特异性。我们使用纹状体前后分区内的[18F]多巴速率常数，测试了一个人工神经网络模型对精神分裂症患者与正常对照的区分能力，并将该模型与对相同数据的一般线性分析进行了比较。参与研究的有19名被诊断为偏执型精神分裂症的患者和31名健康受试者。使用偏侧化商数实现了最大分类——人工神经网络模型正确识别了94%的对照和89%的患者，相当于89%的敏感性和94%的特异性。使用所有双侧纹状体区域正确分类了74%的对照和84%的患者，相当于84%的敏感性和74%的特异性。相比之下，一般线性分析效果不佳，仅正确分类了58%的对照和63%的患者。总体而言，这些分析表明了模式识别工具在基于单个靶点的分子成像对精神病患者进行分类方面的潜在用途。（C）2008爱思唯尔B.V.保留所有权利。
Striatal dopaminergic overactivity has been implicated in the pathophysiology of schizophrenia on the basis of in vivo neuroimaging studies. In particular, elevated striatal dopamine synthesis and storage has been repeatedly demonstrated in schizophrenia using the radiotracer 6-[18F] fluoro-L-DOPA ([18F] DOPA) and positron emission tomography (PET). Conventionally analysed [18F] DOPA PET imaging lacks the sensitivity or specificity to be used diagnostically. The aim of this study was to determine if the application of an Artificial Neural Network (ANN) would improve classification of images, and increase the sensitivity and specificity of [18F] DOPA as a potential diagnostic test for schizophrenia.We tested an ANN model in the discrimination of schizophrenic patients from normal controls using [ 18F] DOPA rate constants within the anterior-posterior subdivisions of the striatum, and compared the model with a general linear analysis of the same data. Participating in the study were 19 patients diagnosed with paranoid schizophrenia and 31 healthy subjects.Maximum classification was achieved using laterality quotients, - the ANN model correctly identified 94% of the controls and 89% of the patients, equivalent to 89% sensitivity and 94% specificity. Using all bilateral striatal regions correctly categorised 74% of the controls and 84% of the patients, equivalent to 84% sensitivity and 74% specificity. In comparison, the general linear analysis performed poorly, correctly classifying only 58% of the controls and 63% of the patients. Overall, these analyses have shown the potential utility of pattern recognition tools in the classification of psychiatric patients based upon molecular imaging of a single target. (C) 2008 Elsevier B.V. All rights reserved.