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Neuroimaging biomarkers to predict treatment response in schizophrenia: the end of 30 years of solitude?

机译:神经影像生物标记物预测精神分裂症的治疗反应:孤独症30年的终结?

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摘要

Studies that have used structural magnetic resonance imaging (MRI) suggest that individuals with psychoses have brain alterations, particularly in frontal and temporal cortices, and in the white matter tracts that connect them. Furthermore, these studies suggest that brain alterations may be particularly prominent, already at illness onset, in those individuals more likely to have poorer outcomes (eg, higher number of hospital admissions, and poorer symptom remission, level of functioning, and response to the first treatment with antipsychotic drugs). The fact that, even when present, these brain alterations are subtle and distributed in nature, has limited, until now, the utility of MRI in the clinical management of these disorders. More recently, MRI approaches, such as machine learning, have suggested that these neuroanatomical biomarkers can be used for direct clinical benefits. For example, using support vector machine, MRI data obtained at illness onset have been used to predict, with significant accuracy, whether a specific individual is likely to experience a remission of symptoms later on in the course of the illness. Taken together, this evidence suggests that validated, strong neuroanatomical markers could be used not only to inform tailored intervention strategies in a single individual, but also to allow patient stratification in clinical trials for new treatments.
机译:使用结构磁共振成像(MRI)的研究表明,患有精神病的人大脑会发生变化,特别是在额叶和颞叶皮质以及连接它们的白质束中。此外,这些研究表明,在病情发作时,脑部改变可能尤其突出,这些人更可能具有较差的预后(例如,住院次数较多,症状缓解,功能水平以及对初次治疗的反应较差)。抗精神病药治疗)。即使在存在时,这些脑部改变实际上也是微妙的且分布在自然界中,这一事实一直限制了直到现在,MRI在这些疾病的临床管理中的应用。最近,诸如机器学习之类的MRI方法已经表明,这些神经解剖生物标记物可用于直接的临床益处。例如,使用支持向量机,已将在疾病发作时获得的MRI数据用于显着准确地预测特定个体是否有可能在疾病后期缓解症状。综上所述,这一证据表明,经过验证的,强大的神经解剖学标记物不仅可以用于为单个个体提供量身定制的干预策略,还可以在临床试验中为新治疗方法的患者分层。

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