Chen Yu-Jen, Liu Chih-Min, Hsu Yung-Chin, Lo Yu-Chun, Hwang Tzung-Jeng, Hwu Hai-Gwo, Lin Yi-Tin, Tseng Wen-Yih Isaac
Institute of Medical Device and Imaging, National Taiwan University College of Medicine, Taipei, Taiwan.
Department of Psychiatry, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan.
Hum Brain Mapp. 2018 Jan;39(1):575-587. doi: 10.1002/hbm.23867. Epub 2017 Oct 28.
A schizophrenia diagnosis relies on characteristic symptoms identified by trained physicians, and is thus prone to subjectivity. This study developed a procedure for the individualized prediction of schizophrenia based on whole-brain patterns of altered white matter tract integrity.
The study comprised training (108 patients and 144 controls) and testing (60 patients and 60 controls) groups. Male and female participants were comparable in each group and were analyzed separately. All participants underwent diffusion spectrum imaging of the head, and the data were analyzed using the tract-based automatic analysis method to generate a standardized two-dimensional array of white matter tract integrity, called the connectogram. Unique patterns in the connectogram that most accurately identified schizophrenia were systematically reviewed in the training group. Then, the diagnostic performance of the patterns was individually verified in the testing group by using receiver-operating characteristic curve analysis.
The performance was high in men (accuracy = 0.85) and satisfactory in women (accuracy = 0.75). In men, the pattern was located in discrete fiber tracts, as has been consistently reported in the literature; by contrast, the pattern was widespread over all tracts in women. These distinct patterns suggest that there is a higher variability in the microstructural alterations in female patients than in male patients.
The individualized prediction of schizophrenia is feasible based on the different whole-brain patterns of tract integrity. The optimal masks and their corresponding regions in the fiber tracts could serve as potential imaging biomarkers for schizophrenia. Hum Brain Mapp 39:575-587, 2018. © 2017 Wiley Periodicals, Inc.
精神分裂症的诊断依赖于训练有素的医生所识别的特征性症状，因此容易受到主观因素的影响。本研究开发了一种基于白质纤维束完整性改变的全脑模式对精神分裂症进行个体化预测的程序。
该研究包括训练组（108例患者和144例对照）和测试组（60例患者和60例对照）。每组中男性和女性参与者具有可比性，并分别进行分析。所有参与者均接受头部弥散谱成像，数据采用基于纤维束的自动分析方法进行分析，以生成标准化的二维白质纤维束完整性阵列，称为连接图。在训练组中系统地评估连接图中最能准确识别精神分裂症的独特模式。然后，通过使用受试者工作特征曲线分析在测试组中对这些模式的诊断性能进行个体验证。
男性的诊断性能较高（准确率=0.85），女性的诊断性能令人满意（准确率=0.75）。在男性中，该模式位于离散的纤维束中，正如文献中一直报道的那样；相比之下，该模式在女性的所有纤维束中广泛分布。这些不同的模式表明，女性患者微观结构改变的变异性高于男性患者。
基于不同的全脑纤维束完整性模式对精神分裂症进行个体化预测是可行的。纤维束中的最佳掩膜及其相应区域可作为精神分裂症潜在的影像学生物标志物。《人类大脑图谱》39:575 - 587，2018年。©2017威利期刊公司。
