Department of Information Engineering, University of Padova, Padua, Italy.
J Neural Transm (Vienna). 2011 Apr;118(4):563-70. doi: 10.1007/s00702-010-0548-7. Epub 2011 Jan 4.
We performed a dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) analysis to study the role of the demographic/clinical information on perfusion parameters between patients with schizophrenia and normal control subjects. 39 schizophrenia patients and 27 normal controls were studied with a Siemens 1.5T magnet. PWI images were obtained following intravenous injection of paramagnetic contrast agent (gadolinium-DTPA). For each perfusion parameter, i.e. relative cerebral blood flow (rCBF), relative cerebral blood volume (rCBV), mean transit time (MTT) and time-to-peak (TTP), the best predictor model was computed in left and right frontal cortex following a stepwise strategy. First of all, a linear model, including all the sociodemographic information and clinical variables as predictors was computed. At each step, the least significant predictor was excluded and a new linear model was evaluated until all predictors were excluded. Then, the best predictor model was selected based on the F statistic value and on the p value. The models for the rCBF and the rCBV both in the left and right frontal cortex were estimated independently from each other, and the best models contained the same predictors, i.e. clinical state, age, and length of illness. No significant models were obtained for the MTT and the TTP. This study showed a decrease in rCBF and rCBV frontal cortex values in subject affected by schizophrenia. Future DSC-MRI studies should further investigate the role of cerebral perfusion for the pathophysiology of the disease by recruiting first-episode patients and by considering cerebellar, parietal and temporal regions.
我们进行了一项动态磁敏感对比磁共振成像(DSC-MRI)分析,以研究人口统计学/临床信息对精神分裂症患者和正常对照组之间灌注参数的作用。 39 名精神分裂症患者和 27 名正常对照者在西门子 1.5T 磁体上进行了研究。在静脉注射顺磁性对比剂(钆-DTPA)后获得 PWI 图像。对于每个灌注参数,即相对脑血流量(rCBF)、相对脑血容量(rCBV)、平均通过时间(MTT)和达峰时间(TTP),我们使用逐步策略在左、右额叶皮层中计算出最佳预测模型。首先,计算一个线性模型,其中包括所有社会人口统计学信息和临床变量作为预测因子。在每个步骤中,排除最不重要的预测因子,并评估一个新的线性模型,直到所有预测因子都被排除。然后,根据 F 统计值和 p 值选择最佳预测模型。左、右额叶皮层的 rCBF 和 rCBV 模型都是相互独立估计的,最佳模型包含相同的预测因子,即临床状态、年龄和病程。对于 MTT 和 TTP,没有得到显著的模型。这项研究表明,受精神分裂症影响的患者额叶皮层 rCBF 和 rCBV 值降低。未来的 DSC-MRI 研究应通过招募首发患者并考虑小脑、顶叶和颞叶区域,进一步研究脑灌注在疾病病理生理学中的作用。