MR ASSESSMENT OF TRANSIENT CEREBRAL ISCHEMIA

最近的临床试验表明，早期使用溶栓剂rt-PA可以改善某些缺血性中风患者的临床结果。但是，即使在3小时的“治疗机会之窗”内开始治疗，也很少有病例从rt-PA中获得显著的好处，一些患者实际上可能会恶化。开发更有效的治疗方案并将治疗窗口延长至较晚时间点将取决于临床医生的能力，以区分有可能受益于溶栓(或其他一些治疗)的缺血性中风患者与那些在再灌注前建模以区分缺血脑组织与从不可逆转的受损组织(即无反应或溶栓后可能恶化)中恢复(即接受治疗干预)的潜在患者的能力，从而选择治疗方案。我们的方法是基于一个机械假设，即多参数MRI通过考虑组织中水的多种生物物理状态和组织灌流，将产生比任何单一MRI参数更完整的缺血脑组织分类。该项目的次要目标将是根据成功或不成功的再灌注来确定再灌注后治疗效果的MRI适应症，以及对恢复、状态不变或相关组织的进一步恶化的影响。在开发基于MRI的组织模型以预测当前资金期间的缺血组织病理学和最终结果的基础上，我们建议使用多参数MRI数据方法结合复杂的数据分析例程来实现这些目标。

Recent clinical trials have shown that early treatment using the thrombolytic agent, rt-PA, can improve the clinical outcome in certain patients with ischemic stroke. But even when treatment is initiated within the 3 hour "therapeutic window of opportunity", there are few cases that derive significant benefit from rt-PA and some patients may actually deteriorate. The development of more effective treatment options and extension of the therapeutic window to later time points will depend on the ability of clinicians to differentiate patients with ischemic stroke that have the potential to benefit from thrombolysis (or some other therapy) from those that will model to differentiate ischemic brain tissue, prior to reperfusion, with the potential for recovery (i.e. receptive to therapeutic intervention) from irreversibly damaged tissues (i.e. no response or may worsen with thrombolysis) for the purpose of selecting treatment options. Our approach is based on a mechanistic hypothesis that multi-parameter MRI, by accounting for the multiple biophysical states of water in tissue and tissue perfusion, will yield a more complete classification of ischemic brain tissue than any single MRI parameter. A secondary goal of the project will be to define post reperfusion MRI indications of treatment efficacy in terms of successful or unsuccessful reperfusion and the implications for recovery, no change in status or further deterioration of the involved tissue. Based on development of MRI based tissue models to predict ischemic histopathology and eventual outcome during the current funding period, we propose to accomplish these objectives using a multi- parameter MRI data approach in conjunction with sophisticated data analysis routines.