MR ASSESSMENT OF TRANSIENT CEREBRAL ISCHEMIA

最近的临床试验表明，早期使用溶栓剂rt-PA治疗可以改善某些缺血性卒中患者的临床结局。但是，即使在3小时的“治疗机会窗”内开始治疗，也很少有病例从rt-PA中获得显著获益，有些患者实际上可能恶化。开发更有效的治疗方案和将治疗窗延长到更晚的时间点将取决于临床医生区分有可能从溶栓中获益的缺血性卒中患者的能力（或一些其他疗法）与那些将建模以区分缺血性脑组织的疗法相比，在再灌注之前，具有从不可逆损伤组织（即无反应或可能因溶栓而恶化）恢复（即接受治疗干预）的潜力，以选择治疗方案。我们的方法是基于一个机械的假设，多参数MRI，通过占组织和组织灌注的水的多个生物物理状态，将产生一个更完整的分类缺血性脑组织比任何单一的MRI参数。该项目的次要目标是定义再灌注后MRI治疗有效性的指征，包括成功或不成功的再灌注以及对恢复、状态无变化或受累组织进一步恶化的影响。基于基于MRI的组织模型的开发，以预测缺血性组织病理学和当前资助期间的最终结果，我们建议使用多参数MRI数据方法结合复杂的数据分析程序来实现这些目标。

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.