Bianciardi Marta, Toschi Nicola, Polimeni Jonathan R, Evans Karleyton C, Bhat Himanshu, Keil Boris, Rosen Bruce R, Boas David A, Wald Lawrence L
Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Building 149, 13th Street, Charlestown, Boston, MA 02129, USA
Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Building 149, 13th Street, Charlestown, Boston, MA 02129, USA Medical Physics Section, Department of Biomedicine and Prevention, Faculty of Medicine, University of Rome 'Tor Vergata', Via Montpellier 1, 00133 Rome, Italy.
Philos Trans A Math Phys Eng Sci. 2016 May 13;374(2067). doi: 10.1098/rsta.2015.0184.
The influence of cardiac activity on the viscoelastic properties of intracranial tissue is one of the mechanisms through which brain-heart interactions take place, and is implicated in cerebrovascular disease. Cerebrovascular disease risk is not fully explained by current risk factors, including arterial compliance. Cerebrovascular compliance is currently estimated indirectly through Doppler sonography and magnetic resonance imaging (MRI) measures of blood velocity changes. In order to meet the need for novel cerebrovascular disease risk factors, we aimed to design and validate an MRI indicator of cerebrovascular compliance based on direct endogenous measures of blood volume changes. We implemented a fast non-gated two-dimensional MRI pulse sequence based on echo-planar imaging (EPI) with ultra-short repetition time (approx. 30-50 ms), which stepped through slices every approximately 20 s. We constrained the solution of the Bloch equations for spins moving faster than a critical speed to produce an endogenous contrast primarily dependent on spin volume changes, and an approximately sixfold signal gain compared with Ernst angle acquisitions achieved by the use of a 90° flip angle. Using cardiac and respiratory peaks detected on physiological recordings, average cardiac and respiratory MRI pulse waveforms in several brain compartments were obtained at 7 Tesla, and used to derive a compliance indicator, the pulsatility volume index (pVI). The pVI, evaluated in larger cerebral arteries, displayed significant variation within and across vessels. Multi-echo EPI showed the presence of significant pulsatility effects in both S0 and [Formula: see text] signals, compatible with blood volume changes. Lastly, the pVI dynamically varied during breath-holding compared with normal breathing, as expected for a compliance indicator. In summary, we characterized and performed an initial validation of a novel MRI indicator of cerebrovascular compliance, which might prove useful to investigate brain-heart interactions in cerebrovascular disease and other disorders.
心脏活动对颅内组织粘弹性特性的影响是脑-心相互作用发生的机制之一，并且与脑血管疾病有关。目前的风险因素，包括动脉顺应性，并未完全解释脑血管疾病风险。目前，脑血管顺应性是通过多普勒超声检查和磁共振成像（MRI）测量血流速度变化来间接估计的。为了满足对新型脑血管疾病风险因素的需求，我们旨在设计并验证一种基于直接测量血容量变化的内源性指标的脑血管顺应性MRI指标。我们实施了一种基于回波平面成像（EPI）的快速非门控二维MRI脉冲序列，其重复时间极短（约30 - 50毫秒），每隔约20秒对各层面进行扫描。我们对自旋速度超过临界速度的Bloch方程求解进行约束，以产生主要依赖于自旋体积变化的内源性对比度，与使用90°翻转角进行的Ernst角采集相比，信号增益约为六倍。利用生理记录中检测到的心脏和呼吸峰值，在7特斯拉磁场下获取了几个脑区的平均心脏和呼吸MRI脉冲波形，并用于推导顺应性指标——搏动体积指数（pVI）。在较大的脑动脉中评估的pVI在血管内和血管间均显示出显著差异。多回波EPI显示在S0和[公式：见原文]信号中均存在显著的搏动效应，这与血容量变化相符。最后，正如对顺应性指标的预期，与正常呼吸相比，屏气期间pVI会动态变化。总之，我们对一种新型脑血管顺应性MRI指标进行了表征并进行了初步验证，这可能对研究脑血管疾病和其他疾病中的脑-心相互作用有用。
