Liu Peiying, Li Yang, Pinho Marco, Park Denise C, Welch Babu G, Lu Hanzhang
Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.
Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA; Biomedical Engineering Graduate Program, UT Southwestern Medical Center, Dallas, TX 75390, USA.
Neuroimage. 2017 Feb 1;146:320-326. doi: 10.1016/j.neuroimage.2016.11.054. Epub 2016 Nov 23.
Cerebrovascular reactivity (CVR), the ability of cerebral vessels to dilate or constrict, has been shown to provide valuable information in the diagnosis and treatment evaluation of patients with various cerebrovascular conditions. CVR mapping is typically performed using hypercapnic gas inhalation as a vasoactive challenge while collecting BOLD images, but the inherent need of gas inhalation and the associated apparatus setup present a practical obstacle in applying it in routine clinical use. Therefore, we aimed to develop a new method to map CVR using resting-state BOLD data without the need of gas inhalation. This approach exploits the natural variation in respiration and measures its influence on BOLD MRI signal. In this work, we first identified a surrogate of the arterial CO fluctuation during spontaneous breathing from the global BOLD signal. Second, we tested the feasibility and reproducibility of the proposed approach to use the above-mentioned surrogate as a regressor to estimate voxel-wise CVR. Third, we validated the "resting-state CVR map" with a conventional CVR map obtained with hypercapnic gas inhalation in healthy volunteers. Finally, we tested the utility of this new approach in detecting abnormal CVR in a group of patients with Moyamoya disease, and again validated the results using the conventional gas inhalation method. Our results showed that global BOLD signal fluctuation in the frequency range of 0.02-0.04Hz contains the most prominent contribution from natural variation in arterial CO. The CVR map calculated using this signal as a regressor is reproducible across runs (ICC=0.91±0.06), and manifests a strong spatial correlation with results measured with a conventional hypercapnia-based method in healthy subjects (r=0.88, p<0.001). We also found that resting-state CVR was able to identify vasodilatory deficit in patients with steno-occlusive disease, the spatial pattern of which matches that obtained using the conventional gas method (r=0.71±0.18). These results suggest that CVR obtained with resting-state BOLD may be a useful alternative in detecting vascular deficits in clinical applications when gas challenge is not feasible.
脑血管反应性(CVR),即脑血管扩张或收缩的能力,已被证明在各种脑血管疾病患者的诊断和治疗评估中能提供有价值的信息。CVR映射通常在收集血氧水平依赖(BOLD)图像时,通过吸入高碳酸气体作为血管活性刺激来进行,但吸入气体的内在需求以及相关设备设置在将其应用于常规临床使用中构成了实际障碍。因此,我们旨在开发一种无需吸入气体,利用静息态BOLD数据来映射CVR的新方法。这种方法利用呼吸的自然变化并测量其对BOLD MRI信号的影响。在这项工作中,我们首先从全局BOLD信号中识别出自发性呼吸期间动脉CO波动的替代指标。其次,我们测试了将上述替代指标用作回归变量来估计体素级CVR的所提方法的可行性和可重复性。第三,我们在健康志愿者中用通过吸入高碳酸气体获得的传统CVR映射验证了“静息态CVR映射”。最后,我们测试了这种新方法在检测一组烟雾病患者异常CVR方面的效用,并再次使用传统气体吸入方法验证了结果。我们的结果表明,0.02 - 0.04Hz频率范围内的全局BOLD信号波动包含来自动脉CO自然变化的最显著贡献。使用该信号作为回归变量计算的CVR映射在各次运行中具有可重复性(组内相关系数ICC = 0.91±0.06),并且在健康受试者中与基于传统高碳酸血症方法测量的结果表现出很强的空间相关性(r = 0.88,p < 0.001)。我们还发现静息态CVR能够识别狭窄闭塞性疾病患者的血管舒张功能缺陷,其空间模式与使用传统气体方法获得的模式相匹配(r = 0.71±0.18)。这些结果表明,当气体激发不可行时,通过静息态BOLD获得的CVR可能是临床应用中检测血管缺陷的一种有用替代方法。