Department of Physiology, University of Toronto, Toronto, ON, Canada.
Department of Anaesthesia and Pain Management, University Health Network, Toronto, Canada.
Sci Rep. 2024 Jul 25;14(1):17121. doi: 10.1038/s41598-024-68047-w.
Resting cerebral perfusion metrics can be calculated from the MRI ΔR* signal during the first passage of an intravascular bolus of a Gadolinium-based contrast agent (GBCA), or more recently, a transient hypoxia-induced change in the concentration of deoxyhemoglobin ([dOHb]). Conventional analysis follows a proxy process that includes deconvolution of an arterial input function (AIF) in a tracer kinetic model. We hypothesized that the step reduction in magnetic susceptibility accompanying a step decrease in [dOHb] that occurs when a single breath of oxygen terminates a brief episode of lung hypoxia permits direct calculation of relative perfusion metrics. The time course of the ΔR* signal response enables both the discrimination of blood arrival times and the time course of voxel filling. We calculated the perfusion metrics implied by this step signal change in seven healthy volunteers and compared them to those from conventional analyses of GBCA and dOHb using their AIF and indicator dilution theory. Voxel-wise maps of relative cerebral blood flow and relative cerebral blood volume had a high spatial and magnitude congruence for all three analyses (r > 0.9) and were similar in appearance to published maps. The mean (SD) transit times (s) in grey and white matter respectively for the step response (7.4 (1.1), 8.05 (1.71)) were greater than those for GBCA (2.6 (0.45), 3.54 (0.83)) attributable to the nature of their respective calculation models. In conclusion we believe these calculations of perfusion metrics derived directly from ΔR* have superior merit to calculations via AIF by virtue of being calculated from a direct signal rather than through a proxy model which encompasses errors inherent in designating an AIF and performing deconvolution calculations.
静息脑灌注指标可以通过静脉内注射钆基对比剂(GBCA)的第一通过期的 MRI ΔR信号来计算,或者最近,通过短暂缺氧引起的脱氧血红蛋白浓度变化 ([dOHb]) 来计算。传统分析遵循一个代理过程,包括在示踪动力学模型中对动脉输入函数 (AIF) 进行解卷积。我们假设,当单口气终止短暂的肺缺氧时,[dOHb] 呈阶跃下降伴随的磁导率阶跃下降允许直接计算相对灌注指标。ΔR信号响应的时间过程既可以区分血液到达时间,也可以区分体素填充的时间过程。我们在七名健康志愿者中计算了该阶跃信号变化所隐含的灌注指标,并将其与 GBCA 和 dOHb 的常规分析进行了比较,这些常规分析使用它们的 AIF 和指示剂稀释理论。对于所有三种分析(r>0.9),相对脑血流量和相对脑血容量的体素图具有高度的空间和幅度一致性,并且与已发表的图相似。阶跃响应的灰质和白质的平均(SD)渡越时间(s)分别为 7.4(1.1)、8.05(1.71),大于 GBCA 的 2.6(0.45)、3.54(0.83),这归因于它们各自的计算模型的性质。总之,我们认为这些直接从 ΔR*计算得出的灌注指标的计算优于通过 AIF 的计算,因为它们是从直接信号而不是通过包含指定 AIF 和执行解卷积计算固有误差的代理模型计算得出的。