Kainerstorfer Jana M, Sassaroli Angelo, Hallacoglu Bertan, Pierro Michele L, Fantini Sergio
Department of Biomedical Engineering, Tufts University, 4 Colby St, Medford, MA 02155.
Department of Biomedical Engineering, Tufts University, 4 Colby St, Medford, MA 02155.
Acad Radiol. 2014 Feb;21(2):185-96. doi: 10.1016/j.acra.2013.10.012.
Perturbations in cerebral blood volume (CBV), blood flow (CBF), and metabolic rate of oxygen (CMRO2) lead to associated changes in tissue concentrations of oxy- and deoxy-hemoglobin (ΔO and ΔD), which can be measured by near-infrared spectroscopy (NIRS). A novel hemodynamic model has been introduced to relate physiological perturbations and measured quantities. We seek to use this model to determine functional traces of cbv(t) and cbf(t) - cmro2(t) from time-varying NIRS data, and cerebrovascular physiological parameters from oscillatory NIRS data (lowercase letters denote the relative changes in CBV, CBF, and CMRO2 with respect to baseline). Such a practical implementation of a quantitative hemodynamic model is an important step toward the clinical translation of NIRS.
In the time domain, we have simulated O(t) and D(t) traces induced by cerebral activation. In the frequency domain, we have performed a new analysis of frequency-resolved measurements of cerebral hemodynamic oscillations during a paced breathing paradigm.
We have demonstrated that cbv(t) and cbf(t) - cmro2(t) can be reliably obtained from O(t) and D(t) using the model, and that the functional NIRS signals are delayed with respect to cbf(t) - cmro2(t) as a result of the blood transit time in the microvasculature. In the frequency domain, we have identified physiological parameters (e.g., blood transit time, cutoff frequency of autoregulation) that can be measured by frequency-resolved measurements of hemodynamic oscillations.
The ability to perform noninvasive measurements of cerebrovascular parameters has far-reaching clinical implications. Functional brain studies rely on measurements of CBV, CBF, and CMRO2, whereas the diagnosis and assessment of neurovascular disorders, traumatic brain injury, and stroke would benefit from measurements of local cerebral hemodynamics and autoregulation.
脑血容量(CBV)、脑血流量(CBF)和脑氧代谢率(CMRO2)的改变会导致氧合血红蛋白和脱氧血红蛋白组织浓度的相关变化(ΔO和ΔD),这可以通过近红外光谱(NIRS)测量。一种新的血流动力学模型已被引入,以关联生理扰动和测量量。我们试图使用该模型从随时间变化的NIRS数据中确定cbv(t)和cbf(t) - cmro2(t)的功能轨迹,并从振荡NIRS数据中确定脑血管生理参数(小写字母表示CBV、CBF和CMRO2相对于基线的相对变化)。这种定量血流动力学模型的实际应用是NIRS临床转化的重要一步。
在时域中,我们模拟了由脑激活引起的O(t)和D(t)轨迹。在频域中,我们对在定频呼吸范式期间脑血流动力学振荡的频率分辨测量进行了新的分析。
我们已经证明,使用该模型可以从O(t)和D(t)可靠地获得cbv(t)和cbf(t) - cmro2(t),并且由于微血管中的血液传输时间,功能性NIRS信号相对于cbf(t) - cmro2(t)延迟。在频域中,我们确定了可以通过血流动力学振荡的频率分辨测量来测量的生理参数(例如,血液传输时间、自动调节的截止频率)。
进行脑血管参数的无创测量的能力具有深远的临床意义。功能性脑研究依赖于CBV、CBF和CMRO2的测量,而神经血管疾病、创伤性脑损伤和中风的诊断和评估将受益于局部脑血流动力学和自动调节的测量。