A regular reader of this blog had an excellent idea. She suggested discussing methods related to cerebrovascular physiology. I will thus try to come up with posts related to specific methods used to study cerebral blood flow, cerebral oxygenation, cerebral autoregulation, etc. This new section will also be used to answer your questions (to the best of my knowledge) regarding methods used in this research field. I don’t pretend to know everything. So if you have any comments to add to the discussion, it will be very appreciated!
In this first post, I am answering Jess Inskip’s questions.
Question: Why do some researchers describe mean CBFV as the arithmetic mean, while others use the integral under the envelope of the CBFV tracing? Surely the latter is more important, as it is the waveform that seems to be sensitive to perturbations rather than the raw SBF and DBF.
Answer: Mean cerebral blood flow velocity (Vmean) is measured using velocity associated with maximal frequencies of the Doppler shifts (envelope). Vmean can be used as an index of cerebral blood flow if we assume that: 1) maximal velocity is proportional to the mean velocity of the blood flow in the vessel; 2) the vessel’s cross-sectional area remains constant. Although Vmean in the MCA increases in parallel with the inflow of the internal carotid artery, with the initial slope index of the 133Xenon clearance-determined cerebral blood flow, and with regional cerebral blood flow measurements by positron emission tomography during exercise for example, some argue that changes in velocities associated with the maximal frequencies of the Doppler shift doesn’t necessarily reflect changes in flow. These authors use the intensity-weighted mean velocity (VIWM), which is based on the complete velocity spectrum. The latter represents a mean velocity averaged over the entire cross section of the blood vessel. However, while small changes in the angle of insonation of a cerebral artery is of no consequence for the maximal velocity, the average flow velocity is affected by the angle of insonation. So, other investigators such as Secher et al. (J Appl Physiol 2006) argue that changes in cerebral flow velocity during exercise are essentially lost when attention is not on Vmean.
Willie CK et al. J Neurosci Methods 196:221-237, 2011
Lohmann H et al. in Baumgartner RW (ed): Handbook on Neurovascular Ultrasound. Front Neurol Neurosci. Basel, Karger, 2006, vol 21, pp 1–10
Aaslid R et al. J Neurosurg 57:769-774, 1882
Poulin MJ et al. J Appl Physiol 86:1632-1637, 1999
Question: Is there a way to determine how to curve fit the relationship between PETCO2 and cerebral blood flow. Many seem to continue to define this as a linear relationship, yet other recent research groups have shown that this should be a sigmoidal relationship (even when these two groups seem to be working in the same PETCO2 ranges).
Answer: The utilization of the right model to study this relationship remains ambiguous to me. First, you need to choose the technique to evaluate the cerebrovascular reactivity to CO2. Accordingy to Ainslie (see Interesting reading for the reference), you need to choose the method to evaluate cerebrovascular reactivity to CO2 according to your experimental question, and a clear choice of method to study it (steady-state changes in CO2 vs. modified rebreathing) is problematic until the physiology of cerebrovascular control is better understood.
I think that, for the moment, it is the same for the determination of the right model to study the relationship between PaCO2/PetCO2 and cerebral blood flow, since there exists a plethora of models. Indeed, you can model steady-state cerebrovascular CO2 reactivity using a least squares linear regression, a biasymptotic curve analysis;, a dynamic single-compartment model, an exponential function, etc. When using modified CO2 rebreathing, a lot of studies used linear regression although some investigators demonstrated a non-linear relationship between PaCO2 and cerebral blood flow.
So, it is true that several studies are quantifying cerebrovascular reactivity to CO2 using a linear regression. One simple reason is that more complex modeling of cerebrovascular reactivity to CO2 is too complicated for clinical use. Also, more data points are needed with an exponential model vs. a linear model…Still, an interesting benefit with exponential models = more precise data fitting. This being acknowledged, a recent study suggests that the fitting strategy doesn’t seem to influence results…at least for the estimated PaCO2 range of interest (20-60 mmHg). So, is there a way to determine how to curve fit this relationship? It depends, most likely, on the aim of your study…
Question: Furthermore, if you are looking at CO2 reactivity at resting conditions and after perturbation X, what if one of the effects of the perturbation x is in fact altering the shape of the relationship between PETCO2 and CBF.
Answer: You have an excellent point. I don’t necessarily have the answer. What I can tell is that reactivity to CO2 is higher during hypercapnia vs. hypocapnia (potential mechanism: more important impact of vasodilator vs. vasoconstrictor mediators on vascular tone). In addition, factors such as hydration, caffeine, time of day, posture, etc. have an influence on the relationship between cerebral blood flow and reactivity to CO2. Finally, this relationship could also be affected by CO2-induced changes in arterial pressure.
Ainslie P et al. Am J Physiol Regul Integr Comp Physio 296: R1473-R1495, 2009