FMRI data modulators 1: Heart rate

It's 2027 and you are preparing to run a new fMRI experiment. Since 2023 you've been working on a custom 7 T scanner that was developed to mitigate several issues which plagued the early decades of fMRI. Long gone are the thermal shim and gradient drifts of yesteryear, courtesy of an intelligent water cooling system that maintains all hardware at near constant temperature even when the scanner is run flat out. Your scanner also has a custom gradient set with active shielding over the subject's chest. It means the rise time of the gradients is limited only by peripheral nerve stimulation in the subject's face and scalp, not by the possibility of causing fibrillation in the heart. You can use a slew rate four times faster than on the scanner you had back in 2017, meaning distortions of your 1 mm cubic voxels, acquired over the entire brain (including cerebellum!) are minuscule. What's more, your images no longer suffer from translations and shearing because of the subject's chest motion. Your scanner tracks the magnetic field across the subject's head and actively compensates for the effects of breathing. When used with the comfortable head restraint system that mates directly to the receiver electronics - which itself monitors changes in coil loading to ensure the 128-channel array coil doesn't impart its own bias field onto your images - you have finally got to the point in your career where you no longer worry about head motion.

Almost. There's no doubt the hardware of the future could be remarkable compared to today's scanners. Our current scanners are clinical products being used for science rather than scientific instruments per se. However, even if we were to supersede BOLD with a non-vascular "neural current" contrast mechanism, the basic physics of MRI suggests that we will have to consider real brain motion in the future, just as we do today. Perhaps we can differentiate this brain motion from the contrast of interest using multiple echoes or some other trick, but I don't envisage being able to ignore the brain's vasculature entirely, whereas I am optimistic that improved scanner engineering might one day ameliorate the mechanical and thermal instabilities. Real brain motion and regional variation in pulsatility are likely to be biological limits that must be accommodated rather than eliminated.


What are the mechanisms of concern?

We can restrain the subject's skull quite well using a bite bar or a printed case. Inside the skull, however, is a gelatinous blob of brain, highly vascularized, under a small positive pressure (the intracranial pressure, ICP). The brain will tend to throb with the heart rate (HR) as blood is pumped into the brain through the arteries. The arterial network is spatially heterogeneous and so we see heterogeneous motion across the brain. The arteries enter at the base of the brain, causing the entire midbrain and brainstem to move relative to the cortex. Locally, tissue close to large vessels can demonstrate greater displacements than tissue just a few millimeters away. These regional perturbations will arise with a range of delays relative to the cardiac output, as the blood pressure wave migrates from the heart. The greater the distance from the heart, the longer the lag. We'll see in a later post how this phenomenon can be used to estimate blood pressure.

There are also cardiac driven pulsations in the cerebrospinal fluid (CSF). These can be visualized as small displacements of tissue adjacent to the ventricular system as well as in sulci of the cortex. Pulsation in CSF and the changing velocity of blood in large vessels also tend to produce image contrast changes. This isn't real brain motion, of course, but it is a consideration if one is attempting to use local signal properties or overall image contrast to ameliorate regional pulsatility. A new paper by Viessmann et al. provides a timely investigation of the issues, concluding that fluctuations in partial volumes of blood and CSF/interstitial fluid give rise to local T2* changes over the cardiac cycle. So the final complexity is again temporal. The cardiac cycle is itself non-stationary, leading to dynamic changes in the locations of blood, CSF and brain tissue.