My Wish List for the Ultimate fMRI System

 

The ultimate MRI scanner cake my wife made about 6 years ago to celebrate both the 50th birthday of my colleague Sean Marrett and the installation of our new 7T scanner.

I recently had a meeting where the topic discussed was: “What would we like to see in the ideal cutting edge and future-focussed fMRI/DTI scanner?” While those who use fMRI are used to some progress being made in pulse sequences and scanner hardware, the technological capability exists to create something substantially better than we have now.

In this blog posting, I start out with a brief overview of what 
we currently have now in terms of scanner technology. The second part of this blog is then focussed on what my ideal fMRI system would have. Lastly, the article ends with a summary outline of my wish list – so if you want to get the gist of this blog, scroll to the list at the bottom. Enjoy and enter your comments! Feedback, pushback, and more ideas are welcome! 

What is the current state of fMRI technology now?

Field Strength:

The world has over fifty 7T systems. I would estimate that at least a third of these are, for the most part, “turn-key.” The field has wide bore 3T systems – allowing for greater patient comfort and the ability to fit more or bulkier subject interface devices inside. GE has come out with a prototype head only 3T system at Mayo Clinic that has an incredibly small footprint and much less need for liquid helium as a coolant. The NIH is also planning to receive a human 11.7T scanner, hopefully by next year, after the first one quenched several years ago. Soon, 7T will achieve FDA clearance, and when it does the price of a 7T will perhaps (hopefully) drop from the currently prohibitive $8M to $10M down to (a less prohibitive) $7M or less as the clinical market grows. 

Pulse Sequences and Image Reconstruction:

With few exceptions, the current fMRI scanners are clinical scanners. This means that they have the latest clinically relevant pulse sequences – some that carry over to fMRI applications, including a version of susceptibility weighted imaging (SWI), diffusion imaging, and high tissue contrast capability.

Most scanners now have some form of parallel acceleration (such as SENSE, GRAPPA, or derivatives) – allowing higher resolution for fMRI and DTI, and shorter scan times for structural imaging. Some scanners, assuming there is a research agreement in place, have access to the latest novel pulse sequences for fMRI, namely “simultaneous multi-slice” (SMS) and multi-echo. SMS allows entire multi-slice volumes to be obtained in ½ to ⅛ the time of standard acquisition. Multi-echo has advantages that come with collecting multiple (up to five) simultaneous and differentially T2*-weighted time series – allowing time series cleanup and at the very least, increased temporal SNR and CNR.

What the field does NOT have is an easy way for researchers to create, share, and test pulse sequences and reconstruction methodology across scanners and vendors. It’s difficult, even for a skilled MR physicist, to modify a product pulse sequence – not because pulse sequence programming is intrinsically complicated but because the operating environment many vendors is somewhat of a mess – patched together from outdated platforms, and modified over the years without major overhauls. While it may be slightly easier to modify an extremely simplified pulse sequence, it’s then much more difficult to then add the appropriate safety checks that are required for distribution.  This entire mechanism could be cleaned up substantially, allowing researchers to focus more on pulse sequence innovation than navigating the pulse sequence programming idiosyncrasies.

Regarding image reconstruction, with some work, it’s possible to save raw data and then port to another computer to perform reconstruction. This is generally cumbersome and vendors don’t typically give out the code to their proprietary reconstruction methods, so the images that are independently reconstructed are typically never as good as those of the scanners themselves. This is also a source of concern as such things as image smoothing, image unwarping, and other operations are performed in the background, further amplifying the differences in images coming from different vendors and scanners. 

At the NIH, a gadgetron was created that takes raw data from scanners across several vendors, so that such a reconstruction, comparison test-bed could be used. This is a model for what should be commonly available on all future scanners – helping recon development and reducing variability across scanners. This would be a more effective tool if it could start with the vendors’ latest recon code, and then have it modified to reduce variability across scanners or at the very least allow for a more accurate scanner comparison. 

Gradient Coils:

Gradients have improved. The most advanced commercial scanner at the moment, the Siemens 3T Prisma, have a maximum gradient strength of 80 mT/m or 8 Gauss/cm, and a maximum slew rate of 200T/m/s. This slew rate, coming from a whole body gradient system, is enough to exceed biologic limits on dB/dT (the rate of change, per unit time, of the B-field), causing peripheral nerve stimulation.

The most powerful human scanner built to date is the Human Connectome Scanner – also a 3T and made by Siemens. The first system resides at the Massachusetts General Hospital Martinos Center. A second system is planned for Cardiff University in the UK. It has gradients in which each axis has four parallel drives that are independently powered by two sources per gradient, performance specs of 300 mT/m gradient strength, a standard slew rate of 200T/m/s, and has the power requirements of a nuclear submarine. 

Manufacturer constructed head gradient coils have claimed performance specs that include a maximum gradient strength of 85 mT/m and a stunning 700 T/m/s slew rate. Indeed the connectome scanner is optimized for diffusion imaging, requiring large gradients, and the prototype head gradient coils mentioned are optimized for high speed imaging with a higher possible – and allowed –  high slew rate. With the high slew rates, gains can also be made in diffusion imaging, as the higher slew rate enables the appropriate diffusion weighting to be achieved in less time, thus boosting signal to noise.

An important factor when thinking of gradient coils is that the local head gradient coil can switch much faster than a whole body gradient coil when scanning humans not only because it has lower inductance, but most importantly, because the gradients do not extend much beyond the head coil itself, thus keeping the maximum dB/dT at the extreme ends around isocenter at a level below that which would cause peripheral nerve stimulation. This shorter length of the coil allows greater flexibility in how fast the gradients can switch, benefitting other sequences than just diffusion weighting.

Radiofrequency Coils:

RF coils have steadily improved since the 90’s when single channel “quadrature” coils were the norm. Since about 2000, multi-channel receive coils have become more popular, starting with 4 then 8 then 16 channels. Now, at 3T, 32 channel receive coils are the norm. The advantages are two-fold. First, with smaller coils (and an array of small coils to maintain whole brain coverage), there is an increase in signal to noise ratio. Second, with the various parallel imaging techniques, the coils themselves, because of their non-overlapping sensitivity profiles and spatial distribution, aid in spatially encoding the data, saving time and improving some aspects of image quality.

Shim Coils:

When a head is placed in a scanner, it distorts the magnetic field. If these field inhomogeneities are not corrected, then the image quality suffers. Warping and signal dropout are common manifestations of an inhomogeneous magnetic field that has been poorly shimmed. Typically, shimming is performed to smooth out the magnetic field. The basic operation of shimming involves adjustment of the current in coils situated in the bore of the magnet. In the past decade, auto-shim algorithms have been able to take the user out of this process, speeding up the procedure. The shims on most magnets are designed to approximate the spherical-harmonic functions. These functions are orthogonal (independent) over any sphere centered at the origin. This approach (resistive shims up to 2nd or 3rd degree) works sufficiently well for most high resolution, multi-shot, clinical pulse sequences, however, as anyone doing EPI at 7T can tell you, they still fall far short of satisfactory. Especially at high fields, low resolution EPI results in signal dropout, and high resolution EPI results in extreme warping. I believe we have the technology to solve this. It’s just a matter of implementation. A possible remedy is described in the second part of this blog. 

Motion Correction:

Post processing methods perform well but not perfectly in motion correction. Still, any motion near a signal intensity gradient or beyond about 1 mm, is imperfectly corrected – and the data are typically thrown out. Couple that with spin-history effects, etc..we have room to improve. Motion compensation on the acquisition end has shown promise. We have navigator pulses for multi-shot imaging as well as devices that measure displacement optically then feed that information back to the gradient settings to compensate for each line of k-space. These approaches also have variable success and are mostly aimed at cleaning up single, multi-shot structural images associated with standard clinical use of the scanners.

Other Features:

What are the other features that are potentially more widely useful in a scanner that have been implemented in some form now? One that comes to mind are simultaneous positron emission tomography (PET) and MRI scanners. These have PET detectors positioned in the bore so that both MRI and PET images may be obtained simultaneously. This is admittedly a very niche market as most PET/MRI comparisons can easily be done separately. Only with the observation of either very transient effects or non-repeatable effects does this approach shine. My sense is that more experiments will be devised that capitalize on the simultaneity of the collection of this information.

Another feature would be better integration of subject interface devices with the scanning environment. Currently visual and auditory stimuli as well as button boxes, eye trackers, etc.. are fitted in an ad-hoc manner into clinical scanners, requiring a relatively large amount of setup time. All these could be integrated into an fMRI scanner such that they are always available and ready to go.

What would I want in the ultimate fMRI system?

 

Field Strength:

7T is definitely where both fMRI and structural imaging are going. The gains in SNR, CNR, and they qualitative types of unique contrast are clear for both fMRI and clinical applications. For clinical applications, one can much more easily see gray matter plaques in MS and iron deposits with various disorders. Susceptibility contrast provides exquisite detail in imaging the venous vasculature and iron deposits, and the higher SNR allows for gains in resolution and/or speed. The issues involved with specific absorption rate (SAR), shim, RF inhomogeneity, and different relaxation rates are all solvable at 7T. For functional MRI, the gains in studying resting state fMRI are clear, as physiologic noise (including spontaneous neuronal activation induced fluctuations) even further dominates the signal. The imaging of cortical layers and orientation columns has only been demonstrated at fields at or above 7T. This resolution and the increased sensitivity to fluctuations balanced with our ability to solve the engineering hurdles clearly points to 7T as the desired field strength. The gains made at higher fields than 7T are not clear yet, as the engineering problems associated with going higher currently appear much more challenging. So, my perfect fMRI scanner field strength would be a 7T.

Pulse sequences and Reconstruction:

The field of fMRI has been neglected by vendors for the past quarter century. Creating and implementing a pulse sequence is perhaps analogous to writing a novel in machine language rather than using a word processing program. Regarding fMRI, there is the untapped potential of novel pulse sequences for looking at different functional contrasts, simultaneous acquisition of complementary contrasts (flow, BOLD, volume, etc..), high resolution, etc.. The development and testing of pulse sequences would be significantly accelerated if we had the equivalent of Microsoft Word for pulse sequence development, or at the very least, and open access structure for writing, testing, and disseminating pulse sequences. The rate at which new pulse sequences for fMRI are disseminated through clinical vendor product releases or even as works in progress to researchers is somewhat anemic. An example: Arterial Spin Labelling. This sequence, tremendously useful for noninvasively measuring baseline perfusion and activation-induced perfusion changes, was invented and patented in the early 90’s. It was only until the patent ran out (17 years later) that it became a feature on most clinical scanners.

We need a more robust research environment for developing, testing, and disseminating new pulse sequences. If a Microsoft Word – type platform is out of the question. It would be extremely helpful for pulse sequence development if the vendors created a modular sequence allowing researchers to play with multiple knobs easily. If such a sequence were developed, fMRI acquisition sophistication and diversity would grow more rapidly, but of course ultimately, we are limited by our own imaginations.

One example of what has worked for me over the years was an all purpose modular and easily modifiable pulse sequence. Back in the 90’s, Eric Wong and his colleagues developed a “swiss army knife” of pulse sequences called “spep.” It was highly modular, allowing almost complete control of RF pulses, gradient placement, readout window placement, resolution – all adjustable using adjustment of single variables, called CV’s or control variables, in the code. It led to the development of several novel ASL sequences (QUIPPS, Q2TIPS for example) and has been instrumental to my own research exploring multi-echo EPI, the effects of diffusion weighting on fMRI, and many other projects. 

Regarding image reconstruction, all fMRI researchers would benefit substantially from an open and entirely modifiable reconstruction platform provided by the vendor. As mentioned above, one platform created by users, called the gadgetron, takes raw k-space data from multiple scanners and applies a reconstruction algorithm to it. It cannot be emphasized how important it is for something like this to exist and be vendor supported – as it opens up a source of potential standardization across scanners as large multi-scanner fMRI and DTI databases are being created. Currently, vendors do not typically supply recon code, so those programming the gadgetron  have been starting mostly from scratch. 

In today’s environment of open, fully sharable data, it’s essential, at the very least, to know precisely how the images were created, and then perhaps establish a standard reconstruction across vendors, substantially reducing image variability across vendors. Again, we referring to our home built pulse sequence mentioned above: “spep” as an example. This sequence relies on a stripped down recon, and the images differ substantially from those produced using the product recon – thus limiting its utility. If researchers develop pulse sequences, they should have access to the image recon code. 

Gradient Coils:

The issue of gradient coils is tricky as there is not one ideal configuration. The need for whole body imaging is sometimes useful – even for fMRI, thus requiring whole body gradients. However, most fMRI researchers would be happy with a head gradient coil that allows easy patient access and all the advantages that come with it.

The ideal fMRI scanner would perhaps have both a body coil and a modular insert gradient coil with two modes – high slew rate and high gradient strength. The high slew rate would use less windings and the high gradient strength would use more windings – all changeable by the flip of a switch – or even electronically – allowing each configuration to be activated during a pulse sequence (i.e. very short readout window EPI with high diffusion weighting gradient lobes).

The head coil would be able to switch gradients faster without inducing peripheral nerve stimulation. Simulations have shown that a head gradient coil could slew to 100mT/m (more than sufficient for most purposes) at a slew rate of 700 mT/m/s without inducing peripheral nerve stimulation, while a whole body gradient could slew to 100mT/m with a slew rate of only 100 mT/m/s without inducing peripheral nerve stimulation.

As I mentioned before, until vendors start caring more about fMRI development (which is until fMRI becomes more clinically relevant) these exciting, and quite achievable capabilities will likely go unfulfilled.

Radiofrequency Coils:

RF receive: While the standard RF coil arrays used today consist of up to 32 channels, it’s not clear to me if more will result in clear improvements. It is clear that there is considerable room for improvement in coil configuration. In an array coil placement could be optimized either for SNR gains or for spatial encoding as with SENSE, SMASH or even SMS imaging. Currently, we make do with one configuration for both. Coil placement could also be much closer to the head. Flexible coil caps or rigid configurations that fit much more snugly at least above the eyes and down the back of the head would substantially improve SNR.

RF excitation: RF receive coils have been discussed but, so far, no vendor has a seamless multi-channel excitation package. Having multiple excitation coils is useful for several purposes. The first and foremost is that their power can be independently adjusted to “RF-shim” or make a more homogenous excitation distribution such that the RF flip angles are uniform throughout the brain – making for more interpretable contrast. This feature is still being developed. A major obstacle is the risk that once RF power is set for each coil, there man be unforeseen “hotspots” in RF power, exceeding the current SAR limits and potentially heating the subject. So far, no clear solution has been proposed to this problem. The second feature is that different coils, in theory, could be tuned to excite different frequencies or frequency widths – allowing for simultaneous spectroscopic imaging or magnetization transfer imaging. This would be extremely advantageous to multiple fMRI studies.

Shim Coils:

As suggested above, there are clear limits to adding more orthogonal shim coils. The amount of current needed for fully shimming the head at 7T is currently not practical. Even with third order shims are not effective in creating a homogenous field around sharply defined field inhomogeneities near the ears and sinuses. While the effect of the currently poor shimming performance is minimal with normal clinical imaging, at 7T with either high resolution (warping) or low resolution (signal dropout) it is still prohibitive. For the perfect fMRI scanner, I think alternative solutions are possible. Each solution is also “stackable” in that they can be used together in a synergistic manner. Shim can indeed be “solved.”

Shim coils closer to the head: Strategies have been proposed to use the RF coils to support an adjustable DC current. This should be standard on all scanners.

Specialized, anatomically specific shim coils: Strategies have also been proposed that involve placement of specific shim coil loops on the nose or at the ears. These have been shown to be quite effective as the small field distribution around these small, close to the head coils can effectively target the small sharply varying fields around sinuses and ears.

Non-orthogonal multi-shim array: A recently introduced alternative has been multi-coil shim array – up to 128 loops of wire driven independently offers more power and flexibility in counteracting field homogeneities induced around and inside the head at high fields. Here, the solutions are arrived by iteratively calculating the fields necessary for each coil to target specifically focused inhomogeneities.

Shim strategy: slice specific shims. When shimming is carried out – in particular with orthogonal shim coils – eliminating field inhomogeneity in one part of the brain can come at a cost of creating greater field inhomogeneities in another part of the brain. One solution that has been demonstrated is slice specific shimming. This solution would require rapidly switching the shim coil currents between slice collection, requiring more power in the shim current amplifiers – all very doable.

Strategically placed passive shims: It has been shown many years ago that strategic placement of diamagnetic materials of specific shapes on or near the head – or even in the mouth, can help smooth out some of the more problematic field inhomogeneities. While perhaps a bit cumbersome, one could imaging subjects wearing a “shim mask” to achieve this purpose.

Field cameras: Lastly, the effect on Bo by breathing has not been mentioned at all because it’s not at all compensated for in standard scanners. At high field, it has a very pronounce effect, especially if performing multi-shot EPI for fMRI. There currently exist “field cameras” that measure the dynamic changes in Bo that occur. These are quite expensive but potentially game changing when it comes to removing breathing related artifacts in fMRI. Having a field camera setup with each scanner and then using it for prospective motion correction by feeding the Bo field information either to the shims and/or to the gradients, would substantially increase stability.

Shim parameter settings: Lastly, it’s clear that most heads are more or less the same. Typically shimming takes time because the shimming procedure starts from scratch for each subject. Long ago our 3T Bruker scanner had the option for saving shim settings for each subject. An alternative solution would be to have perhaps 5 differing “starting” shim settings to account for most head types. This would save considerable time in shimming as the algorithms would start much closer to the “solution.”

Motion Correction:

Again, the clinical vendors have favored motion correction strategies that target standard clinical imaging. While these are somewhat effective, they fall short for EPI sequences used in EPI. One approach to prospective motion involving using optical sensors on specific targets (currently a moire pattern), involves detection of motion and then feeding back that information to the gradients to compensate. This approach has been a disappointment so far. I believe that a simple optical camera that images the entire head, then using that information fed back to the scanners, would perhaps be more robust for prospective motion correction.

With fMRI, high resolution is a desired feature. Common single shot EPI solutions have been parallel imaging, zoomed imaging methods, or partial k-space imaging. Recently multi-shot techniques, particularly 3D EPI, have been experiencing a resurgence. However, these approaches suffer from time series instability that only becomes a non-factor when the time series SNR is so low that thermal noise matches time series instability. In the past navigator pulses have been used for phase correction in multi-shot time series. Having navigators implemented in these sequences would greatly enhance their utility for fMRI.

Other Features:  

As PET is experiencing something of a resurgence, especially since it is so complementary to many fMRI studies, it makes sense to have a built in PET capability that is not too spatially intrusive and does not interfere with scanner, gradient, or shimming performance. Currently, robust PET/MRI capability exists. 

In addition to a PET scanner it seems reasonable that such capabilities as in-scanner EEG, TMS, optical imaging, and tDCS could be engineered into the scanner, allowing easy use when needed.

Real time fMRI, with an open pipeline allowing for open access real time analysis, would also be essential – especially for pushing fMRI into the clinical realm. In the clinical setting, it’s essential to obtain usable information quickly. This information would range from time series quality and subject motion – determining if the scans need to be redone – to functional maps that allow clinicians to make decisions. While vendors provide the ability to see the raw images come up in real time, a seamless, open access pipeline to raw k-space data or image data, and a seamless time series processing platform would be essential.

Quieter pulse sequences, quieter gradients, or active noise cancellation in the bore: A major drawback in MRI and fMRI is the extreme loudness of the scanner during the scanning process. Sound levels are in the range of 130 dB. In the base RARE or BURST sequences have proven to be substantially quieter, and, perhaps with navigator pulses (as they are multi-shot) could be useful for many fMRI applications that require less scanner noise.

While vendors have worked towards developing quieter gradients, more EPI specific engineering could go further – as the higher frequency “vibrational modes” associated with a range of EPI gradient readouts could be dampened with the correct reinforcement.

Active noise cancellation. This technology has been around for some time and has been implemented with variable success in headphones in the scanner, a major limitation of sound canceling headphones is that most of the sound is still transmitted through the skull so the net attenuation is only about 30dB. I’m not certain if it is possible, but perhaps an entire bore sound cancellation device might prove effective in canceling the noise before it even reaches the head.

Lastly, it would be tremendously useful to have some sort of non-compete agreement between vendors in the research arena, so that the scanner business is forced to be consistent with the movement towards open science. While companies can continue to compete in the clinical arena, this competition is no reason to hold back progress in fMRI research.  Accompanying this open access environment would be an open technical fMRI community that would be able to share vendor experiences, pulse sequences, image reconstruction algorithms, processing methods, hardware, and other aspects of fMRI seamlessly.

—-

 

Below is a list summarizing all the desired features on an fMRI-optimized scanner that I have discussed above.

 

  1. Field strength: 7 Tesla
  2. Pulse sequences and recon:
    • Open-access platform for pulse sequence development and sharing
    • Single highly modular and easily modifiable pulse sequence.
    • Navigator pulses for multi-shot fMRI pulse sequences.
    • Silent RARE or BURST type pulse sequences.
    • Open access image reconstruction code across vendors.
  3. Gradient Coils:
    • Head insert with high slew rate mode (for readout) and high gradient mode (for diffusion weighting), electronically switchable.
    • Body Coil if outside of neck ASL tagging or just BOLD of lower spine is needed.  
  4. RF coils:
    • Customized separate coil configurations for high SNR and parallel imaging
    • 32 channels
    • Flexible and closer to the head coil configurations.
    • Multi-channel and configurable multi-band (and bandwidth) with accompanying RF shim algorithms that are simple and easy to use.
  5. Shim Coils:
    • Both orthogonal and non-orthogonal multi-coil configurations.
    • Location-targeted local shim coils.
    • Option for mask with passive shims.
    • Use of RF coils for shims.
    • Slice dependent shimming.
    • Save-able or pre-set shim settings for head types.
  6. Motion correction:
    • Navigator pulses for multi-shot fMRI sequences.
    • Whole head image based prospective motion correction. 
  7. Other features:
    • Simultaneous PET and fMRI
    • Scanner engineered simultaneous TMS, EEG, tDCS, and optical imaging.
    • Real time fMRI with open access to k-space and image data.
    • Quieter pulse sequences, gradients, and/or bore-wide active noise cancellation.
    • Reduced vibrational nodes for gradients at EPI frequencies.
    • Non-compete, open science agreement by vendors for non-clinical market.
    • Open fMRI community to share scanner experience, ideas, pulse sequences, image reconstruction methods, and hardware.

 

Author: Peter Bandettini

Peter Bandettini has been working in functional brain imaging since he started his Ph.D. thesis work on fMRI method development in 1991 in the Biophysics Department at the Medical College of Wisconsin (MCW). After completing a post doc at Massachusetts General Hospital in 1996 and a brief Assistant Professorship at MCW, he became Chief of Functional Imaging Methods and Director of the Functional MRI Facility at the National Institutes of Health in Bethesda, MD. He is also Editor-In-Chief of NeuroImage and has been active in both the MRI community (International Society for Magnetic Resonance in Medicine) and the Brain Imaging Methods community (Organization for Human Brain Mapping). All his views and posts are his own.

6 thoughts on “My Wish List for the Ultimate fMRI System”

  1. Nice summary and wish-list, Peter…all at hand or within easy reach.
    Now after spending my career in the lab chasing these goals largely for a relatively small community of scientists affording the highest fields and fanciest facilities for human In-vivo, I have another wish-list that would include practical considerations like cost, field-supportability, accessibility, portability, and ease-of-use, all without compromise to performance, that would extend our science labs to the rest of the world. This wish list is requiring some rethinking about how we do MRI, and opens up a lot of new possibilities. As we RF guys say, “stay tuned!”

    T.

    1. Thanks Tommy. I’m definitely interested in hearing more of your ideas. Especially intrigued about the rethinking of how we do MRI…and yes, my own wish list did not include most of practical considerations that constrain us all.

  2. Hi Peter, Thanks for the comprehensive list! We’ve been looking closely at head motion and motion-related errors (MRE) a lot in the past few years, and at this point my suspicion is that the floor in “latent motion” is actually defined by chest motion rather than direct mechanical motion of the head. This is at 3 T, so would be doubly true at 7 T. The problem with all attempts at motion correction as performed today, whether real time during acquisition or in post processing, is the assumption of linearity, often treating the image volume as a rigid body. Moving to slice-based corrections would be a step in the right direction, as would slice-by-slice shimming. The latter would be particularly useful because it would be possible in principle to start to tackle some of the non-linearity imposed by motion (head or chest) due to the field sensitivity of the phase encode axis in particular (i.e. distortion during EPI readout).

    These considerations are causing me to want to think of shimming, gradient (switching) speed and motion as three sides of the same box. We can reduce the sensitivity to non-linear shim perturbations by switching more quickly. But to do that requires getting the heart out of the high region of dB/dt. An asymmetric gradient set is one way. But active body shielding would be another. Let’s say we have some sort of pickup loop shielding that gets rid of the largest components of switched field across the chest. If that shielding was on the chest then in all likelihood it would make chest-based modulation of magnetic field across the head even worse! But what if the switched field shielding was fixed in space, while other pickup loops on the chest determined where the chest was in such a way that the modulation of field across the head could be computed? It might be possible to use the system as a continuum to update the shims across the head slice-by-slice to offset the chest motion, while simultaneously offsetting the health risk from faster switched gradients. The goal would be to get the gradient speed boosted until peripheral nerve stimulation in the face or neck were limiting, while simultaneously stabilizing the head signals from perturbation by chest motion.

    Final thought, related to the speed limit imposed by PNS in the neck/face. What I would like to see is an fMRI scanner specification determined in reverse from the biological limits we know and understand. We have good estimates for the point spread function of vascular contrast mechanisms, for example. This gives us a target specification for voxel size, with smaller voxels giving us diminishing returns unless the contrast mechanism is altered. For whole brain coverage we know we need to sample not slower than 2 sec, giving us a minimum spatial-temporal specification. Let’s say 1 mm voxels in 1 sec, whole brain, for some round numbers. Our current understanding of neurovascular coupling and the PSF suggests that going smaller or faster would produce modest gains right now, but I’m not against halving all the numbers to make it a moon shot!

    1. Thanks for these insightful comments! Regarding your first point, I tend to agree the chest motion is a problem and it’s nonlinear. In addition to what you mentioned. The use of a Bo field camera may help correct this. I really like the concept of an active body dB/dt shield. Never really thought of that! Great concept that might push the limits of what we can do. Gradient coil geometry does has some effect but still, at the neck/face, the limits might be unavoidable (as you mention). I also like the idea of using a target dB/dt approach to engineering an entire system! Perhaps you might want to post something on your blog on that! There really are so many interesting directions and possible solutions to try!

      1. Hi Peter, when we use our printed head restraints along with fast sampling (e.g. with MB-EPI) we see quite clearly the effects of chest motion, yet the amplitude of the “high frequency” (i.e. respiratory) signal modulations is very similar to conventional foam head restraint. This is what’s leading me to think that we might be barking up the wrong tree wrt the minimum achievable subject motion. Further circumstantial evidence in support of chest motion being the limit comes from the recent stable trait papers, especially the finding that body-mass index (BMI) is a good predictor of a subject’s “head motion.” Larger chests should generate larger modulation of B0, of course, but there is also the potential relationship between body size and cardiovascular fitness which likely determines depth and frequency of breaths. Whatever detection method is used – field probes, cameras, what have you – I think the key will be to provide real time updates to the shims slice-by-slice. Anything less will leave the non-linear effects of field perturbation in the image. It’s a tricky problem but my sense today is that this is the motion-limiting regime people are running into when comparing across groups.

        Wrt shielding the heart from the switched fields, I know Richard Bowtell has worked on this sort of thing. I seem to recall Peter Mansfield may have worked on an E-field shield of some sort a while ago, too. When I have some time I’ll review the literature and find out what the state-of-the-art looks like.

  3. Thanks Peter for this wonderfull list !
    – What about the post-processing ? What could be for you Expectation of a Software processing fMRI (including DTI ? same time ?) ?
    Regards
    Bruno

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