After a very long wait that spanned two prefabricated buildings - we weren't supposed to call them trailers, some sort of negative connotation - the Henry H. Wheeler, Jr. Brain Imaging Center took its first step into a permanent home yesterday with the move of the BIC's existing 3 T Siemens Trio scanner into one of the magnet bays in Li Ka Shing Center for Biomedical and Health Sciences (LKS). With space for two 3 T MRIs, a 7 T MRI, a MEG and a host of functional support facilities, including TMS and EEG prep rooms as well as mechanical and electrical workshops, there will be quite a lot of moving in to be done over the years ahead. For the time being, however, the task is to get the very busy Trio back up and scanning as quickly as possible. Here are a few pictorial and video highlights of the magnet move, with a couple of interesting and hopefully educational features indicated.
The magnet had been ramped down a week before, allowing a lot of preparatory work disconnecting cables and getting access to the removable roof section above the scanner's old home. In this photo you can see the copper foil of the removable roof section, a component of the scanner's Faraday shield (to reject external RF):
The removable roof section was lifted out by crane:
Then the magnet, weighing some 32,000 lbs with the patient table sled attached and the cryostat full of liquid helium, was lifted out and staged in an adjacent parking lot:
Wednesday, May 23, 2012
Tuesday, May 22, 2012
More fMRI experiments are ruined by subject motion than any other single cause. At least, that is my anecdotal conclusion from a dozen years' performing post-acquisition autopsies on "bad" data. The reasons for this vulnerability are manifold, starting with the type of subjects you're trying to scan. You may be interested in people for whom remaining still is difficult or impossible without sedation of some kind.
However, I think there is another reason why many (most?) fMRIers end up with more subject motion than is practicable: they haven't taken the time to think through the different ways that subjects can thwart your best efforts. In other words, what we are considering is largely experimental technique, or bedside manner as medical types refer to this stuff.
With the possible (and debatable) exception of bite bars, which aren't popular for myriad reasons, there is no panacea for motion. Why? As we shall see, it's not just movement of the head that's a concern. You need to consider a subject's comfort, arousal level, propensity to want to breathe, and many other things that might be peripheral to your task but are very much on the mind of your (often fMRI-naive) subjects.
Now, before we get any farther I need to outline what this post will cover, and what it won't. The focus of this post is on single-shot, unaccelerated gradient echo EPI - the sort of plain vanilla sequence that the majority of sites use for fMRI. I won't be covering the effects of motion on parallel imaging such as GRAPPA, for example. I will also restrict discussion here to the effects of motion on axial slices. Hopefully you can extrapolate to different slice prescriptions. But, rest assured that this isn't the last word in motion, not by a long chalk. Motion has come up before on this blog, e.g. in relation to GRAPPA for EPI, and the ubiquity of the problem implies that the issue will arise in many subsequent posts, too. Take today's post as an introduction to the general problem.
My final caveat on the utility of today's post. As this blog is focused on practical matters I will restrict the bulk of the discussion to things that you'll see and can control online, in real time. There are many tools that can be used to provide useful diagnostics post hoc, some of which I will mention. But this isn't a post aimed at showing you what went wrong. Rather, the intent of this post is to describe what is going wrong, such that you might be able to intercede and fix the situation. Some sites have useful real-time diagnostics that can tell you when (and perhaps how) a subject is moving, but they aren't widespread. Thus, for today's post we shall keep things simple and restrict the discussion to what can be seen in the EPIs themselves, as they are acquired.
WARNING: If you haven't run an fMRI experiment in a while then you might want to stop reading this post here and go and review the earlier post, Understanding fMRI artifacts: "Good" axial data. That post highlights our target: the low motion case.
Let's start simply. Here is a video of a subject intentionally moving his eyes to a target. Saccading is the technical term, I hear. (See Note 1 for experimental details. Parameters were fixed throughout for this post, unless mentioned to the contrary in any section below.) There are twenty volumes played back at a rate of 5 frames/sec:
Tuesday, May 1, 2012
Whatever you call them - spikes, sparks or arcs - the presence of unwanted electrical discharges during data acquisition can have a dramatic effect on the appearance of your EPIs and will likely result in poor or unusable data. (See Note 1.) There are many potential sources of unwanted electrical discharges - what I shall refer to as spikes for the rest of this post, regardless of the origin - in and around an MRI scanner. They can arise from within the scanner itself, or from items in the magnet room, or from items of clothing on a subject who hasn't been screened quite as thoroughly as he might have been.
Before we get to the sources, however, let's take a look at what we're talking about. Take a look at this mosaic of EPIs:
See the problem? No? Exactly! As I have mentioned several times in the past, many artifacts are best (or only) seen once the background level is brought up. Like this:
Aha! We clearly see the artifacts in this view: strange, variable patterns across entire slices.
Now, it isn't always necessary to crank the background intensity up to be able to see the effects of spikes, as we will see below. But as a general rule, the very first signs of spiking will be quite subtle and will likely be hidden away down in the noise with the N/2 ghosts and all the other crud. This is when you want to catch them, before they become intense and wreck your experiment. So, just to reinforce the point, take a look at this video and see if you can detect any anomalies in the images: